STOCHASTICS REVISITED

The Stochastics we studied earlier did not prove to be a useful indicator. But using brute force computer calculation there may have been a combination of profits, i.e. we found the 39 day Stochastics to be profitable using a simplistic rule. Buy the stock when Stochastics K moves above the 50% line, provided that both the price and Stochastics K have made a new high, and sell/ sell short the stock when the K stochastics moves below the 50% line provided again that both the price and K stockastics have made a new low.

This simplistic rule did uncover some gains worthwhile to notice them. There is no smoothing of the K in this decision rule, thus only the value Stochastics K is used to signal trades. The above rule did provide some consistent results for medium values of K, while it was not profitable for low values, or higher values of K.

One bad point was that there was only 40% of the trades which produced profit while the other 60% produced losses. Still, this indicator was profitable in the end.

RELATIVE STRENGTH INDEX

Relative strength Index or RSI is a complicated indicator. It is evaluates as follows:

RSI = 100 - [100 / (1+RS)] where RS is the ratio of exponentially smoothed moving average of n- period gains, to exp. smoothed moving average of n- period losses.

RSI only takes into consideration the close price of the stock. This indicator takes many values from the past so it may be seen as better than other indicators which may take only one value from the past i.e. the ROC for example. Therefore, we can say that RSI is more reliable than other indicators though again the RS value ratio may complicate things by adding some noise and make the indicator sometimes unreliable.

The RSI does not work well with small values of n and it works better with higher values of the period n, therefore it is better to work with high values of n.

One way to use RSI is to buy when the RSI crosses above 50%, while to sell when RSI crosses below 50%. For n = 21- day the best results were manifested in backtesting trials. In this setting, in overall, this indicator fared well in the backtesting trials thus, it may be a good tool to use for trading.

VOLUME ACCUMULATION OSCILLATOR

The Volume Accumulation Oscillator has been created by Mark Chaikin. It is a rather complicated formula represented as follows:

VAO = [Close price for a period n - (High price for a period n + Low price for a period n) / 2] * Volume for same period n

VAO = [Cn - (Hn + Ln) / 2] * Vn where n is the period.

What this indicator tries to do is to express the Close price for the period n as a percent of the High and Low of the same period and then weighted, or multiplied by the compounding Volume of the same period.

Right from the beginning, we can say that because volume is a value that often can be erratic, this indicator may suffer from the whimsical ups and downs of the multiplication by the Volume. Perhaps if Volume is smoothed out with a Moving Average may bring better results.

We tested this indicator with doing backtesting and what we found was that the indicator indeed is erratic, i.e. the curves created by n versus equity, were not smooth but jumped high/ low depending on n. Long periods of n, i.e. at n being from 30 to 100 poor results were produced.

Therefore, we cannot say that this indicator is a reliable indicator. Also we see no value to it as it behaves at low standard depending on other indicators. Even smoothing the results with moving averages did not produce any good results therefore, the conclusion can be said that the indicator is not of much value to the stock trader.

INTEREST RATES AND STOCK PRICES

An interesting association may be uncovered if we test the interest rates of government securities with the stock market. Using monthly or weekly data we uncover that predicting stocks using the rate of change of interest rates, i.e. the one month rate of change which is the current value subtracted from the previous month rate of change, is a profitable system as well as the weekly rate of change, i.e. the 2 week rate of change produced the best results. These two systems produced positive profits that were quite high. Therefore, we can say that the 1 month rate of change of goverment interest rates as well as the 2- week rate of change of the same government securities is producing good results. Results showed that interest rates needed to move quite higher before they were able to influence the stock market. Small changes to the interest rates did not show any association with the stock market, therefore, in the end the interest rates ROC may not be a useful indicator, unless the interest rates raised, or lowered substantially.

Another association can be made that when interest rates are low, they show profitability towards the stock market, but when they are raised above a theshold value then they begin to influence the stock market. Therefore, low values of government interest rates do not have any correlation with the stock market. Interest rates need to move to higher values rather than stay at low values in order to have influence with the stock market.

DIRECTION OF SIMPLE MOVING AVERAGE

The Moving Average is a popular indicator and here we take a view at how it works when it changes direction, i.e. falling, or rising.

This indicator is the same as the Rate of Change ROC, because when the ROC crosses zero the same event works with the moving average, i.e. it changes direction. We shall not follow both here, only the Moving Average changing direction.

Some backtesting done proves that the n-day optimal for Moving Average changing direction is 31 days, i.e. the same optimal n for the ROC indicator. Since it is redundant to follow both indicators, the reader is refered to the post we already made about the ROC.

COMMODITY CHANNEL INDEX

To clear something out from the beginning, although this indicator has Commodity in the title it is equally applicable to stocks as well. Thus, we well use it for stocks.

The CCI is a complicated indicator. The formula, or formulas to calculate it is/ are as follows below.
There are a few steps to calculate this indicator. For a period characterized by n the indicator requires the following calculations:

CCI = (Mean price for a period - Moving Average for the period) / 0.015 * D

Mean Price for a period = (High of the period + Low of the period + close for the period) / 3
Moving Average for the period is the Moving Average of the Mean price that was just calculated above.
D = 1/n Sum of i=1 to n [Absolute value of Mean price for the period - Moving Average M]

The result of CCI is a statistical measure of the movement of the price and we shall not discuss the technical jargon here.

The indicator is to be used as a percent value usually ranging from -100% to +100%. The rule for buying/ selling the stock is that buy the stock when the indicator is above 100% and sell the stock when the indicator fall below -100%.

After backtesting such indicator, the best result was found to be when n = 90. Although this is a good indicator, the values between +100% and -100% had some impact in the buying/ selling of the stock because it would keep the position outside the stock price and some trends would not be followed thus it would lose profitability. Perhaps it would have been better if instead of making the neutral period to be from +100% to -100%, we could make this to be 0. This was backtested with the stock being bought when the indicator crossed above 0% and sold when it crossed below 0%. The results were suprising because the indicator faired quite well and interesting ly it gave more profit.

The conclusion is that more testing is needed to show whether this indicator is useful to the stock trader. As the results show the indicator can be used without the margin of -100% to +100%.
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NEW HIGH, NEW LOW RATIO

With this indicator, the new high and new low values play some interest when they are divided to create the oscillator. Backtesting of this rationale was hopeful to uncover any positive results. Because of some randomness that exists when single values are taken from stock past data, usually the moving average of the stock values is taken before the backtesting is to run.

With various backtesting runs, it was found that the 10 day Moving Average was the best to smooth out the slightly erratic data of the stock. The results were layed down in statistical formation which is out of the context of this book. Therefore we will not discuss how the results were gathered for this indicator.

One interesting occurrence about this indicator was that the value of New High / New Low that showed some positive results was found to be around 40, i.e. the 10 day MA of (New High/ New Low) = 40.

The results do not hold much value because they were constructed in terms of statistical analysis rather than pure traditional backtesting. The conclusion is therefore that this indicator needs more studying and testing because it can be shown whether it is useful in predicting stock price movement.

Perhaps someone undertake the job to backtest this indicator in a better formation, i.e. simplier terms of buying or selling when the ratio hits a specific value without using statistical practices. Therefore we cannot conclude whether it is a good indicator in this respect. More research is basically needed to uncover any usefulness in this particular indicator.
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[I would request perhaps any readers who may find the topics discussed here as interesting, then they may want to contribute some money so I have available resources to write more topics. If you can submit a small payment for example to my paypal account email chrisk144@gmail.com then I can continue writing my blogs without delay, or hesitations because of my busy time/ schedule, or lack of resources. Thank you very much.]