When a day trader trades any market, there are always risks. One risk is missing when an equity is overbought or oversold. In other words, the market is about to turn around and you are still happily placing trades on the assumption that the current trend will continue. A technical tool that can help avoid this problem is a stochastic indicator. There are Markov chains and continuous time stochastic processes. Do you need to know the difference? A risk in trading is getting so involved with the details of a technical indicator that you forget that you are only asking it to answer a simple question about the market being overbought or oversold. Such can be the case with things like Markov Chains and continuous time stochastic processes.
Introducing the Relationship Between Stock Markets and Markov Chains or Continuous Time Stochastic Processes
Stochastics evolved out of mathematics and the study of seemingly random processes like the movements of gas molecules. Their use in stock markets started in the 1950s when George Lane adapted a simplified version of stochastics to help a trader decide if it is time to buy or sell a stock. A continuous time stochastic process involves numbers that change with time instead of a set of constants. This is applicable to the stock market where prices change over time. A Markov chain is a continuous stochastic process in which each succeeding event is derived from the one before it. This, again, is how the stock market works. The point is that stochastics help tell a day trader if they are looking at an overbought or oversold position.
Examining How These Models Can Be Used to Predict Future Stock Prices
You do not need to be a mathematical genius to benefit from stochastics. Stochastics can be based on months, weeks, or days. A common approach is to pick the prior 14 time periods (days). The charting software on your trading platform will do the calculations for you. Based on prior session highs and lows the stochastic calculation spits out indicators that can be superimposed on the price chart or displayed below. Day traders typically use this indicator along with at least one other to help spot overbought or oversold stock positions.
Explaining the Differences Between Markov Chains and Continuous Time Stochastic Processes
Remember our warning about getting so involved in the technical details of your indicators that you forget that you are using them for a specific, simple purpose? The future development of a Markov chain depends on its current state and not on how it got there. A continuous time stochastic process takes into account the process of getting to the current state. As a practical day trader, you likely do not care about the specifics so long as the indicator tells you when to buy or sell.
Looking at the Advantages and Disadvantages of Using These Models for Stock Market Analysis
Technical indicators, including stochastics, are useful. However, no technical tool is perfect. Successful day traders commonly use a couple of indicators. With stochastics it is essential to identify the current trend before relying on the stochastic indicator. It is common for day traders to combine a stochastic indicator with a moving average. Successful day traders have learned discipline in choosing, entering, managing and exiting their trades. Stochastics or any technical indicator need to be used as part of this approach and not as a stand alone cure all.
Analyzing an Example of a Markov Chain or Continuous Time Stochastic Process Used in Stock Market Analysis
Since we are writing this for day traders and not for professors of mathematics, we will dispense with the underlying mathematics
You are day trading commodity futures and using a moving average to average out the confusion of moment by moment fluctuations. You see an upward trend that you suspect may be exhausting itself. You look at your stochastic indicator to see if it is showing you an overbought position or not. You do not need to do the calculations because your platform does them. You are asking the indicator to answer a simple question.
Summarizing the Key Takeaways About the Relationship Between Stock Markets and Markov Chains or Continuous Time Stochastic Processes
Stochastic processes, continuous time processes, and Markov chains are mathematical tools that have a wide range of uses in science and technology. They have a specific use for stock traders. A simple application of a stochastic process helps a day trader identify overbought or oversold positions that often occur as a market trend is about to expire. The trader, or investor, does not want to bail out and miss out on ongoing profits and they do not want to get blindsided either. Here is where these indicators come into play.