StockFusion Studio

StockFusion Studio 2.0 is the new generation of intelligent trading advisor based on unique Aura Forecast Engine (patents No 2003611241, 2003611242). Product is based on many years of studies in nonlinear stochastic dynamics and turbulence theory applications to the short term fluctuations of world markets performed in the Russian Academy of Science. It comprises the wide variety of market forecasting algorithms including seasonal ARIMA, Stepwise Best Regressions, Finite State Markov Automation offered as ready to use adaptive trading strategies with adjustable trading commission correction and threshold trade triggers.

Automated expert system instantly selects the best strategy for every market symbol by using elaborate nonparametric statistics such as Friedman coefficient, Hurst coefficient, fractal dimension, K-Sample and Kruskal-Wallis tests, Shannon probability, asymmetry, excess, correlation radius and many others. Applied together these tools allow to achieve unique accuracy in sharp trade signals ensured with true recurrent back testing over the whole trading history of each symbol.

Free unlimited data access to all world stock universe is the courtesy of integrated Yahoo finance downloader service. Additional data sources include direct connectivity to Equis MetaStock®, CSV text worksheets, TeleChart 2008® and QuotesPlus® data warehouses as well as own native SQL drivers to Microsoft Access® and Microsoft SQL Server®, IBM DB2® UDB, Oracle® 10i.

Stunning Vista style user interface offers unique charting abilities with over a hundredth of technical indicators available in multiple concurrent charting windows with arbitrary drill down scaling. Concise trading performance reports and trade history listings are ready exportable into MS Office format. Batch system scan offers one click automatic optimization of the whole user portfolio.

Free open API enables unlimited system extensibility both in data access and additional forecasting technologies which then are natively consumed in system kernel expert reasoning. SOAP, DCOM and C++ bindings give easy direct integration with virtually any enterprise infrastructure including Java, NET, Delphi, MS Office, online portals and interactive web services.

Walk forward test

Q: We all know that future performance does not resemble past performance. If I have found a good trading model for a stock, should I perform some walk forward test? If yes, how can I reserve some price data (which has never been seen by the model) for the walk forward test? Technically, how can I conduct the test?

A: Our models are purely statistical. We took every care to avoid any chance of using forward info or any other technique, which could compromise optimization results in live trading. One could expect that the models will perform in future approximately same as they did in the past. At least as far as fundamental statistics will not completely change for given symbol.

Best model selection

Q: I am not sure about the proper means to assess the quality of a trading model (algorithm plus trading strategy) for a given stock. Is it purely based on the Performance Report? So, the model giving the highest % of winning trades and highest net profit should be the best? However, in most cases, the Expert Advisor does not give the best trading model in terms of performance report – why is that so?

A: Expert advisor selects the model with the best net profit. It does not relate to the number of winning trades. For instance, the strategy may well have the number of loosing trades exceeding the number of winning trades, while the average profit per winning trade will increase the average loss of loosing trades. Such a strategy will still be profitable. Therefore, we consider net profitability as the only reliable measure of efficiency of a strategy. It is combined, of course, with special statistics estimating stability of the results.

Profit percent on radar view

Q: When I use the Radar-Calculate buttons to scan a group of stocks, a table named “Portfolio Optimizer” will appear. In this table, one algorithm is assigned to each stock. However, the Profit % related to each stock is zero. Judging from the list of algorithms alone, with no information on the Profit %, how do I know which stock is the best performer?

A: Radar screen should be manually calculated to display actual up to date values for every symbol in your portfolio. Use “Calculate” button above radar view to start calculation. If portfolio contains many symbols, this calculation may take a significant time depending on the performance of computer. Watch progress of calculation in status bar on bottom of the main window. All fields on radar will be filled with appropriate values when calculation completes. Do not forget calculating portfolio before inspecting the results.

Purpose of technical indicators

Q: What is the main purpose of using the indicators? Are they just for visual display? If I press the Expert Advisor button, will the indicators on display be put into the subsequent calculation process and affect the result?

A: In contrast to forecasting algorithms, which pretend using historical data about a time series to foresee its future behavior, technical indicators typically depict some aggregated characteristics of a time series in the past. Even despite these patterns might be looking attractive in terms of predicting the future trends, they typically rely on certain time lags in revealing the tendency. We generally believe that indicators are useless in market prediction. They are added merely to satisfy the people familiar with other platforms. We do not use indicators in market forecasting and strategy calculations. Only predictors take part in a strategy optimization.

Indicators in multiple windows

Q: When I insert moving averages into a price chart, they appear together with the price curve (in candlesticks form); that is OK. However, when I insert oscillators, they appear at the lower part of the same chart (not in separate windows), making the upper part (price curve + moving averages) highly compressed and illegible. Can I display oscillators in separate chart/window below the price chart to leave more space for the latter?

A: On the chart ribbon find “Indicator” group. Use it to manage indicators.

1. Select from up to four available chart panes in “Window” combo box on top.
2. Select any indicator in “Available” combo box on bottom.
3. Hit “Add” button to add selected indicator to selected window.
4. Indicator will move into combo “Active”, containing all selected indicators.
5. New window will appear showing the selected indicator, if it was now visible before.
6. Hit “Remove” button to remove selected active indicator from chart.
7. Hit “Clear” to remove all indicators from all charts.

Recurrence of results

Q: We run your system several times on the same or slightly changed input data and obtain the results, which do not match exactly in each case. Does it mean that the results are unstable and not trustworthy?

A: Our expert system contains very complex forecasting algorithms. It includes wavelet regressions, neural networks, complex statistical optimizers and nonlinear filters. These technologies involve calculations thousands times exceeding in volumes all typical indicators supplied with trading platforms. All computers operate on finite precision arithmetic. It typically has 15 digits accuracy. In very long and complex calculations even small discrepancies tend to sum up and bring noticeable divergences preventing the results of several runs to coincide exactly even on the same data supplied. What matters here, is the tendency in behavior of such errors.

If the results of several consecutive runs do not differ considerably and has the tendency to match exactly with the increase in the input data volume, then we can tell that algorithm is stable and has the convergence point in the multidimensional phase space. In other words, we can say that algorithm has attractor, which guarantees statistical accuracy and consistency of the results on the ensemble of representative input statistics. Convergence is governed by Lyapunov exponents and other chaos measures. This style of convergence escapes full literacy and exhibits sporadic misfits and other phenomena. Key indicator is then steady decrease in the number and amplitude of such deviations with increase of data series length, which indicates underlying model convergence to stable result in terms of its phase space.

Results of all our algorithms generally coincide in consecutive runs. Coincidence is, however, not literal because of convergence aspects of inner optimizers. On short data series, coincidence is poor or even completely absent due to statistically insignificant data. Coincidence much improves on longer series and gets better with additional data added in most cases. It indicates correct model structure and its applicability to market forecasting. In many cases, good reproduction of results requires quite long data series of thousand points and more. Exactly this statistical convergence gives our technology fundamental benefits over the most common technical indicators.

Missing values in indicators

Q: In some cases, indicators have some points missing or are completely void. Does it mean that system does not work?

A: We offer the full-fledged expert system in market forecasting. Unlike the vast majority of simple technical indicators, it makes very complicated market modeling to produce expert inference on the future market trends. As any real expert, out technology cannot always have the exact opinion on the market trend. In some cases, it may have just not enough data for that. Then the user is responsible to provide more market depth to algorithm to expect more accuracy. In other cases, data appear just too volatile or dubious to make any clear expert decision. In such situation, expert system gives the void result, which means “no clear advice available on the moment”. As any professional and honest expert, our system is not afraid to admit its limitations in certain situations. It is much better to sustain from advice, if conditions are vague, than giving false advise and provoking possible losses. 

Optimal market depth

Q: User manual gives special table of allowed input lengths for each algorithm. Why different algorithms require different length of input data? How we can choose this length optimally in each case to achieve the best performance?

A: We offer algorithms of different complexity levels. Simple algorithms typically work well on very short input data. However, many algorithms are adaptive. It means that they automatically adjust their settings based on input data to achieve best forecasting performance.

As with humans, algorithms have only one way to learn – they learn on the previous experience. This experience is passed to algorithm in a form of market history. The longer history is provided, the better experience will have algorithm to learn. As with humans, there is no guarantee that algorithm will learn well, provided it has good initial data. However, not giving enough data is solid guarantee that even good algorithms will have no experience to educate on it properly.

Each algorithm has the minimal survival data length. Without minimal data, it simply cannot live and operate. All initial data points on chart will be just void until this minimal limit is reached, indicating that algorithm is not operational until enough data history has been collected. However, it means exactly the survival limit. Calculation starts immediately as soon as the limit is reached. Nevertheless, it does not mean that calculation on these limit condions is perfectly accurate. Algorithm with the minimal data is as the newborn baby: it is very unnatural to expect from it to be market genius. You must teach it with enough historical data to expect better professional expertise. The more data you provide the better results you can expect.

On another side, the calculation time grows with the amount of data. On the real time stream forecast will appear useless, if it arrives later than the forecasted event really happens. Hence, the user must choose the balance between the desired accuracy and the allowed data depth to get the timely market advises depending on performance of computer.

Displacement issues

Q: TradeStation, Ninja Trader and other trading platforms allow showing indicators with some displacement against original price chart. How we can pick up the best displacement for indicators?

A: Our platform is not just another technical indicator suite. Instead, it is the complex forecasting engine carefully tuned up to the incoming data stream. We took extraordinary efforts to ensure the precise synchronization with the incoming data to achieve the best possible accuracy of market indicators.

Artificially displacing indicator against its original market synchronization will completely obscure its built-in forecasting ability and will produce completely misleading results lacking any validity. It will yield artificial results and will prevent the tests on historical data to match real live market performance because broken synchronization will cause engine to use forward-looking information and fake all historical testing process. At no circumstances user can introduce any displacement to indicator displays to avoid false results and overall confusion.

Predictors behave different to indicators in terms of displacement. By meaning, they express future value intrinsically displaced into the future on the number of steps equal to the forecast length input into algorithm. We calculate market predictions for the next market step or, with the less accuracy, for the few next steps. It is advised and encouraged to adjust manually predictors exactly to this amount of forward steps (typically one) to get best trading advises.

Predictors and indicators

Q: Some algorithms in user guide are referred as predictors, others – as indictors. What is the difference between these two kinds of algorithms in trading usage?

A: We offer classical indicator style algorithms intended as the analysis tool for historical data and as an auxiliary supplement in building custom strategies by the user. Indicators are very similar in their usage to the standard technical indicators common in most trading platforms.

Predictors, even though very similar in display to indicators, are much more elaborate algorithms in mathematical sense. They are designed not to simply monitor the price dynamics, but to predict future dynamics depending on existing historical prices. Predicted future price serves as the advice to trader to make immediate decision on the current positions to maximize returns. Trader may wish to perform certain actions depending on the predicted price change. For instance, trader may wish to close position, if he will see that the price is likely to move down on the next bar, according to predictor. In this way, predictors serve as precise trading advisors.

Futures, Forex and Equities Trading Strategies on Your Favorite Dealing Platform.

Futures, Forex and Equities Trading Strategies on Your Favorite Dealing Platform.

Unraveling The Mystery Of Stock Prices

Here’s a simple method you can apply to interpret financial charts. It uses classical statistics as well as a number of simple chart indicators, which may help you better understand classical charts from the viewpoint of random processes.

Every trader is familiar with stock charts. To most traders the chart is just a common tool, like a hammer is to the carpenter. The exception is the new trader reading charts for the first time or the advanced trader who begins to question the value of the charts he or she watches.

Financial charting is specific. There are many exotic charts common to most modern trading platforms. You may begin with the classical bar charts or candlesticks and continue on to Equivolume, kagi, renko, and others. Add to that numerous technical indicators and strategy signals, and you have something packed full with useful information.

You want to concentrate as much useful information as possible into the chart so you can make timely trading decisions. To the newbie trader, this may appear to be confusing and artificial. To the seasoned professional, trying to determine what information is truly valuable for profitable trading is a vital concern.

Although financial charts can be vivid and attractive, they do tend to have contradictions with modern statistics. The charts can introduce dubious and unstable measures, which in turn become the basis of popular trading strategies. This could increase the risk of your trading operations.

In this article, I will identify the shortcomings of typical charting from a simple mathematical viewpoint and offer some easy indicators and techniques that you can apply to unravel the mystery of common charting data.

Checkout my recent paper in Stocks & Commodities, March 2010
http://www.traders.com/Documentation/FEEDbk_Docs/2010/03/Zinchenko.htm
http://store.traders.com/stcov281unmy.html

Lag correlation analysis

StockFusion Studio includes the powerful lag correlation matrix for discovery of symbol dependencies. It calculates cross correlation of selected symbol with other symbols over a range of time lags. If strong correlation exists, then correlated symbol can serve as a sort of predictor.

For example, we see that EKK for some reason correlates with EVO on lag 16. This means that if EVO has some price change, it is 42% likely that EKK will have very same price change in 16 trading days after that. Similar dependencies should exist intraday also.

Portfolio correlation matrix

Portfolio correlation matrix is the powerful tool for your portfolio optimization. It allows optimal portfolio balancing be excluding from it closely correlated symbols. If you have several closely correlated symbols in portfolio, they similarly behave on market changes and do not add any stability to your portfolio. You must try to keep in portfolio only poorly related symbols. This generally increases portfolio stability because it will increase probability of some symbols growing when the others are on down slump.


StockFusion Studio gives you powerful option of optimizing your portfolio through correlation matrix analysis, which will highlight optimal combination of symbols in your portfolio.

Adding new symbols to symbol lookup list

It may eventually happen that your favorite symbol is not present in our Yahoo symbol lookup database, for example, due to a lag in database update. In this case, it is very easy to add symbol to lookup list, happen it is valid symbol existing on Yahoo Finance.

Go to "Home & Basics > Symbol" and simply enter proper symbol into search box. Then hit "Search" button. Symbol will be permanently added to lookup list and show up on chart.

StockFusion Studio supports all world exchanges EOD data free of any subscription fees with its new Yahoo data provider. All registered customers are encouraged to download new version with a lot of other exciting extensions at
http://www.stockfusion.net/download/sfstudio.exe

Data are courtesy of Yahoo Finance
http://finance.yahoo.com/exchanges

Supported exchanges include:

American Stock Exchange
BATS Trading
Chicago Board of Trade
Chicago Mercantile Exchange
NASDAQ Stock Exchange
New York Board of Trade
New York Commodities Exchange
New York Mercantile Exchange
New York Stock Exchange
OTC Bulletin Board Market
Pink Sheets
Buenos Aires Stock Exchange
Vienna Stock Exchange
Australian Stock Exchange
Sao Paolo Stock Exchange
Toronto Stock Exchange
TSX Venture Exchange
Shanghai Stock Exchange
Shenzhen Stock Exchange
Copenhagen Stock Exchange
Paris Stock Exchange
Berlin Stock Exchange
Bremen Stock Exchange
Dusseldorf Stock Exchange
Frankfurt Stock Exchange
Hamburg Stock Exchange
Hanover Stock Exchange
Munich Stock Exchange
Stuttgart Stock Exchange
XETRA Stock Exchange
Hong Kong Stock Exchange
Bombay Stock Exchange
National Stock Exchange of India
Jakarta Stock Exchange
Tel Aviv Stock Exchange
Milan Stock Exchange
Korea Stock Exchange
KOSDAQ
Mexico Stock Exchange
Amsterdam Stock Exchange
New Zealand Stock Exchange
Oslo Stock Exchange
Singapore Stock Exchange
Barcelona Stock Exchange
Bilbao Stock Exchange
Madrid Fixed Income Market
Madrid SE C.A.T.S.
Madrid Stock Exchange
Stockholm Stock Exchange
Swiss Exchange
Taiwan OTC Exchange
Taiwan Stock Exchange
London Stock Exchange

The accuracy of trading performance back testing

Even beginner trader is well aware how important is testing of trading strategy on historical price data to estimate its efficiency. Everybody who tried to write own strategies in Metastock® or Trade Station® was able to watch performance charts of initial capital growth throughout the period of strategy execution and also everybody observed typical statements: “past performance is not a guarantee or a reliable indication of future results” which typically accompany performance charts. One can wonder why at all to pay so much attention to quantities without any exact reliability. The simple answer tells: because there is nothing better to measure trading prospects.

People with basic knowledge of mathematics would surely remember to mention probability theory associated with stock market modeling and high degree of error associated with market trend forecasting. This serves as a root to numerous strategies of risk management, which seek to achieve the balance between profits from aggressive trades and associated losses in case when the market direction estimate is incorrect. However, in many cases such estimates appear also wrong.

There is simple and evident proof for such a high volatility of market forecasts. Market itself is extremely complex system and to date there is no proven theory to explain it in any finite model allowing for easy trend calculation. The most risk estimates suppose that market behaves as some black box system with associated plain probability measures such as moving averages and variances approximating error limits. Nevertheless, there is quite generic evidence that these criteria appear inadequate in most market conditions.

This phenomenon is due to multiplication effect of market influences. Consider long pipeline transporting raw oil. Suppose every part of pipeline can suffer accident with some known probability. It may seem that the ultimate probability of pipeline fault as a whole will appear as a simple sum of associated probabilities for every fragment of a pipeline. However, it is not the case because the fault in every pipeline segment would cause the fault of the pipeline as a whole. Therefore, cumulative probability would appear not as a sum but as a product of associated probabilities. In mathematical terms, it will mean that there will be severely violated the conditions of so known Central Limit Theorem, which defines the statistical variance as a reliable measure of probability distribution associated with the value. It reveals that the most risk management strategies implemented worldwide are not reliable.

Only few mathematicians with good background in statistics can understand and rigidly prove this point. However, one should not be mathematician to observe its real world manifestation in abrupt huge losses of trading institutions and world market instabilities, which, by far, are not the results of errors of some evil minded individuals, as often told to wide public, but are due to fundamental stochastic laws which rule the modern market.

There exist special mathematical techniques devised to diminish the influences of cause multiplication factor on the accuracy of ultimate statistical estimates. Known as nonparametric statistics, they are well described in many statistical textbooks. The simplest of such measures is median point of distribution, which acts as a reliable nonparametric replacement of the average value. Another measures concern special statistical hypothesis testing techniques aimed to estimate reliability in cases where regular variance looses its sense as illustrated above.

Aura Forecast Engine (http://stockfusion.net) is the special forecasting platform, which makes use of nonparametric statistics and other nonlinear techniques such as Friedman coefficient, Hurst coefficient, fractal dimension, K-Sample and Kruskal-Wallis tests and Shannon probability to make automatic expert choice of best market forecasting strategy appropriate to any given set of historical data. It allows making back testing alternatives and measuring the risk in different terms against common trading performance standard. Even despite past profitability chart may look impressive in term of immediate strategy goal, it appears not reliable in terms of estimating future trading performance, which greatly dissolves common risk estimates based on it. Much less known nonparametric alternatives can serve as better reliability guides to investors seeking the better weighted revenue indicators.