Netflix rise after new pricing model while asset managers want ultra long bonds

# Tag Archives: model

# How to model Bitcoin volatility and Which countries grow their wealth

How to model Bitcoin volatility and Which countries grow their wealth

# Watch this video Matlab video on how to use Symbolic Math Toolbox to visually build model using MuPAD editor

Watch this video Matlab video on how to use Symbolic Math Toolbox to visually build model using MuPAD editor

Continue reading

# Initial Karen Supertrader algo Simulink model with plot

Initial Karen Supertrader algo Simulink model with plot

As explained in both videos

# Simulink call put parity options trading model with C or C++ code

Simulink call put parity options trading model with C code

Here is the first one which is closer to a real world example with C or C++ source code

# Matlab Simulink future trading model on basis

# Eurodollars, Japanese yen, Interest rate parity example, and Cost of Carry model

Eurodollars, Japanese yen,Interest rate parity example, and Cost of Carry model

# I just posted possibly links to connect a R model or algo into Metatrader forex trading platform for order and execution

I just posted possibly links to connect a R model or algo into Metatrader forex trading platform for order and execution

Go here:

# Quality R packages that potential financial researchers and quant traders who model or build a strategy and algorithm

Quality R newbie packages that potential financial researchers and quant traders who model or build a strategy and algorithm

As a newbie to R, I thought it would be worthy to note a few quality R packages that seem to have more advanced some functionality that Matlab does not even give you. Here is my experience thus far:

**RTAQ**

This is a tough one to gauge as I have recently tried to get something working with this but will only work with New York Stock Exchange data. At first I thought you could easily download like in Yahoo Finance but I don’t think you can. It seems strange when there are two versions file of this trade and quote capture system.

**xts**

This seems to be a pretty popular way to convert market data into a time series data frame used throughout other financial R packages listed here.

**quantstrat**

Another sophisticated R package where you can combine with blotter is to apply different classic technical indicators to your market objects. You can apply indicators, signals, and rules using technical analysis indicators like MACD, RSI, and Bollinger Bands. You can even apply your own algorithm to these as well which leads into quant related type of modeling.

**blotter**

Another useful package for first round of testing within R. This can be at the core of many analytical trading systems with capabilities to capture end of day market data, set currency rate, and create portfolio, and accounts, and with sophisticated charting capabilities.

**PerformanceAnalytics**

This is easily one of the best R packages yet since it has some very decent charting capabilities you can find in popular trading platforms like Metatrader. You can easily add different type of charting lines to plots. It contains a great and easy way to extract different types of statistical and market data.

**Other worthy R packages to mention include:**

quantmod

lspm

PortfolioAnalytics

FinancialInstrument

TTR

signalextraction

I hope this helps those out new to the world of R

# Crucial and many helpful R packages and research papers for finance and HFT with quant model, algo, and strategy example

Crucial and many helpful R packages and research papers for finance and HFT with quant model, algo, and strategy example

Note none of these have NOT been verified or validated yet but don’t mind me, I feel like a kid in a candy factory with these!

With Interactive Brokers and R:

http://blog.fosstrading.com/2010/05/introducing-ibrokers-and-jeff-ryan.html

http://cran.r-project.org/web/packages/IBrokers/vignettes/RealTime.pdf

Implied volatility:

http://www.r-bloggers.com/the-only-thing-smiling-today-is-volatility/

For volatility forecasting using GARCH

http://www.r-bloggers.com/trading-using-garch-volatility-forecast/

Time series analysis and computational finance Cointegration test

www.stat.ucl.ac.be/ISdidactique/Rhelp/library/tseries/html/00Index.html

urca R package with Conintegration

http://cran.r-project.org/web/packages/urca/index.html

http://global-4-lvs-colossus.opera-mini.net/hs36-13/15877/1/-1/cran.r-project.org/urca.pdf

Limit Order Book R package

http://r-forge.r-project.org/R/?group_id=790 <– not in CRAN but does not seem to have a download link

Engle Granger coefficient test

http://cran.r-project.org/web/packages/tsDyn/tsDyn.pdf

CRAN – Package crawl random walk theory

http://cran.r-project.org/web/packages/crawl/index.html

Time series analysis in r (includes autocorrelation p17)

http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf

Ljung box test in r (includes times series)

Ljung Box part of this: http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf

http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf

Auto regressive estimation model

http://cran.r-project.org/web/packages/cts/vignettes/kf.pdf

Auto regressive is part of http://quantlabs.net/r-blog/2012/05/excellent-tutorial-on-using-urca-r-package-for-var-cointegration-statistical-tests-non-stationary-processes-benchmarks-and-estimating-models/

R time series pair trading Engle and Granger cointegartion

http://cran.r-project.org/web/packages/PairTrading/PairTrading.pdf

Volatility models

http://cran.r-project.org/web/packages/realized/realized.pdf

Brownian Motion

http://cran.r-project.org/web/packages/sde/sde.pdf

Non parametric regression estimation

http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-nonparametric-regression.pdf

Time based arbitrage opportunities

http://www.r-bloggers.com/time-based-arbitrage-opportunities-in-tick-data/

Bid Ask spread with tick data rtaq R package

http://cran.r-project.org/web/packages/RTAQ/RTAQ.pdf

Tick data bid ask spread

http://cran.r-project.org/web/packages/FinTS/FinTS.pdf

High frequency data analysis in r with taq data base

http://faculty.washington.edu/ezivot/research/hfanalysis.pdf

Probability of observing k arrivals

http://cran.r-project.org/web/packages/HMM/HMM.pdf

Note Amihud reference of cran in the following research paper:

http://poseidon01.ssrn.com/delivery.php?ID=595118123002081089030087126071081068052035058029030050009002086102005018011112069076118021122027111056019097028001082100025005051092069006116118100098122075080031073081071095115105007093083028120122&EXT=pdf

Info and market impact

http://www.econ.kuleuven.be/public/n09022/RTAQ_vignette.pdf

Most profitable hedge fund strategy in r

http://www.r-bloggers.com/most-profitable-hedge-fund-style/

Econometric Analysis of Financial Market Data

http://www.math.uncc.edu/~zcai/FE-notes.pdf

PCA in R

http://www.r-bloggers.com/principal-component-analysis-use-extended-to-financial-economics-part-2/

Statistical arbitrage in r

http://www.r-bloggers.com/most-profitable-hedge-fund-style/

Dynamic modeling of mean-reverting spreads for statistical arbitrage

http://imperial.academia.edu/GiovanniMontana/Papers/1104540/Dynamic_modeling_of_mean-reverting_spreads_for_statistical_arbitrage

CAPM n r (note PerformanceAnalytics R package may be just as effective)

http://cran.r-project.org/web/packages/BLCOP/vignettes/BLCOP.pdf

Package RTAQ liquidity arbitrage

http://cran.r-project.org/web/packages/RTAQ/index.html

Crucial and many helpful R packages and research papers for finance and high frequency trading with a quant model, algo, and strategy example

Note none of these have NOT been verified or validated yet but don’t mind me, I feel like a kid in a candy factory with these!

With Interactive Brokers and R:

http://blog.fosstrading.com/2010/05/introducing-ibrokers-and-jeff-ryan.html

http://cran.r-project.org/web/packages/IBrokers/vignettes/RealTime.pdf

Implied volatility:

http://www.r-bloggers.com/the-only-thing-smiling-today-is-volatility/

Time series analysis and computational finance Cointegration test

www.stat.ucl.ac.be/ISdidactique/Rhelp/library/tseries/html/00Index.html

urca R package with Conintegration

http://cran.r-project.org/web/packages/urca/index.html

http://global-4-lvs-colossus.opera-mini.net/hs36-13/15877/1/-1/cran.r-project.org/urca.pdf

Limit Order Book R package

http://r-forge.r-project.org/R/?group_id=790

Engle Granger coefficient test

http://cran.r-project.org/web/packages/tsDyn/tsDyn.pdf

CRAN – Package crawl random walk theory

http://cran.r-project.org/web/packages/crawl/index.html

Time series analysis in r (includes autocorrelation p17)

http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf

Ljung box test in r (includes times series)

http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf

Auto regressive estimation model

http://cran.r-project.org/web/packages/cts/vignettes/kf.pdf

R time series pair trading Engle and Granger cointegartion

http://cran.r-project.org/web/packages/PairTrading/PairTrading.pdf

Volatility models

http://cran.r-project.org/web/packages/realized/realized.pdf

Brownian Motion

http://cran.r-project.org/web/packages/sde/sde.pdf

Non parametric regression estimation

http://cran.r-project.org/doc/contrib/Fox-Companion/appendix-nonparametric-regression.pdf

Time based arbitrage opportunities

http://www.r-bloggers.com/time-based-arbitrage-opportunities-in-tick-data/

Bid Ask spread with tick data rtaq R package

http://cran.r-project.org/web/packages/RTAQ/RTAQ.pdf

Tick data bid ask spread

http://cran.r-project.org/web/packages/FinTS/FinTS.pdf

High frequency data analysis in r with taq data base

http://faculty.washington.edu/ezivot/research/hfanalysis.pdf

Probability of observing k arrivals

http://cran.r-project.org/web/packages/HMM/HMM.pdf

Note Amihud reference of cran in the following research paper:

http://poseidon01.ssrn.com/delivery.php?ID=595118123002081089030087126071081068052035058029030050009002086102005018011112069076118021122027111056019097028001082100025005051092069006116118100098122075080031073081071095115105007093083028120122&EXT=pdf

Info and market impact

http://www.econ.kuleuven.be/public/n09022/RTAQ_vignette.pdf

Most profitable hedge fund strategy in r

http://www.r-bloggers.com/most-profitable-hedge-fund-style/

Econometric Analysis of Financial Market Data

http://www.math.uncc.edu/~zcai/FE-notes.pdf

PCA in R

http://www.r-bloggers.com/principal-component-analysis-use-extended-to-financial-economics-part-2/

Statistical arbitrage in r

http://www.r-bloggers.com/most-profitable-hedge-fund-style/

Dynamic modeling of mean-reverting spreads for statistical arbitrage

http://imperial.academia.edu/GiovanniMontana/Papers/1104540/Dynamic_modeling_of_mean-reverting_spreads_for_statistical_arbitrage

CAPM n r (note PerformanceAnalytics R package may be just as effective)

http://cran.r-project.org/web/packages/BLCOP/vignettes/BLCOP.pdf

Package RTAQ liquidity arbitrage

http://cran.r-project.org/web/packages/RTAQ/index.html