Volume 6, No. 1, First Quarter 2008
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Practitioner's Digest
Practitioner’s Digest • Vol. 6, No. 1
The “Practitioners Digest” emphasizes the practical significance of manuscripts featured in the “Insights” and “Articles” sections of the journal. Readers who are interested in extracting the practical value of an article, or who are simply looking for a summary, may look to this section.
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Insight
Why is There a Home Bias? Count the Teeth!
Under somewhat idealized conditions, investors would achieve the best risk return tradeoff by allocation equity investment in each country equal to its percentage share of world equity capitalization. But factual evidence confirms that domestic investors prefer domestic stocks. For example, domestic investors allocate about 90 percent of their portfolios to domestic equity even though US equity accounts for only about 50 percent of the world equity. This amounts to placing a 40 percent side bet on US equity. This is referred to as the home bias. Why does it exist? Many reasons have been given including lack of transparency, asymmetric information, investor protection, and transaction costs. This article recounts the experience and associated transactions cost of a US investor in Prague who attempts to buy individual stocks on the local market.
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Article
Estimation Error and Portfolio Optimization: A Resampling Solution
Markowitz (1959) mean-variance (MV) portfolio optimization has been the practical standard for asset allocation and equity portfolio management for almost 50 years. However it is known to be overly sensitive to estimation error in risk-return estimates and have poor out-of-sample performance characteristics. The Resampled Efficiency (RE) techniques presented in Michaud (1998) introduce Monte Carlo methods to properly represent investment information uncertainty in computing MV portfolio optimality and in defining trading and monitoring rules. This paper reviews and updates the literature on estimation error and RE portfolio optimization and rebalancing. We resolve several open issues and misunderstandings that have emerged since Michaud (1998). In particular, we show RE optimization to be a Bayesian-based generalization and enhancement of Markowitz's solution.
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Article
Bayes vs. Resampling: A Rematch
We replay an investment game that compares the performance of a player using Bayesian methods for determining portfolio weights with a player that uses the Monte Carlo based resampling approach advocated in Michaud (Efficient Asset Management. Boston: Harvard Business School, 1998). Markowitz and Usmen (Journal of Investment Management 1(4), 925, 2003), showed that the Michaud player always won. However, in the original experiment, the Bayes player was handicapped because the algorithm that was used to evaluate the predictive distribution of the portfolio provided only a rough approximation. We level the playing field by allowing the Bayes player to use a more standard algorithm. Our results sharply contrast with those of the original game. The final part of our paper proposes a new investment game that is much more relevant for the average investora one-period ahead asset allocation. For this game, the Bayes player always wins.
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Article
The Profound Effects of Automation on Stock Markets Around the World
We document the profound impact of technology on the functioning of financial markets around the world. Specially, we report a strong trend towards fully automated trading systems. This trend is associated with a significant decline in the cost of equity capital. These findings are consistent with the notion that computerization enhances liquidity, informativeness, and valuations in the stock markets. These results have practical significance for investors routing their trades, firms choosing their listing venues, stock exchanges crafting their competitive organizational strategies, and regulators contemplating policy initiatives.
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Article
A Model of Fund Growth For Managed Futures: Evidence of Managerial Skill
Fund size is an essential component of a funds overall value. In this work, we argue that growth in fund size results from managerial skill. To test this argument, we estimate a model that links fund growth to performance characteristics. We use the model to isolate significant performance characteristics and confirm that the model has predictive power out-of-sample. Hence, we verify that manager skill exists. This model may be useful to academics, fund managers, and fund allocators.
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Case Study
Case Studies
“Case Studies” presents a case pertinent to contemporary issues and events in investment management. Insightful and provocative questions are posed at the end of each case to challenge the reader. Each case is an invitation to the critical thinking and pragmatic problem solving that are so fundamental to the practice of investment management.
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Book Review
The Little Book of Value Investing
The Little Book of Common Sense Investing
“Book Reviews” identifies important, and often popular, new books from a wide range of investment topics. Beyond providing a summary and review of the content and style of the books, “Book Reviews” seeks to contribute to a conscious, critical, and informed approach to investment literature.
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Article
NOISE, CAPM AND THE SIZE AND VALUE EFFECTS
We model a continuous time one factor economy where stock prices are noisy proxies of the informationally efficient stock values. The pricing error process is modeled as a mean-reverting process, which gives us a well-defined notion of over-pricing (positive pricing error) and under-pricing (negative pricing error) in the market. We show that in this economy, cap-weighting is a sub-optimal portfolio strategy. This is because, in a capweighting scheme, portfolio weights are driven by market prices; as such, more weights are allocated to over-valued stocks and less weight to under-valued stocks.
More importantly, we show that the CAPM would be rejected in this one factor economy with noise. Regressing portfolio returns against market clearing portfolio returns, non-capweighted portfolios exhibit significant alpha on average!
Additionally, a value tilted or size tilted portfolio is predicted to outperform(risk-adjusted). By construction, value and size are not risk factors in our one factor economy. However, in the cross-section, large cap stocks and high price-to-book stocks (growth stocks) tend to underperform. This is because higher capitalization stocks and higher price-to-books stocks are indeed more likely to be stocks with positive pricing errors.
We note that prices are explicitly inefficient in our economy. However, the inefficiency does not lead to arbitrage opportunities. We carefully show conditions which prevent arbitrage in our informationally inefficient economy.
The paper contributes to the anomalies literature by showing that mean-reversion in stock returns and the Fama–French size and value effects are driven by the same market defect—pricing noise! This suggests that models, such as disposition effect and information herding, which can generate stock price over-reaction and therefore mean-reversion in stock prices, can also explain the value and size puzzle.