Posts Tagged ‘ backtesting ’

Modeling Couch Potato strategy

October 25, 2012
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Modeling Couch Potato strategy

I first read about the Couch Potato strategy in the MoneySense magazine. I liked this simple strategy because it was easy to understand and easy to manage. The Couch Potato strategy is similar to the Permanent Portfolio strategy that I have analyzed previously. The Couch Potato strategy invests money in the given proportions among different

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Permanent Portfolio – Transaction Cost and better Risk Parity

October 9, 2012
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Permanent Portfolio – Transaction Cost and better Risk Parity

I want to address comments that were asked in my last post, Permanent Portfolio – Simple Tools, about Permanent Portfolio strategy. Specifically: The impact of transaction costs on the perfromance and Create a modified version of risk allocation portfolio that distributes weights across 3 asset classes: stocks(SPY), gold(GLD), and treasuries(TLT), and only invests into cash(SHY)

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Permanent Portfolio – Simple Tools

October 4, 2012
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Permanent Portfolio – Simple Tools

I have previously described and back-tested the Permanent Portfolio strategy based on the series of posts at the GestaltU blog. Today I want to show how we can improve the Permanent Portfolio strategy perfromance using following simple tools: Volatility targeting Risk allocation Tactical market filter First, let’s load the historical prices for the stocks(SPY), gold(GLD),

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Minimum Correlation Algorithm Example

September 23, 2012
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Minimum Correlation Algorithm Example

Today I want to follow up with the Minimum Correlation Algorithm Paper post and show how to incorporate the Minimum Correlation Algorithm into your portfolio construction work flow and also explain why I like the Minimum Correlation Algorithm. First, let’s load the ETF’s data set used in the Minimum Correlation Algorithm Paper using the Systematic

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Permanent Portfolio

September 17, 2012
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Permanent Portfolio

First, just a quick update: I’m moving the release date of the SIT package a few months down the road, probably in November. Now back to the post. Recently I came across a series of interesting posts about the Permanent Portfolio at the GestaltU blog. Today I want to show you how to back-test the

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Extending Gold time series

September 10, 2012
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Extending Gold time series

While back-testing trading strategies I want all assets to have long history. Unfortunately, sometimes there is no tradeable stock or ETF with sufficient history. For example, I might use GLD as a proxy for Gold allocation, but GLD is only began trading in November of 2004. We can extend the GLD’s historical returns with its

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Adaptive Asset Allocation – Sensitivity Analysis

August 20, 2012
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Adaptive Asset Allocation – Sensitivity Analysis

Today I want to continue with Adaptive Asset Allocation theme and examine how the strategy results are sensitive to look-back parameters used for momentum and volatility computations. I will follow the sample steps that were outlined by David Varadi on the robustness of parameters of the Adaptive Asset Allocation algorithm post. Please see my prior

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Adaptive Asset Allocation

August 13, 2012
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Adaptive Asset Allocation

Today I want to highlight a whitepaper about Adaptive Asset Allocation by Butler, Philbrick and Gordillo and the discussion by David Varadi on the robustness of parameters of the Adaptive Asset Allocation algorithm. In this post I will follow the steps of the Adaptive Asset Allocation paper, and in the next post I will show

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Factor Attribution to improve performance of the 1-Month Reversal Strategy

July 16, 2012
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Factor Attribution to improve performance of the 1-Month Reversal Strategy

Today I want to show how to use Factor Attribution to boost performance of the 1-Month Reversal Strategy. The Short-Term Residual Reversal by D. Blitz, J. Huij, S. Lansdorp, M. Verbeek (2011) paper presents the idea and discusses the results as applied to US stock market since 1929. To improve 1-Month Reversal Strategy performance authors

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1-Month Reversal Strategy

July 12, 2012
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1-Month Reversal Strategy

Today I want to show a simple example of the 1-Month Reversal Strategy. Each month we will buy 20% of loosers and short sell 20% of winners from the S&P 500 index. The loosers and winners are measured by prior 1-Month returns. I will use this post to set the stage for my next post

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