The article presents the result of optimization of transaction systems based on the intersection of the moving average and the closing price (signal of purchase and sale) for 404 shares listed on the Warsaw Stock Exchange (WSE). The goal is to find specific regularities (statistics) for all analyzed companies, not to optimize the system for each of them. It is similar to describing the properties of the whole forest after analyzing each tree,
Data/Methods:
For each equity, the survey covered 5,000 sessions or less if shares were traded in a shorter time horizon. The moving average types used in the study were: Simple Moving Average (SMA), Linearly Weighted (WMA), Exponentially weighed (EMA), Triangular Weighted Average (TWA) plus possibly two types of moving averages more: The End Point Moving Average and Adaptive Moving Average. The moving average length varies from 3 to 200 sessions.
Results/Expected Results:
So far, the results clearly indicate that for all types of averages, transaction systems were optimized in the vast majority by sort-term averages, which confirms the investors' tendency to process transactions with a speculative rather than an investment bias. Ranking of the effectiveness of the three types of moving averages; WMA, SMA and EMA unambiguously indicated that for the most part the highest rates of return were obtained for transaction systems based on WMA, before SMA and EMA. Differences in the effectiveness of the trading systems based on WMA and SMA were small, but the systems using these two types of moving averages proved to be much more efficient than systems based on EMA. The results will be extended after analyzing the remaining moving averages.