I’m beginning a series on how all traders can use TradersStudio to their maximal advantage. I figure this has a couple of purposes: the first is to show fellow traders some of the tips and tricks to developing amazing systems, and the second is to show how TradersStudio fits into the broader picture of trading. TradersStudio is, after all, a tool to help traders understand how to develop and test real-world strategies. Showing a feature of this product will hopefully both spur stellar trading ideas in you and also show you how to implement those within the program.
But before I show you how TradersStudio solves all these problems, I must first show what the problems are in developing winning automated trading strategies.
This concept of developing automated strategies is very important. In my conversations with traders, I have found a small percentage of stock traders who trade using a mechanical approach. I find it hard to believe, but many stock traders believe that mechanical systems cannot be developed to trade stocks that outperform a ‘Buy-and-Hold’ strategy. A major reason is that they do not understand the issues in terms of preparing the data for stock trading and the effects that it has on the results.
Most stock traders use what is called ‘split-adjusted’ data, which is similar to ‘ratio-adjusted’ data in commodities. The problem in using this type of data is that the adjustment destroys the dollar returns, historical daily range, and the original price levels. The only advantage is that it correctly calculates the percent return.
Let’s continue with this explanation. If the price of a stock moves too high or too low, the management of the issuing company splits the stock to encourage trading. 99% of stock splits occur because the price is too high. Suppose that a stock rallies to $50 and management decides to split it 2 shares for 1 share. The net result is no real change in company valuation, but there are two shares of $25 stock on the books for every one share of $50 stock. If the gap on the chart cannot be smoothed, false trades occur in testing because the unadjusted chart looks like the price dropped from $50 to $25. ‘Split-adjusted’ data is a way to solve this problem.
‘Split-adjusted’ data is produced by dividing the prices prior to a stock split by the factor of that stock split. For example 2 in the case of a 2 for 1 split, this cuts the previous daily ranges in half. There is a problem, however, when a stock split occurs too many times. If the splits happen frequently, the ‘split-adjusted’ data can get ridiculous. An extreme example of this problem is Microsoft® stock. The split-adjusted price of Microsoft is $0.11 if stock splits are handled going back to 1988 when the real price of the stock was about $34! As we will see a few paragraphs later, TradersStudio helps us solve this problem.
Dividends also create problems with split-adjusted data. This used to be an issue for Dow 30 companies and utility stocks. However, changes in tax treatment where options have to be expensed and dividends receive better tax treatment have helped make dividends become more popular. The price of a stock drops on the day the dividend is assigned to the existing owner of the stock, which causes a down tick on the chart. When analyzing mature companies like those included in the S&P 500, it must be remembered that dividends can account for as much as one half of the return of buy-and-hold strategies. When profits from dividends are compounded and reinvested back into stocks, dividends can have a huge effect on the compound returns.
Other dividend related problems could cause major changes in system results even if dividend-adjusted data is used. Assume that our system rules tell us to buy at the highest high of the last 12 months. During that time, the stock has had a high of $40, but has paid a $2 dividend since the high. Most system developers would buy if the price exceeds $40, but since the dividend was subtracted since the high price was made; the real adjusted 12-month high is $38. If the stock were bought at $38 instead of $40 across hundreds of shares of stocks over decades, the results of the system would be changed drastically. Now, you can begin to understand why stock traders do not believe in mechanical systems because it is difficult to isolate the issues involved in obtaining realistic back test results to compare system back test results to real world performance.
Even though we may have access to clean data, dividend splits, split-adjusted data, and a few other problems can create a lot of problems. Fortunately, when building automated systems, sometimes it’s best to use an automated program. In the next section of this tutorial, we’ll see how TradersStudio helps us solve these problems and backtest strategies in the most efficient manner. air max schwarz air max schwarz