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Dr. Anton Fokin The Svedberg Laboratory, Sweden

Dr. Anton Fokin The Svedberg Laboratory, Sweden. Outline. R-Quant is a software toolbox, which provides a financial researcher or quantitative investor with an advanced object oriented data analysis framework.

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Dr. Anton Fokin The Svedberg Laboratory, Sweden

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  1. Dr. Anton Fokin The Svedberg Laboratory, Sweden

  2. Outline R-Quant is a software toolbox, which provides a financial researcher or quantitative investor with an advanced object oriented data analysis framework. R-Quant is a stand-alone extension of the ROOT and it is especially designed to work with financial objects. • What is R-Quant • Physics meets Finance • R-Quant tools • Conclusions

  3. Where physics meets finance Quark-Gluon Plasma?

  4. Where physics meets finance Or Market Crash? Phase transition?

  5. What is inside?

  6. Data management R-Quant tools Modern financial data management reflects all the features of full-scale data acquisition and storage systems we used to deal with in our experiments. In finance we talk about tens and hundreds of Gigabytes of off-line data. Real time data come with tick intervals ranging from seconds to hours.

  7. Base instruments TAsset TRiskFreeAsset TBankAccount TObligation TRiskyAsset TStock TBond TFund Financial derivatives TDerivativative TFutures TOption TSwap R-Quant tools Inheritance trees representing base and derivative financial instruments make a perfect example of the object oriented software development.

  8. Asset pricing R-Quant tools • A number of standard pricing methods including • Black-Scholes • Finite difference • Binomial • Trinomial • Monte-Carlo

  9. Time series and technical analysis R-Quant tools Statistical tools for time series analysis. Tens of embedded indicators and signals. Opportunity to add new indicators via ROOT macro processor and script compiler using C++ interpreter as a script processor. Powered with ROOT visualization facility.

  10. Portfolio management and optimization R-Quant tools • Modern Portfolio Theory (MPT) • Capital Asset Pricing Model (CAPM) • Quadratic optimization problem for thousands of variables with a number of constraints • ROOT MINUIT • Simulated annealing with Metropolis algorithm • Genetic optimization

  11. Artificial Neural Networks and Genetic Algorithms R-Quant tools ANN are used in finance for pattern recognition and forecasting. ANN have the capability to learn underlying market dynamics from noisy and complex time series data. GA can help to build optimal neural network topologies, select good indicators, create new indicators from existing ones, etc.

  12. Fuzzy logic and expert systems R-Quant tools In our experiments as well as in finance we use rather fuzzy definitions such as “high” or “low” which have different numerical value in different situations. R-Quant implements forward (conclusion) and backward (explanation) chain techniques. Fuzzy objects may also serve as inputs for neural network applications. Facts: dollar value goes up while operating on the US stock market Rule database: if stock market = US and dollar = up then interest rate = down if interest rate = down then stock market = up Conclusion: US stock market goes up

  13. Technology transfer is possible in both directions (ROOT2000) Thanks to the ROOT team R-Quant is an open (source) project Welcome to use Welcome to join Contacts http://garbo.lucas.lu.se/~kosu_fokin/rquant.htm Email:fokin@tsl.uu.se Conclusions

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