Probability and Statistics in Finance
Probability and statistics are used a lot within the financial field. They are used to build mathematical models, to estimate risk and to enable the professionals within finance to make decisions based on historical data. This is a very wide field, however this page will cover some of the fundamentals and give example of usage areas.
Technical Analysis (TA)
Technical analysis refers to when you, based on historical data, make decisions in the present whether you should buy or sell a certain financial good (stocks, ETF’s, funds, commodities etc). In other words, technical analysis tries to predict the future based on historical data. This does make sense in some ways, for example, if you assume that the stock market is cyclical, that it goes up and downs according to a certain pattern. Technical analysis also makes sense if you think that it is possible to model and predict human behavior. There has been a lot of studies and research within the field of technical analysis, and the results are perhaps not so positive. In a study made in 2008 [1], researchers showed that “..over 5,000 popular technical trading rules are not consistently profitable in the 49 country indices that comprise the Morgan Stanley Capital Index once data snooping bias is accounted for.”. In simple terms, they showed that over 5000 popular technical analysis techniques, or rules, were not able to earn any money on the market. Hence, at least to this paper, and a lot of peoples opinions, technical analysis does not work in a real world scenario. However, despite all of this, there is still a lot of people who believe in, and use technical analysis every day, and research is still being made in the field.
However, to gain a good understanding of technical analysis, it is important to have a good understanding of probability and statistics.
Is it necessary to understand probability and statistics?
Above we discussed that technical analysis (TA) may not, on average, be a successful strategy according to the study done where 5000 TA techniques were evaluated. However, it is important to note that this is not “proof” that TA does not work, it is simply proof of, that in this case, for this setting, TA techniques were not successful for the period evaluated. So it is to be seen more as a indication, a lead, to be careful to believe to much in TA techniques. To improve and create new TA techniques, it is important to have a fundamental understanding of probability and statistics, since much of these techniques build upon this.
References:
[1] Marshall, Ben R. and Cahan, Rochester H. and Cahan, Jared, Technical Analysis Around the World (August 1, 2010). Available at SSRN: https://ssrn.com/abstract=1181367 or http://dx.doi.org/10.2139/ssrn.1181367