It would be prudent for investors to give due regard and weightage to aspects of technical analysis while making decisions with respect to their investments in the stock markets. Technical analysis in itself would revolve around the application of statistical and mathematical models and formulae to the historical daily price and volume data of the stocks they (that is, the investors) may have under study; with a view to identifying trends both upward and downward which are likely to repeat themselves in the future.
It would be fair to assume that the large financial institutions (including but not limited to the investment banks), brokerage arms and subsidiaries of large banks, brokerage houses, insurance companies, pension funds, high networth investors and the savvy individual investors would be utilizing technical analysis to augment their investment decision making process; which may otherwise be based on the tenants of fundamental analysis. Therefore, to scoff at this aspect of stock analysis would be at the peril of the persons doing so.
At the onset technical analysis would be based on the study of the historical moving averages of various periodicities, while applying the same directly onto the price charts of the stocks the investor may have under study for further analysis.
There are three types of moving averages; namely, the simple moving average, the weighted moving average and the exponential moving average. It is expected that the investor would know how to calculate these averages while applying them to the historical price volume data of the stocks he may have under study.
Now, the first of these averages (the simple moving average) has come across criticism on two counts; the fist being that it assigns equal weightage to each of the base observations. For instance, in the case of a 14 day simple moving average; each of the 14 preceding price values is counted once and given equal importance of one-fourteenth in the average. While the second would be that as the simple moving average moves across time, its fluctuations would be dependent on just two numbers, the new number being added and the oldest number being dropped. Thus, if the new number were to be greater than the number being dropped, the average across all values would increase along with the moving average itself.
With a view to overcome these two lacunas of the simple moving average, we may consider the weighted moving average. In the case of the weighted moving average, more importance and therefore a greater weightage would be given to the more recent observations while giving proportionately lesser importance and therefore lesser weightage to the older observations. The drawback in this case would be the cumbersome nature of the calculation to be repeated every day in the case of the daily weighted moving average.
To overcome the drawback of the weighted moving average, some investors would consider the application of the exponential moving average to the price data of the stocks they may have under study for onward investment at a subsequent date.
An exponential system would be based on assigning a weightage of 18% to the current price and the remaining 82% to the previous value of the moving average itself in the case of a 10 day exponential moving average series. The proportionate weight assigned to the most recent observation is also called the smoothing constant. To determine the smoothing constant, the investor may divide two by one more than the number of terms in the simple moving average he wishes to construct. For instance, the smoothing constant required to construct an exponential moving average equivalent to a 10 day simple moving average would be two divided by eleven; which is 0.18 (the smoothing constant for the 10 day exponential moving average). After establishing the moving average as equal to the first day price; the moving average would be updated every day by multiplying the new current price by 0.18 and adding it to the produce derived from multiplying the previous exponential average value by 0.82.
In an exponential moving average series, while the effective weight assigned to any historical value would decline as it becomes older; every day's price would always have some weight in the exponential moving average. Its weight never declines to zero while tends towards it. An exponential moving average would be quite like a weighted moving average, and would be easier to update.
It would be safe to expect that most investors both big and small would also be applying more sophisticated methods and techniques to calculate the moving averages. But, amongst the three described above the exponential moving average would be the best; while realizing that the array of moving average systems is infinite.
These moving averages are applied and studied thereafter with a view to enable investment decisions on both the buy side as well as on the sell side. Usually, the investor would apply relevant moving average based on his investment time horizon. For the short term he may apply the 5 day, the 7 day or the 10 day moving average; for the medium term he may apply the 14 day, the 21 day or the 28 day moving average; while for the long term the investor would most likely apply the 50 day and the 200 day moving average. When stock prices are above these moving averages, then these moving average provide a visual of probable support price levels in case of stock prices declining; while if the stock prices are below the moving averages, then the moving averages would substitute for price resistance levels; which would be price levels beyond which the stock price is unlikely to move during an up move in prices. Indeed some investors would apply more than one moving average to the same price chart to also study the moving average crossovers in conjunction with the price in relation to such moving averages of the price of the stocks under study.
It would be fair to state that, that moving averages would be useful in determining whether a stock price is trending upwards or downwards and in differentiating between price actions occurring above or below these moving averages. As trends do persist into the future, moving average analysis would have an important place as a market forecasting tool. On the flip side, there would be others who would opine that there are no magic numbers with regard to monitoring and following a 5 day or 20 day, or a 13 day or a 14 day or a 30 day or a 39 day moving average series; while some period series may have worked well in the past, they may not oblige in the future. This would be so, as neither the length nor the type of moving average applied would make much difference when the market and stock prices are in an uptrend or a downtrend based on fundamental factors both micro-economic as well as macro-economic.