About Trading Decision Support System TraDeSS-1

Trading Decision Support System TraDeSS-1 is for institutional traders and investors who deal with ETFs, commodities, and big-volume equities. It is a comprehensive and effective software to help finding the best trading opportunities, maximizing profitability using several predictive models with back-testing features, and optimizing algorithms by running simulations.

TraDeSS-1 is equipped with an advanced forecasting state-of-the-art system. The predicting can be done using nine forecast methods of different nature. Only one method, a combination of a few ones, or all together can be used. Each method is provided with back-test calculation to estimate the accuracy of forecast within the recent performance period. The back-testing computations play an important role if more than one method is selected. It allows assigning a weight to each method in a composed result; the weights are proportional to the ability of the methods to predict the price.

The comparative analysis of simulations shows that systems based on predicted entry-exit signals generate a better profit in around 70% cases than random-entry trading systems. As well as, it should be noted that a multi-model forecast provides a significant improvement over the best individual forecast. It can be explained by the existence of many different independent factors contributing to the error in each forecast which is normally distributed around an actual value.

Since sometimes predictions can fail, to preserve a principal amount in a volatile market, the software enables simulating different risk management approaches. Depending on the character of particular trading assets and the current market conditions some ideas can work better than others. To optimize the strategy in a particular case, the software enables testing different algorithm configurations and finding automatically the best ones. It is especially important for exit points to minimize losses (and ultimately maximize an overall profit). All optimizations can be done automatically by scanning 64 possible logical combinations and adjusting numerical parameters.

TraDeSS-1 has a functionality that allows estimating a hypothetical maximum possible profit in case of 100% accurate forecast. Although an actual forecast cannot be so accurate, this feature combined with comparative analysis enables discovering the best trading opportunities among different types of financial instruments. Calculating maximum theoretical return allows finding optimal buy and sell signals. Also it helps estimating a reasonable amount of initial investment at given transaction fee. Users can choose to re-invest each time a new or the same amount and see the difference in results.

The software has forward testing and assets management features. It allows monitoring the simulated or actual completed transactions, reflecting total trading activity, and evaluating the success of trading in overall. It enables working with many separate data files that is convenient in case of managing multiple assets and keeping the archives of older activities.

TraDeSS-1 has also a few independent tools, such as, technical indicators predictor, cycle analysis forecast, Neural Network (NN) forecast, fundamental 3-month rating model for equities, etc. The detailed description is presented in User's Manual (accessible from menu Help after downloading and installing the software). The software is available via the registration (no payment data collected and no obligation to buy).

A fully-functional software during initial 30-day period is free. To continue using the software after 30 days, the subscription is required (subscription link is available from the software interface). Technical support and updates are included. Annual lease and perpetual license are available. Paid on-site training (how to use the software) can be provided.

Market Crowd Factor: Why Trend Might Not Be Your Friend Sometimes

“An advertisement said, 'Send me $1 and I will let you know how it was easy for me to become a millionaire.'
A man who wants to be a millionaire sent $1 in an envelop.
After a while he received a reply: 'I became a millionaire by asking to send me $1'
The next day, the advertisement said, 'Send me $1 and I will let you know how it was easy for me to become a billionaire.'”
- Author unknown

An advanced and robust principle, idea, or system might help to win in the stock market. But what if it is used by almost all market participants? Would everyone be a winner? Read to find out about cases when stock investing can be successful or risky.

Although a successful stock market investing or trading is complicated, in general, it consists of three major parts: analyzing data and possible future, making decision, and executing this decision. The same applies in case of automated trading - just these parts incorporated in the system and work in the same way. If we abstract from non-controllable external factors, we could clearly see that the quality of our decision and consequently the outcome depend on input data and their processing to make an optimal decision. What input data are the best and how to convert them into a meaningful information and finally into a right action?

Quality vs. quantity. First of all, apparently, too many data, especially, that are non-relevant to the searching result, might make the solution too noisy and with error ranges that exceed the accuracy of a certain solution. That is why most market participants use a limited but sufficient enough the set of input data in order to transform it further into a necessary information with a minimal uncertainty. The second important task is a processing with the highest quality of extracting worthy information. A good processing enables enriching the information while trying to avoid losing any value in the translation process.

Sometimes trend might be your friend. Is it possible to find and use the best universal principles and systems in stock trading? The second question - is it possible to make money using methods, systems, or ideas that are employed by many? It seems collective actions can be beneficial. For instance, if there is a uptrend - many would join the movement and add more pushing power up. Although a crowd behavior could be useful, sometimes, it can lead to unexpected results.

What if everyone does the same. Typical example - many thought that February could be a good month to invest because institutional funds' managers could increase their portfolios in March. Many converted cash into stocks in February pushing market up. Then when buying power exhausted and funds were unable to support this trend - the stock market collapsed. Another examples, several years ago October was a low month but since too many talked about this annual cycle, it is not the case anymore - everybody buys in October and pushes the market higher.

One more danger of crowd. Some classical books warn investors - when everyone is very bullish in the stock market - this is time when the market can crush because there is no one left who can invest more money to support the uptrend. It was in case of a hi-tech bubble in 2000. What factors influence our investing or trading decision? The opinion of most market participants? But their opinions link to their actions - that is why a trend might be built on sands and it can let you down anytime.

The benefit of using a new or rare approach. Let's imagine the situation - a group of people read the same book, for example, "How to Find Mushrooms" and all go to one forest. Evidently, then there would be more chances to find mushrooms in the places that are not recommended in this book. The conclusion - stock trading can be successful also in case of using something new or something that is used by limited number of traders.

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Typical 10 Phases of Stock Market Disturbance

Within bear or bull market there are always fluctuations in stocks prices. It can be said about indexes, ETFs, and most other investing instruments. As example, let's consider an equilibrium market state that is based on a realistic evaluation. Assume it is a starting point. Then at some moment a good news released with the expectation that is above a realistic evaluation. The first reaction would be a price up-move (stage 1).



As prices are tend to rise, many would follow a simple strategy to join a growth movement that additionally enforced by greed (stage 2). Since there are always some participants in the market that might got this news with a delay or are too big to make the decision and perform transactions fast, the curve price might continue rising but with a slight less slope (stage 3). Normally, news can be accompanied by other overly optimistic opinions. Also there is always a room for some errors and miscalculations. These factors can be materialized in a short spike of prices (stage 4).

At some point, when a buying power exhausted and there are no other factors to sustain the growth, a reversal happens. All fast trading systems and dynamic participants of the market including short-sellers push the market down rapidly (stage 5). When the correction technically becomes more obvious, many start selling; the movement becomes stronger additionally enforced by fear and leads prices below the equilibrium line (stage 6).

Since fear is more strong drive than greed, normally the value of downtrend gradient is bigger than uptrend one. Two phases that are similar to ones existing in the uptrend curve part, delay (7) and miscalculation (8), follow until a bounce back (9). The after-bounce curve part can have a decaying-fluctuation pattern (stage 10). This pattern finally approaches the market evaluation to the equilibrium line.


Practically, very often, all described above consequent 10 phases might not be observed clearly due to several reasons. One of them is a fact that a single isolated news happens very seldom. Another typical reason is that all factors that drive the market might not be available in the form of publicly available information all the time.

© Alex Shmatov. Published with permission of the copyright owner. Further reproduction prohibited without permission.