High-Frequency Data Modelling with R software

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1 High-Frequency Data Modelling with R software Piotr Wójcik University of Warsaw, Faculty of Economic Sciences QFRG-Eurex Conference Piotr Wójcik (WNE UW) QFRG-Eurex Conference 1 / 28

2 What is R? freely available language and environment for statistical computing and graphics (very similar to S in S-Plus), a well developed intuitive, flexible and convenient programming language, initially written by Ross Ihaka and Robert Gentleman at the Department of Statistics of the University of Auckland in New Zealand, current R is the result of a collaborative effort with contributions from all over the world, Piotr Wójcik (WNE UW) QFRG-Eurex Conference 2 / 28

3 R is hot! Piotr Wójcik (WNE UW) QFRG-Eurex Conference 3 / 28

4 Good analyst/trader = good programer A good analyst/trader has to be a good programmer!!! The choice includes a number of alternatives (used in financial modelling): R, SAS, Matlab, Mathematica, S-Plus, C++, Python, others. Piotr Wójcik (WNE UW) QFRG-Eurex Conference 4 / 28

5 Why use R in high-frequency data modelling? (1) open-source, free, Piotr Wójcik (WNE UW) QFRG-Eurex Conference 5 / 28

6 Why use R in high-frequency data modelling? (2) good to know it, universal, including many additional packages not only for statistics or quantitative finance, Piotr Wójcik (WNE UW) QFRG-Eurex Conference 6 / 28

7 Why use R in high-frequency data modelling? (3) at least 10 years ahead of commercial packages, A key benefit of R is that it provides nearinstant availability of new and experimental methods created by its user base without waiting for the development/release cycle of commercial software. SAS recognizes the value of R to our customer base... Michael Gilliland, Product Marketing Manager SAS Institute, Inc. There are very few things that SAS or SPSS will do that R cannot, while R can do a wide range of things that the others cannot. Robert A. Muenchen, author, R for SAS and SPSS Users Piotr Wójcik (WNE UW) QFRG-Eurex Conference 7 / 28

8 Why use R in high-frequency data modelling? (4) (world-) wide R community easy to learn get help online. software # of blogs* R 365 SAS 40 Stata 8 Others 0-3 * in March 2012 Source: R is becoming the lingua franca of analytic statistics. Piotr Wójcik (WNE UW) QFRG-Eurex Conference 8 / 28

9 Discussion lists subscribers Similar relations hold for discussion lists subscribers, stackoverflow discussions... Piotr Wójcik (WNE UW) QFRG-Eurex Conference 9 / 28

10 R strengths data manipulation and management, statistics, graphics, programming language, user friendly interface RStudio, thousands of available packages with specialized functions, active user community (forums, discussion groups), Piotr Wójcik (WNE UW) QFRG-Eurex Conference 10 / 28

11 R weaknesses standard interface not very user friendly, lack of commercial support, usually several possible ways to do the same, slower than programming languages (like C++, Perl, Java). Piotr Wójcik (WNE UW) QFRG-Eurex Conference 11 / 28

12 Where to find R? Piotr Wójcik (WNE UW) QFRG-Eurex Conference 12 / 28

13 R conference on finance Piotr Wójcik (WNE UW) QFRG-Eurex Conference 13 / 28

14 R blogs Piotr Wójcik (WNE UW) QFRG-Eurex Conference 14 / 28

15 R blogs Piotr Wójcik (WNE UW) QFRG-Eurex Conference 15 / 28

16 R blogs blog.fosstrading.com Piotr Wójcik (WNE UW) QFRG-Eurex Conference 16 / 28

17 Milktrader blo Piotr Wójcik (WNE UW) QFRG-Eurex Conference 17 / 28

18 Rseek Piotr Wójcik (WNE UW) QFRG-Eurex Conference 18 / 28

19 Data types useful for high-frequency time series data type package description ts base regularly spaced time series mts base regularly spaced multipletime series zoo zoo regular/irregular and arbitrary time stamp classes xts xts an extension of the zoo class High-frequency begins when indexing only by date alone becomes insufficient (intra-day, tick data). A time series object in R includes a data matrix and a vector of associated date/time stamps. Classes for high-frequency time series: low frequency high frequency time series zoo xts time index Date POSIXlt/POSIXct Piotr Wójcik (WNE UW) QFRG-Eurex Conference 19 / 28

20 Useful packages quantmod getting the historical and (delayed) real-time data automatically, many TA tools, easy analyses of OHLC type data, TTR, catools efficient functions for rolling analyses, performanceanalytics measures of strategy performance (eg. Sharpe Ratio, MDD, Calmar Ratio, Sortino Ratio, Upside Potential Ratio, Treynor Ratio), realized package for realized variance analyses, IBrokers, RTAQ direct connection to commercial HFD providers, and many many others... Piotr Wójcik (WNE UW) QFRG-Eurex Conference 20 / 28

21 Sample plot Piotr Wójcik (WNE UW) QFRG-Eurex Conference 21 / 28

22 Strategy based on a single moving average Piotr Wójcik (WNE UW) QFRG-Eurex Conference 22 / 28

23 Strategy based on two intersecting moving averages Piotr Wójcik (WNE UW) QFRG-Eurex Conference 23 / 28

24 Strategy based on Bollinger Bands Piotr Wójcik (WNE UW) QFRG-Eurex Conference 24 / 28

25 Strategy based on MACD oscillator Piotr Wójcik (WNE UW) QFRG-Eurex Conference 25 / 28

26 Strategy based on Relative Strength Index Piotr Wójcik (WNE UW) QFRG-Eurex Conference 26 / 28

27 Strategy based on a Hurst expnent Piotr Wójcik (WNE UW) QFRG-Eurex Conference 27 / 28

28 Thank you for your attention! Piotr Wójcik (WNE UW) QFRG-Eurex Conference 28 / 28

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