Dr. Anton Fokin

The Svedberg Laboratory, Sweden

OutlineOutline

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

Where physics meets financeWhere physics meets finance

Quark-Gluon Plasma?

Where physics meets financeWhere physics meets finance

Or Market Crash?

Phase transition?

What is inside?What is inside?

R-Quant R-Quant toolstools

Data managementModern 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.

R-Quant R-Quant toolstools

Base instruments

– TAsset– TRiskFreeAsset

TBankAccount TObligation

– TRiskyAsset TStock TBond TFund

Financial derivatives

– TDerivativative TFutures TOption TSwap

Inheritance trees representing base and derivative financial instruments make a perfect example of the object oriented software development.

R-Quant R-Quant toolstools

Asset pricing A number of standard pricing methods including

• Black-Scholes• Finite difference• Binomial• Trinomial• Monte-Carlo

R-Quant R-Quant toolstools

Time series and technical analysis

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.

R-Quant R-Quant toolstools Portfolio management

and optimization

• 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

R-Quant R-Quant toolstools Artificial Neural Networks

and Genetic Algorithms

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.

R-Quant R-Quant toolstools

Fuzzy logic and expert systems

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 theninterest rate = down

if interest rate = down thenstock market = up

Conclusion:

US stock market goes up

ConclusionsConclusions 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