425 search results for "quantmod"

Volatility Quantiles

June 4, 2012
By
Volatility Quantiles

Today I want to examine the performance of stocks in the S&P 500 grouped into Quantiles based on one year historical Volatility. The idea is very simple: each week we will form Volatility Quantiles portfolios by grouping stocks in the S&P 500 into Quantiles using one year historical Volatility. Next we will backtest each portfolio

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Backtesting Classical Technical Patterns

May 28, 2012
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Backtesting Classical Technical Patterns

In the last post, Classical Technical Patterns, I discussed the algorithm and pattern definitions presented in the Foundations of Technical Analysis by A. Lo, H. Mamaysky, J. Wang (2000) paper. Today, I want to check how different patterns performed historically using SPY. I will follow the rolling window procedure discussed on pages 14-15 of the

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Quick View on Correlations of Different Instruments

May 24, 2012
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Quick View on Correlations of Different Instruments

In this post, I will demonstrate how to quickly visualize correlations using the PerformanceAnalytics package. Thanks to the package creators, it is really easy correlation and many other performance metrics. The first chart looks at the rolling 252 day correlation of nine sector ETFs using SPY as the benchmark. As expected the correlation is rather … Continue reading...

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Classical Technical Patterns

May 21, 2012
By
Classical Technical Patterns

In my presentation about Seasonality Analysis and Pattern Matching at the R/Finance conference, I used examples that I have previously covered in my blog: Month of the Year Seasonality – I introduced the Seasonality charts in the Historical Seasonality Analysis: What company in DOW 30 is likely to do well in January? post. I also

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Another cut at market randomness

May 20, 2012
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Another cut at market randomness

I have some background in computer security and one day found myself tasked with assessing the quality of randomness for session id tokens generated by popular web frameworks (namely Java and .NET). As it turns out, NIST have developed a series of tests for just this purpose detailed here.As a non-believer in the absolute randomness of markets, I thought...

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Cross Sectional Correlation

May 7, 2012
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Cross Sectional Correlation

Diversification is hard to find nowadays because financial markets are becoming increasingly correlated. I found a good visually presentation of Cross Sectional Correlation of stocks in the S&P 500 index in the Trading correlation by D. Varadi and C. Rittenhouse article. Let’s compute and plot the average correlation among stocks in the S&P 500 index

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Volatility Position Sizing to improve Risk Adjusted Performance

April 30, 2012
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Volatility Position Sizing to improve Risk Adjusted Performance

Today I want to show how to use Volatility Position Sizing to improve strategy’s Risk Adjusted Performance. I will use the Average True Range (ATR) as a measure of Volatility and will increase allocation during low Volatility periods and will decrease allocation during high Volatility periods. Following are two good references that explain these strategy

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Varying Window Length for Linear Models on Stocks

April 24, 2012
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Varying Window Length for Linear Models on Stocks

In a previous post, we discussed ideas generated by a Timely Portfolio post about Linear Models on Stock. I wanted to see if there was a relationship between the window length of the running mean of the linear regression slope estimate and the running mean of the correlation between fitted and observed values. The parameters

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Intraday Backtest

April 22, 2012
By
Intraday Backtest

I came across a free source of Intraday Forex data while reading Forex Trading with R : Part 1 post. You can download either Daily or Hourly historical Forex data from the FXHISTORICALDATA.COM. The outline of this post: Download and Import Forex data Reference and Plot Intraday data Daily Backtest Intraday Backtest First,I created a

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A thought on Linear Models on Stocks

April 16, 2012
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A thought on Linear Models on Stocks

Timely Portfolio has a nice post about linear models sytems for stock. The idea follows from the steps below: Get the weekly closing values of the S&P 500. Choose a time window (i.e. 25 weeks) and for each window, linearly regress the subset of closing values Choose an investment strategy based on the residuals, the

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