558 search results for "Trading"

More orthodox ARMA/GARCH trading

December 14, 2011
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More orthodox ARMA/GARCH trading

The system described in the earlier series for ARMA trading was in fact an “extreme” version of the more common, orthodox approach prevailing in the literature. Recently I tried using R to reproduce the results of a particular paper, and that lead to a lot of new developments … How is typically ARMA trading simulated?

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Multi-Asset Backtest : Rotational Trading Strategies

December 5, 2011
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Multi-Asset Backtest : Rotational Trading Strategies

I want to discuss the implementation of Rotational Trading Strategies using the backtesting library in the Systematic Investor Toolbox.The Rotational Trading strategy switches investment allocations throughout the time, betting on few top ranked assets. For example, the ranking can be based on relative strength or momentum. A few examples of the Rotational Trading Strategies (or

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Trading Strategy Sensitivity Analysis

November 28, 2011
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Trading Strategy Sensitivity Analysis

When designing a trading strategy, I want to make sure that small changes in the strategy parameters will not transform the profitable strategy into the loosing one. I will study the strategy robustness and profitability under different parameter scenarios using a sample strategy presented by David Varadi in the Improving Trend-Following Strategies With Counter-Trend Entries

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Pre-computing a trading plan in parallel

November 11, 2011
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Pre-computing a trading plan in parallel

R version 2.14 introduced a new package, called parallel. This new package combines the functionality from two previous packages: snow and multicore. Since I was using multicore to parallelise my computations, I had to migrate to the new package and decided to publish some code. Often trading strategies are tested using the daily closing price

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Pair trading strategy : how to use "PairTrading" package

October 25, 2011
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Pair trading strategy : how to use "PairTrading" package

Mr.Ishikawa(my old friend) and I developed "PairTrading" package, and uploaded it on CRAN.This article shows you how you can use it.The pair trading is a market neutral trading strategy and gives traders a chance to profit regardless of market conditions. The idea of this strategy is quite simple. 1 : Select two stocks(or any assets) moving similarly 2 : Short...

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Backtesting a Simple Stock Trading Strategy: Part 3

October 17, 2011
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Backtesting a Simple Stock Trading Strategy: Part 3

Note: This post is NOT financial advice!  This is just a fun way to explore some of the capabilities R has for importing and manipulating data.   In a previous post, I examined a simple stock trading strategy: Find the high point over the la...

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Trading Mean Reversion with Augen Spikes

October 14, 2011
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Trading Mean Reversion with Augen Spikes

One of the more interesting things I have come across is the idea of looking at price changes in terms of recent standard deviation, a concept put forward by Jeff Augen. The gist is to express a close to close return as a function of the standard devia...

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Backtesting Part 2: Splits, Dividends, Trading Costs and Log Plots

September 16, 2011
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Backtesting Part 2: Splits, Dividends, Trading Costs and Log Plots

Note: This post is NOT financial advice!  This is just a fun way to explore some of the capabilities R has for importing and manipulating data.   In my last post, I demonstrated how to backtest a simple momentum-based stock trading strategy ...

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Backtesting a Simple Stock Trading Strategy

September 13, 2011
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Backtesting a Simple Stock Trading Strategy

Note: This post is NOT financial advice!  This is just a fun way to explore some of the capabilities R has for importing and manipulating data.   I recently read a post on ETF Prophet that explored an interesting stock trading strategy in Ex...

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Trading volume forecast for an illiquid stock

August 8, 2011
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Trading volume forecast for an illiquid stock

When dealing with transaction cost analysis, a stock’s volume is assumed to be stable or foreseeable.  However, there is different picture, then we are dealing with an illiquid stock. It is relatively easy to forecast the volume of a liquid stock, because trading volume has high autocorrelation – the volumes at t and t+1 are correlated. For

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