Free Ebook Pairs Trading: A Bayesian Example, by Stefan Hollos, J. Richard Hollos
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Pairs Trading: A Bayesian Example, by Stefan Hollos, J. Richard Hollos
Free Ebook Pairs Trading: A Bayesian Example, by Stefan Hollos, J. Richard Hollos
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Have you ever wondered whether Bayesian analysis can be applied toward the stock market? We did, and set out to investigate.
This 70 page ebook shows you how to find relationships between stocks or exchange traded funds (ETFs) using Bayesian analysis.
A relationship that most traders are probably familiar with is linear correlation. This is sometimes used as the basis for pairs trading. But linear correlation is just one way that stocks or ETFs can be related.
The analysis we present in this ebook can be used to exploit almost any kind of relationship that may exist between stocks or ETFs. The ebook will show how to calculate the probability of a stock or ETF ending the day up or down based on what other stocks or ETFs are doing.
A probability is more useful than a simple up or down signal. It quantifies the certainty of a prediction and allows a trader to take a position consistent with a given level of risk.
Any active trader should find the techniques presented in this ebook useful. We are only going to examine the relationships in one small group of ETFs as an example of what is possible but the same techniques will work for any set of stocks, ETFs, or even bonds.
The tool we use to calculate the probability of a positive or negative return on a stock or ETF is called a Bayesian classifier. It is called a classifier because it calculates probabilities for only two discrete outcomes: positive or negative.
The method we use to calculate these probabilities is called Bayes' Theorem.
In this ebook we not only show you the results of our analysis, but we show you HOW to do the analysis,... AND we give you the Bayesian classification software (available on our website) that we have developed FREE of charge. The software alone is worth several times that of this ebook.
Disclaimer
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
- Sales Rank: #438538 in eBooks
- Published on: 2012-08-31
- Released on: 2012-08-31
- Format: Kindle eBook
Most helpful customer reviews
3 of 3 people found the following review helpful.
Statistical Pairs Trading, Short and Sweet
By Dr. Mitchell R. White
I enjoyed this volume, a quick presentation on pairs trading with some worked examples. I also like it for its ability to get to the point. First a disclaimer: I"m not a trader. However, I am interested in relationships between variables, as I work in statistical inference. because the book begins with Bayes' Theorem, a simple and powerful equation in probability, I was drawn to the subject to learn how others use Bayes in their fields.
Since many folks who trade stocks this way (pairs trading and related) are not formal statisticians, they rely on knowing a bit about goes on "under the hood" and then they drive using programs. This is not an exposition of the code or the programs' details, however. That said, I did enjoy their discussion about binary classification and the simple diagrams they used to show the power (or lack thereof, at times) of the basic algorithm. I also found their presentation of the key diagnostics, such as accuracy, true positive rate, and so on, to be clear and on the mark. The "confusion matrix" is readily recognized by statisticians as a simple contingency table, and so the following discussion is easy to read.
Electrical engineers will recognize the ROC curve. The authors avoid a lot of potential distractions by not diving into the details of receiver operating characteristics; better to simply label it, show it, and press. The extensive presentation on what different curves look like and what they mean, in a practical sense, is nicely done.
Since I have no intention of using this method for trading purposes, I cannot address the adequacy thereof. The apparent accuracy of the method, though, is impressive: 73.9% for one case, where a fair coin would be approximately zero. I hope to perform similar magic on predictive situations for my clients in manufacturing, and I'm thankful to have read this book.
For my tastes, the improvements the authors could make would include a glossary, a short but detailed exposition on how to get, install and test the basic programs, and a bit more balance between what works (or has worked) and what doesn't.
All in all, though, a nice pamphlet and good value.
2 of 3 people found the following review helpful.
The book requires programs you may not have.
By Spanky
I purchased this book because I am curious about pairs trading. I'm disappointed in this book because in order to get the most benefit from it one needs to have some familiarity with c programming, unix and AWK programming (information that wasn't provided chapter 2 of the book). Before purchasing the book, I downloaded the free sample that's available for the Kindle. I do this to see if the material requires software or specific knowledge that is outside of my education level. I certainly believe the author of the book should have put this crucial information either in the Disclaimer section or in Chapter 1.
Oh, by the way, the author's disclaimer states that the "results are based on simulated or hypothetical performance results that ...do not represent actual trading."
My disclaimer: I am not a professional trader, but I do trade options on a regular basis. Moreover, I am not a mathematician, but I have a relatively strong background in mathematics, having had courses in second year calculus and differential equations (but I took these about 40 years ago). I also have a minor in applied statistics. There is a chance that I misunderstood the information provided in the book. so, if that is the case, I apologize in advance.
I went to the web page provided in the book (www.extrom.com) and I found it to be full of interesting information.
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