# Posts Tagged ‘ Strategy ’

## Multiple Factor Model – Fundamental Data

January 28, 2012
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The Multiple Factor Model can be used to decompose returns and calculate risk. Following are some examples of the Multiple Factor Models: The expected returns factor model: Commonality In The Determinants Of Expected Stock Returns by R. Haugen, N. Baker (1996) The expected returns factor model: CSFB Quantitative Research, Alpha Factor Framework on page 11,

## Time Series Matching with Dynamic Time Warping

January 20, 2012
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THIS IS NOT INVESTMENT ADVICE. The information is provided for informational purposes only. In the Time Series Matching post, I used one to one mapping to the compute distance between the query(current pattern) and reference(historical time series). Following chart visualizes this concept. The distance is the sum of vertical lines. An alternative way to map

## Time Series Matching strategy backtest

January 17, 2012
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This is a quick post to address comments raised in the Time Series Matching post. I will show a very simple example of backtesting a Time Series Matching strategy using a distance weighted prediction. I have to warn you, the strategy’s performance is worse then the Buy and Hold. I used the code from Time

## Time Series Matching

January 13, 2012
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THIS IS NOT INVESTMENT ADVICE. The information is provided for informational purposes only. If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck. Do you want to know what S&P 500 will do in the next week, month, quarter? One way to make an

## Trading using Garch Volatility Forecast

January 5, 2012
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Quantum Financier wrote an interesting article Regime Switching System Using Volatility Forecast. The article presents an elegant algorithm to switch between mean-reversion and trend-following strategies based on the market volatility. Two model are examined: one using the historical volatility and another using the Garch(1,1) Volatility Forecast. The mean-reversion strategy is modeled with RSI(2): Long when

## Rotational Trading Strategies: borrowing ideas from Engineering Returns

December 19, 2011
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Frank Hassler at Engineering Returns blog wrote an excellent article Rotational Trading: how to reduce trades and improve returns. The article presents four methods to reduce trades: Trade less frequently. I.e. weekly instead of daily rebalancing. Different criteria for enter / exit a trade. Smooth the rank over the last couple of bars. Combination of

## Backtesting Rebalancing methods

December 15, 2011
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I wrote about Rebalancing in the Asset Allocation Process Summary post. Deciding how and when to rebalance (update the portfolio to the target mix) is one of the critical steps in the Asset Allocation Process. I want to study the portfolio performance and turnover for the following Rebalancing methods: Periodic Rebalancing: rebalance to the target

## Backtesting Minimum Variance portfolios

December 12, 2011
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I want to show how to combine various risk measures I discussed while writing the series of posts about Asset Allocation with backtesting library in the Systematic Investor Toolbox. I will use Minimum Variance portfolio as an example for this post. I recommend reading a good discussion about Minimum Variance portfolios at Minimum Variance Sector

## Simple and Profitable

December 8, 2011
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The end of the month effect was examined by MarketSci in the The Last Day of the Month Blahs post. The idea is simple: buy on the last day of the month and sell a few days later. This idea was put into a strategy by Quanting Dutchman in the Strategy 2 – Monthly End-of-the-Month

## Multi-Asset Backtest : Rotational Trading Strategies

December 5, 2011
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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