Basic philosophy explained.

There are number of well known technical analysis software packages that can perform plenty of  number crunching on the basis of parameters defined by the user. Unfortunately, these standard TA software packages have little or no ability to optimize their internal parameters for better performance of real trading. They can calculate and display 100+ technical indicators on the basis of predefined internal parameters. They urge user for ‘do it yourself curve fitting’ with the recommendation to select suitable values of internal parameters. A diligent user of such software package is trying hard to find optimal values of parameters. He is experimenting with various values of parameters, asking friends for ‘hot tips’, searching for ‘hot tips’ on Internet and losing his or her leisure time on activities, which could be done automatically with some more sophisticated software package. The question is, why the software vendors have not defined such optimal parameters in the software itself, or in the user manual? The answer is very simple – they are not able to do so, because there are no universally valid values of parameters for calculating technical indicators!

Many vendors of technical analysis software are trying to make an impression that their software is better because it can calculate more technical indicators than other software packages. The question is why they offer so many technical indicators and not only one technical indicator, which is the best of all. The answer is also very simple. There is no such technical indicator with universal validity and relevant trading performance. Any technical indicator is only an oversimplified model of stock trading with no universal validity and with no relevant trading performance.

I notice occasionally various remarks about ‘curve fitting’. Authors of these remarks are trying to make an impression that curve fitting is something wrong, which is artificially improving the back testing performance of the technical analysis software, with no impact on the performance of real trading. On the other hand, these ‘anti curve fitting gurus" do not hesitate to search for hot tips and rumors about formulas, suitable values of parameters for calculating various technical indicators or use their own ‘secret hot tips’ in hope of achieving better trading performance. These activities in fact can also be regarded as curve fitting, namely, as ‘do it yourself curve fitting’ on the basis of rumors. For example, questions on number of days for calculating moving averages are very frequent.

There is also another approach to curve fitting, namely curve fitting on the basis of mathematical optimization. Curve fitting on the basis of mathematical optimization is natural and useful process of learning, during which unknown parameters of the mathematical model of stock trading are determined in order to achieve the best back testing performance and thus improving the performance of the real trading. The real danger is not in the curve fitting, but in the mathematical model of trading itself, which in extreme negative cases can either:

• perfectly fit to past trading history, with no ability to generate profitable trading recommendations for new data or
• badly fit to past trading history, also with no ability to generate profitable trading recommendations for new data.

Theoretically perfect way of generating buy - sell recommendations is to have a mathematical model or theory of trading without any internal parameters, which fits to all stocks and all situations of the stock market and requires no learning on historical data. Of course, theoretically perfect model or theory of trading is not available and belongs into the realm of science fiction.

The best, really available way of generating buy - sell recommendations is to use adaptive mathematical models of trading with small number of internal parameters, capable to optimize these internal parameters on daily basis, on the latest historical data. StockMarketMirror software is based on the adaptive mathematical models of trading with small number of internal parameters, that are optimized daily on historical data.

The absence of  parameter optimization and absence of back testing function in the technical analysis software package is almost 100% guarantee of bad performance of real trading. Excellent back testing performance of any technical analysis software is necessary precondition (but not sufficient) for high quality technical analysis software, which is worth trying and eventually using on the regular basis.

Low purchasing price of technical analysis software is another marketing factor used to attract users. Of course the purchasing price must be affordable, but the most important factor is the bottom line after one or more years of trading. If the software purchase price is $30 and you lost $5000 after one year of trading, the bottom line is minus $5030. If you pay $200 for software and make profit of $5000 by using it with stock trading, your bottom line is plus $4800. Some users may want to calculate their leisure time, spent by the computer using the software package or searching for ‘hot tips’ into their expenditures. In this case, software features like automatic (or single click) generating of buy - sell recommendations plays important role. StockMarketMirror software can generate all its recommendations with a single mouse click and even automatically, in cooperation with Task Scheduler and its price is affordable.

One remark, frequently seen on internet is asking, why software vendors are selling their technical analysis software, instead of becoming multimillionaires by using their own software. They are adding, that there is no stock technical analysis multimillionaire and therefore, all technical analysis is a dubious pseudo teaching. People, making those malicious remarks do not care to name a single software author or software package that is doing such claims of becoming multimillionaire by using their software. The reasons, why software vendors are developing technical analysis software are the same as in the case of other software. Professionals are developing software in order to earn for a living by some useful activity and to make some profit. Amateurs are developing software because they like it or they are trying to become professionals.