Global Asset Allocation and Stock Selection
Asset Management Teams and Research Initiatives: 2004
Group Code:
Gold Asset Management
Topic: Comparison of Investment Styles along Tactical Trading Strategies
Is it better to diversify across Countries or Sectors? This report attempts to answer this question by first analyzing 3 Investment Styles; Country-based, Sector-based and also a Mixed. For each investment style, a forecasting model was built and evaluated along six Trading Strategies such as Buy and Hold, 2-Longs, and Long-Short.
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Group Code: Beagle Capital
Topic: Multi-Factor Residual-Based Trading Strategy
In order to effectively implement a potential trading strategy, we choose to sample the highly liquid stocks in the Dow Jones Composite Index (Dow 30). We use the residuals from our multi-factor model to construct a variety of screens and sort the stocks into three portfolios. Our model is estimated on a daily basis and we generate daily residuals. The portfolios are rebalanced weekly. After running a vareity of screens, we score each screen's portfolios and re-sort based on the score.
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Group Code:
Granite Investments
Topic: Stock Selection in the United States
Granite Investments’ objective is to create a long-short trading strategy to generate positive returns and limit market risk. We did this through a quantitative stock screening process using seven factors, looking to find strong predictive powers of these factors on market returns, both positive and negative. Upon finding strong predictability, we would purchase long the stocks in the top quintile of predicted returns and short the stocks in the bottom quintile, generating a return spread.
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Group Code:
The Hemline Theorists
Topic: Pairs Trading Analysis
We apply the theory of cointegration to analyze various pairs trading models - going long one security while hedging market and industry-specific risk by shorting another similar security. We focus on a trading strategy involving Ford and General Motors (GM), but also test the model's robustness by extending it to other industry pairs.
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Group Code:
Strategic Partners
Topic: Comparing Stock Sorting Methodologies
We conduct a theoretical and empirical comparison of independent and sequential sorting methodologies. We show that the
correlation between factors is critical in making the choice between an independent and sequential sort. We also propose a novel adjustment in the
scoring methodology that allows for migration adjustment.
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Group Code:
Midas Capital Management
Topic: Signal Theory and Earnings Surprises
This study examines the relationship of stock price movement and earnings announcement surprises. More specifically, we examine how earnings surprise impacts stock price on the day of the earnings announcement, how stock price reacts immediately following earnings surprise announcements, and the post-earnings announcement drift phenomenon that follows the initial price movement. Our finding indicates that using signal theory; we can adequately predict the rough shape of the price curve prior to and following the earning announcement surprise. We believe that this work lays a sound foundation for further research in the future.
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Group Code:
Golden Toque Capital
Topic: Screening Based Stock Selection, Industry Comparisons
The main goal of our project is to explore and extend the findings from the "Stock Selection in Emerging Markets: Portfolio Strategies for Malaysia, Mexico and South Africa" (Harvey, et al.) into another area of interest. This idea was prompted by the recent availability of FactSet as a learning tool and the potential practical applications resulting. After a number of iterations, we found great interest in exploring applications segmented by industries within the US market, and the potential to optimize on these constraints.
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Class of 2004 email
FACTSET groups