How to Use Math to Gain Success in Stock Trading
With the prominence that mathematical prodigies have in movies and TV shows, applying math to everything from finding a killer to winning in Vegas, you could be forgiven for thinking that math will help you conquer the stock market. Were that true, someone likely would have done it by now. But math can help you do better in stock trading. It's just a matter of recognizing risks and probabilities.
No mathematical system, however advanced, can predict the actual future. But sophisticated mathematics can calculate the probability of events. This works in the stock market by helping traders minimize the likelihood that something bad might happen before a certain date or other precursor. It works like insurance: Actuarial tables cannot predict the date or cause of your death, for example, but they can give insurers a better general idea of the time frame or nature of your demise.
Losing Less Often
Successful stock traders such as Warren Buffet often give the impression that successful trading means 100 percent accuracy. But most successful traders are right only half the time at best. Simple mathematics shows that "winning" on only four or five of every 10 trades can put a trader ahead, depending on how much was won versus how much was lost. Earning $2,000 on four trades while losing $1,500 on the other six still puts you ahead by $500. Mathematics, teamed with patience, builds stock market wealth more reliably than "big score" attempts.
Gaussian Laws vs. Power Laws
Gaussian math calculates random fluctuations of uncorrelated entities. This sounds ideal for playing the undulating stock market, except that stock market transactions are all correlated. Gaussian logic, therefore, cannot predict sudden crashes. Power law, on the other hand, calculates how changes in the value of one quantity affect another quantity, such as how a company's value affects stock prices in its industry. This helps calculate standard deviations, which can help traders better understand potential risks and allow them to buy or sell accordingly.
"Quants" are traders who use quantitative analysis to make financial trades. Computer-based quantitative analysis, which studies how amounts, or quantities, relate to each other, is the most common mathematical model used by trading houses. The field includes algorithms, which study patterns of behavior in entities such as the financial sector. These calculations can help identify potential risks ahead, but overreliance on quantitative models and algorithms can lead to wild speculation, imprudent investing and "flash crashes." This is when the market takes an unanticipated nosedive.