Global Asset Allocation and Stock Selection

Asset Management Teams and Research Initiatives: 2005

Group Code: Cam's Crazies

Topic: Long/Short Trading Strategy

Our objective is to develop a quantitative long/short model that generates positive and consistent returns with no market exposure (Beta of 0). We choose this topic for a couple of reasons. First, we thought it would be interesting and practical. Second, we wanted to test market efficiency to see if there were systematic ways to generate alpha - positive returns from security selection. Third, and most importantly, we thought there was a slight chance that our findings could make us money.

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Group Code: Alpha

Topic: Multifactor Predictions of Sector Returns

We looked at different factors to see how well they can predict performance in different industries. Our goal was then to use the predictive power of these factors to establish scoring screens for each of the industries and test them out of sample to see if a good long-short strategy had been discovered.

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Group Code: The Fuqua Five

Topic: Dynamically Weighted Multivariate Factor Scored Model

We modified a pre-existing multivariate factor model that had been developed by Joseph Kippels in conjunction with an independent study moderated by Cam Harvey. We ran additional stock screens and looked at how susceptible the factors were to macroeconomic changes, such as the slope of the yield curve based on the yields of the 1 year and 10 year treasury securities. The equal weighted modified model delivered an arithmetic average long-short long tier 1-short tier 10 “zero investment” monthly positive return of 1.32% with a monthly standard deviation of 5.7% (annually 19% with 20% standard deviation) ignoring all transaction costs and assuming all cash from shorts could be reinvested. The portfolio consisting of going long tiers 1 and 2 and short tiers 9 and 10 produced a monthly return of 1.1% with a standard deviation of 4.3% (annually 16% with 13% standard deviation). More interestingly, the long-short portfolio had a negative correlation with the S&P500 promising a further expansion of the efficient frontier in an overall portfolio strategy.

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Group Code: Global Blue Devil Partners

Topic: Migration Tracking and Dynamic Weighting

Global Blue Devil Partners wanted to explore: mechanics of factor selection and evaluation; migration tracking; and static and dynamic weighting for long-short asset management.

Group Code: Volatility

Topic: A Factor-Based Strategic Approach to Hedged Investing

This project is motivated by the concept of pairs trading. Specifically, we look to develop a portfolio strategy which largely neutralizes systemic risk and industry specific risk. Furthermore, we seek to identify a dynamic portfolio strategy which outperforms a general pairs trading strategy through the creation of a “basket” of securities. These industry-specific long and short “baskets” are identified on a monthly basis through a screen of targeted fundamental factors.

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Group Code: Duke Investment Analytics

Topic: Interfractile Migration Tracking for Long-Short Asset Management

This research investigates the potential informational benefits of interfractile migration tracking in the context of long/short equity trading strategies based on factor sorts. We research an assortment of valuation-based factors and present assessments of their performance in selecting stocks to comprise long/short portfolios. We define various metrics to quantify interfractile migration histories for each firm, and establish a framework to evaluate whether interfractile migration tracking provides information that can improve performance in fractile-based long/short portfolios. For a selected basis factor, we implement our evaluative framework, analyzing the informational benefit of interfractile migration tracking for that basis factor.

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Group Code: Benchmark Management

Topic: Construction of Long-Short Strategies for Medium Capitalization Equities

Limit universe of stocks to firms with middle capitalization ($500M to $2B) market values and establish long-short portfolios based on quantitative stock screens.

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Group Code: Midas Asset Management

Topic: Conditional Weighted Value + Growth Portfolio (a.k.a. MCP)

Optimize weights between value and growth trading styles periodically (monthly) on basis of conditional information available at the end of last period, so that the total returns and/or risk adjusted returns of our dynamic trading rule beat those of the benchmark portfolios and/or other selected benchmarks.

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Group Code: Emerging Investors

Topic: The Dual Simple Moving Average Crossover for Long-Short Management

Moving Averages are widely used technical indicators. In principle they are easy to use due to its mathematical simplicity. But implementation issues such as establishing the optimal length of the MAs, telling the difference between crossovers that have some "momentum" (either up or down) and those that will quickly revert, and knowing the universe of stocks where this method will be more profitable, are all arduous tasks in practice. For this paper we designed and tested four different approaches to DMAC, and applied them to the S&P 500 over 10 years using Factset. Among other topics, we explore here issues such as trading on expected crossover versus trading afterwards, normalization of price movements, and optimal time intervals between measurements. Our results suggest that there might be some momentum after crossover occurs, so the traditional approach (trading only after crossover instead of anticipating it) leads to better results. We also suggest some possible improvements to our tests.

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Group Code: Beyond the Frontier

Topic: Screening based stock selection in the US

Our objective is to build a stock selection model that consistently outperforms the S&P 500 index per unit of risk and to develop a framework to systematically get Beyond The Frontier.

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Class of 2005 email

Auditors email