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A bit more on the economics of Bitcoin

Posted by Grow Your Bitcoin, Get Free BTC on 1.30.2014 Label:
January 2014 - Hello friend Grow Your Bitcoin, Get Free BTC, In the article you read this time with the title January 2014, we have prepared well for this article you read and take of information therein. hopefully fill posts we write this you can understand. Well, happy reading.

Title : A bit more on the economics of Bitcoin
link : A bit more on the economics of Bitcoin

see also


January 2014

I'm still trying to understand the details of how cryptocurrencies like Bitcoin work. But the general principles involved seem clear enough, so let me start by explaining (what I think) these are. I'll let the experts out there fill in the gaps (and correct any errors I may have made). So what follows is basically an introductory lecture I would deliver to a class on the subject.

This is about the payment system: the way we pay and get paid for things. Any payment system has to solve the following two problems:

    [1] How to transfer credits across accounts in an honest, secure, and reliable manner;
     and
    [2] How to manage the total supply of credits over time.

The earliest (and arguably still most important) payment system relies on informal communal record-keeping. In small communities (villages, networks consisting of close friends, or work colleagues, clubs, etc.) a lot of what gets produced and consumed relies on what one might call "social credit" designed to exploit multilateral gains to trade (even when bilateral gains to trade are absent). In small groups, it is relatively easy for many members of the community to keep track of individual contributions to, and individual withdrawals from, the collective good. I may sometimes ask a favor of a team member even if we both know I have no direct way to return the favor personally. At the same time, I may be asked to deliver a favor to a team member even if we both know he/she has no direct way to return the favor personally. We just do these things because it is in our collective self-interest. In such reciprocal "gift-giving" economies, the currency that facilitates exchange consists of individual reputations (credit histories). If credit histories are easily observed by members of the community, then its difficult to misrepresent or distort your credits, or steal credits from others. If you try to do so, and if you are caught, you may be ostracized from the community, or worse. (

I mention this idea of "communal monitoring" because some form of it seems to play a critical role in the practical application of the Bitcoin protocol.

As a practical matter, the "social credit" system described above seems to work well for small groups, but not so well for larger communities. It's tough to keep track of the individual credit histories of thousands or millions of people, let alone ensure that such records remain a true representation of history. In large communities, many individuals become "anonymous" to one another. Anonymity here means that anything they do in a transient bilateral meeting will not be observed and recorded by the community. That's too bad because efficiency may have dictated that a gift be made in such a meeting. The gift might have been made if the gift-giver received (a social) credit for his/her sacrifice. But if no social credit is forthcoming (because nobody can see it), then the trade does not take place, even though it should have (in an ideal world).

One solution to this problem is monetary exchange. That is, imagine that there exists a set of durable, divisible, portable, recognizable physical object that is hard to steal/counterfeit (the way that reputations need to be hard to steal or counterfeit). Then contributors (workers) could build up credit by accumulating this object, and recipients (consumers) could draw down their credit by spending this object. As it circulates in this manner, this object becomes money. According to this interpretation, money is nothing more than a substitute for the missing (excessively costly) communal record-keeping technology (see Ostory 1973, Townsend 1987, and Kocherlakota 1998).

In a monetary economy, there is no explicit communal monitoring going on. If money is difficult to steal/counterfeit, then the only way I could have acquired it is by working for it (or by having someone else who worked for it bequeath it to me as a gift). When I show up at my local Starbucks and ask for a triple grande latte, they won't hand over my drink until I show evidence my contributions to society. The evidence is in the form of the money that I earned from work. As I hand over my money, I debit my wallet and credit the Starbucks wallet. This transfer of credits involves no intermediary--it is a "self-serve" accounting mechanism.

Of course, many exchanges do take place via intermediaries like banks and clearinghouses. A check drawn on my bank account is an instruction to debit my account and credit another account. The accounts sit on the books of a third party--the intermediary. The money in this case need not even take a physical form -- it can exist simply as a book-entry object. Today, these book-entry objects take the form of electronic digits, and these digits are debited and credited across accounts managed by banks with instructions from debit card technology.

O.K., well suppose that you do not trust the government (or central bank) and their paper money. Suppose you want the convenience of electronic money (so no commodity money). And moreover, suppose you do not want to rely on a third party like a bank. Maybe you don't trust them, or you do not like their fees, or the records of your purchases they keep, or the fact that your identity is associated with your account. What is the alternative?

What we want is some way to replicate the cash experience using electronic digits instead of physical currency. Recall that in bilateral cash transactions, the accounting is done on a self-service basis without the help of the community or some other third party. When it comes to digital money transferred over the internet across a large network of users, self-serve accounting is not likely to be practical. The self-serve part will have to be replaced by some communal monitoring service (obviously not a delegated third party, since this is what we are trying to avoid). I'll try to explain why in a moment, but first let me considered an idealized world where the relevant information is costlessly accessible to all members of the community.

Digital cash with communal record-keeping and communal monetary policy

Digital cash consists of information encoded electronically as bits. For concreteness, let's call digital cash "e-coins" and assume that an e-coin takes the form of a unique N-digit serial number.

[A1] Assume that the serial numbers of every e-coin created are recorded in a public data bank for all to see.

There is an initial money supply (50 bitcoins in the case of the Bitcoin protocol) and a publicly known protocol that governs money creation. In a nutshell, money growth can only occur by "communal consent." In the present context, you can think of monetary policy as a rule for money creation (and distribution), where the rule can only be changed by communal consent.

Members of the community possess "computer wallets" where e-coins are stored in an encrypted file and managed by a computer app (you can download these programs for free). Computer wallets have a public address, like a P.O. box (the identity of the wallet is not known, and a person may own several wallets). So people can send money to your wallet, but only you can extract money from your wallet (only you possess a private digital key for this purpose).

[A2] The e-coin content of every wallet is part of the public database.

So here's how things might work. Suppose a buyer wants to send an e-coin to a seller. Essentially, the buyer sends a message to the community: I wish to send e-coin SN01234 to [seller's wallet address]. A digital signature ensures that this message could only have originated from the buyer's wallet.

[A3] All messages are publicly observable.

 (The italicized sentences above emphasize the assumed information structure. For Bitcoin, there is even more information than this: the entire transaction history of every wallet is part of the public database.)

Now, if every member can costlessly scan and verify every element of the public database, the transaction process should be straightforward. First, the seller can see that the buyer does indeed own e-coin SN01234. Second, by comparing SN01234 to the public database of serial numbers outstanding, the seller can see that SN01234 is unique and was not counterfeited by the buyer. Third, the seller can see that the buyer is not trying to "double spend" SN01234 (e.g., by simultaneously offering it to another merchant's wallet).

The practical problem with this protocol is not that information assumptions [A1]-[A3] are violated. The information is available. There's just so much of it that not everyone can be expected to absorb it all instantaneously. It is time lag that opens the door for scammers. The task of legitimizing, recording, and updating the database has to be delegated in some manner. In the Bitcoin protocol, the task is not delegated to any single third party, rather it is delegated to members of the community who wish to "volunteer" their monitoring services.

Now, the precise details of how this public monitoring and record-keeping is done presently escapes me. The basic idea is that the monitoring activity must be made costly, because otherwise there is an incentive for scammers to announce that their scam deals (e.g., attempts to double spend) are legitimate. In Bitcoin, the monitors (miners) are required to solve a complicated mathematical problem (consumes energy and CPU time), the answer to which is easily verifiable. I think that (somehow) the verification of this answer also verifies the legitimacy of the transaction (someone help me out here).

But if it is costly for miners to verify transactions, what motivates them to do it? There is a reward, of course. In Bitcoin, the reward comes in two forms: newly minted bitcoin and/or service fees. So in the Bitcoin protocol, the verification costs are partly financed via seigniorage. I do not understand the exact mechanics of this process, in particular, the cryptographic techniques involved, and how the parameters are varied over time (for example, to ensure that the supply of bitcoins never exceeds 21 million). Maybe some smart person can explain it to me in plain language. (Here is a good attempt).

Before I leave this part of the discussion, I want to make a remark about the "mining" activity in Bitcoin. A lot of people, including Paul Krugman, appear confused about it. I initially shared in this confusion. Mining actual gold for the purpose of increasing the money supply is indeed socially wasteful. That's because an existing supply of gold can be stretched into an arbitrarily large supply of real money balances via an appropriate deflation. But the mining activity in Bitcoin is not a social waste--it is the cost associated with operating a payment system of this particular form when people have an incentive to cheat. The analog here is the cost associated with opening and maintaining your checking account at a bank.

Is Bitcoin a good money?

One could argue that the USD is at least partially backed by its ability to discharge real tax obligations. But bitcoins truly are purely fiat in nature (they have no intrinsic use in either consumption or production). Does this mean that the value of bitcoins must eventually crash to zero (their fundamental value)? No.

Bitcoins are information -- record-keeping devices. You can't eat my credit history either, but some companies would value (and pay for) this information nevertheless. So as long as Bitcoin conveys accurate information, its value can persist indefinitely. (There is, of course, the threat of entry, though Bitcoin appears to have a substantial early-mover advantage.)

One problem with Bitcoin as a currency is that its purchasing power sometimes fluctuates violently and at high frequency. As I have argued before, a desirable property of a monetary instrument is that it possess a relatively stable short-run rate of return. (A stable long-run rate of return is nice, but not essential, since other assets than money can be utilized as long-term stores of wealth.). Let's take a look at the USD price of bitcoin:


Holy cow. (Wish I had bought in at 5 cents!)

What accounts for this price volatility? (By comparison, the real rate of return on USD over the same period of time was a relatively stable -1% p.a.). Well, it might have something to do with the thinness of the USD/BTC market (can anyone point me to some evidence?). Or it might have something to do with the fact that bitcoin is not a unit of account (even if it is a medium of exchange, prices are usually denominated in USD). Both of these problems might diminish over time as the popularity of the instrument grows.

But my own take on this is that the price volatility reflects the perception that the supply of bitcoins is (relatively) fixed. This, combined with large fluctuations in the demand for bitcoin, naturally results in huge rate of return volatility. We saw the same thing under gold standard monetary regimes (where gold was a unit of account). In principle, an "elastic" supply of currency (even the credible threat of an elastic supply) can be used to offset sudden changes in demand to keep the rate of return (inflation rate) on money relatively stable.

Trust

My colleague, Francois Velde of the Chicago Fed, has a nice primer on Bitcoin. (It delves into the mechanics of the cryptography involved, but I still find many parts of his discussion a little vague.) But in terms of what sort of trust is involved in Bitcoin and similar endeavors, I like what he has to say here:
[B]itcoin protocol is based on open-source software. Bitcoin is what bitcoin users use. The general principles of bitcoin and its early versions are attributed to an otherwise unknown Satoshi Nakamoto; improvements, bug fixes, and repairs have since been carried out by the community of bitcoin users, dominated by a small set of programmers.

Although some of the enthusiasm for bitcoin is driven by a distrust of state-issued currency, it is hard to imagine a world where the main currency is based on an extremely complex code understood by only a few and controlled by even fewer, without accountability, arbitration, or recourse.
 Yes, it's hard to imagine. But maybe it's because we lack imagination? Only time will tell.

I'm still trying to understand the details of how cryptocurrencies like Bitcoin work. But the general principles involved seem clear enough, so let me start by explaining (what I think) these are. I'll let the experts out there fill in the gaps (and correct any errors I may have made). So what follows is basically an introductory lecture I would deliver to a class on the subject.

This is about the payment system: the way we pay and get paid for things. Any payment system has to solve the following two problems:

    [1] How to transfer credits across accounts in an honest, secure, and reliable manner;
     and
    [2] How to manage the total supply of credits over time.

The earliest (and arguably still most important) payment system relies on informal communal record-keeping. In small communities (villages, networks consisting of close friends, or work colleagues, clubs, etc.) a lot of what gets produced and consumed relies on what one might call "social credit" designed to exploit multilateral gains to trade (even when bilateral gains to trade are absent). In small groups, it is relatively easy for many members of the community to keep track of individual contributions to, and individual withdrawals from, the collective good. I may sometimes ask a favor of a team member even if we both know I have no direct way to return the favor personally. At the same time, I may be asked to deliver a favor to a team member even if we both know he/she has no direct way to return the favor personally. We just do these things because it is in our collective self-interest. In such reciprocal "gift-giving" economies, the currency that facilitates exchange consists of individual reputations (credit histories). If credit histories are easily observed by members of the community, then its difficult to misrepresent or distort your credits, or steal credits from others. If you try to do so, and if you are caught, you may be ostracized from the community, or worse. (

I mention this idea of "communal monitoring" because some form of it seems to play a critical role in the practical application of the Bitcoin protocol.

As a practical matter, the "social credit" system described above seems to work well for small groups, but not so well for larger communities. It's tough to keep track of the individual credit histories of thousands or millions of people, let alone ensure that such records remain a true representation of history. In large communities, many individuals become "anonymous" to one another. Anonymity here means that anything they do in a transient bilateral meeting will not be observed and recorded by the community. That's too bad because efficiency may have dictated that a gift be made in such a meeting. The gift might have been made if the gift-giver received (a social) credit for his/her sacrifice. But if no social credit is forthcoming (because nobody can see it), then the trade does not take place, even though it should have (in an ideal world).

One solution to this problem is monetary exchange. That is, imagine that there exists a set of durable, divisible, portable, recognizable physical object that is hard to steal/counterfeit (the way that reputations need to be hard to steal or counterfeit). Then contributors (workers) could build up credit by accumulating this object, and recipients (consumers) could draw down their credit by spending this object. As it circulates in this manner, this object becomes money. According to this interpretation, money is nothing more than a substitute for the missing (excessively costly) communal record-keeping technology (see Ostory 1973, Townsend 1987, and Kocherlakota 1998).

In a monetary economy, there is no explicit communal monitoring going on. If money is difficult to steal/counterfeit, then the only way I could have acquired it is by working for it (or by having someone else who worked for it bequeath it to me as a gift). When I show up at my local Starbucks and ask for a triple grande latte, they won't hand over my drink until I show evidence my contributions to society. The evidence is in the form of the money that I earned from work. As I hand over my money, I debit my wallet and credit the Starbucks wallet. This transfer of credits involves no intermediary--it is a "self-serve" accounting mechanism.

Of course, many exchanges do take place via intermediaries like banks and clearinghouses. A check drawn on my bank account is an instruction to debit my account and credit another account. The accounts sit on the books of a third party--the intermediary. The money in this case need not even take a physical form -- it can exist simply as a book-entry object. Today, these book-entry objects take the form of electronic digits, and these digits are debited and credited across accounts managed by banks with instructions from debit card technology.

O.K., well suppose that you do not trust the government (or central bank) and their paper money. Suppose you want the convenience of electronic money (so no commodity money). And moreover, suppose you do not want to rely on a third party like a bank. Maybe you don't trust them, or you do not like their fees, or the records of your purchases they keep, or the fact that your identity is associated with your account. What is the alternative?

What we want is some way to replicate the cash experience using electronic digits instead of physical currency. Recall that in bilateral cash transactions, the accounting is done on a self-service basis without the help of the community or some other third party. When it comes to digital money transferred over the internet across a large network of users, self-serve accounting is not likely to be practical. The self-serve part will have to be replaced by some communal monitoring service (obviously not a delegated third party, since this is what we are trying to avoid). I'll try to explain why in a moment, but first let me considered an idealized world where the relevant information is costlessly accessible to all members of the community.

Digital cash with communal record-keeping and communal monetary policy

Digital cash consists of information encoded electronically as bits. For concreteness, let's call digital cash "e-coins" and assume that an e-coin takes the form of a unique N-digit serial number.

[A1] Assume that the serial numbers of every e-coin created are recorded in a public data bank for all to see.

There is an initial money supply (50 bitcoins in the case of the Bitcoin protocol) and a publicly known protocol that governs money creation. In a nutshell, money growth can only occur by "communal consent." In the present context, you can think of monetary policy as a rule for money creation (and distribution), where the rule can only be changed by communal consent.

Members of the community possess "computer wallets" where e-coins are stored in an encrypted file and managed by a computer app (you can download these programs for free). Computer wallets have a public address, like a P.O. box (the identity of the wallet is not known, and a person may own several wallets). So people can send money to your wallet, but only you can extract money from your wallet (only you possess a private digital key for this purpose).

[A2] The e-coin content of every wallet is part of the public database.

So here's how things might work. Suppose a buyer wants to send an e-coin to a seller. Essentially, the buyer sends a message to the community: I wish to send e-coin SN01234 to [seller's wallet address]. A digital signature ensures that this message could only have originated from the buyer's wallet.

[A3] All messages are publicly observable.

 (The italicized sentences above emphasize the assumed information structure. For Bitcoin, there is even more information than this: the entire transaction history of every wallet is part of the public database.)

Now, if every member can costlessly scan and verify every element of the public database, the transaction process should be straightforward. First, the seller can see that the buyer does indeed own e-coin SN01234. Second, by comparing SN01234 to the public database of serial numbers outstanding, the seller can see that SN01234 is unique and was not counterfeited by the buyer. Third, the seller can see that the buyer is not trying to "double spend" SN01234 (e.g., by simultaneously offering it to another merchant's wallet).

The practical problem with this protocol is not that information assumptions [A1]-[A3] are violated. The information is available. There's just so much of it that not everyone can be expected to absorb it all instantaneously. It is time lag that opens the door for scammers. The task of legitimizing, recording, and updating the database has to be delegated in some manner. In the Bitcoin protocol, the task is not delegated to any single third party, rather it is delegated to members of the community who wish to "volunteer" their monitoring services.

Now, the precise details of how this public monitoring and record-keeping is done presently escapes me. The basic idea is that the monitoring activity must be made costly, because otherwise there is an incentive for scammers to announce that their scam deals (e.g., attempts to double spend) are legitimate. In Bitcoin, the monitors (miners) are required to solve a complicated mathematical problem (consumes energy and CPU time), the answer to which is easily verifiable. I think that (somehow) the verification of this answer also verifies the legitimacy of the transaction (someone help me out here).

But if it is costly for miners to verify transactions, what motivates them to do it? There is a reward, of course. In Bitcoin, the reward comes in two forms: newly minted bitcoin and/or service fees. So in the Bitcoin protocol, the verification costs are partly financed via seigniorage. I do not understand the exact mechanics of this process, in particular, the cryptographic techniques involved, and how the parameters are varied over time (for example, to ensure that the supply of bitcoins never exceeds 21 million). Maybe some smart person can explain it to me in plain language. (Here is a good attempt).

Before I leave this part of the discussion, I want to make a remark about the "mining" activity in Bitcoin. A lot of people, including Paul Krugman, appear confused about it. I initially shared in this confusion. Mining actual gold for the purpose of increasing the money supply is indeed socially wasteful. That's because an existing supply of gold can be stretched into an arbitrarily large supply of real money balances via an appropriate deflation. But the mining activity in Bitcoin is not a social waste--it is the cost associated with operating a payment system of this particular form when people have an incentive to cheat. The analog here is the cost associated with opening and maintaining your checking account at a bank.

Is Bitcoin a good money?

One could argue that the USD is at least partially backed by its ability to discharge real tax obligations. But bitcoins truly are purely fiat in nature (they have no intrinsic use in either consumption or production). Does this mean that the value of bitcoins must eventually crash to zero (their fundamental value)? No.

Bitcoins are information -- record-keeping devices. You can't eat my credit history either, but some companies would value (and pay for) this information nevertheless. So as long as Bitcoin conveys accurate information, its value can persist indefinitely. (There is, of course, the threat of entry, though Bitcoin appears to have a substantial early-mover advantage.)

One problem with Bitcoin as a currency is that its purchasing power sometimes fluctuates violently and at high frequency. As I have argued before, a desirable property of a monetary instrument is that it possess a relatively stable short-run rate of return. (A stable long-run rate of return is nice, but not essential, since other assets than money can be utilized as long-term stores of wealth.). Let's take a look at the USD price of bitcoin:


Holy cow. (Wish I had bought in at 5 cents!)

What accounts for this price volatility? (By comparison, the real rate of return on USD over the same period of time was a relatively stable -1% p.a.). Well, it might have something to do with the thinness of the USD/BTC market (can anyone point me to some evidence?). Or it might have something to do with the fact that bitcoin is not a unit of account (even if it is a medium of exchange, prices are usually denominated in USD). Both of these problems might diminish over time as the popularity of the instrument grows.

But my own take on this is that the price volatility reflects the perception that the supply of bitcoins is (relatively) fixed. This, combined with large fluctuations in the demand for bitcoin, naturally results in huge rate of return volatility. We saw the same thing under gold standard monetary regimes (where gold was a unit of account). In principle, an "elastic" supply of currency (even the credible threat of an elastic supply) can be used to offset sudden changes in demand to keep the rate of return (inflation rate) on money relatively stable.

Trust

My colleague, Francois Velde of the Chicago Fed, has a nice primer on Bitcoin. (It delves into the mechanics of the cryptography involved, but I still find many parts of his discussion a little vague.) But in terms of what sort of trust is involved in Bitcoin and similar endeavors, I like what he has to say here:
[B]itcoin protocol is based on open-source software. Bitcoin is what bitcoin users use. The general principles of bitcoin and its early versions are attributed to an otherwise unknown Satoshi Nakamoto; improvements, bug fixes, and repairs have since been carried out by the community of bitcoin users, dominated by a small set of programmers.

Although some of the enthusiasm for bitcoin is driven by a distrust of state-issued currency, it is hard to imagine a world where the main currency is based on an extremely complex code understood by only a few and controlled by even fewer, without accountability, arbitration, or recourse.
 Yes, it's hard to imagine. But maybe it's because we lack imagination? Only time will tell.

A Beginners Guide to Margin Trading on Bitfinex: Why you Shouldn't be Trading on Exchanges

Posted by Grow Your Bitcoin, Get Free BTC on 1.18.2014 Label: , , , , , , , , , , ,
January 2014 - Hello friend Grow Your Bitcoin, Get Free BTC, In the article you read this time with the title January 2014, we have prepared well for this article you read and take of information therein. hopefully fill posts Artikel altcoin, Artikel bear, Artikel Bitcoin, Artikel bitfinex, Artikel bull, Artikel daytrading, Artikel exchange, Artikel fundamental analysis, Artikel margin trading, Artikel market, Artikel technical analysis, Artikel trading, we write this you can understand. Well, happy reading.

Title : A Beginners Guide to Margin Trading on Bitfinex: Why you Shouldn't be Trading on Exchanges
link : A Beginners Guide to Margin Trading on Bitfinex: Why you Shouldn't be Trading on Exchanges

see also


January 2014

So I've been talking a lot about Bitfinex recently, since I started using it about 2 weeks ago. Up until now, I've been using a variety of exchanges including Bitstamp and BTC-E to trade my Bitcoin. I just want to point out that there is a big distinction between exchanges, and trading platforms like Bitfinex. On exchanges, all I could do was sell Bitcoin at a high, and buy them back at a low, or hold some USD in the hopes of snatching up some cheap Bitcoin. In fact, I'm sure all of you reading this have been trying to do exactly that for the last few months. If you haven't heard of Margin trading, get ready to be blown away; you'll be kicking yourself for not doing so earlier.


When I first started trading on Bitfinex, I was totally tripping out about how I didn't find out about this platform and trade on it earlier. Trust me, when you start using Bitfinex to Margin Trade, you'll be wondering wtf you've been doing on those exchanges for the last few months. Because that's exactly how I felt, and that's also why I'm so excited to share it with you. Since then, quite a few people have been asking me on Twitter to cover some Margin Trading and Bitfinex trading material. So here goes nothing.

DISCLAIMER: As much as I like Bitfinex and recommend them for Trading, I do not endorse the site in any way. I do not know if they'll close down today, tomorrow, or a year from now. I also do not know how they handle their funds internally and whether that will pose a problem in the near future. Please trade with caution, and only use money you can afford to lose. If you hear anything negative (e.g. withdrawl issues etc.) about Bitfinex on Reddit/Bitcointalk/Twitter, please make sure to let me know too! 


You must be wondering, first of all, what exactly is Margin Trading? In a nutshell, margin trading is basically borrowing money from the broker (trading site) for trading. Bitfinex currently offers a leverage of 1:1 up to 2.5:1, meaning that you can borrow 1 up to 2.5 Bitcoin for every 1 Bitcoin deposited. For beginner traders, I suggest changing your leverage right after you set up you account to 1:1. Keep in mind that by borrowing funds, you'll be subjected to interest charges (10-13%) which is automatically factored in when you close your position. If you're inexperienced, please listen to my advice, or you could get burnt badly (although 2.5 leverage is pretty decent). For example, if you use 2.5:1 leverage, and short sell your whole account from $800, but price goes up by $800/2.5=$320 to $1120, you're going to lose ALL your Bitcoin in your account (even lower than that actually, because of a platform's stop-out level and margin call). Of course, this can be easily managed with a good trade size & risk management strategy, which I will cover later.

There are 3 options to choose from on Bitfinex; Exchange, Margin Trade, and Liquidity Swaps. If you head to their 'how it works' page, you'll be able to find a good explaination of each of the 3 different functions available. More importantly, I will only focus on Margin Trading, because that's all you'll need to get started on Bitcoin/Litecoin trading.


Let me just orientate you the site before we go on further. Once you create your Bitfinex account, you'll arrive at this page as you see below. So first of all, click on Margin Trade, and select the currency pair that you would like to trade. Secondly, you can see your active positions held, for example I have a sell order (indicated by the '-' sign) at a price of $845, and I'm making ~5% on my trade at the time of posting. You can also see a 'close' action available, which allows you to close your position at the current market price. Thirdly, you can see some of my active orders; red is sell, and green is buy. I have already set 5 different buy positions on $BTCUSD at $701, $688, $622, $555, $471, and 3 sells at $850, $899, and $988. You can see already, that there's much more room to play around with trading on Bitfinex as compared to a traditional exchange. And lastly, the 4th section is where you place your orders. There's 5 different kinds of order types, namely Limit, Market, Stop, Trailing Stop, and Fill or Kill. Do read the links provided for an explaination of each different order type.



So what we'll focus on here is how to actually place orders, and how to manage your orders on Bitfinex. For more about technical analysis and an introduction to trading strategies, visit my previous blog post here. If you're thinking of starting out on trading, I highly advice reading the linked article, as well as this set of very good resources by Reddit user ClydeMachine.

Let's say we deposit 10 Bitcoins into Bitfinex for trading, and we think that the general trend is going down, and want to place a short sell to capitalize on the fall. You'll place a Limit Order, enter your price say $850, for a total of 1 Bitcoin, and click the Margin Sell button. Let's also say from Technical Analysis you figure out that the next support levels are at $760, and $700. So at the same time, you can also place a Limit Buy order for something like 0.5 BTC at $760, and 0.5 BTC at $700. On top of that, if you think that there's a strong resistance at $900 and feel that it may break up to $900 but not beyond that, you can also place a Stop Buy Order at $910, or a Trailing Stop Order for $60 (provided it's currently $850, it will add on the market price -- they both work the same way, only different in the way the position is entered). And if you're going long (buying because you think the market is bullish), it'll be the exact opposite of a short sell as mentioned above.

When your $850 sell order is reached, it will then appear on your Active Orders (section 2) list. From there, if the price moves in your favour, and reaches $700, you'll make 0.5*($850-$760) + 0.5*($850-$700) for a total profit of $120. Point to note is that your Limit orders will cancel each other out. On the other hand if market moves against your favour, and completes your Stop or Trailing stop orders at $910, you'll lose $60 on your trade.

With regard to choosing a suitable leverage for yourself, this is really up to your own personal risk preference, as well as how much you have to trade with. If you have more BTC to play around with, you can choose to deposit more and use a low leverage, unless of course you're in the mood to gamble. But again, please trade safe. This more or less covers Bitcoin trading on Bitfinex. Sign up with me and get 10% off your trading fees for 30 days here. If you have more questions, feel free to tweet me @onemanatatime.


With that, I just want to also cover some of the basics of Bitcoin Trading and share what I think are the most important tips for you traders out there. If you're thinking, why should you listen to me; I have to be honest and say that I've only been trading Bitcoin since September 2013, although I have some experience from Forex Automated Trading since November 2012. On the other hand, since making my first few mistakes trading, I've been putting a lot of effort into researching the topic, and I believe I have a pretty good fundamental understanding of the Bitcoin market. I like to think that I learn pretty fast, but who knows, I could just be getting lucky. Either way, I've made a few pretty good predictions since early December 2013, and I'm just here to help all of you who are interested to learn more.

As mentioned right at the start, one of the most important traits of a good trader is to be disciplined in your trade sizes and plan a risk management strategy that suits your risk-propensity and style. Before you dismiss the importance of this statement, I just want to add that I've been playing poker for over 5 years, and I know how important money management is in being successful as a poker player; and trading is no different. In Equities/Forex trading, traders typically risk 1-2% of their whole portfolio on any single trade. On the other hand, I understand that this % is wayyyy too small for any of you reading this (all you gamblers...). I'll just point out that I typically risk about 10% of my whole portfolio on each position, and up to 50% for active trades. If Bitcoin goes to $400-500 within the next 4 weeks, I'll be sure to be going all-in on a long position.

Secondly, the markets are ever evolving. Don't rely on static indicators or use past price-actions as a judgement of the future. Bitcoin is a largely free-floating market with no party controlling it per say (although you can argue that governments can manipulate prices, such as China's ban), and as such the price is truly an average price based on the sentiment of market participants. What comes as a surprise to me, is that there is still a very large uncertainty among the general adopter of bitcoin regarding its future potential. As such, we're currently seeing the tanking/falling of price I have been predicting for a week. On the other hand, any critical news (government level more than anything else) can affect Bitcoin price drastically and we'll have to see how China acts over the next weeks. I personally believe we'll see a last dip, before prices start climbing up, and finally breaking $1200 around March or April (start of the financial year, and we'll see huge businesses follow Overstock's lead, as well as investor and Wall St $$ pour into Bitcoin) this year and we'll probably see the start of the next bubble. In fact, I would make another bold prediction for 2014, that China will reverse this current ban. Things are heating up, and will get crazy. This time, be smart!

Lastly, plan your trades well! Don't jump into a trade without having planned out not just your entry position, but your exit plan (stop loss) as well as your target price. If you can't determine either one, wait for a better setup! Always look for a setup where you have a higher reward to risk ratio, of at least 2:1. Meaning that your stop loss is $50 away, while your take profit is $100 away.

I've also compiled a few of the most commonly asked questions I came across over the last few days:
  1. How do you judge price levels / How do you do Technical Analysis?

    First of all, please take TA only as a supplement to fundmental analysis, and more importantly with general market sentiment and psychology. For now, all I use is Fibonacci, and some basic resistance/support based on previous price-action. Nothing spectacular at all. As you can see, I'm not a very experienced trader, and really don't pay much attention to TA (but it helps, although too much TA is not good either). That's why I prefer to use a crystal ball.

  2. Why do you think price is going down now?

    I think news is factored in by the time you hear about it (more or less), and this only becomes more true as time goes on. It is more important to look at the market as a whole, from a bird's eye view. Think about the psychology of the market. For example, currently markets are bearish (since the huge drop 5th December 2013, coupled with a lower low on the 18th Dec, and a double top at around $1000) and many are uncertain of how China is going to act moving forward, and hence are generally uncertain about Bitcoin's future. We'll need some big news for prices to start climbing up again, but that'll just be a matter of time.
  3. I have lost a bunch of coins in the past from stupid trades. I have lost confidence in trading.

    Learn to manage your trades & crypto portfolio. My general guideline to everyone is to keep at least 50% in BTC/LTC and largely for the long haul, maybe about 20-30% for trading, and use the rest for your favourite Altcoins. Altcoin prices are highly volatile, and when prices of Bitcoin fall, you'll see that Altcoins fall much much harder. On the other hand, when Bitcoin goes up, you'll see Altcoins climb much faster. Considering that, now'd be a perfect time to stock up on cheap altcoins until Bitcoin starts climbing again.
  4. I (think I) believe in Bitcoin's future. Should I be worried about the price dropping?

    If you really believe in Bitcoin's future, gather as much FIAT as you can right now and buy your Bitcoin while we still have prices under $850. We probably won't be seeing such prices again once Bitcoin starts to skyrocket past $1200, making the November 2013 bubble look like nothing; just think how the April 2013 bubble looked like in November. Oh, and Bitcoin is going to change the world.

So there you go, I hope this post can help you get started on Bitcoin Margin Trading. If you haven't got your account by now, sign up with my referral code and enjoy 10% off your trading fees for the first 30 days. Click here to get started on Bitfinex.

Lastly, I'm building a list of very strong Bitcoin traders on Twitter, and looking to find only the best thought leaders on the topic. Do check it out the Crypto Trading List and feel free to give any feedback or suggestions for who else should be in there. Also feel free to visit my TradingView profile where I chart out my Bitcoin (and some Litecoin soon) predictions. If you haven't watched this video by @ChrisDunnTV, highly recommend checking it out!

Bitcoin Basics (Part 5) - "How To Make Money Trading Bitcoin"

I'm thinking of a few topics for my next blog post. Would you like to see something about Bitcoin Daytrading & Technical Analysis, a revisit & review of Altcoins, Poker & Daytrading, or something about Dogecoin? Drop a comment, send me a message with the form right at the bottom, or tweet me at @onemanatatime.

So I've been talking a lot about Bitfinex recently, since I started using it about 2 weeks ago. Up until now, I've been using a variety of exchanges including Bitstamp and BTC-E to trade my Bitcoin. I just want to point out that there is a big distinction between exchanges, and trading platforms like Bitfinex. On exchanges, all I could do was sell Bitcoin at a high, and buy them back at a low, or hold some USD in the hopes of snatching up some cheap Bitcoin. In fact, I'm sure all of you reading this have been trying to do exactly that for the last few months. If you haven't heard of Margin trading, get ready to be blown away; you'll be kicking yourself for not doing so earlier.


When I first started trading on Bitfinex, I was totally tripping out about how I didn't find out about this platform and trade on it earlier. Trust me, when you start using Bitfinex to Margin Trade, you'll be wondering wtf you've been doing on those exchanges for the last few months. Because that's exactly how I felt, and that's also why I'm so excited to share it with you. Since then, quite a few people have been asking me on Twitter to cover some Margin Trading and Bitfinex trading material. So here goes nothing.

DISCLAIMER: As much as I like Bitfinex and recommend them for Trading, I do not endorse the site in any way. I do not know if they'll close down today, tomorrow, or a year from now. I also do not know how they handle their funds internally and whether that will pose a problem in the near future. Please trade with caution, and only use money you can afford to lose. If you hear anything negative (e.g. withdrawl issues etc.) about Bitfinex on Reddit/Bitcointalk/Twitter, please make sure to let me know too! 


You must be wondering, first of all, what exactly is Margin Trading? In a nutshell, margin trading is basically borrowing money from the broker (trading site) for trading. Bitfinex currently offers a leverage of 1:1 up to 2.5:1, meaning that you can borrow 1 up to 2.5 Bitcoin for every 1 Bitcoin deposited. For beginner traders, I suggest changing your leverage right after you set up you account to 1:1. Keep in mind that by borrowing funds, you'll be subjected to interest charges (10-13%) which is automatically factored in when you close your position. If you're inexperienced, please listen to my advice, or you could get burnt badly (although 2.5 leverage is pretty decent). For example, if you use 2.5:1 leverage, and short sell your whole account from $800, but price goes up by $800/2.5=$320 to $1120, you're going to lose ALL your Bitcoin in your account (even lower than that actually, because of a platform's stop-out level and margin call). Of course, this can be easily managed with a good trade size & risk management strategy, which I will cover later.

There are 3 options to choose from on Bitfinex; Exchange, Margin Trade, and Liquidity Swaps. If you head to their 'how it works' page, you'll be able to find a good explaination of each of the 3 different functions available. More importantly, I will only focus on Margin Trading, because that's all you'll need to get started on Bitcoin/Litecoin trading.


Let me just orientate you the site before we go on further. Once you create your Bitfinex account, you'll arrive at this page as you see below. So first of all, click on Margin Trade, and select the currency pair that you would like to trade. Secondly, you can see your active positions held, for example I have a sell order (indicated by the '-' sign) at a price of $845, and I'm making ~5% on my trade at the time of posting. You can also see a 'close' action available, which allows you to close your position at the current market price. Thirdly, you can see some of my active orders; red is sell, and green is buy. I have already set 5 different buy positions on $BTCUSD at $701, $688, $622, $555, $471, and 3 sells at $850, $899, and $988. You can see already, that there's much more room to play around with trading on Bitfinex as compared to a traditional exchange. And lastly, the 4th section is where you place your orders. There's 5 different kinds of order types, namely Limit, Market, Stop, Trailing Stop, and Fill or Kill. Do read the links provided for an explaination of each different order type.



So what we'll focus on here is how to actually place orders, and how to manage your orders on Bitfinex. For more about technical analysis and an introduction to trading strategies, visit my previous blog post here. If you're thinking of starting out on trading, I highly advice reading the linked article, as well as this set of very good resources by Reddit user ClydeMachine.

Let's say we deposit 10 Bitcoins into Bitfinex for trading, and we think that the general trend is going down, and want to place a short sell to capitalize on the fall. You'll place a Limit Order, enter your price say $850, for a total of 1 Bitcoin, and click the Margin Sell button. Let's also say from Technical Analysis you figure out that the next support levels are at $760, and $700. So at the same time, you can also place a Limit Buy order for something like 0.5 BTC at $760, and 0.5 BTC at $700. On top of that, if you think that there's a strong resistance at $900 and feel that it may break up to $900 but not beyond that, you can also place a Stop Buy Order at $910, or a Trailing Stop Order for $60 (provided it's currently $850, it will add on the market price -- they both work the same way, only different in the way the position is entered). And if you're going long (buying because you think the market is bullish), it'll be the exact opposite of a short sell as mentioned above.

When your $850 sell order is reached, it will then appear on your Active Orders (section 2) list. From there, if the price moves in your favour, and reaches $700, you'll make 0.5*($850-$760) + 0.5*($850-$700) for a total profit of $120. Point to note is that your Limit orders will cancel each other out. On the other hand if market moves against your favour, and completes your Stop or Trailing stop orders at $910, you'll lose $60 on your trade.

With regard to choosing a suitable leverage for yourself, this is really up to your own personal risk preference, as well as how much you have to trade with. If you have more BTC to play around with, you can choose to deposit more and use a low leverage, unless of course you're in the mood to gamble. But again, please trade safe. This more or less covers Bitcoin trading on Bitfinex. Sign up with me and get 10% off your trading fees for 30 days here. If you have more questions, feel free to tweet me @onemanatatime.


With that, I just want to also cover some of the basics of Bitcoin Trading and share what I think are the most important tips for you traders out there. If you're thinking, why should you listen to me; I have to be honest and say that I've only been trading Bitcoin since September 2013, although I have some experience from Forex Automated Trading since November 2012. On the other hand, since making my first few mistakes trading, I've been putting a lot of effort into researching the topic, and I believe I have a pretty good fundamental understanding of the Bitcoin market. I like to think that I learn pretty fast, but who knows, I could just be getting lucky. Either way, I've made a few pretty good predictions since early December 2013, and I'm just here to help all of you who are interested to learn more.

As mentioned right at the start, one of the most important traits of a good trader is to be disciplined in your trade sizes and plan a risk management strategy that suits your risk-propensity and style. Before you dismiss the importance of this statement, I just want to add that I've been playing poker for over 5 years, and I know how important money management is in being successful as a poker player; and trading is no different. In Equities/Forex trading, traders typically risk 1-2% of their whole portfolio on any single trade. On the other hand, I understand that this % is wayyyy too small for any of you reading this (all you gamblers...). I'll just point out that I typically risk about 10% of my whole portfolio on each position, and up to 50% for active trades. If Bitcoin goes to $400-500 within the next 4 weeks, I'll be sure to be going all-in on a long position.

Secondly, the markets are ever evolving. Don't rely on static indicators or use past price-actions as a judgement of the future. Bitcoin is a largely free-floating market with no party controlling it per say (although you can argue that governments can manipulate prices, such as China's ban), and as such the price is truly an average price based on the sentiment of market participants. What comes as a surprise to me, is that there is still a very large uncertainty among the general adopter of bitcoin regarding its future potential. As such, we're currently seeing the tanking/falling of price I have been predicting for a week. On the other hand, any critical news (government level more than anything else) can affect Bitcoin price drastically and we'll have to see how China acts over the next weeks. I personally believe we'll see a last dip, before prices start climbing up, and finally breaking $1200 around March or April (start of the financial year, and we'll see huge businesses follow Overstock's lead, as well as investor and Wall St $$ pour into Bitcoin) this year and we'll probably see the start of the next bubble. In fact, I would make another bold prediction for 2014, that China will reverse this current ban. Things are heating up, and will get crazy. This time, be smart!

Lastly, plan your trades well! Don't jump into a trade without having planned out not just your entry position, but your exit plan (stop loss) as well as your target price. If you can't determine either one, wait for a better setup! Always look for a setup where you have a higher reward to risk ratio, of at least 2:1. Meaning that your stop loss is $50 away, while your take profit is $100 away.

I've also compiled a few of the most commonly asked questions I came across over the last few days:
  1. How do you judge price levels / How do you do Technical Analysis?

    First of all, please take TA only as a supplement to fundmental analysis, and more importantly with general market sentiment and psychology. For now, all I use is Fibonacci, and some basic resistance/support based on previous price-action. Nothing spectacular at all. As you can see, I'm not a very experienced trader, and really don't pay much attention to TA (but it helps, although too much TA is not good either). That's why I prefer to use a crystal ball.

  2. Why do you think price is going down now?

    I think news is factored in by the time you hear about it (more or less), and this only becomes more true as time goes on. It is more important to look at the market as a whole, from a bird's eye view. Think about the psychology of the market. For example, currently markets are bearish (since the huge drop 5th December 2013, coupled with a lower low on the 18th Dec, and a double top at around $1000) and many are uncertain of how China is going to act moving forward, and hence are generally uncertain about Bitcoin's future. We'll need some big news for prices to start climbing up again, but that'll just be a matter of time.
  3. I have lost a bunch of coins in the past from stupid trades. I have lost confidence in trading.

    Learn to manage your trades & crypto portfolio. My general guideline to everyone is to keep at least 50% in BTC/LTC and largely for the long haul, maybe about 20-30% for trading, and use the rest for your favourite Altcoins. Altcoin prices are highly volatile, and when prices of Bitcoin fall, you'll see that Altcoins fall much much harder. On the other hand, when Bitcoin goes up, you'll see Altcoins climb much faster. Considering that, now'd be a perfect time to stock up on cheap altcoins until Bitcoin starts climbing again.
  4. I (think I) believe in Bitcoin's future. Should I be worried about the price dropping?

    If you really believe in Bitcoin's future, gather as much FIAT as you can right now and buy your Bitcoin while we still have prices under $850. We probably won't be seeing such prices again once Bitcoin starts to skyrocket past $1200, making the November 2013 bubble look like nothing; just think how the April 2013 bubble looked like in November. Oh, and Bitcoin is going to change the world.

So there you go, I hope this post can help you get started on Bitcoin Margin Trading. If you haven't got your account by now, sign up with my referral code and enjoy 10% off your trading fees for the first 30 days. Click here to get started on Bitfinex.

Lastly, I'm building a list of very strong Bitcoin traders on Twitter, and looking to find only the best thought leaders on the topic. Do check it out the Crypto Trading List and feel free to give any feedback or suggestions for who else should be in there. Also feel free to visit my TradingView profile where I chart out my Bitcoin (and some Litecoin soon) predictions. If you haven't watched this video by @ChrisDunnTV, highly recommend checking it out!

Bitcoin Basics (Part 5) - "How To Make Money Trading Bitcoin"

I'm thinking of a few topics for my next blog post. Would you like to see something about Bitcoin Daytrading & Technical Analysis, a revisit & review of Altcoins, Poker & Daytrading, or something about Dogecoin? Drop a comment, send me a message with the form right at the bottom, or tweet me at @onemanatatime.

U.S. Inflation Expectations: Low, But Rising

Posted by Grow Your Bitcoin, Get Free BTC on 1.17.2014 Label:
January 2014 - Hello friend Grow Your Bitcoin, Get Free BTC, In the article you read this time with the title January 2014, we have prepared well for this article you read and take of information therein. hopefully fill posts we write this you can understand. Well, happy reading.

Title : U.S. Inflation Expectations: Low, But Rising
link : U.S. Inflation Expectations: Low, But Rising

see also


January 2014

There's been a lot of talk lately about the threat of global deflation. According to Christine Lagarde, Managing Director of the IMF:
“With inflation running below many central banks’ targets, we see rising risks of deflation, which could prove disastrous for the recovery.”
And closer to home:
Ms Lagarde’s comments were echoed by Charles Evans, president of the Chicago Fed. “The recent news on inflation has not been good,” he said in a speech on Wednesday. “Inflation is too low and is running well below the FOMC’s 2 per cent target.”
Inflation in the U.S. is indeed running below target, but what about inflation expectations? Here are some market-based measures of U.S. inflation expectations (based on TIPS spreads) for two, five, and ten years out:


According to this data, inflation expectations in the second quarter of 2013 declined significantly at all horizons. The sudden jump down in expectations in the summer corresponds with the sudden rise in Treasury yields associated with the so-called "taper tantrum" following the June 19 FOMC meeting.

But it is interesting to note that immediately after the taper tantrum, inflation expectations recovered and stabilized, albeit at low levels (especially at the two and five year horizons). At the same time, nominal yields rose and remain elevated (with the 10 year hovering at or just below 3%).

What is even more interesting the reaction of inflation expectations after the December 2013 FOMC meeting, where the taper was actually implemented (the timing of which came as a surprise to most market participants). Short-run inflation expectations, in particular, appear to be on an upward trajectory. The effect is less evident at longer horizons.

I'm not going to offer any interpretation of what economic forces are at play here (I'll leave it up to you to offer your take on things in the comments section). One thing I can say though is that this data will provide at least a small measure of comfort to Fed policy makers concerned about the threat of deflation.

There's been a lot of talk lately about the threat of global deflation. According to Christine Lagarde, Managing Director of the IMF:
“With inflation running below many central banks’ targets, we see rising risks of deflation, which could prove disastrous for the recovery.”
And closer to home:
Ms Lagarde’s comments were echoed by Charles Evans, president of the Chicago Fed. “The recent news on inflation has not been good,” he said in a speech on Wednesday. “Inflation is too low and is running well below the FOMC’s 2 per cent target.”
Inflation in the U.S. is indeed running below target, but what about inflation expectations? Here are some market-based measures of U.S. inflation expectations (based on TIPS spreads) for two, five, and ten years out:


According to this data, inflation expectations in the second quarter of 2013 declined significantly at all horizons. The sudden jump down in expectations in the summer corresponds with the sudden rise in Treasury yields associated with the so-called "taper tantrum" following the June 19 FOMC meeting.

But it is interesting to note that immediately after the taper tantrum, inflation expectations recovered and stabilized, albeit at low levels (especially at the two and five year horizons). At the same time, nominal yields rose and remain elevated (with the 10 year hovering at or just below 3%).

What is even more interesting the reaction of inflation expectations after the December 2013 FOMC meeting, where the taper was actually implemented (the timing of which came as a surprise to most market participants). Short-run inflation expectations, in particular, appear to be on an upward trajectory. The effect is less evident at longer horizons.

I'm not going to offer any interpretation of what economic forces are at play here (I'll leave it up to you to offer your take on things in the comments section). One thing I can say though is that this data will provide at least a small measure of comfort to Fed policy makers concerned about the threat of deflation.

Pissing Contests

Posted by Grow Your Bitcoin, Get Free BTC on 1.16.2014 Label:
January 2014 - Hello friend Grow Your Bitcoin, Get Free BTC, In the article you read this time with the title January 2014, we have prepared well for this article you read and take of information therein. hopefully fill posts we write this you can understand. Well, happy reading.

Title : Pissing Contests
link : Pissing Contests

see also


January 2014

Take a look at the cartoon to your right. It's funny, no? But humor aside, the cartoon reflects a serious idea. It's the idea that wealth transfers from the rich to poor can create wealth--at least, in depressed economic conditions. This basic idea is a staple of undergraduate level "Keynesian" economics -- the so-called "spending multiplier."

In terms of the cartoon, this is how the spending multiplier works. Imagine that the rich dude drops a dollar in the poor guy's tin cup. Or, equivalently, imagine that the state takes the rich dude's shoes and gives them to the poor guy. (The multiplier story does not depend on whether transfers are voluntarily or not, or whether they are made with cash or in kind.) What happens next?

Well, let's imagine that there's an unemployed cobbler in the neighborhood and that the poor guy really wants shoes. Then the poor guy takes his dollar and uses it to order shoes from the (previously) unemployed cobbler. Shoe production (GDP) goes up. The same thing happens if the rich dude wants to replace his stolen shoes. The spending multiplier at this stage is one: a one unit transfer of shoes results in a one unit increase in the production of shoes.

But a multiplier greater than one is possible if there are also unemployed butchers, seamstresses, etc. That is, after receiving his dollar, the cobbler himself goes on a shopping spree, the effect of which is to increase employment in other depressed sectors.

What is the empirical support for this seductive idea? In a recent WSJ piece, Robert Barro argues that there is no "meaningful" support for the idea (either theoretical or empirical). Barro's dismissal of the "wealth transfers create wealth" idea was quickly mocked by Paul Krugman, who called it "anti-scientific." Antonio Fatas also weighs in here with his own characterization of what he calls the "anti-demand coalition."

Goodness, where to begin? Well, first off, I think that Barro goes too far in suggesting that there is no "meaningful" theoretical support for the idea (it depends on what one considers "meaningful," I suppose). We can certainly write down coherent "Keynesian" models where the result--or something like it--holds. The result can also hold in models with perfectly flexible prices, like the OLG model, or neoclassical models with credit constraints (see also the work of Roger Farmer). Of course, whether one buys into all the assumptions that drive these results is another matter. But this is where the need for empirical support comes in. And of course, that's one of the most problematic parts of our discipline.

I'm not sure what the evidence says about the wealth-creating propensity of wealth transfers in depressed economies. Let's just say that I, like many others, are skeptical that the mechanism is quantitatively important. As Barro says, "I am awaiting more empirical evidence." Note that Krugman offers no direct empirical support for the proposition in question. For that matter, nor does Barro provide any for his favored hypothesis. So far, all we have is a pissing contest.

I've already explained why I don't like the way Barro pissed on "Keynesian" theory. Now let me explain why I don't like the way Krugman pissed on "regular" economics. Here is Krugman:
If you read Barro’s piece, what you see is a blithe dismissal of the whole notion that economies can ever suffer from am inadequate level of “aggregate demand” — the scare quotes are his, not mine, meant to suggest that this is a silly, bizarre notion, in conflict with “regular economics.”
While macroeconomists frequently use terms like aggregate supply and demand, one should keep in mind that these objects are not so straightforward to identify in general equilibrium theory (let alone in reality) where everything seems to depend on everything else simultaneously. In any case, "regular economics" offers plenty of examples where equilibrium allocations are socially inefficient. While a well-designed policy intervention may be desirable in such circumstances, it does not necessarily imply that wealth is created through wealth transfers, although this may certainly be the case. So we don't need theories of "deficient demand" to motivate policy interventions.
You’d never know, either from the WSJ or from people like Barro, why anyone ever felt that regular economics — the economics of supply and demand and all that — was inadequate. But you see, there are these things we call recessions. And if you believe regular economics is all there is, you should find them very upsetting.
The suggestion that Barro -- or anyone who does not subscribe to the "deficient demand hypothesis"--somehow missed the recession is quite funny. I know this is too much to bear for the true believer, but alternative interpretations are possible.
Think, for example, about the Great Recession and its aftermath. Regular economics says that economies should normally get richer each year, as their work force and capital stock grow, and technology advances. But after 2007 the United States and other advanced countries suddenly went into reverse, becoming poorer instead of richer, and for an extended period too.
Regular economics says no such thing of course. Whether an economy grows or not depends on a host of factors, including the parameters of the institutional environment (property rights, tax regimes, regulatory regime, etc.). Here is Antonio Fatas using the same rhetorical device to make the other side seem silly and anti-scientific:
Their models are only driven by changes in the productive capacity of an economy which means that the Great Recession (or the Great Depression) must have been the result of some destruction in our capital stock or our inability to remember how to work or produce or somehow our technology got worst than in previous years.
First of all, technology does not not have to "get worse" to generate a temporary recession. It is easy to build equilibrium models with Schumpeterian "gales of creative destruction" that generate recessions. Although I have never seen it, one could conceivably combine this impulse mechanism with a Fisherian "debt-deflation" dynamic to produce prolonged economic slumps from a positive technology shock.

Second, it is easy to generate what look like "aggregate demand events" in even RBC models. One way to do this is to hypothesize the existence of a "news shock;" see, for example, here. Most dynamic models have something like this equation living inside them:

Investment = Increasing function of ( Expected After-tax Return to Investment )

So investment demand (the most volatile component of GDP) depends on "news" (information) concerning the likely future return to investment. Note that investment could be interpreted broadly here to include human capital investment and (in labor market search theories) investment in recruiting activities.

It is not implausible to imagine that expectations concerning future returns might fluctuate a lot, or remain depressed for long periods of time. (This was certainly an important theme in business cycle theory well before Keynes ever coined the term "animal spirits.") Changes in these expectations are likely to be interpreted by econometricians as "aggregate demand shocks" because they induce movements in output and employment when contemporaneous measures of "supply" (technology and capital) remain fixed.

An important question here, I think, concerns the source of these expectation shocks. Do expectations move around passively in accordance with movements in the perceived reality? In other words, do people become rationally optimistic/pessimistic ex ante (even if they may be wrong, ex post)? Or do expectations move about in ways that are inconsistent with the surrounding reality--irrational mood swings? Or can expectations themselves move about for no good reason, shaping reality in a manner that results in a self-fulfilling prophecy? (Here is a paper on the question.)

But surely, one might say, is it not obvious that the current problem is insufficient demand? For example, many firms cite as their main problem a "lack of sales." In the same vein, Fatas reports:
In fact, when most people are asked to describe the dynamics of economic crisis, they immediately refer to some notion that shortages of demand cause recessions.
But as I have discussed before (here), we have to be careful how we map these individual (micro) impressions to what is actually happening at the macro level. Consider, for example, a market-clearing model with intersectoral linkages (like the original RBC model). A real shock in one sector is going to affect the derived demand for a product in another sector. An individual supplier in this model may very well report a "lack of sales" to be his main problem--but this does not necessarily have anything to do with the deficient demand hypothesis. Similarly, we can't say something like "Hey, if the problem really is deficient demand, then wouldn't we expect all beggars to have signs like the guy in the cartoon above?"  No, I'm afraid not.

I am not even sure I agree with Fatas on the point of why so many people appear to resist the idea of countercyclical policy. A majority of people likely do buy into countercyclical policy--there certainly seem to be a lot of "automatic stabilizers" built into the U.S. economy, and both the fiscal and monetary authorities have taken considerable discretionary measures (some would have liked more, and some would have liked less, of course). But maybe Fatas is correct in saying many people just do not trust the government to do the right thing with sequestered resources in current economic circumstances and given the current political climate. Most economic models assume away inconvenient political-economy issues. Optimal interventions can be easily identified in theory, but whether the political landscape is likely to permit implementation of an optimal policy is a different question altogether.

This is already getting way to long for a blog post, but I'd like to conclude with one final thought. At the end of the day, the real issue at stake was how to rationalize an extension to UI benefits. It should be noted that Barro was not arguing against the UI extension -- indeed, his column was subtitled: Food stamps and other transfers aren't necessarily bad ideas, but there's no evidence that they spur growth.

O.K., let's suppose transfer doesn't spur growth (create wealth). There are still other ways to rationalize the extension using "regular" economics. There is a consumption-insurance aspect that might be relevant in a world of incomplete insurance markets. There is the idea of helping the unemployed finance an extended spell of job search to increase the likelihood of a good match. And so on. The same holds true for how we can rationalize public infrastructure investment based on standard cost-benefit analysis--a lot of unemployed construction workers and interest rates at very low levels. Let's stop the pissing contest and start looking for some common ground here.

Take a look at the cartoon to your right. It's funny, no? But humor aside, the cartoon reflects a serious idea. It's the idea that wealth transfers from the rich to poor can create wealth--at least, in depressed economic conditions. This basic idea is a staple of undergraduate level "Keynesian" economics -- the so-called "spending multiplier."

In terms of the cartoon, this is how the spending multiplier works. Imagine that the rich dude drops a dollar in the poor guy's tin cup. Or, equivalently, imagine that the state takes the rich dude's shoes and gives them to the poor guy. (The multiplier story does not depend on whether transfers are voluntarily or not, or whether they are made with cash or in kind.) What happens next?

Well, let's imagine that there's an unemployed cobbler in the neighborhood and that the poor guy really wants shoes. Then the poor guy takes his dollar and uses it to order shoes from the (previously) unemployed cobbler. Shoe production (GDP) goes up. The same thing happens if the rich dude wants to replace his stolen shoes. The spending multiplier at this stage is one: a one unit transfer of shoes results in a one unit increase in the production of shoes.

But a multiplier greater than one is possible if there are also unemployed butchers, seamstresses, etc. That is, after receiving his dollar, the cobbler himself goes on a shopping spree, the effect of which is to increase employment in other depressed sectors.

What is the empirical support for this seductive idea? In a recent WSJ piece, Robert Barro argues that there is no "meaningful" support for the idea (either theoretical or empirical). Barro's dismissal of the "wealth transfers create wealth" idea was quickly mocked by Paul Krugman, who called it "anti-scientific." Antonio Fatas also weighs in here with his own characterization of what he calls the "anti-demand coalition."

Goodness, where to begin? Well, first off, I think that Barro goes too far in suggesting that there is no "meaningful" theoretical support for the idea (it depends on what one considers "meaningful," I suppose). We can certainly write down coherent "Keynesian" models where the result--or something like it--holds. The result can also hold in models with perfectly flexible prices, like the OLG model, or neoclassical models with credit constraints (see also the work of Roger Farmer). Of course, whether one buys into all the assumptions that drive these results is another matter. But this is where the need for empirical support comes in. And of course, that's one of the most problematic parts of our discipline.

I'm not sure what the evidence says about the wealth-creating propensity of wealth transfers in depressed economies. Let's just say that I, like many others, are skeptical that the mechanism is quantitatively important. As Barro says, "I am awaiting more empirical evidence." Note that Krugman offers no direct empirical support for the proposition in question. For that matter, nor does Barro provide any for his favored hypothesis. So far, all we have is a pissing contest.

I've already explained why I don't like the way Barro pissed on "Keynesian" theory. Now let me explain why I don't like the way Krugman pissed on "regular" economics. Here is Krugman:
If you read Barro’s piece, what you see is a blithe dismissal of the whole notion that economies can ever suffer from am inadequate level of “aggregate demand” — the scare quotes are his, not mine, meant to suggest that this is a silly, bizarre notion, in conflict with “regular economics.”
While macroeconomists frequently use terms like aggregate supply and demand, one should keep in mind that these objects are not so straightforward to identify in general equilibrium theory (let alone in reality) where everything seems to depend on everything else simultaneously. In any case, "regular economics" offers plenty of examples where equilibrium allocations are socially inefficient. While a well-designed policy intervention may be desirable in such circumstances, it does not necessarily imply that wealth is created through wealth transfers, although this may certainly be the case. So we don't need theories of "deficient demand" to motivate policy interventions.
You’d never know, either from the WSJ or from people like Barro, why anyone ever felt that regular economics — the economics of supply and demand and all that — was inadequate. But you see, there are these things we call recessions. And if you believe regular economics is all there is, you should find them very upsetting.
The suggestion that Barro -- or anyone who does not subscribe to the "deficient demand hypothesis"--somehow missed the recession is quite funny. I know this is too much to bear for the true believer, but alternative interpretations are possible.
Think, for example, about the Great Recession and its aftermath. Regular economics says that economies should normally get richer each year, as their work force and capital stock grow, and technology advances. But after 2007 the United States and other advanced countries suddenly went into reverse, becoming poorer instead of richer, and for an extended period too.
Regular economics says no such thing of course. Whether an economy grows or not depends on a host of factors, including the parameters of the institutional environment (property rights, tax regimes, regulatory regime, etc.). Here is Antonio Fatas using the same rhetorical device to make the other side seem silly and anti-scientific:
Their models are only driven by changes in the productive capacity of an economy which means that the Great Recession (or the Great Depression) must have been the result of some destruction in our capital stock or our inability to remember how to work or produce or somehow our technology got worst than in previous years.
First of all, technology does not not have to "get worse" to generate a temporary recession. It is easy to build equilibrium models with Schumpeterian "gales of creative destruction" that generate recessions. Although I have never seen it, one could conceivably combine this impulse mechanism with a Fisherian "debt-deflation" dynamic to produce prolonged economic slumps from a positive technology shock.

Second, it is easy to generate what look like "aggregate demand events" in even RBC models. One way to do this is to hypothesize the existence of a "news shock;" see, for example, here. Most dynamic models have something like this equation living inside them:

Investment = Increasing function of ( Expected After-tax Return to Investment )

So investment demand (the most volatile component of GDP) depends on "news" (information) concerning the likely future return to investment. Note that investment could be interpreted broadly here to include human capital investment and (in labor market search theories) investment in recruiting activities.

It is not implausible to imagine that expectations concerning future returns might fluctuate a lot, or remain depressed for long periods of time. (This was certainly an important theme in business cycle theory well before Keynes ever coined the term "animal spirits.") Changes in these expectations are likely to be interpreted by econometricians as "aggregate demand shocks" because they induce movements in output and employment when contemporaneous measures of "supply" (technology and capital) remain fixed.

An important question here, I think, concerns the source of these expectation shocks. Do expectations move around passively in accordance with movements in the perceived reality? In other words, do people become rationally optimistic/pessimistic ex ante (even if they may be wrong, ex post)? Or do expectations move about in ways that are inconsistent with the surrounding reality--irrational mood swings? Or can expectations themselves move about for no good reason, shaping reality in a manner that results in a self-fulfilling prophecy? (Here is a paper on the question.)

But surely, one might say, is it not obvious that the current problem is insufficient demand? For example, many firms cite as their main problem a "lack of sales." In the same vein, Fatas reports:
In fact, when most people are asked to describe the dynamics of economic crisis, they immediately refer to some notion that shortages of demand cause recessions.
But as I have discussed before (here), we have to be careful how we map these individual (micro) impressions to what is actually happening at the macro level. Consider, for example, a market-clearing model with intersectoral linkages (like the original RBC model). A real shock in one sector is going to affect the derived demand for a product in another sector. An individual supplier in this model may very well report a "lack of sales" to be his main problem--but this does not necessarily have anything to do with the deficient demand hypothesis. Similarly, we can't say something like "Hey, if the problem really is deficient demand, then wouldn't we expect all beggars to have signs like the guy in the cartoon above?"  No, I'm afraid not.

I am not even sure I agree with Fatas on the point of why so many people appear to resist the idea of countercyclical policy. A majority of people likely do buy into countercyclical policy--there certainly seem to be a lot of "automatic stabilizers" built into the U.S. economy, and both the fiscal and monetary authorities have taken considerable discretionary measures (some would have liked more, and some would have liked less, of course). But maybe Fatas is correct in saying many people just do not trust the government to do the right thing with sequestered resources in current economic circumstances and given the current political climate. Most economic models assume away inconvenient political-economy issues. Optimal interventions can be easily identified in theory, but whether the political landscape is likely to permit implementation of an optimal policy is a different question altogether.

This is already getting way to long for a blog post, but I'd like to conclude with one final thought. At the end of the day, the real issue at stake was how to rationalize an extension to UI benefits. It should be noted that Barro was not arguing against the UI extension -- indeed, his column was subtitled: Food stamps and other transfers aren't necessarily bad ideas, but there's no evidence that they spur growth.

O.K., let's suppose transfer doesn't spur growth (create wealth). There are still other ways to rationalize the extension using "regular" economics. There is a consumption-insurance aspect that might be relevant in a world of incomplete insurance markets. There is the idea of helping the unemployed finance an extended spell of job search to increase the likelihood of a good match. And so on. The same holds true for how we can rationalize public infrastructure investment based on standard cost-benefit analysis--a lot of unemployed construction workers and interest rates at very low levels. Let's stop the pissing contest and start looking for some common ground here.

Embarking on my Bitcoin Trading Journey: Learn Basic Technical Analysis

Posted by Grow Your Bitcoin, Get Free BTC on 1.08.2014 Label: , , , , , , , , , , , , , , ,
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Title : Embarking on my Bitcoin Trading Journey: Learn Basic Technical Analysis
link : Embarking on my Bitcoin Trading Journey: Learn Basic Technical Analysis

see also


January 2014

My Trading Experience

I first dabbled with Trading and Technical Analysis back in November 2012, when I first got into Forex Trading. Back then, I was introduced to an Automated Forex Robot that could rake in passive income of about 5-10% a month, and used a Martingale (doubling) strategy for trading. In less than 3 months, half of my account went bust because I was using too high of a risk-reward setting, coupled with a highly volatile GBP/USD market on the 4th of January 2013.

I did a fair share of Finance courses during my Business studies, and had a basic understanding of the Equity and Forex markets, and thought that I knew what I was doing. But oh was I so wrong! After this setback, I began to learn more about Technical Analysis to supplement my Auto Trading, and more importantly, to really understand what I was investing in.

I continued using the Forex Robot for the next 10 months up till November 2013, as I began to shift out my funds into Bitcoin after finally turning a profit in August. Since then, I have been following Bitcoin more closely, and have been super interested in learning how to trade Bitcoin.



Getting Started

Back when I was learning more about Forex trading, I went to Forex school at Babypips, and learnt some of the fundamentals of chart reading and trading, such as reading candles and trading concepts. Unfortunately, I dropped out somewhere through Elementary School, after they lost me with all kinds of different indicators I could not see the use for. On the other hand, I still do think Babypips is a fantastic resource, especially for beginners who are keen to learn how to trade and better understand the Bitcoin market.

More recently, since I made my first few panic buys and sells and lost some Bitcoins trading, I have been picking up again on Technical Analysis and Trading strategies. I'm not an expert at this, and neither should you take my words as investment advice, but I'm here to share some of my thoughts on Bitcoin trading, and I hope it is of great help to you!

If you have any questions, feel free to tweet me at @onemanatatime.

Learn the Basics of Trading

If you're a beginner trader, first thing you should learn is to read charts. Chart patterns signal to traders that the price of a security is likely to move in one direction or another when the pattern is complete. I'd like to bring your attention three chart patterns that will appear very often. I also took the time to show you how these relate to Bitcoin trading with the charting tools I use on TradingView. Enjoy!



Secondly, another analysis tool I think is very useful, is the Fibonacci Extension. Fibonacci is pretty tough to understand, and more so to chart with Bitcoin due to the lack of available tools which allow for it. But in essence, the Fibonacci sequence is a unique string of numbers which adds the sum of the two numbers before it, and is the deravitive of the Golden Ratio. People like to call them the "magic" numbers, and very aptly so, as they're present all throughout Nature.

Jason Stapleton shares the secret of Fibonacci Trading; that is to understand that Fibonacci (extension) is simply a tool. But when employed properly, and in conjunction with other indicators, it can present enourmously profitable, high reward low risk trading opportunities. Watch his video here:


Lastly, I'd like to share a trading pattern called the Elliott Wave Principle. It emphasizes an understanding of Investor Psychology, and explains why prices fluctuate in zig-zag patterns. If you thought Fibonacci was tough to understand, let's have Babypips put this in perspective. Babypips teaches Fibonacci in Elementary school Grade 3, whereas Elliott Wave is taught in "Summer School". In that sense, Eliott Wave would be a great concept to learn and understand, as a supplement to your foundational understanding. Click on the links above to read and learn more about both theories!

Bitcoin Trading

By now, you'd probably be saying: "Sure, these resources all give me a good basic understanding of trading markets, but how does that apply to Bitcoin?" Since learning the fundamentals, I've been looking around for good resources to learn Bitcoin Trading from but with not much luck. Here I'll be sharing some handy videos to guide you on your Bitcoin trading journey.

I didn't get around to learning proper Bitcoin trading strategies, until early December when I chanced upon Chris Dunn's first Bitcoin trading video and prediction.


I watched @ChrisDunnTV's first Bitcoin prediction video on the 6th of December 2013, and the rest of his "How To Day Trade" 5 part series videos. Somehow, I had a gut feeling that he was the ONLY guy trading Bitcoin who actually knew what he was talking about. 



Since then, he's made and nailed 5 back-to-back Bitcoin predictions, each with 15-30% profit. Watch his last prediction play out with immaculate precision. Watch the video here: Incredible Live Bitcoin Trading!


This is a long one, but here's another great video I highly recommend watching: 60 Minute Stock Trading Blueprint Webinar.

If you liked his content, watch his other videos on his YouTube channel and follow him on twitter @ChrisDunnTV for the latest updates!

Lastly, I also very much believe in Chris Dunn's trading perspective. I think more than analyzing news articles, or technical analysis, the most important aspect of trading is to understand the market sentiment. Hence, I also want to highlight how many Bitcoin traders are currently looking at certain time frames (e.g. in 12 hours from now) to determine a price for entry. I'd just like say that that's not going to work! Instead of narrow time frames, and random $ amounts; think about Price-Action, Resistance, and Support.

Another piece of advice, is to match the Price-Action of both a long term-time period as well as a short-term one, when trying to make judgement calls. I personally use Bitcoinwisdom.com for reading a chart, and use anything from a 6h to 1d Time Interval for a long-term period, and anything from a 5m to 30m chart for short-term analysis.


Past Trades & Predictions

My very first prediction about Bitcoin came in my first blog post about Bitcoin hitting $1000 by the end of 2013. I wrote the post on 14 November 2013, and you can read it here: Is the Bitcoin train ever turning back? $1000 by year end?

Then on 28 November 2013, I wrote another blog post about an incoming Litecoin crash. I related the price surge during that time, to the Bitcoin bubble of April's Cyprus fiasco. At that time, I had no clue how to judge resistance and support, but interestingly, the wisdom of crowds (more or less) pulled through with the right answer. Litecoin peaked at $50, before crashing down over 50%.


Since I began learning to trade, the added market understanding has given me a better insight into estimating a fair price for altcoins, as well as to judge support/resistance levels to look for entry/exit points. I have made a few spot-on Altcoin predictions of my own over the last weeks, as you can see on my previous blog posts about WorldCoin, NXTcoin, and DogeCoin here and eMunie and EarthCoin here. Follow me on Twitter or my blog to get the latest updates on Altcoin opportunities!

And last but not least, here was my first Bitcoin prediction. Click the link to see how my first prediction panned out on TradingView. I didn't know what I was doing, but I guess that's what they call Beginner's Luck. ;)


Today's Prediction
I think Bitcoin will be looking to retest the $544 support level of Bitstamp, before picking up for a new All Time High. But before we can go the Moon, Earth's gravity is causing a small nosedive into the $650-$720 levels, and I'll enter if my Sell order goes through at $850.


And here's a friendly reminder about following Bitcoin or Altcoin predictions:


Follow me on TradingView as I create new charts with Buy/Sell opportunities, or Twitter @onemanatatime for the latest updates! Don't forget to enter your vote for the Bitcoin price poll on the right column of this blog. Here's my vote, what's yours?




With that, I'd like to end off with this; good luck trading, and HUAT AH! And here's a quote from The Alchemist, by Paulo Coelho.

My Trading Experience

I first dabbled with Trading and Technical Analysis back in November 2012, when I first got into Forex Trading. Back then, I was introduced to an Automated Forex Robot that could rake in passive income of about 5-10% a month, and used a Martingale (doubling) strategy for trading. In less than 3 months, half of my account went bust because I was using too high of a risk-reward setting, coupled with a highly volatile GBP/USD market on the 4th of January 2013.

I did a fair share of Finance courses during my Business studies, and had a basic understanding of the Equity and Forex markets, and thought that I knew what I was doing. But oh was I so wrong! After this setback, I began to learn more about Technical Analysis to supplement my Auto Trading, and more importantly, to really understand what I was investing in.

I continued using the Forex Robot for the next 10 months up till November 2013, as I began to shift out my funds into Bitcoin after finally turning a profit in August. Since then, I have been following Bitcoin more closely, and have been super interested in learning how to trade Bitcoin.



Getting Started

Back when I was learning more about Forex trading, I went to Forex school at Babypips, and learnt some of the fundamentals of chart reading and trading, such as reading candles and trading concepts. Unfortunately, I dropped out somewhere through Elementary School, after they lost me with all kinds of different indicators I could not see the use for. On the other hand, I still do think Babypips is a fantastic resource, especially for beginners who are keen to learn how to trade and better understand the Bitcoin market.

More recently, since I made my first few panic buys and sells and lost some Bitcoins trading, I have been picking up again on Technical Analysis and Trading strategies. I'm not an expert at this, and neither should you take my words as investment advice, but I'm here to share some of my thoughts on Bitcoin trading, and I hope it is of great help to you!

If you have any questions, feel free to tweet me at @onemanatatime.

Learn the Basics of Trading

If you're a beginner trader, first thing you should learn is to read charts. Chart patterns signal to traders that the price of a security is likely to move in one direction or another when the pattern is complete. I'd like to bring your attention three chart patterns that will appear very often. I also took the time to show you how these relate to Bitcoin trading with the charting tools I use on TradingView. Enjoy!



Secondly, another analysis tool I think is very useful, is the Fibonacci Extension. Fibonacci is pretty tough to understand, and more so to chart with Bitcoin due to the lack of available tools which allow for it. But in essence, the Fibonacci sequence is a unique string of numbers which adds the sum of the two numbers before it, and is the deravitive of the Golden Ratio. People like to call them the "magic" numbers, and very aptly so, as they're present all throughout Nature.

Jason Stapleton shares the secret of Fibonacci Trading; that is to understand that Fibonacci (extension) is simply a tool. But when employed properly, and in conjunction with other indicators, it can present enourmously profitable, high reward low risk trading opportunities. Watch his video here:


Lastly, I'd like to share a trading pattern called the Elliott Wave Principle. It emphasizes an understanding of Investor Psychology, and explains why prices fluctuate in zig-zag patterns. If you thought Fibonacci was tough to understand, let's have Babypips put this in perspective. Babypips teaches Fibonacci in Elementary school Grade 3, whereas Elliott Wave is taught in "Summer School". In that sense, Eliott Wave would be a great concept to learn and understand, as a supplement to your foundational understanding. Click on the links above to read and learn more about both theories!

Bitcoin Trading

By now, you'd probably be saying: "Sure, these resources all give me a good basic understanding of trading markets, but how does that apply to Bitcoin?" Since learning the fundamentals, I've been looking around for good resources to learn Bitcoin Trading from but with not much luck. Here I'll be sharing some handy videos to guide you on your Bitcoin trading journey.

I didn't get around to learning proper Bitcoin trading strategies, until early December when I chanced upon Chris Dunn's first Bitcoin trading video and prediction.


I watched @ChrisDunnTV's first Bitcoin prediction video on the 6th of December 2013, and the rest of his "How To Day Trade" 5 part series videos. Somehow, I had a gut feeling that he was the ONLY guy trading Bitcoin who actually knew what he was talking about. 



Since then, he's made and nailed 5 back-to-back Bitcoin predictions, each with 15-30% profit. Watch his last prediction play out with immaculate precision. Watch the video here: Incredible Live Bitcoin Trading!


This is a long one, but here's another great video I highly recommend watching: 60 Minute Stock Trading Blueprint Webinar.

If you liked his content, watch his other videos on his YouTube channel and follow him on twitter @ChrisDunnTV for the latest updates!

Lastly, I also very much believe in Chris Dunn's trading perspective. I think more than analyzing news articles, or technical analysis, the most important aspect of trading is to understand the market sentiment. Hence, I also want to highlight how many Bitcoin traders are currently looking at certain time frames (e.g. in 12 hours from now) to determine a price for entry. I'd just like say that that's not going to work! Instead of narrow time frames, and random $ amounts; think about Price-Action, Resistance, and Support.

Another piece of advice, is to match the Price-Action of both a long term-time period as well as a short-term one, when trying to make judgement calls. I personally use Bitcoinwisdom.com for reading a chart, and use anything from a 6h to 1d Time Interval for a long-term period, and anything from a 5m to 30m chart for short-term analysis.


Past Trades & Predictions

My very first prediction about Bitcoin came in my first blog post about Bitcoin hitting $1000 by the end of 2013. I wrote the post on 14 November 2013, and you can read it here: Is the Bitcoin train ever turning back? $1000 by year end?

Then on 28 November 2013, I wrote another blog post about an incoming Litecoin crash. I related the price surge during that time, to the Bitcoin bubble of April's Cyprus fiasco. At that time, I had no clue how to judge resistance and support, but interestingly, the wisdom of crowds (more or less) pulled through with the right answer. Litecoin peaked at $50, before crashing down over 50%.


Since I began learning to trade, the added market understanding has given me a better insight into estimating a fair price for altcoins, as well as to judge support/resistance levels to look for entry/exit points. I have made a few spot-on Altcoin predictions of my own over the last weeks, as you can see on my previous blog posts about WorldCoin, NXTcoin, and DogeCoin here and eMunie and EarthCoin here. Follow me on Twitter or my blog to get the latest updates on Altcoin opportunities!

And last but not least, here was my first Bitcoin prediction. Click the link to see how my first prediction panned out on TradingView. I didn't know what I was doing, but I guess that's what they call Beginner's Luck. ;)


Today's Prediction
I think Bitcoin will be looking to retest the $544 support level of Bitstamp, before picking up for a new All Time High. But before we can go the Moon, Earth's gravity is causing a small nosedive into the $650-$720 levels, and I'll enter if my Sell order goes through at $850.


And here's a friendly reminder about following Bitcoin or Altcoin predictions:


Follow me on TradingView as I create new charts with Buy/Sell opportunities, or Twitter @onemanatatime for the latest updates! Don't forget to enter your vote for the Bitcoin price poll on the right column of this blog. Here's my vote, what's yours?




With that, I'd like to end off with this; good luck trading, and HUAT AH! And here's a quote from The Alchemist, by Paulo Coelho.

What is the OLG model of money good for?

Posted by Grow Your Bitcoin, Get Free BTC on 1.04.2014 Label:
January 2014 - Hello friend Grow Your Bitcoin, Get Free BTC, In the article you read this time with the title January 2014, we have prepared well for this article you read and take of information therein. hopefully fill posts we write this you can understand. Well, happy reading.

Title : What is the OLG model of money good for?
link : What is the OLG model of money good for?

see also


January 2014

I want to say a few things in response to Brad DeLong's post concerning the usefulness of overlapping generations (OLG) models of money (and on the value of "microfoundations" in general). Let's start with this:
As I say over and over again, forcing your model to have microfoundations when they are the wrong microfoundations is not a progressive but rather a degenerative research program.
Why is he saying this "over and over again" and to whom is he saying it? What if I had said "As I say over and over again, forcing your model to have hand-waving foundations when they are the wrong hand-waving foundations is not a progressive but rather degenerative research program."? That would be silly. And the quoted passage above is just as silly.

A theory usually take the following form: given X, let me explain to you why Y is likely to happen. The "explanation" is something that links X (exogenous variables) to Y (endogenous variables). This link can be represented abstractly as a mapping Y = f(X).

There are many different ways to construct the mapping f. One way is empirical: maybe you have data on X and Y, and you want to estimate f. Another way is to just "wave your hands" and talk informally about the origins and properties of f. Alternatively, you might want to derive f based on a set of assumed behavioral relations. Or, you may want to deduce the properties of f based on a particular algorithm (individual optimization and some equilibrium concept -- the current notion of "microfoundations"). Some brave souls, like my colleague Arthur Robson, try to go even deeper--seeking the biological foundations for preferences, for example.

I don't think we (as a profession) should be religiously wedded to any one methodological approach. Which way to go often depends on the question being asked. Or perhaps a particular method is "forced" because we want to see how far it can be pushed (the outcome is uncertain -- this is the nature of research, after all). And I'm not sure what it means to have the "wrong" microfoundations. (Is it OK to have the wrong "macrofoundations?") Any explanation, whether expressed verbally or mathematically, is based on assumption and abstraction. Something "wrong" can always be found in any approach -- but this is hardly worth saying--let alone saying "over and over again."

Now on to the OLG model of money. Here is DeLong again:
Yes, it seemed to me that handwaving was not good. But saying something precise and false–that we held money because it was the only store of value in a life-cycle context, and intergenerational trade was really important–seemed to me to be vastly inferior to saying something handwavey but true–that holding money allows us to transact not just with those we trust to make good on their vowels but with those whom we do not so trust, and that as a result we can have a very fine-grained and hence very productive division of labor.
Not many people know this, but the OLG model (invented first by Allais, not Samuelson) is just an infinite-horizon version of Wicksell's triangle. The following diagram depicts a dynamic version of the triangle. Adam wants to eat in the morning, but can only produce food at night. Betty wants to eat in the afternoon, but can only produce food in the morning. Charlie wants to eat at night, but can only produce food in the afternoon (assume food is nonstorable).


In the model economy above, there are no bilateral gains to trade (if we were to pair any two individuals, they would not trade). Sometimes this is called a "complete lack of coincidence of wants." There are, however, multilateral gains to trade: everyone would be made better off by producing when they can, and eating when they want to (from each according to their ability, to each according to their need).

Consider an N-period version of the triangle above. Adam still wants bread in period 1, but can only produce bread in period N. Now send N to infinity and interpret Adam as the "initial old" generation (they can only produce bread off into the infinite future). Interpret Betty as the initial young generation (they produce output in period 1, but want to consume in period 2), and so on. Voila: we have the OLG model.

I've always considered Wicksell's triangle a useful starting point for thinking about what might motivate monetary trade (sequential spot market trade involving a swap of goods for an object that circulates widely as an exchange medium). In particular, while there is an absence of coincidence of wants, we can plainly see how this does not matter if people trust each other (a point that DeLong alludes to in the quoted passage above). If trust is lacking--assume, for example, that only Adam is trustworthy--then Adam's IOU (a claim against period N output) can serve as a monetary instrument, permitting intertemporal trade even when trust is in short supply.

An exchange medium is valued in an OLG model for precisely the same reason it is in the Wicksell model or, for that matter, any other model that features a limited commitment friction. So if anyone tries to tell you that the OLG model of money relies on money being the only store of value to facilitate intergenerational trade, you now know they are wrong. The overlapping generation language is metaphorical.

In any case, as it turns out, the foundation of monetary exchange relies on something more than just a lack of trust. A lack of trust is necessary, but not sufficient. As Narayana Kocherlakota has shown (building on the work of Joe Ostroy and Robert Townsend) a lack of record-keeping is also necessary to motivate monetary exchange (since otherwise, credit histories with the threat of punishment for default can support credit exchange even when people do not trust each other).

Also, as I explain here, a lack of coincidence of wants seems neither necessary or sufficient to explain monetary exchange. (Yes, I construct a model where money is necessary even when there are bilateral gains to trade.)

Are any of these results interesting or useful? Well, I find them interesting. And I think the foundations upon which these results are based may prove useful in a variety of contexts. We very often find that policy prescriptions depend on the details. On the other hand, I have nothing against models that simply assume a demand for money. These are models that are designed to address a different set of questions. Sometimes the answers to these questions are sensitive to the assumed microstructure and sometimes they are not. We can't really know beforehand. That's why it's called research.

Finally, is a "rigorous microfoundation" like an OLG (Wicksell) model really necessary to deduce and understand the points made above? I suppose that the answer is no. But then, it's also true that motor vehicles are not necessary for transport. It's just that using them let's you get there a lot faster and more reliably.

I want to say a few things in response to Brad DeLong's post concerning the usefulness of overlapping generations (OLG) models of money (and on the value of "microfoundations" in general). Let's start with this:
As I say over and over again, forcing your model to have microfoundations when they are the wrong microfoundations is not a progressive but rather a degenerative research program.
Why is he saying this "over and over again" and to whom is he saying it? What if I had said "As I say over and over again, forcing your model to have hand-waving foundations when they are the wrong hand-waving foundations is not a progressive but rather degenerative research program."? That would be silly. And the quoted passage above is just as silly.

A theory usually take the following form: given X, let me explain to you why Y is likely to happen. The "explanation" is something that links X (exogenous variables) to Y (endogenous variables). This link can be represented abstractly as a mapping Y = f(X).

There are many different ways to construct the mapping f. One way is empirical: maybe you have data on X and Y, and you want to estimate f. Another way is to just "wave your hands" and talk informally about the origins and properties of f. Alternatively, you might want to derive f based on a set of assumed behavioral relations. Or, you may want to deduce the properties of f based on a particular algorithm (individual optimization and some equilibrium concept -- the current notion of "microfoundations"). Some brave souls, like my colleague Arthur Robson, try to go even deeper--seeking the biological foundations for preferences, for example.

I don't think we (as a profession) should be religiously wedded to any one methodological approach. Which way to go often depends on the question being asked. Or perhaps a particular method is "forced" because we want to see how far it can be pushed (the outcome is uncertain -- this is the nature of research, after all). And I'm not sure what it means to have the "wrong" microfoundations. (Is it OK to have the wrong "macrofoundations?") Any explanation, whether expressed verbally or mathematically, is based on assumption and abstraction. Something "wrong" can always be found in any approach -- but this is hardly worth saying--let alone saying "over and over again."

Now on to the OLG model of money. Here is DeLong again:
Yes, it seemed to me that handwaving was not good. But saying something precise and false–that we held money because it was the only store of value in a life-cycle context, and intergenerational trade was really important–seemed to me to be vastly inferior to saying something handwavey but true–that holding money allows us to transact not just with those we trust to make good on their vowels but with those whom we do not so trust, and that as a result we can have a very fine-grained and hence very productive division of labor.
Not many people know this, but the OLG model (invented first by Allais, not Samuelson) is just an infinite-horizon version of Wicksell's triangle. The following diagram depicts a dynamic version of the triangle. Adam wants to eat in the morning, but can only produce food at night. Betty wants to eat in the afternoon, but can only produce food in the morning. Charlie wants to eat at night, but can only produce food in the afternoon (assume food is nonstorable).


In the model economy above, there are no bilateral gains to trade (if we were to pair any two individuals, they would not trade). Sometimes this is called a "complete lack of coincidence of wants." There are, however, multilateral gains to trade: everyone would be made better off by producing when they can, and eating when they want to (from each according to their ability, to each according to their need).

Consider an N-period version of the triangle above. Adam still wants bread in period 1, but can only produce bread in period N. Now send N to infinity and interpret Adam as the "initial old" generation (they can only produce bread off into the infinite future). Interpret Betty as the initial young generation (they produce output in period 1, but want to consume in period 2), and so on. Voila: we have the OLG model.

I've always considered Wicksell's triangle a useful starting point for thinking about what might motivate monetary trade (sequential spot market trade involving a swap of goods for an object that circulates widely as an exchange medium). In particular, while there is an absence of coincidence of wants, we can plainly see how this does not matter if people trust each other (a point that DeLong alludes to in the quoted passage above). If trust is lacking--assume, for example, that only Adam is trustworthy--then Adam's IOU (a claim against period N output) can serve as a monetary instrument, permitting intertemporal trade even when trust is in short supply.

An exchange medium is valued in an OLG model for precisely the same reason it is in the Wicksell model or, for that matter, any other model that features a limited commitment friction. So if anyone tries to tell you that the OLG model of money relies on money being the only store of value to facilitate intergenerational trade, you now know they are wrong. The overlapping generation language is metaphorical.

In any case, as it turns out, the foundation of monetary exchange relies on something more than just a lack of trust. A lack of trust is necessary, but not sufficient. As Narayana Kocherlakota has shown (building on the work of Joe Ostroy and Robert Townsend) a lack of record-keeping is also necessary to motivate monetary exchange (since otherwise, credit histories with the threat of punishment for default can support credit exchange even when people do not trust each other).

Also, as I explain here, a lack of coincidence of wants seems neither necessary or sufficient to explain monetary exchange. (Yes, I construct a model where money is necessary even when there are bilateral gains to trade.)

Are any of these results interesting or useful? Well, I find them interesting. And I think the foundations upon which these results are based may prove useful in a variety of contexts. We very often find that policy prescriptions depend on the details. On the other hand, I have nothing against models that simply assume a demand for money. These are models that are designed to address a different set of questions. Sometimes the answers to these questions are sensitive to the assumed microstructure and sometimes they are not. We can't really know beforehand. That's why it's called research.

Finally, is a "rigorous microfoundation" like an OLG (Wicksell) model really necessary to deduce and understand the points made above? I suppose that the answer is no. But then, it's also true that motor vehicles are not necessary for transport. It's just that using them let's you get there a lot faster and more reliably.

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