

Comparison between Matlab and R Reference
TO begin with I have started using Matlab few years back but I am totally dependent on my tech buddies to code for me or test simulations simulations for me. They are not from trading community so it was okay for me, but I think time has come that I should start my statistical work independently. I don't have technical or statistical background so somewhere I read that R is more suitable for person like me. So many times I have tried to understand Matlab but for some reason or other find the task quite repellent. Never went ahead of few basic codes.
Today accidentally came across the link for Rexcel which is the plugin for data transfer and manipulation between R and excel. So this thread is kind of a biproduct of that trigger and thought of using R again stuck out it's neck. Expect opinions from other members who are directly or indirectly familiar with the subject or who are interested in the subject.
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 


Found this useful link
MATLAB / R Reference, by David Hiebeler
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 
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Playing with R and can't agree more about nonuser friendly interface. But it's okay since it's open source and developed along with time so features must have piled up in non constructive manner. But so far seems like R is more statistical oriented..
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 


By the way this link is useless for feature comparisons, it's more to do with conversion/comparison of codes and functions across the platform.
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 
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Might be you can develop it in R, because I found Matlab script language is very twisted and that's one of the big reason I switched over to R. This might be because Matlab mostly used for Physical science than statistical analysis. Some where I read that Matlab was developed by programmers for programmers and R was developed by statisticians for statisticians.
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 


I have a very basic query...and i guess many have similar of this.
Just think/suppose i am a ordinary trader , even layman when i see and compare R/MatLab with my trading tactices. Can any body make me understand how and in what way i may use this in my day trading to make it more better ? My question might sound very broad nature and obvious , even obvious to answer in cryptic style as R/MatLab....but as i am ( as assumed ) ordinary trader so i expect answer in layman language. How it can improve my day trading ?
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Harvest The Moon !! Nest The Market !! 


It's all about getting an edge in trading and finding a solution for your strategy. I am sure there are so many brilliant ideas in every professional traders mind, but they can't implement it only because they don't know how to put those ideas in more constructive and organized way. Traders who based their trading decision on pure statistical analysis rather than limiting it to bar or candle pattern then R/ML come very handy. Matlab/R is not a trading or charting platform. One way to look at it as a strategy builder. You can analyze data in any human way possible, and it is very quick. POC or VAH values used in Marketprofile can be calculated with so much ease once you know the basic scripting language of the software, and analyzing that data for backtesting is also lightening fast and we are talking about tick data. Normally Multicharts huff and puff when performed some backtesting based on marketprofile for more than 1 year and that for 1 minute data. To begin with it is tough to build a strategy based on auction theory in regular software, we name it a discretionary approach and rely on manual calculations. But in Matlab or R you can build strategy very easily and even backtest it or optimize it, whether you are a believer of system trading or discretionary trading is a moot point, fact is you have got an edge now it's up to you how to use it. There are so many examples.. like mixing fundamental analysis and technical analysis, time based projections, bidask studies, option data analysis, portfolio analysis, market neutral strategies etc..( one very simple statestical arbitrage system I have tested in Multicharts portfolio backtester and realised that portfolio backtester doesn't use bar magnification technique which make the testing so unreliable ) Furthermore if you want to have live data feed then its also possible with toolbox or addons
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The essence of mathematics is not to make simple things complicated, but to make complicated things simple. 


It is your idea that makes money  not the tools. In trading research, tools like Matlab and R are primarily used for two purposes. 1) Identifying what works, and when. 2) Identifying / proving what does not work and when. #2 is easier compared to #1. Primary research techniques for trading are : Timeseries analysis  To uncover the statistical characteristics of a specific timeseries. This gives a good idea of what methods will work or won't work. Stochastic analysis  Identify deterministic / random behavior of prices. Corelation analysis  Namely cointegration, pairs trading etc. Help find arbitrage opportunities. Or you could use these tools to investigate your trading results / trade entry/exits. For example, in a trendfollowing system how does the system (trades) perform when the price is more than 2 sigma away from the moving average ? A good book "EvidenceBased Technical Analysis" by David Aronson will give a lot of ideas which can be used to validate your trading ideas in Matlab or R. One of my friends here in Mumbai (a banned member of IndiTraders) developed a good model of pairs trading which he trades live. He uses Matlab to continuously validate / verify the corelation models. 
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