计量经济分析 = Econometric analysis

Investor Psychology and Security Market Under- and Overreactions

Investors face numerous challenges when seeking to estimate the prospective performance of a longonly investment in commodity futures. For instance, historically, the average annualized excess retu...

The Strategic and Tactical Value of Commodity Futures

International Momentum Strategies

Neural networks are used in business organizations for providing intelligent decision support. The ABI/Inform bibliographic database has over 1 000 publications on business-related research in neur...

A bibliometric analysis

The need to rebalance institutional assets to a policy benchmark is a simple fact of life While it may be possible for investors to allow portfolios to drift over a period of time, they will eventually have to address the misallocation this causes, as the mix becomes increasingly concentrated, overexposed to the riskier asset classes and underexposed to the more conservative asset classes Some investors may rebalance the asset mix by systematically directing new money into the underweight asset classes or by choosing the overweight asset classes as a source for withdrawals Others may choose to rebalance on a quarterly basis, before they are called upon to report to their investment committee However loosely the constraints on active moves away from policy benchmark are defined, the authors argue that the fact remains that a fund9s assets and liabilities must appropriately balance; drifting too far from the policy benchmark can prove disastrous when markets fail to deliver what one has been conditioned to expect

Rebalancing a Global Policy Benchmark

We model a continuous time one factor economy where stock prices are noisy proxies of the informationally efficient values. The pricing error process is modeled as a mean-reverting process; this gives us a well defined notion of over-pricing and under-pricing in the market, and stocks fluctuates between being over-priced and under-priced. We show that in this economy, cap-weighting is a sub-optimal portfolio strategy. A non-cap-weighted portfolio outperforms a cap-weighted portfolio with the same factor exposure. This is because, in a cap-weighting scheme, portfolio weights are driven by market prices; as such, more weights are allocated to overvalued stocks and less weight to undervalued stocks. Following the same intuition, we show that in the cross-section, large cap stocks tend to underperform small cap stocks and high price-to-book stocks (growth stocks) tend to underperform low price-to-book stocks (value stocks). In this economy, if we proxy the hidden risk factor with the market clearing portfolio and regress stock returns against market returns (a CAPM regression), a non-cap-weighted portfolio exhibits significant alpha! However, when we regress the same non-cap-weighted portfolio against market, size and value, the Fama-French style regression exhibits factor loadings on value and size with insignificant alpha. Clearly, value and size are not risk factors in our economy! Value and size shows up in our regressions because the market portfolio is a poorly constructed proxy for the hidden risk factor. 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 effects 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.

Noise, capm and the size and value effects

This article deals with loss harvesting, which has become a well-known tool for the management of taxable portfolios. By “harvesting” losses, the authors refer to the process of realizing capital losses which, for tax purposes, can be offset against any gains an investor may have. Often, this can bring the capital gains taxes down to zero or even create loss carryforwards for future tax years. How much is it worth to the taxable investor? Specifically, if one assumes no stock selection skill whatsoever, how much can we increase the after-tax returns on a portfolio by combining loss harvesting with otherwise passive portfolio management? The answer is that loss harvesting adds a great deal of value, far more than most active strategies can hope to achieve, net of trading costs and capital gains taxes. The authors find that loss harvesting is remarkably robust, adding substantial value over time, whether markets are volatile or quiet, strong or soft.

Loss Harvesting: What's It Worth to the Taxable Investor?

Foreword. Preface. Chapter 1. Efficient Indexing for an Inefficient Market. Evidence of Market Efficiency. The Case for Indexing. Evidence of Market Inefficiency. Conclusion. Chapter 2. Origins of the Fundamental Index Concept. The Origins of Research Affiliates Fundamental Index (RAFI). A Series of Aha! Moments Research Affiliates Fundamental Index. Fundamental Index Performance. Concluding Thoughts: A Better Way to Invest. Chapter 3. Investors Greatest Errors. Negative Alpha. Practicing What We Preach. Conclusion. Chapter 4. The Virtues of Index Funds. The Appeal of Equity Investing. Equity Investing Choices. The One Guarantee in Investments-Costs Matter. Index Fund Advantages. Avoiding the Performance Game. Concluding Point. Chapter 5. The Index Fund's Achilles Heel. Market Efficiency: Two Interpretations. Constructing a Well-Functioning Index. The Achilles Heel of Cap-Weighting. The Problems with Equal Weighting. Concluding Thoughts. Chapter 6. A Fundamental(ly) Better Index. Building the Fundamental Index. Adjustments for non-dividend-paying companies. Why Multiple Measures of Company Size? Advantages of a Composite Measure. An Index of the Broad Economy. Capacity and Liquidity. Reconstituting the Fundamental Index: Keeping Turnover Low. Concluding Comments. Chapter 7. Fundamental Index Performance in U.S. Stocks. RAFI US Large Company Performance. Digging Deeper across Market Cycles. Digging Deeper into Different Time Periods. An Equal Comparison: Fundamental Index vs. Equal Weighting. Out-of-Sample Results: Small Companies. Using the Fundamental Index with Style: Growth and Value Applications. Narrowing the Focus: NASDAQ. Narrowing the Focus: REITs. Narrowing the Focus: Sector Performance. Extending the Analysis Back in Time. Conclusion. Chapter 8. Beyond Borders: Fundamental Index Performance in Global Markets. Fundamental Index Performance in Global Markets. Multicountry Portfolios. Emerging Markets. Consistency Counts. Concluding Comments: Lessons Learned From the Global Markets. Chapter 9. Has Theory Led the Profession Astray? Will the Real Active Strategy Please Step Forward? The Origins of Cap Weighting. Apparent Validation of Cap Weighting by Theory. Forty Years Later: Empirical Results of the CAPM. Ockham's Razor Applied. Concluding Comments: Theory and the Profession. Chapter10. The Basic Criticism: Our Style and Size Tilt. Merely a Value Tilt. Small-Cap Bias. Fama and French Factors. Some Big Surprises in Small Companies. Conclusion. Chapter 11. Other Common Critiques: Hits and Misses. Mining the Data? Costs. Is It an Index? Do We Know Which Stocks Are Overvalued? How Long Can It Last? Conclusion. Chapter 12. Why Trust the Fundamental Index Concept? Stock Logic. The Present vs. the Future: How Often Is Wall Street Right? Why Does Wall Street Get It Wrong? Dynamic Style and Size Exposures: When Do We Want Value and Small Cap? Show Me the Numbers. Fundamental Index Strategy vs. the Crystal Ball. Does the Fundamental Index Concept work in Bonds? Conclusion. Chapter 13. The Future for the Fundamental Index: Secular Market Considerations. What Can We (Rationally) Expect from Our Investments? Forecasting Bond Returns. Forecasting Stock Returns. The Fundamental Index Strategy in a Low-Return Environment. The Outlook for Pricing Errors. Could Pricing Errors Actually Increase? Conclusion. Chapter 14. Using the Fundamental Index. Asset Allocation and the Fundamental Index Strategy. Should We Change Our Benchmark? Diversifying the Passive Allocation. Different Markets, Different Investors, Different Needs. Conclusion. Appendix. Notes. References. Index.

The Fundamental Index: A Better Way to Invest

Recent index literature is replete with innovations that are based on quantitative strategies and predicated on sensible investment beliefs. Empirical studies confirm that these strategies deliver economically large and statistically significant excess returns over cap-weighted market benchmarks in nearly all regions and countries, over long periods of time. In this article, the authors show that inverting these portfolio-construction algorithms does not reverse the out-performance. Indeed, the upside-down strategies often outperform the originals. This paradoxical result is driven by the phenomenon that seemingly unrelated, non-value-based strategies and their inverted counterparts often have unintended and almost unavoidable value and small-cap tilts. Even Burt Malkiel’s legendary blindfolded monkey, throwing darts at the Wall Street Journal’s stock page, would produce a portfolio with a substantial value- and small-cap bias that would have historically outperformed the S&P 500. The value and small-cap tilts stem from the fact that non-price-based weighting schemes sever the link between a company’s share price and its weight in the portfolio. Clearly, the inverted strategy of a non-price-weighted strategy is still a non-price-weighted strategy, would con-sequently have a value and small-cap tilt, and would there-fore have outperformed historically.

Robert D. Arnott

Papers

Rebalancing a Global Policy Benchmark

Noise, capm and the size and value effects

Loss Harvesting: What's It Worth to the Taxable Investor?

The Fundamental Index: A Better Way to Invest

The Surprising Alpha From Malkiel’sMonkey and Upside-Down Strategies