Monday, August 25, 2008
Behavioral finance we can all use
In their new book "Nudge: Improving Decisions About Health, Wealth and Happiness", U of Chicago economist Richard Thaler (of behavioral finance fame) and Harvard law professor Cass Sunstein gave a few pieces of personal finance advice, one of which coincided with my point in a previous post: buy insurance with the largest deductible available. The others are: don't invest much in your employer's stock, don't pay points on mortages, and don't pay for extended warranties. The book is reviewed in the NYT Book Review.
Friday, August 22, 2008
Predicting SP500 futures using investor sentiment
Ronald Domingues, an economics graduate student, has done an interesting study of how well a group of qualified investors with superior skills can predict the movement of the SP500 index. This group of qualified investors are selected by their track records of making correct predictions, and as a result of submitting their predictions going forward, they are eligible to be notified of the average predictions of other qualified investors, thus enabling them to make a better informed investment decision.
In other words, the elite will benefit from the collective wisdom of other elites -- sort of like the real world, isn't it?
How well does it work in practice? Well, they correctly predicted whether SP500 index will go up, down, or flat, a whopping 65.2% of the time. The details can be found on his website, where you can also sign up to see if you can join the elite.
In other words, the elite will benefit from the collective wisdom of other elites -- sort of like the real world, isn't it?
How well does it work in practice? Well, they correctly predicted whether SP500 index will go up, down, or flat, a whopping 65.2% of the time. The details can be found on his website, where you can also sign up to see if you can join the elite.
Saturday, August 16, 2008
More on parameterless trading model
I have written before that my ideal trading model is one that has no parameters, and what ways there are to accomplish this. Actually, I forgot to mention that a trading strategy proposed by Dr. Andrew Lo discussed previously is in fact parameterless, and the technique is so general that it can be applied to any mean-reverting strategy.
The technique is simply this: maintain a long (or short) portfolio with capital proportional to the distance between a supposedly mean-reverting measure and its long-term mean value.
For e.g. if you are pair-trading PEP vs KO, and you believe that the spread between PEP and KO is mean-reverting, then this spread is the mean-reverting measure you should employ.
As the spread moves away from its mean, keep buying (or shorting) the spread in equal dollar amount. And as the spread reverts, keep selling (or buying) the spread in the same dollar amount. What this dollar amount should be depends on: a) the total buying power you possess, b) the expected maximum deviation of the spread from its mean, and c) how often you intend to buy/short. Note that point c is not a parameter: it is arbitrary and limited only by transaction costs, technology, and other operational issues. As for the expected maximum deviation, it can be obtained by observing the history of the spread since inception.
This scheme thus obviates the need for entry or exit thresholds, and with them, the possibility of data-snooping bias. (You may still want to impose an entry threshold based on transaction cost consideration - but that would not count as a free parameter.)
The technique is simply this: maintain a long (or short) portfolio with capital proportional to the distance between a supposedly mean-reverting measure and its long-term mean value.
For e.g. if you are pair-trading PEP vs KO, and you believe that the spread between PEP and KO is mean-reverting, then this spread is the mean-reverting measure you should employ.
As the spread moves away from its mean, keep buying (or shorting) the spread in equal dollar amount. And as the spread reverts, keep selling (or buying) the spread in the same dollar amount. What this dollar amount should be depends on: a) the total buying power you possess, b) the expected maximum deviation of the spread from its mean, and c) how often you intend to buy/short. Note that point c is not a parameter: it is arbitrary and limited only by transaction costs, technology, and other operational issues. As for the expected maximum deviation, it can be obtained by observing the history of the spread since inception.
This scheme thus obviates the need for entry or exit thresholds, and with them, the possibility of data-snooping bias. (You may still want to impose an entry threshold based on transaction cost consideration - but that would not count as a free parameter.)