I'm pretty much done writing the program for my next buy and hold post, but there's been some setbacks and it has taken longer than expected. I should be able to finish it the weekend after I get back from Thanksgiving holidays. In the mean time, enjoy some Kaizen BoE quotes. I love it when Central Bankers admit mistakes.
"Because a number of countries, most obviously China, chose to peg their currencies either to the dollar or to a basket in which the dollar featured heavily, the FOMC had to cut rates more aggressively to maintain domestic activity than would have been the case if the dollar had been free to depreciate against them. Moreover, by virtue of the currency pegs, this monetary looseness in the United States was transmitted overseas, despite attempts at sterilisation. Now the primary driver behind the surge in commodity prices over the past three years or so has been the rapid development of the emerging market economies and the consequent growth in commodity demand running up against relatively inelastic supply. But the general pickup in inflation worldwide, together with the appreciation of a range of asset prices, suggests that accommodative monetary policies may have also played a part.
"The pattern of global imbalances that resulted from this mix of policies has vexed policymakers for some time. We knew they were unsustainable and worried that the unwinding might be disorderly, though I don’t think anyone could have guessed the course that events would actually take. But we did see that there were vulnerabilities present. However, nothing very much was done about these imbalances. Why was that?"
...
"Indeed, a central bank seeking to stabilize inflation over a sufficiently long time horizon should necessarily recognize the possible adverse longterm consequences of a credit-driven asset-price boom in its policy deliberations."
All from Charles Bean - Deputy Governor for monetary policy of the BoE -
‘Some Lessons for Monetary Policy from the Recent Financial Turmoil’ -
Remarks at Conference on Globalisation, Inflation and Monetary Policy -
Istanbul, 22 November 2008
Monday, November 24, 2008
Wednesday, November 19, 2008
Kaizen Fed Quotes
"In short, we still do not fully know what caused the run-up in house prices and over-building. Short-term rates were low in 2002-04 as the Federal Reserve countered the risks it saw to good economic performance, and these low rates probably had some effect on housing markets at the time. But the problems largely built up after policy rates were well on their way to neutral, and other factors appear to have played major roles. We have learned little about the likely effect that a somewhat higher funds rate would have had on the speculative element of prices. Of course, it is important to keep an open mind about the relationship of short-term interest rates and speculative activity. If it becomes clear that monetary policy can predictably influence the evolution of bubbles, central banks should take that ability into account when crafting policies intended to keep output rising in line with its potential and inflation low and stable." - Vice Chairman Donald L. Kohn At the Cato Institute's Twenty-Sixth Annual Monetary Policy Conference, Washington, D.C., November 19, 2008, "Monetary Policy and Asset Prices Revisited"
Tuesday, November 18, 2008
AQR and Leverage
Damian over at Skill Analytics wrote a post on the AQR article from Allaboutalpha.
I agree with his sentiments regarding the way they determine their leverage. I would guess they don't use that formula to determine their leverage but it could be a simplification of something they do use. Nevertheless I would strongly advise not using it.
Let's use l as leverage. They have two portfolios A and B with correlation p and standard deviations stdev(A) and stdev(B). The standard deviation of the portfolio is
stdev(p)=[(stdev(A)/2)^2+(stdev(B)/2)^2+.5*stdev(A)*stdev(B)*p]^2
They set (stdev(A)+stdev(B))/2=l*stdev(p) or l=(stdev(A)+stdev(B))/(2*stdev(p))
Now, if I were to assume that stdev(B)=x*stdev(A) just for mathematical simplification
that would mean l=(1+x)*stdev(a)/(2*[(stdev(A)^2*(1+x^2))/4+.5*x*p*stdev(A)^2]^.5
and: l=(1+x)/[(1+2*x*p+x^2]^.5
So what we have from this little mathematical porn is that if there's no correlation then l=(1+x)/[1+x^2]^.5. In other words if the standard deviations of each asset are the same (x=1) and correlation is 0, then you'd use leverage l=2^.5 which is the maximum leverage you would use. Strangely, as the ratio of the two variances goes from something like x=.75 to 1.25, the peak is when x=1 and declines on either side. The same is generally true for other correlations except that the closer the correlation is to 1, the lower the leverage.
So why does this matter. Basically, if you were to use a system like this to determine your leverage, it is based on two things, the correlation between the two assets and the difference between the variances. In other words, the levels of variance do not matter in this framework, only the difference between the two assets' variances. The correlation part makes sense, but this seems a little too simplistic.
I agree with his sentiments regarding the way they determine their leverage. I would guess they don't use that formula to determine their leverage but it could be a simplification of something they do use. Nevertheless I would strongly advise not using it.
Let's use l as leverage. They have two portfolios A and B with correlation p and standard deviations stdev(A) and stdev(B). The standard deviation of the portfolio is
stdev(p)=[(stdev(A)/2)^2+(stdev(B)/2)^2+.5*stdev(A)*stdev(B)*p]^2
They set (stdev(A)+stdev(B))/2=l*stdev(p) or l=(stdev(A)+stdev(B))/(2*stdev(p))
Now, if I were to assume that stdev(B)=x*stdev(A) just for mathematical simplification
that would mean l=(1+x)*stdev(a)/(2*[(stdev(A)^2*(1+x^2))/4+.5*x*p*stdev(A)^2]^.5
and: l=(1+x)/[(1+2*x*p+x^2]^.5
So what we have from this little mathematical porn is that if there's no correlation then l=(1+x)/[1+x^2]^.5. In other words if the standard deviations of each asset are the same (x=1) and correlation is 0, then you'd use leverage l=2^.5 which is the maximum leverage you would use. Strangely, as the ratio of the two variances goes from something like x=.75 to 1.25, the peak is when x=1 and declines on either side. The same is generally true for other correlations except that the closer the correlation is to 1, the lower the leverage.
So why does this matter. Basically, if you were to use a system like this to determine your leverage, it is based on two things, the correlation between the two assets and the difference between the variances. In other words, the levels of variance do not matter in this framework, only the difference between the two assets' variances. The correlation part makes sense, but this seems a little too simplistic.
Sunday, November 9, 2008
Buy and Hold (Part 2)
This is the second part in a three part series. The first is here.
To look into why buy and hold doesn't work, I wanted to compare a relatively simple asset allocation strategy with the typical 60/40 stock/bond allocation. I obtained data from the Global Financial Database for the S&P500 and 10 year treasuries going back to 1921. Now the S&P500 wasn't actually published before 1950 or so, they use the methodology going back farther. Also there really wasn't a way to invest in the indices until the 70s or later. As with most things in finance, this isn't perfect by a long shot and is just showing what could happen.
The strategy I looked into compares stocks and bonds. I looked at whether bonds have outperformed stocks in the past 12 and 6 months. I gave a weight of 2/3rds to the 12 month ratio and 1/3 to the 6 month ratio. So if stocks outperform bonds in 12 months and 6 months, they get a value of 1, and bonds get a value of -1. If stocks outperform in 12 months, but bonds outperform over 6 months, stocks get a value of 1/3 and bonds get a value of -1/3.
Since I am comparing a strategy against 60/40 allocations, I decided that my starting point would be the 60/40. I use a base value of 60% for the stock allocation and the bond allocation is always 100%-stock. There is no leverage so stocks and bonds are capped at 0% and 100%. Finally, there is a multiplier against each of these values, so if stocks start at 60% with a multiplier of 20%, then if stocks have a value of +1, their allocation is 80% (and 20% bonds). A fairly simple, straightforward strategy.
Since there are caps, the efficient frontier is truncated at the top (as you increase the multiplier the stock level just goes to 100% or 0% immediately). However, the clear result is that you can improve returns by increasing allocations when different asset classes are outperforming relative to each other. The best Sharpe ratio I reported was actually with a multiplier of .6, indicating that if stocks are outperforming on both a 12 month and 6 month basis, you should be in 100% stocks and vice-versa for bonds. If over the next 6 month period stocks outperform (but bonds have outperformed over the 12 month period), then you should increase your stock position to 40% (according to this strategy). Since 1995 this strategy has outperformed the buy and hold by 50%, or an alpha of 3.2%. Since 1970, it would have lost money in 73, 81, and 87 (it was entirely in stocks in October 87, if you were wondering), but 73 and 81 were quite mild.
Another strategy to come in part 3, hopefully by next weekend.
To look into why buy and hold doesn't work, I wanted to compare a relatively simple asset allocation strategy with the typical 60/40 stock/bond allocation. I obtained data from the Global Financial Database for the S&P500 and 10 year treasuries going back to 1921. Now the S&P500 wasn't actually published before 1950 or so, they use the methodology going back farther. Also there really wasn't a way to invest in the indices until the 70s or later. As with most things in finance, this isn't perfect by a long shot and is just showing what could happen.
The strategy I looked into compares stocks and bonds. I looked at whether bonds have outperformed stocks in the past 12 and 6 months. I gave a weight of 2/3rds to the 12 month ratio and 1/3 to the 6 month ratio. So if stocks outperform bonds in 12 months and 6 months, they get a value of 1, and bonds get a value of -1. If stocks outperform in 12 months, but bonds outperform over 6 months, stocks get a value of 1/3 and bonds get a value of -1/3.
Since I am comparing a strategy against 60/40 allocations, I decided that my starting point would be the 60/40. I use a base value of 60% for the stock allocation and the bond allocation is always 100%-stock. There is no leverage so stocks and bonds are capped at 0% and 100%. Finally, there is a multiplier against each of these values, so if stocks start at 60% with a multiplier of 20%, then if stocks have a value of +1, their allocation is 80% (and 20% bonds). A fairly simple, straightforward strategy.
Since there are caps, the efficient frontier is truncated at the top (as you increase the multiplier the stock level just goes to 100% or 0% immediately). However, the clear result is that you can improve returns by increasing allocations when different asset classes are outperforming relative to each other. The best Sharpe ratio I reported was actually with a multiplier of .6, indicating that if stocks are outperforming on both a 12 month and 6 month basis, you should be in 100% stocks and vice-versa for bonds. If over the next 6 month period stocks outperform (but bonds have outperformed over the 12 month period), then you should increase your stock position to 40% (according to this strategy). Since 1995 this strategy has outperformed the buy and hold by 50%, or an alpha of 3.2%. Since 1970, it would have lost money in 73, 81, and 87 (it was entirely in stocks in October 87, if you were wondering), but 73 and 81 were quite mild.Another strategy to come in part 3, hopefully by next weekend.
Buy and Hold (Part 1)
I can get behind the argument that the average investor should index. Security selection is difficult and most don't want to spend the time to attempt to outperform the index. Time spent trying to outperform the index might be better spent doing other things (esp. based on the size of their holdings).
However, the decision to index or not index is one part of the equation. The investor chooses not only the securities to invest in, but the relative proportions of different asset classes, or holdings in different ETFs/Index funds. If you believe in buy and hold, you might keep your asset allocation constant over time, changing them only as your risk aversion increases as you age (to hold more bonds). Given the cyclical nature of our economic system, this strategy is incredibly misguided. Different asset classes perform different over different time periods, suggesting that an investor should change their allocation as economic conditions change. Put more emphasis on stocks when the economy is doing well and pare back when it slows.
The mutual fund industry is interested in selling Beta, but due to the cyclical nature of the economy, many investors sell their funds as the market falls. In effect, the mutual fund companies receive more volatile, cyclical earnings as their AUM flucuates. However, if they were to focus on products taking advantage of cycles rather than just offering Beta, they would see less liquidation as markets fail, and investors would be less likely to sell their funds. Earnings would be less cyclical. Further, I would argue that this focus could result in a much more successful fund manager than normal. If people view their products as safer, not only would they be more willing to hold their assets with that firm in the long-term, but they would also want to hold more assets with them.
One concern you could have is that if all funds were structured as broad asset allocation funds that take advantage of the cycle, economic cycles would moderate. While I think returns to the strategy would be competed away in such a situation, I think there are three criticisms to that argument. First, not all funds would want to manage funds in that way. At present, most people are happy believing buy and hold is the best way to manage money or they believe their own method is more succesful, it would hard to convince everyone. Second, not everyone would structure their funds the same way. Some would focus on economic data, some might focus on valuations, some on technicals and momentum, while others could use a combination. Not all of the signals would come at the same time. Finally, for that argument to be true, the lack of participation of major investors would be a sufficient condition to smooth the business cycle. Personally, I am of the view that economic cycles are the fault of the Federal Reserve and they appear in specific sectors due to primarily technological change but also government regulations. The strategies I will look at don't try to time these changes, but use momentum data to figure out when others think it has changed. So if everyone were following this strategy, surely the momentum data would no longer be viable, but I doubt everyone would follow it.
I plan on following this post up with two more posts detailing two strategies I have looked at. One is simple enough that anyone could implement, but the second is more complex.
However, the decision to index or not index is one part of the equation. The investor chooses not only the securities to invest in, but the relative proportions of different asset classes, or holdings in different ETFs/Index funds. If you believe in buy and hold, you might keep your asset allocation constant over time, changing them only as your risk aversion increases as you age (to hold more bonds). Given the cyclical nature of our economic system, this strategy is incredibly misguided. Different asset classes perform different over different time periods, suggesting that an investor should change their allocation as economic conditions change. Put more emphasis on stocks when the economy is doing well and pare back when it slows.
The mutual fund industry is interested in selling Beta, but due to the cyclical nature of the economy, many investors sell their funds as the market falls. In effect, the mutual fund companies receive more volatile, cyclical earnings as their AUM flucuates. However, if they were to focus on products taking advantage of cycles rather than just offering Beta, they would see less liquidation as markets fail, and investors would be less likely to sell their funds. Earnings would be less cyclical. Further, I would argue that this focus could result in a much more successful fund manager than normal. If people view their products as safer, not only would they be more willing to hold their assets with that firm in the long-term, but they would also want to hold more assets with them.
One concern you could have is that if all funds were structured as broad asset allocation funds that take advantage of the cycle, economic cycles would moderate. While I think returns to the strategy would be competed away in such a situation, I think there are three criticisms to that argument. First, not all funds would want to manage funds in that way. At present, most people are happy believing buy and hold is the best way to manage money or they believe their own method is more succesful, it would hard to convince everyone. Second, not everyone would structure their funds the same way. Some would focus on economic data, some might focus on valuations, some on technicals and momentum, while others could use a combination. Not all of the signals would come at the same time. Finally, for that argument to be true, the lack of participation of major investors would be a sufficient condition to smooth the business cycle. Personally, I am of the view that economic cycles are the fault of the Federal Reserve and they appear in specific sectors due to primarily technological change but also government regulations. The strategies I will look at don't try to time these changes, but use momentum data to figure out when others think it has changed. So if everyone were following this strategy, surely the momentum data would no longer be viable, but I doubt everyone would follow it.
I plan on following this post up with two more posts detailing two strategies I have looked at. One is simple enough that anyone could implement, but the second is more complex.
Saturday, November 8, 2008
Presidential Inaugurals
Following Obama's Victory Speech earlier this week, the news media informed us that it was one of his best speeches yet. I don't dispute that, despite my belief that ideas matter and his aren't that good. But I wanted to see how Obama's speech compares to other speeches in American history. Now it isn't always easy to get your hands on victory speeches, b/c American President-elects didn't always give them. I compared his speech to Bush's speeches and Clinton's victory speeches using a tool that calculates a bunch of statistics of how complex your language is. One statistic, more commonly quoted is apparently called the Flesch-Kincaid grade level. According to this statistic, Obama's speech wasn't that much different from the more recent Victory Speeches.
However, I decided to go further back, mainly out of an interest in finding old Presidential speeches/addresses to see how politicians used to talk to Americans. So I found all of the inaugural speeches for Presidents since 1896 (since McKinley bridges both centuries I included both of his) and ran them through this tool. The tool provides many different statistics of how complex different texts are and I don't really know enough to tell which ones are best. So I created a Z-Statistic for one and then averaged them all to create one single value for each President(the negative of Flesch reading ease tests were used). Z-statistics are a little unrealistic, but I'm just using them as the first-best method of simplification. I couldn't find Eisenhower's 1956 speech, so I just assumed they had the same values (not realistic, but only used for creating the statistic).
While his speech is not an inaugural address and this method isn't perfect, Obama falls in at 27 of 29. For a speech listed as his best, it fails the complexity of language test. Surprisingly, Bush's second inaugural used quite complex language, as well as Nixon's inaugural speech. Clinton's first speech was not as "good" as either of Reagan's (by this standard), but his second was.
A final problem I didn't note is that since we have had television, these speeches have definitely changed. Earlier speeches mostly ran in the newspapers, are longer and could be thought of as like a State of the Union Address that we would see today. I took the time to read Coolidge and Taft's speeches to get a feel for them and they lay out all sorts of policies in much further detail than current ones do. Compare that to Bush I's speech where he talks in generalities and a Thousand Points of Light, but nothing specific. Here's another surprising fact, Bush II's second inaugural was the most complex inaugural since television began.
A well-received speech doesn't necessarily mean it was well-written or at a high grade level. It is as much true that you need to deliver the speech properly. Based on my analysis, I think the MSM is thinking more of the delivery of his speech rather than necessarily the content or eloquence of his speech. I did my best to quantify the eloquence, but the content is left to you.
Or you could think that the media is just completely biased for this guy (mi amigo, my compatriot, that one, my friend).
Note: For reference, if you add in MLK's "I have a dream" speech, it is close to Reagan's second inaugural. This post would fall between T. Roosevelt and Bush II.
However, I decided to go further back, mainly out of an interest in finding old Presidential speeches/addresses to see how politicians used to talk to Americans. So I found all of the inaugural speeches for Presidents since 1896 (since McKinley bridges both centuries I included both of his) and ran them through this tool. The tool provides many different statistics of how complex different texts are and I don't really know enough to tell which ones are best. So I created a Z-Statistic for one and then averaged them all to create one single value for each President(the negative of Flesch reading ease tests were used). Z-statistics are a little unrealistic, but I'm just using them as the first-best method of simplification. I couldn't find Eisenhower's 1956 speech, so I just assumed they had the same values (not realistic, but only used for creating the statistic).
While his speech is not an inaugural address and this method isn't perfect, Obama falls in at 27 of 29. For a speech listed as his best, it fails the complexity of language test. Surprisingly, Bush's second inaugural used quite complex language, as well as Nixon's inaugural speech. Clinton's first speech was not as "good" as either of Reagan's (by this standard), but his second was.
A final problem I didn't note is that since we have had television, these speeches have definitely changed. Earlier speeches mostly ran in the newspapers, are longer and could be thought of as like a State of the Union Address that we would see today. I took the time to read Coolidge and Taft's speeches to get a feel for them and they lay out all sorts of policies in much further detail than current ones do. Compare that to Bush I's speech where he talks in generalities and a Thousand Points of Light, but nothing specific. Here's another surprising fact, Bush II's second inaugural was the most complex inaugural since television began.
A well-received speech doesn't necessarily mean it was well-written or at a high grade level. It is as much true that you need to deliver the speech properly. Based on my analysis, I think the MSM is thinking more of the delivery of his speech rather than necessarily the content or eloquence of his speech. I did my best to quantify the eloquence, but the content is left to you.
Or you could think that the media is just completely biased for this guy (mi amigo, my compatriot, that one, my friend).
Note: For reference, if you add in MLK's "I have a dream" speech, it is close to Reagan's second inaugural. This post would fall between T. Roosevelt and Bush II.
Thursday, October 23, 2008
Corzine idea
I was just watching Jon Corzine on the Daily Show and I got to thinking about an idea for a research paper. It would be interesting to trace the major Cabinet secretaries (like Defense, Treasury, etc) back to Wall Street. It would be interesting to look at their political ideologies and see how Wall Street has or hasn't influenced them generally over time and was there any bias to a certain political party (or ideology, since the parties have changed)?
Wednesday, October 22, 2008
Willing to admit it
Arnold Kling posted today about how Economists as a whole do not know what is going on and that their textbook models are wrong. I couldn't agree more. However, I haven't spoken with anyone who has said, "wow this Rational Exepectations model really helped me forecast this crisis."
Two of my colleagues and I spent some time with Johnny Walker this afternoon... wait I mean John Walker of Oxford Economics. He seemed perfectly willing to admit that his workhorse economic model doesn't work well during this time period. I'm not sure how true this is for academic economists who build models, but I would think that most people who spend their time forecasting are perfectly willing to admit that they use them as a tool to think about the economy rather than something absolute.
In principle Kling is right, it is better to admit pseudo-knowledge than not admit it. I just think that professionals are more willing to admit it than he gives them credit for.
Two of my colleagues and I spent some time with Johnny Walker this afternoon... wait I mean John Walker of Oxford Economics. He seemed perfectly willing to admit that his workhorse economic model doesn't work well during this time period. I'm not sure how true this is for academic economists who build models, but I would think that most people who spend their time forecasting are perfectly willing to admit that they use them as a tool to think about the economy rather than something absolute.
In principle Kling is right, it is better to admit pseudo-knowledge than not admit it. I just think that professionals are more willing to admit it than he gives them credit for.
Sunday, October 19, 2008
How the financial collapse killed libertarianism by partisan hack
I love these death of articles by people ignorant of not just the political philosophy that is their subject, but also the conditions leading to its collapse.
Let us start with his claim that, "after LTCM's collapse, it became abundantly clear to anyone paying attention to this unfortunately esoteric issue that unregulated credit market derivatives posed risks to the global financial system, and that supervision and limits of some kind were advisable." First, credit default swaps as we know them today were still in their infancy in 1998 so it would be difficult to say they were as important to LTCM's collapse as Myron Scholes' shoes were. Second, he's attacking the wrong problem, to me, one of the biggest lessons from LTCM is that risk-models and excessive leverage are a dangerous combination. Those problems were never fixed, but it is hard to say that libertarianism is or isn't the culprit. Libertarians would say that banks who lend money to institutions who use excessive leverage might fail if the bets go wrong, and they should be allowed to fail. Harping on, the author notes that "the Washington Post ran an excellent piece this week on how one such attempt to regulate credit derivatives got derailed." Again, the author fails to distinguish between a credit derivative and a derivative. That article is as much about regulating currency and bond derivatives as it is about CDS.
So here again we are faced with the theory that conservatives, liberals, and a central banker who control the government, conspired together to halt attempts to regulate derivatives. The reader is left to his or her imagination to determine how regulating derivatives would have made a difference. I agree with Ritholtz that the decision to allow investment banks to lever up to more than 30x from their original 15x was a mistake. However, I'm not quite sure what else would have or could have been done. Much of the trade in CREDIT derivatives was to get bad assets or the impact of said assets off their balance sheet, a form of regulatory arbitrage. If they threw up some more regulations, I have little doubt that the industry would have tried to find new, exciting, and complex ways around it.
The author notes that consistent libertarians, as opposed to conservatives like Gramm that he is confusing with libertarians, opposed the bail-out and then he invokes the Great Depression that many could be employed in soup-kitchens. Implicitly he is tying the libertarians with the liquidationist view of the Great Depression. L. White has done a great job explaining how Mellon wasn't a liquidationist and Hayek and Robbins weren't liquidationists.
Finally he argues, "libertarians react to the world's failing to conform to their model by asking where the world went wrong. Their heroic view of capitalism makes it difficult for them to accept that markets can be irrational, misunderstand risk, and misallocate resources or that financial systems without vigorous government oversight and the capacity for pragmatic intervention constitute a recipe for disaster."
First, there are libertarians who believe the market is efficient and there are libertarians who do not believe that. I would say that there are many many more in the latter category. I'm perfectly willing to say that markets can be irrational, misunderstand risk, and misallocate resources. However, I would also be willing to say that almost all of the times when they do this, you can point to a government regulation or a government program that is leading to this. The ABCT doesn't really describe the depth of our current situation on its own, but it sure does a good job explaining how the government encouraged the market to misallocate resources into the housing boom. The difference between the author and I is that I want to see market oversight and market regulation where he only is looking to the government for the solution. Well, I think there are plenty of cases where you can point to the government being the problem.
What's interesting to me, is that the death of socialism was predicted by Hayek and the Austrians several decades before it happened. In all reality, I'll admit that what the Soviets had and Chinese (before Deng) had wasn't really socialism. It was only really tried in the WW1 War Economy in Russia and it failed miserably, as predicted. The system that grew out of it, at least in Russia, was more of a market socialism, mostly socialism, but a little markets and freedom thrown in. Libertarians, mostly Hayekians, have predicted that the global financial system is unsustainable in its current form. Many predicted that the housing boom would lead to a situation like what we're currently experiencing. That's because what we don't have is capitalism and anyone with a brain should realize that. Even before the bail-out bill, we were on our third-way, though not as far to the socialist side as Europe. It's not that this doesn't fit with our model, but when you take our government and say we live in a capitalist country. People like me need and have stood up and said we do not live in a capitalist country. Our theories aren't to blame, our theories told us we would end up in this mess.
Let us start with his claim that, "after LTCM's collapse, it became abundantly clear to anyone paying attention to this unfortunately esoteric issue that unregulated credit market derivatives posed risks to the global financial system, and that supervision and limits of some kind were advisable." First, credit default swaps as we know them today were still in their infancy in 1998 so it would be difficult to say they were as important to LTCM's collapse as Myron Scholes' shoes were. Second, he's attacking the wrong problem, to me, one of the biggest lessons from LTCM is that risk-models and excessive leverage are a dangerous combination. Those problems were never fixed, but it is hard to say that libertarianism is or isn't the culprit. Libertarians would say that banks who lend money to institutions who use excessive leverage might fail if the bets go wrong, and they should be allowed to fail. Harping on, the author notes that "the Washington Post ran an excellent piece this week on how one such attempt to regulate credit derivatives got derailed." Again, the author fails to distinguish between a credit derivative and a derivative. That article is as much about regulating currency and bond derivatives as it is about CDS.
So here again we are faced with the theory that conservatives, liberals, and a central banker who control the government, conspired together to halt attempts to regulate derivatives. The reader is left to his or her imagination to determine how regulating derivatives would have made a difference. I agree with Ritholtz that the decision to allow investment banks to lever up to more than 30x from their original 15x was a mistake. However, I'm not quite sure what else would have or could have been done. Much of the trade in CREDIT derivatives was to get bad assets or the impact of said assets off their balance sheet, a form of regulatory arbitrage. If they threw up some more regulations, I have little doubt that the industry would have tried to find new, exciting, and complex ways around it.
The author notes that consistent libertarians, as opposed to conservatives like Gramm that he is confusing with libertarians, opposed the bail-out and then he invokes the Great Depression that many could be employed in soup-kitchens. Implicitly he is tying the libertarians with the liquidationist view of the Great Depression. L. White has done a great job explaining how Mellon wasn't a liquidationist and Hayek and Robbins weren't liquidationists.
Finally he argues, "libertarians react to the world's failing to conform to their model by asking where the world went wrong. Their heroic view of capitalism makes it difficult for them to accept that markets can be irrational, misunderstand risk, and misallocate resources or that financial systems without vigorous government oversight and the capacity for pragmatic intervention constitute a recipe for disaster."
First, there are libertarians who believe the market is efficient and there are libertarians who do not believe that. I would say that there are many many more in the latter category. I'm perfectly willing to say that markets can be irrational, misunderstand risk, and misallocate resources. However, I would also be willing to say that almost all of the times when they do this, you can point to a government regulation or a government program that is leading to this. The ABCT doesn't really describe the depth of our current situation on its own, but it sure does a good job explaining how the government encouraged the market to misallocate resources into the housing boom. The difference between the author and I is that I want to see market oversight and market regulation where he only is looking to the government for the solution. Well, I think there are plenty of cases where you can point to the government being the problem.
What's interesting to me, is that the death of socialism was predicted by Hayek and the Austrians several decades before it happened. In all reality, I'll admit that what the Soviets had and Chinese (before Deng) had wasn't really socialism. It was only really tried in the WW1 War Economy in Russia and it failed miserably, as predicted. The system that grew out of it, at least in Russia, was more of a market socialism, mostly socialism, but a little markets and freedom thrown in. Libertarians, mostly Hayekians, have predicted that the global financial system is unsustainable in its current form. Many predicted that the housing boom would lead to a situation like what we're currently experiencing. That's because what we don't have is capitalism and anyone with a brain should realize that. Even before the bail-out bill, we were on our third-way, though not as far to the socialist side as Europe. It's not that this doesn't fit with our model, but when you take our government and say we live in a capitalist country. People like me need and have stood up and said we do not live in a capitalist country. Our theories aren't to blame, our theories told us we would end up in this mess.
Monday, October 13, 2008
Malkiel's Wambulance
"It is very tempting to try to time the market. We all have 20/20 hindsight. It is clear that selling stocks a year ago would have been an excellent strategy. But neither individuals nor investment professionals can consistently time the market." - Burton Malkiel
My problem with this statement is that it is not specific. I would agree with him that investment professionals can't time the market on a short-term or medium-term basis, for the most part. However, pretty much everyone knew without 20/20 hindsight that there were big problems in the financial sector, more than a year ago. Some people, using insights from a variety of schools of thought or just plain, old common sense, got out of the market. You don't need to time the market when it goes up, you just need to know that business cycles happen and it pays to get out of the market when the downturn is coming. The regular investor can index away in the good times, but that doesn't mean that always indexing is the proper course of action.
My problem with this statement is that it is not specific. I would agree with him that investment professionals can't time the market on a short-term or medium-term basis, for the most part. However, pretty much everyone knew without 20/20 hindsight that there were big problems in the financial sector, more than a year ago. Some people, using insights from a variety of schools of thought or just plain, old common sense, got out of the market. You don't need to time the market when it goes up, you just need to know that business cycles happen and it pays to get out of the market when the downturn is coming. The regular investor can index away in the good times, but that doesn't mean that always indexing is the proper course of action.
Wednesday, October 8, 2008
Risk and Uncertainty
What I don't like about Free Exchange is that I have no idea who the authors are who contribute to it. I don't know to always read and who to take with a grain of salt.
Here they note that modern finance "seeks to turn uncertainty into risk. You cannot quantify uncertainty, and you cannot trade it. It is pre-finance—and it can be corrosive. Risk, on the other hand, is a probability distribution. It is quantifiable. You can model it and analyse it and it has a value. Therefore, you can trade it." They are right on what modern finance seeks to do and the difference between uncertainty and risk. My problem lies with modern finance and actually turning uncertainty into risk.
I view uncertainty and risk from a Knightian lens. Risk is measurable, uncertainty is not: "The essential fact is that "risk" means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomenon depending on which of the two is really present and operating. ... It will appear that a measurable uncertainty, or "risk" proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all. We ... accordingly restrict the term "uncertainty" to cases of the non-quantitive type."
So, that leads me to wonder can you actually convert uncertainty into risk or can you only reduce and spread out risk? Knight says that risk has an ex-ante probability distribution. In trying to get life insurance, from my perspective I have uncertainty because I cannot measure my risk, but the insurance company can and from their perspective it's a problem of risk. Subjectively, after I get insurance, I would know that after my death, my family would be taken care of. I would no longer have uncertainty (on this one part of the uncertainty of my death, there's a minimum of two others, like how and when), but the insurance company has gained a risk. Actually that may not be accurate. Maybe it is also uncertainty when it hits the balance sheet of the insurance company? Perhaps it is the subjective determination of the insurance company that makes it risk rather than uncertainty? This explanation seems lacking to me. A probability distribution seems outside of value and outside of the human mind. A more satisfying explanation, to me, is that the payouts on the insurance contract are uncertain by themselves for the individual and when transferred to the insurance company. They become risk when there are enough of them that produce a probability distribution.
As an example from modern finance, if you take a bunch of MBS and pool them into a CDO, you have certainly pooled them, but the pool of assets or the structure do not become a measureable probability distribution. So what you have with CDOs is not risk diversification, but taking a bunch of assets with uncertain payoffs, pooling them in a complex structure, and then sending different levels of uncertainty to people. Risk is not diversified, but different levels of uncertainty are spread out among the owners of the tranches to the CDO.
Here they note that modern finance "seeks to turn uncertainty into risk. You cannot quantify uncertainty, and you cannot trade it. It is pre-finance—and it can be corrosive. Risk, on the other hand, is a probability distribution. It is quantifiable. You can model it and analyse it and it has a value. Therefore, you can trade it." They are right on what modern finance seeks to do and the difference between uncertainty and risk. My problem lies with modern finance and actually turning uncertainty into risk.
I view uncertainty and risk from a Knightian lens. Risk is measurable, uncertainty is not: "The essential fact is that "risk" means in some cases a quantity susceptible of measurement, while at other times it is something distinctly not of this character; and there are far-reaching and crucial differences in the bearings of the phenomenon depending on which of the two is really present and operating. ... It will appear that a measurable uncertainty, or "risk" proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all. We ... accordingly restrict the term "uncertainty" to cases of the non-quantitive type."
So, that leads me to wonder can you actually convert uncertainty into risk or can you only reduce and spread out risk? Knight says that risk has an ex-ante probability distribution. In trying to get life insurance, from my perspective I have uncertainty because I cannot measure my risk, but the insurance company can and from their perspective it's a problem of risk. Subjectively, after I get insurance, I would know that after my death, my family would be taken care of. I would no longer have uncertainty (on this one part of the uncertainty of my death, there's a minimum of two others, like how and when), but the insurance company has gained a risk. Actually that may not be accurate. Maybe it is also uncertainty when it hits the balance sheet of the insurance company? Perhaps it is the subjective determination of the insurance company that makes it risk rather than uncertainty? This explanation seems lacking to me. A probability distribution seems outside of value and outside of the human mind. A more satisfying explanation, to me, is that the payouts on the insurance contract are uncertain by themselves for the individual and when transferred to the insurance company. They become risk when there are enough of them that produce a probability distribution.
As an example from modern finance, if you take a bunch of MBS and pool them into a CDO, you have certainly pooled them, but the pool of assets or the structure do not become a measureable probability distribution. So what you have with CDOs is not risk diversification, but taking a bunch of assets with uncertain payoffs, pooling them in a complex structure, and then sending different levels of uncertainty to people. Risk is not diversified, but different levels of uncertainty are spread out among the owners of the tranches to the CDO.
Sunday, September 21, 2008
Quotations
"Bob Rubin as Secretary of the Treasury — I mean, if he was a Hindu and he was being reincarnated, he'd come back as a pail because this guy bailed out everything you can imagine." - Kevin Phillips on Bill Moyers show
HT: Big Picture
HT: Big Picture
Wednesday, September 17, 2008
Taylor Rule
If certain people used certain data series (like MacroAdvisors' Monthly GDP series and CPI) to make a Taylor Rule, they might be pleasantly surprised by investing when Fed Funds is above what is suggested by the Taylor Rule.
Thursday, September 4, 2008
Why doesn't this exist
By law, a hedge fund needs to avoid having too many (100) accredited investors in order to avoid coming under additional regulations. An accredited investor can include a pension fund, a bank, a hedge fund of funds, someone with a million dollars, and other rich persons. An investment company can also act as an accredited investor. However, people who make less than 200k dollars in either of the past two years are not accredited investors and therefore cannot invest in hedge funds. Also, a fund may require a large initial investment that more marginal investors cannot invest in. Furthermore, some of the better funds are hard to invest in, even for large investors. And I'll add in the fact that fund of funds charge an additional layer of fees that are pretty absurd.
So I think if it is legal, there should be structures like a closed end fund that solely invests in a particular hedge fund marketed to these marginal investors in hedge funds. The ideal organization to launch something like this would be an already respected fund of funds, a global investment bank, or some other organization with many contacts among large hedge funds. You could start with like the five or ten largest hedge funds that are open to investors and then expand into more.
Again it would be best sold to the marginal hedge fund investors. Someone with a 500,000+ portfolio and willing to invest 50k in a hedge fund might be willing to do it if they can buy in with a share in a closed end fund that is investing many millions more in a fund. Seems like a winning idea to me, if it's legal and the organization behind it has the relationships.
So I think if it is legal, there should be structures like a closed end fund that solely invests in a particular hedge fund marketed to these marginal investors in hedge funds. The ideal organization to launch something like this would be an already respected fund of funds, a global investment bank, or some other organization with many contacts among large hedge funds. You could start with like the five or ten largest hedge funds that are open to investors and then expand into more.
Again it would be best sold to the marginal hedge fund investors. Someone with a 500,000+ portfolio and willing to invest 50k in a hedge fund might be willing to do it if they can buy in with a share in a closed end fund that is investing many millions more in a fund. Seems like a winning idea to me, if it's legal and the organization behind it has the relationships.
Sunday, August 31, 2008
Resistance and Support
This article has been mentioned on a few sites, I saw it first at Free Exchange.
It notes that prices that end in .99 induce customers to purchase a much higher percentage of sales than would be suggested. It is particularly true for lower priced items, but a purchase like a washer/dryer wouldn't have much effect.
While it is easy to design an experiment in a retail setting to test that theory, it would be much more difficult to test it in the financial markets. However, it seems to me that it would most evidently manifest itself in support and resistance points. I don't think support and resistance really translate well into trading systems. However, they can be useful in explaining behavior in the market (though I admit more value in hindsight than at the time). For instance, a stock might test its five year high several times and after breaking through on higher volume, it will surge significantly. A more active trader could see that and place buy stop orders above the resistance level. The problem with using a system is that sometimes it will go slightly above the resistance and then drop significantly. It is done more based on feel and that's also the problem with testing the effects of support and resistance lines using standard statistical techniques. A sustained, high volume move through a resistance point is more important than a weak one.
Getting back to the BBC article, a resistance line can be thought of like a price of 8 euro. The marginal asset manager might think that a stock is worth no more than 25 dollars. He would be interested in selling at 25 and willing to buy at 24.99. However, in the real world, the decision would really be how much of his portfolio to sell at 24.99 vs. 25.00 and not whether he is buying at 24.99. Due to the same effects noted in the BBC article, he would be much more willing to sell at 25 than at 24.99. The situation works in the reverse for a support line at 25, a manager might only be willing to buy a little at 25.01, but he might be willing to buy more at 25. You may ask shouldn't it be 24.99 where he wants to buy more to be consistent with the article? However, the real meat of the article is that people don't react linearly to these price changes, the same way that portfolio managers or traders might react.
There's one problem with this analysis that I can figure out so far, the prices in the BBC article are all small. While the prices of stocks can be reasonable on the face of it, even a retail investor would probably be buying 100 share lots and a PM would purchase significantly more. So the question is, is it the dollar value that matters or the price that matters? I'm not really sure of the answer, but I would say at the very least support and resistance are important enough that every technical trader would pay attention to them. There has to be some "inefficiency" here.
Testing this would be another problem, but I'm sure some finance professor is already looking into it. I really think that the key would be to look at when it comes to resistance points with light volume or heavy volume. For instance, after identifying resistance points, I would calculate whether they are above a moving average of volume to determine whether a day is a light volume or heavy volume day (might want to do relative to the market as a whole as well) and then I would look at how the stock performs relative to the market. I would identify resistance points using something like Average True Range relative to the stock price. For instance, a 6 dollar stock that moves 25 cents a day might have have support or resistance at the $1 level, but Goldman you might look 20 dollars away for support/resistance. That way you can do all the stocks together and then compare quartiles of stocks based on price or trading volume. Finally, all you have to do is look if high volume violations of resistance points or confirmations of support lines result in prices above those points over the next month (or 3) more so than the low volume.
That's probably a publishable paper right there, biggest problem is probably identifying the resistance points. It would make sense to do it in multiple ways to avoid the criticism that you measure it wrong. If you don't remove earnings days or something, you'll also need to make some kind of assumption to deal with them.
It notes that prices that end in .99 induce customers to purchase a much higher percentage of sales than would be suggested. It is particularly true for lower priced items, but a purchase like a washer/dryer wouldn't have much effect.
While it is easy to design an experiment in a retail setting to test that theory, it would be much more difficult to test it in the financial markets. However, it seems to me that it would most evidently manifest itself in support and resistance points. I don't think support and resistance really translate well into trading systems. However, they can be useful in explaining behavior in the market (though I admit more value in hindsight than at the time). For instance, a stock might test its five year high several times and after breaking through on higher volume, it will surge significantly. A more active trader could see that and place buy stop orders above the resistance level. The problem with using a system is that sometimes it will go slightly above the resistance and then drop significantly. It is done more based on feel and that's also the problem with testing the effects of support and resistance lines using standard statistical techniques. A sustained, high volume move through a resistance point is more important than a weak one.
Getting back to the BBC article, a resistance line can be thought of like a price of 8 euro. The marginal asset manager might think that a stock is worth no more than 25 dollars. He would be interested in selling at 25 and willing to buy at 24.99. However, in the real world, the decision would really be how much of his portfolio to sell at 24.99 vs. 25.00 and not whether he is buying at 24.99. Due to the same effects noted in the BBC article, he would be much more willing to sell at 25 than at 24.99. The situation works in the reverse for a support line at 25, a manager might only be willing to buy a little at 25.01, but he might be willing to buy more at 25. You may ask shouldn't it be 24.99 where he wants to buy more to be consistent with the article? However, the real meat of the article is that people don't react linearly to these price changes, the same way that portfolio managers or traders might react.
There's one problem with this analysis that I can figure out so far, the prices in the BBC article are all small. While the prices of stocks can be reasonable on the face of it, even a retail investor would probably be buying 100 share lots and a PM would purchase significantly more. So the question is, is it the dollar value that matters or the price that matters? I'm not really sure of the answer, but I would say at the very least support and resistance are important enough that every technical trader would pay attention to them. There has to be some "inefficiency" here.
Testing this would be another problem, but I'm sure some finance professor is already looking into it. I really think that the key would be to look at when it comes to resistance points with light volume or heavy volume. For instance, after identifying resistance points, I would calculate whether they are above a moving average of volume to determine whether a day is a light volume or heavy volume day (might want to do relative to the market as a whole as well) and then I would look at how the stock performs relative to the market. I would identify resistance points using something like Average True Range relative to the stock price. For instance, a 6 dollar stock that moves 25 cents a day might have have support or resistance at the $1 level, but Goldman you might look 20 dollars away for support/resistance. That way you can do all the stocks together and then compare quartiles of stocks based on price or trading volume. Finally, all you have to do is look if high volume violations of resistance points or confirmations of support lines result in prices above those points over the next month (or 3) more so than the low volume.
That's probably a publishable paper right there, biggest problem is probably identifying the resistance points. It would make sense to do it in multiple ways to avoid the criticism that you measure it wrong. If you don't remove earnings days or something, you'll also need to make some kind of assumption to deal with them.
Wednesday, August 20, 2008
TAA and switching to bonds
First off, anybody see the ads for Crusoe on NBC during the Olympics, makes me want to break out my MES.
Second, if anyone remembers/cares I took the level 2 exam of the CFA back in June and ended up passing. So congratulations to my brothers.
Third, some ideas come to me that are rather simple, but make a lot of sense looking back on them. I had tried using bonds instead of cash in the TAA model previously, but was unimpressed due to larger volatility. However, I hadn't considered using the TAA investment in bonds. In other words, use the return series that invests in bonds when above the 10 month average and cash otherwise instead of a pure cash index for some asset classes.
The two asset classes I meant to target with this strategy were the two that historically have performed the worst on a Sharpe ratio basis, commodities and foreign equities, in the TAA strategy. I still have the TAA rule for each, but before I evaluate that I look at whether the US equity or foreign equities are below the 10 month average, if that is the case, I will have them invest in the bond TAA strategy. Then, if above the 10 month MA, they invest in that asset class, otherwise they invest in cash.
For comparison, in recent years (since 1990), the TAA strategy for commodites returned 8.8% annually (16.69% s.d., Sharpe .27 with r.f. @ period average), this simple change increases the return to 13.6% (11.8% s.d., Sharpe .79). For foreign equities, the return goes from 7.6% (12.59% s.d., Sharpe .27) to 12.2% return (12.43% s.d., Sharpe .64). The overall strategy improves from 10.7% return (6.85% s.d., Sharpe .94) to 12.5% return (7.01% s.d., 1.17 Sharpe).
Again, the reason I focused on these two was because they perform the worst. Using the strategy on US equities seems to work (Sharpe goes to 1.16) and for REITs (Sharpe goes to 1.15). Overall Sharpe goes down slightly, but for the individual asset classes the Sharpe increases suggesting the decline is due to decreased diversification and higher variances. A 5% increase in the Sharpe ratio individually doesn't impress me as much as the ones for commodities and foreign equities.
I also tested my original intention, just using the bond TAA instead of cash (and nothing more complicated like above) and it works well for REITs, but works best for equities. A marginal improvement on a risk-adjusted basis for the portfolio, but interesting nonetheless.
Second, if anyone remembers/cares I took the level 2 exam of the CFA back in June and ended up passing. So congratulations to my brothers.
Third, some ideas come to me that are rather simple, but make a lot of sense looking back on them. I had tried using bonds instead of cash in the TAA model previously, but was unimpressed due to larger volatility. However, I hadn't considered using the TAA investment in bonds. In other words, use the return series that invests in bonds when above the 10 month average and cash otherwise instead of a pure cash index for some asset classes.
The two asset classes I meant to target with this strategy were the two that historically have performed the worst on a Sharpe ratio basis, commodities and foreign equities, in the TAA strategy. I still have the TAA rule for each, but before I evaluate that I look at whether the US equity or foreign equities are below the 10 month average, if that is the case, I will have them invest in the bond TAA strategy. Then, if above the 10 month MA, they invest in that asset class, otherwise they invest in cash.
For comparison, in recent years (since 1990), the TAA strategy for commodites returned 8.8% annually (16.69% s.d., Sharpe .27 with r.f. @ period average), this simple change increases the return to 13.6% (11.8% s.d., Sharpe .79). For foreign equities, the return goes from 7.6% (12.59% s.d., Sharpe .27) to 12.2% return (12.43% s.d., Sharpe .64). The overall strategy improves from 10.7% return (6.85% s.d., Sharpe .94) to 12.5% return (7.01% s.d., 1.17 Sharpe).
Again, the reason I focused on these two was because they perform the worst. Using the strategy on US equities seems to work (Sharpe goes to 1.16) and for REITs (Sharpe goes to 1.15). Overall Sharpe goes down slightly, but for the individual asset classes the Sharpe increases suggesting the decline is due to decreased diversification and higher variances. A 5% increase in the Sharpe ratio individually doesn't impress me as much as the ones for commodities and foreign equities.
I also tested my original intention, just using the bond TAA instead of cash (and nothing more complicated like above) and it works well for REITs, but works best for equities. A marginal improvement on a risk-adjusted basis for the portfolio, but interesting nonetheless.
Monday, August 18, 2008
TAA and commodity overheating
Just wanted to do a quick blog on the TAA model noted earlier on this blog.
I created an extension to the model based on it achieving a certain return after a set number of months. After that, I looked at whether it makes sense to get out completely or to use a different exit rule (like a 5 month MA instead of 10 month MA). It doesn't get back in until the next time the 10 month MA crosses back over. The general idea is that if an asset class goes up that significantly in such a short period of time, it is unlikely that the returns in the future will be strong, despite being above the 200 day return
I started with a 20% return in a quarter and getting out completely. In that model, there is an improved return. However, closer analysis reveals that it is almost exclusively in the commodities sector. It stays out of almost five years worth trading (239 months vs. 294 months) changing an asset class with 8.8% return and 16.8% volatility to one with a 13.3% return and 13.12% volatility.
I also experimented with different combinations of returns, periods of time, and whether to use a MA average rule to get out or just permanently get out. Several of them perform better than the original TAA rule, but almost all the benefit comes from the commodities sector and the other sectors don't improve enough to be worth it.
I should note that my analysis didn't include the current period (ended in early 08), but the knowledge I take from my analysis is that when commodities rise 20% in a quarter, they historically have a correction.
Note: I also created a more complicated algorithm for the other asset classes that will get back in if the past three months did not have the quarterly 20% return which seems to help reduce volatility and improves the portfolios Sharpe ratio (though the individual ones don't appear that much better. Basically the same thing as the commodity strategy except it is willing to get back in (keeps the same returns for the commodity strategy). 11% return for the overall strategy here with 5.43% volatility. (compared to about 6.85% for the original TAA model).
I created an extension to the model based on it achieving a certain return after a set number of months. After that, I looked at whether it makes sense to get out completely or to use a different exit rule (like a 5 month MA instead of 10 month MA). It doesn't get back in until the next time the 10 month MA crosses back over. The general idea is that if an asset class goes up that significantly in such a short period of time, it is unlikely that the returns in the future will be strong, despite being above the 200 day return
I started with a 20% return in a quarter and getting out completely. In that model, there is an improved return. However, closer analysis reveals that it is almost exclusively in the commodities sector. It stays out of almost five years worth trading (239 months vs. 294 months) changing an asset class with 8.8% return and 16.8% volatility to one with a 13.3% return and 13.12% volatility.
I also experimented with different combinations of returns, periods of time, and whether to use a MA average rule to get out or just permanently get out. Several of them perform better than the original TAA rule, but almost all the benefit comes from the commodities sector and the other sectors don't improve enough to be worth it.
I should note that my analysis didn't include the current period (ended in early 08), but the knowledge I take from my analysis is that when commodities rise 20% in a quarter, they historically have a correction.
Note: I also created a more complicated algorithm for the other asset classes that will get back in if the past three months did not have the quarterly 20% return which seems to help reduce volatility and improves the portfolios Sharpe ratio (though the individual ones don't appear that much better. Basically the same thing as the commodity strategy except it is willing to get back in (keeps the same returns for the commodity strategy). 11% return for the overall strategy here with 5.43% volatility. (compared to about 6.85% for the original TAA model).
Sunday, August 3, 2008
The Economics of Registering to Vote
Well, I should say that it is more the cost/benefit analysis of registering to vote. I recently moved from Queens to Jersey City and there were some thirty-ish professionals outside the PATH entrance who wanted to register me to vote. I am registered in Indiana (where KF's parents live and went to college) and still have my Indiana driver's license.
Walking to the registration table, I figured that (outside of time wasted filling out the form) I was making a cost-less decision. I probably won't vote, but I figure that the margin difference in New Jersey in the general election will be smaller than the margin difference in Indiana. So, if my vote matters at all (probably not), it matters a fraction more in Jersey than Indiana. So the benefits side of the calculus is the expected value of me voting and that influencing the election (probably of me voting times value of my vote and also all future voting decisions and their weight discounted to the present).
However, I didn't realize the costs of voting until a man who either was an unemployed, alcoholic construction worker or homeless (probably the latter) began to convince me not to register. His early arguments weren't that convincing focusing mostly on how much the vote matters and staying off the grid (the first I already knew, the second I didn't care about). However, he mentioned that one of two places they pull jury duty from is the voter rolls. If I am pulled to do jury duty twice a decade in New Jersey that means that I earn like $3.50 (how much the lochness monster takes) and lose a vacation day, I presume.
The problem of how to value the cost is difficult for two reasons. First, the call for jury duty is random and could be modeled like a Poisson process. An easy work around would be that I have jury duty in five years and ten years and discount the costs on those dates back at 6% or so. The second difficulty is valuing a vacation day. I can assume that the value of a vacation day would increase as my income increases since leisure would become more scarce and I would imagine that my income grows significantly five to ten years from now. I could probably model it, but it shouldn't matter that much, as will be seen. My gut feeling is that, in terms of dollars, a vacation day shouldn't affect salary (I get paid the same) and you could assume that it doesn't affect your bonus. However, if you don't use all of your vacation days, you might have worked harder and deserved a higher bonus by accomplishing more work. There is some probability that it will increase your bonus by not taking the vacation day, but it is small and would probably not be a big effect after discounting*. The real place to value the vacation day is in subjective value. The proper trade off is the net benefit of sitting in the sun or skiing out west or sitting in a jury room.
The subjective benefit to skiing with friends relative to sitting in a jury room, for me, outweighs the money (from bonus or the 3.50) and the benefits of being able to vote in New Jersey. I'll stay registered in Indiana and avoid jury duty like the plague.
I'm pretty sure they don't let people who think like me on juries anyway.
*It is small on the margin because it would probably only be if you had like leftover vacation days from the day before and just dropped out from work for like a month. That would probably affect bonus.
Walking to the registration table, I figured that (outside of time wasted filling out the form) I was making a cost-less decision. I probably won't vote, but I figure that the margin difference in New Jersey in the general election will be smaller than the margin difference in Indiana. So, if my vote matters at all (probably not), it matters a fraction more in Jersey than Indiana. So the benefits side of the calculus is the expected value of me voting and that influencing the election (probably of me voting times value of my vote and also all future voting decisions and their weight discounted to the present).
However, I didn't realize the costs of voting until a man who either was an unemployed, alcoholic construction worker or homeless (probably the latter) began to convince me not to register. His early arguments weren't that convincing focusing mostly on how much the vote matters and staying off the grid (the first I already knew, the second I didn't care about). However, he mentioned that one of two places they pull jury duty from is the voter rolls. If I am pulled to do jury duty twice a decade in New Jersey that means that I earn like $3.50 (how much the lochness monster takes) and lose a vacation day, I presume.
The problem of how to value the cost is difficult for two reasons. First, the call for jury duty is random and could be modeled like a Poisson process. An easy work around would be that I have jury duty in five years and ten years and discount the costs on those dates back at 6% or so. The second difficulty is valuing a vacation day. I can assume that the value of a vacation day would increase as my income increases since leisure would become more scarce and I would imagine that my income grows significantly five to ten years from now. I could probably model it, but it shouldn't matter that much, as will be seen. My gut feeling is that, in terms of dollars, a vacation day shouldn't affect salary (I get paid the same) and you could assume that it doesn't affect your bonus. However, if you don't use all of your vacation days, you might have worked harder and deserved a higher bonus by accomplishing more work. There is some probability that it will increase your bonus by not taking the vacation day, but it is small and would probably not be a big effect after discounting*. The real place to value the vacation day is in subjective value. The proper trade off is the net benefit of sitting in the sun or skiing out west or sitting in a jury room.
The subjective benefit to skiing with friends relative to sitting in a jury room, for me, outweighs the money (from bonus or the 3.50) and the benefits of being able to vote in New Jersey. I'll stay registered in Indiana and avoid jury duty like the plague.
I'm pretty sure they don't let people who think like me on juries anyway.
*It is small on the margin because it would probably only be if you had like leftover vacation days from the day before and just dropped out from work for like a month. That would probably affect bonus.
Saturday, July 19, 2008
SEC exempts Market Makers
This big news in the market these days has been the new SEC naked short sale regulations. According to this article, market makers in equities and options have been exempted from the short sale regulations.
In my view there are three main criticisms of the original regulations. The first is resolved by this adjustment. The options market, in particular, was effected by these regulations since it can disrupt hedging operations. Since activity in the options market feeds into the equity markets, if you create regulations that make it less likely someone will make markets in some options, there will be some big effects. The second criticism is the one pointed out by Mish several times that the firms exempted from the shorts has been chosen rather arbitrarily. Finally, is the whole this prevents these companies from going quickly to a fair value and serves as a form of relief for privileged, politically well-connected banks. People lost their life savings on internet companies and rules like this weren't put in place. And I'll leave it at that.
In my view there are three main criticisms of the original regulations. The first is resolved by this adjustment. The options market, in particular, was effected by these regulations since it can disrupt hedging operations. Since activity in the options market feeds into the equity markets, if you create regulations that make it less likely someone will make markets in some options, there will be some big effects. The second criticism is the one pointed out by Mish several times that the firms exempted from the shorts has been chosen rather arbitrarily. Finally, is the whole this prevents these companies from going quickly to a fair value and serves as a form of relief for privileged, politically well-connected banks. People lost their life savings on internet companies and rules like this weren't put in place. And I'll leave it at that.
Thursday, July 17, 2008
Merger Arbitrage
*I generally don't post about specific stocks, but I haven't gotten around to some of the research I meant to do and something I am looking at is increasingly looking worthwhile.
Merger arbitrage is the art of buying companies that are getting acquired and selling companies that are acquiring. When the merger goes through, you collect the spread between them. If the merger doesn't go through, the spread widens and you lose money.
Alpha Natural Resources (ANR) is a coal stock and Cleveland-Cliffs (CLF) is an iron and coal stock. Cleveland-Cliffs announced on July 15th that it will purchase ANR for $22.23 and .95 shares of CLF. On the 16th, ANR opened up around 119 after trading around 95 the past few days and then proceeded to tank back down to a close of around 96 at the close of the 17th. CLF was trading around 110 prior to the announcement and has come down to about 97.25.
Based on current prices, 100 shares of ANR should be worth 22.23*100+97.25*95=$11,462 and only cost $9,580 on the market. Since the value of the ANR is dependent on the value of CLF, you would sell short the CLF in a merger arb situation. This way when you receive the 95 shares of CLF you can deliver them to whomever you borrowed the stock from.
For example, assuming the existing prices are where you buy and short and the merger closes, that means that ANR will be priced such that what you can buy equals 22.23*100+p*95, where p is the price of CLF. If CLF closes out at 100, ANR should be worth 117.23 per share. After your ANR shares are converted to CLF, you can close out your short (worth 95*100 dollars) and keep 2223 (22.23*100). The merger is supposed to complete at the end of the year and depending on how your margin account is handled, it looks like you could put up about 20k for an annualized return of about 20%.
That's not to say that this isn't risky. Merger arbitrage is a very risky business and it admittedly isn't mine. Given how that ANR has fallen fairly significantly since the announcement came out, the market is pricing (excluding shorting costs and TVM) that the stock is only worth three-quarters a share of CLF. I will be waiting for more details, particularly the proxy. Do your homework and certainly don't blindly follow me. I would have bought it on the open of 7/16 and have lost like 20 dollars a share already on ANR and not made it back on CLF. At these prices and this spread, I feel like it would be less risky given the potential gain.
SEC 8-K form
Press Release
edit: Harbinger Capital increased a position from 3/31 of about 8.73% to about 18.36% and announced in a 13D that they would oppose the merger.
Merger arbitrage is the art of buying companies that are getting acquired and selling companies that are acquiring. When the merger goes through, you collect the spread between them. If the merger doesn't go through, the spread widens and you lose money.
Alpha Natural Resources (ANR) is a coal stock and Cleveland-Cliffs (CLF) is an iron and coal stock. Cleveland-Cliffs announced on July 15th that it will purchase ANR for $22.23 and .95 shares of CLF. On the 16th, ANR opened up around 119 after trading around 95 the past few days and then proceeded to tank back down to a close of around 96 at the close of the 17th. CLF was trading around 110 prior to the announcement and has come down to about 97.25.
Based on current prices, 100 shares of ANR should be worth 22.23*100+97.25*95=$11,462 and only cost $9,580 on the market. Since the value of the ANR is dependent on the value of CLF, you would sell short the CLF in a merger arb situation. This way when you receive the 95 shares of CLF you can deliver them to whomever you borrowed the stock from.
For example, assuming the existing prices are where you buy and short and the merger closes, that means that ANR will be priced such that what you can buy equals 22.23*100+p*95, where p is the price of CLF. If CLF closes out at 100, ANR should be worth 117.23 per share. After your ANR shares are converted to CLF, you can close out your short (worth 95*100 dollars) and keep 2223 (22.23*100). The merger is supposed to complete at the end of the year and depending on how your margin account is handled, it looks like you could put up about 20k for an annualized return of about 20%.
That's not to say that this isn't risky. Merger arbitrage is a very risky business and it admittedly isn't mine. Given how that ANR has fallen fairly significantly since the announcement came out, the market is pricing (excluding shorting costs and TVM) that the stock is only worth three-quarters a share of CLF. I will be waiting for more details, particularly the proxy. Do your homework and certainly don't blindly follow me. I would have bought it on the open of 7/16 and have lost like 20 dollars a share already on ANR and not made it back on CLF. At these prices and this spread, I feel like it would be less risky given the potential gain.
SEC 8-K form
Press Release
edit: Harbinger Capital increased a position from 3/31 of about 8.73% to about 18.36% and announced in a 13D that they would oppose the merger.
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