JOIM: 2017
Volume 15, No. 1, First Quarter 2017
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Article
Moore’s Law Vs. Murphy’s Law in the Financial System: Who’s Winning?
Breakthroughs in computing hardware, software, telecommunications, and data analytics have transformed the financial industry, enabling a host of new products and services such as automated trading algorithms, crypto-currencies, mobile banking, crowdfunding, and robo-advisors. However, the unintended consequences of technology-leveraged finance include firesales, flash crashes, botched initial public offerings, cybersecurity breaches, catastrophic algorithmic trading errors, and a technological arms race that has created new winners, losers, and systemic risk in the financial ecosystem. These challenges are an unavoidable aspect of the growing importance of finance in an increasingly digital society. Rather than fighting this trend or forswearing technology, the ultimate solution is to develop more robust technology capable of adapting to the foibles in human behavior so users can employ these tools safely, effectively, and effortlessly. Examples of such technology are provided.
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Article
A Machine Learning Approach to Research Curation for Investment Process
Many investment professionals consider academic research instrumental in improving the quality of the investment process. However, it is hard to extract investment insights from the vast and rapidly expanding research corpus, which requires a large amount of time and human effort in order to absorb. We offer a novel solution to this problem by introducing a machine learning approach to research curation. By comparing the performance and accuracy of humans and machines, we show that a machine learning approach approximates the quality of human curation but offers the strategic benefits of scalability, efficiency and lower cost.
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Article
Picking “Winners” Funds
One of the most crucial decisions for investors and plan sponsors is the selection of funds among the thousands of available alternatives.We find that regardless of the initial criterion used to rank funds based on past performance, more diversified top funds outperform concentrated top funds in the subsequent year. This better performance is attributed to the more consistent returns of funds with diversified holdings. We also find that when the initial criterion is based on a manager’s skill, as measured by a positive intercept in a regression of past fund returns on the five Fama–French factors, active share is a useful tool to predict future winner funds among top skill managers. However, diversified top funds provide slightly higher returns and less severe drawdowns than funds with high active share and top manager skill.
To account for the problem that high information ratio can be associated with low return but even lower tracking error, we introduce the Modified Information Ratio (IR) measure. This measure adjusts the conventional IR to account for an investor’s desired alpha. The Modified IR measure and conventional IR behave similarly with respect to diversification. We find that top Modified IR funds that are also diversified—winner funds—have significantly better future 12-month returns than top Modified IR funds that are concentrated. -
Article
Stock Portfolio Design and Backtest Overfitting
In mathematical finance, backtest overfitting connotes the usage of historical market data to develop an investment strategy, where too many variations of the strategy are tried, relative to the amount of data available. Backtest overfitting is now thought to be a primary reason why investment models and strategies that look good on paper often disappoint in practice. Models and strategies suffering from overfitting typically target the specific idiosyncrasies of a limited dataset, rather than any general behavior, and, as a result, often perform erratically when presented with new data.
In this study, we address overfitting in the context of designing a mutual fund or investment portfolio as a weighted collection of stocks. Very often a newly minted equity-based fund of this type has been designed by an exhaustive computer-based search of some sort to obtain an optimal weighting that exhibits excellent performance based, say, on the past 10 or 20 years’ historical market data, and the fund often highlights this backtest performance.
In the present paper, we illustrate why this back test-driven portfolio design process often fails to deliver real-world performance. We have developed a computer program that, given any desired performance profile, designs a portfolio consisting of common securities, such as the constituents of the S&P 500 index, that achieves the desired profile based on in sample back test data. We then show that these portfolios typically perform erratically on more recent, out-of-sample data. This is symptomatic of statistical overfitting. Less erratic results can be obtained by restricting the portfolio to only positive-weight components, but then the results are quite unlike the target profile on both in-sample and out-of-sample data. -
Case Study
The Revolving Door
“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
Traded Funds and the New Dynamics of 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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Practitioner's Digest
Practitioner’s Digest • Vol. 15, 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.
Volume 15, No. 2, Second Quarter 2017
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Article
The Impact of Different Default Triggers on CMBS Risk Evaluation
This paper presents a structural generalization for pricing commercial mortgage backed securities (CMBS) and their derivatives, CMBX. I compare results for the structural generalization with a reduced-form approach using identical data sets and analyses. My comparisons are made at both the loan and bond levels and cover the period November 2007 through June 2015 using $389 billion of loans serving as the underlying collateral for CMBX Series 1 through 8. The sole difference between the two modelling approaches is found in the set of conditions and methods for simulating the default event which together comprise the ‘default trigger’ that differ for each model. I statistically validate the default estimations and then construct an automated long/short trading strategy using the risk measure Theta to compare the impact of default estimates on investment and risk management decision making. The findings indicate the reduced form provides greater precision than the structural generalization in estimating default events and in assessing trading opportunities.
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Article
Rethinking the Fundamental Law of Active Management
The fundamental law of active management provides a powerful framework for analyzing portfolio diversification and risk-adjusted returns. It states that the information ratio of an unconstrained optimal portfolio is given by the product of the information coefficient (a measure of skill) and the square root of breadth, where breadth is the number of “independent” bets. A basic limitation of previous formulations of the fundamental law is that it was not possible to determine portfolio breadth for realistic portfolios under a general covariance structure. In this paper, we present a new formulation of the fundamental law of active management. We derive a new measure of skill, denoted the Signal Quality, and obtain an exact closed-form expression for the square root of breadth, which we denote as the Diversification Coefficient. Our formulation is easily applied to real-world portfolios described by general covariance matrices. We conclude with a discussion of the transfer coefficient, which measures the drop in portfolio efficiency due to investment constraints.
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Article
A Pitfall in Ethical Investing: ESG Disclosures Reflect Vulnerabilities, not Virtues
It is widely believed that ESG (Environmental, Social, Governance) investing reduces regulatory and reputational risks. In a large global panel, we find that business ethics controversies and regulatory issues are more likely for firms that disclose a richer set of ESG-friendly policies. The effect is attenuated by controlling for size, industry, and country but remains economically and statistically significant. We also show that some prominent ESG indices favor companies that disclose more ESG policies and as a consequence have greater controversy exposure than an ESG-unaware benchmark.
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Article
Horizon Effects that are Larger than You Think: Dynamic Allocation
This paper illustrates optimal dynamic allocation in a traditional two-fund capital market model. As in previous literature, a mean-reverting market portfolio implies a “horizon effect” in typical investors’ allocations. For investors whose risk aversion is higher than the representative investor’s, the horizon effect becomes substantially larger in the capital market model than in previous models.
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Article
Leaning with the Wind: Long-Term Asset Owners and Procyclical Investing
This paper seeks to shed light on the systematic investment patterns of long-term asset owners. Based on a sample of representative portfolios (totaling $24 trillion) for global central banks, U.S. public and private pension funds, U.S. insurers and U.S. endowment funds, four main findings are established. First, asset allocation decisions appear to reflect pro- rather than countercyclical tendencies. Second, procyclicality takes two forms of roughly equal importance—contemporaneous drift (in the sense that portfolio weights are allowed to inherit relative annual returns), and more active multi-year performance chasing. Third, there is little evidence that asset owners lean against time-varying risk premia. Fourth, procyclicality appears most evident in private pension funds. In reconciling these portfolio characteristics with stylized patterns in asset class returns and financial theories, I suggest the long-term asset owners examined in this study do not avail of their long-horizon edge.
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Practitioner's Digest
Practitioner’s Digest • Vol. 15, No. 2
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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Book Review
Book of Value: The Fine Art of Investing Wisely 2016
“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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Case Study
The Rational Investor
“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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Article
In Memory of Stephen A. Ross
JOIM Conference Series, March 2017 / San Diego
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Article
The Legacy of Jack Treynor: Friends Reflect
JOIM Conference Series, March 2017 / San Diego
Volume 15, No. 3, Third Quarter 2017
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Article
Measuring Portfolio Performance: Sharpe, Alpha, or the Geometric Mean?
The most popular portfolio performance measures are the Sharpe ratio and alpha. While the Sharpe ratio is optimal under the capital asset pricing model (CAPM) assumptions of normal return distributions and unlimited borrowing at the risk-free rate, we find that it is not well aligned with investors’ preferences in more realistic settings. Alpha is a poor measure under both the theoretical and the realistic settings. For investors with typical borrowing constraints, the geometric mean provides an alternative measure that is much better than both the Sharpe ratio and alpha. It may very well be the most important single number to consider in portfolio selection.
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Article
What is Value in an Equity Market?
What is value in an equity market? Among investors, there is no universally accepted definition. This paper constructs a value index for the US equity market using the Stock and Watson (1988, 1991) methodology. The new value index is derived from a dynamic single factor model taking five relative valuation metrics as inputs. These inputs are commonly used by investors to gauge whether the market is expensive (low in value) or cheap (high in value). The value index is the (unobserved) common component in the Stock and Watson model. Investors can gauge whether the equity market is cheap or expensive by referring to a historical time series of the value index. We also develop a tactical asset allocation strategy based on the trend of the value index. Its performance indicates that the new value definition contains investible information.
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Article
Market Timing: Sin a Little Resolving the Valuation Timing Puzzle
Successful market timing is a tantalizing holy grail for investors, especially when there seems to be persuasive evidence that simple valuation measures can predict subsequent market performance. But, as both researchers and investors have discovered, outperforming a passive buy-and-hold approach is harder than it might seem. Is market timing a useful source of added value or a sin to be avoided? In this paper we explore the difference between the encouraging in-sample long-horizon evidence and directionally right but weak and disappointing out-of-sample performance.We propose an interpretation that offers a practical enhancement to value timing strategies: adding a dose of momentum.
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Article
Multi-Period Portfolio Rebalancing with Personal Tax
This paper compares two heuristic rebalancing rules for taxable accounts. The first one is trading X percent annually. The second one is based on the result of recent research, which indicate there existence of no-trading zone. The no-trading zone is obtained by using a quadratic function to approximate the optimal value function. We show a simple and implementable approximation. We also show that the no-trading zone-based rebalancing rule performs better than trading X percent annually.
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Practitioner's Digest
Practitioner’s Digest • Vol. 15, No. 3
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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Book Review
The Index Revolution –Why Investors Should Join it Now
“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.
-
Case Study
Portfolio Manager Selection
“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.
Volume 15, No. 4, Fourth Quarter 2017
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Article
How to Calibrate the Risk of Buyout Investments? Through Buyout-Backed Initial Public Offerings
This paper proposes to use the public market returns of buyout-backed initial public offerings (BO-backed IPOs) as a proxy for buyout funds’ appraisal-based returns. Because they provide an economically significant route to exit, and their leverage and fund ownership are still significant three years after the IPO, they represent unique public candidates to directly assess the risks of buyout investments, and to circumvent the stale pricing issue inherent in appraisal-based returns. Our sample covers the 1980–2013 period, and comprises 1,063 BO-backed IPOs. Our risk factor analysis shows that the market betas are close to 1.2, and the loadings on size, value and liquidity are significantly positive. Further, the loadings on the Fama and French profitability and investment are both significantly negative. These results can guide the calibration of the expected return and risk of buyout investments in strategic asset allocation: beyond exposure to Large Cap Equities, approximately 40% of the risk and return of BO-backed IPOs is explained by additional exposure to the market, and exposures to risk factors.
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Article
A Portfolio Strategy with Hedge Funds and Liquid Alternatives
The advent of liquid alternatives in mutual fund format in recent years has brought with it challenges and opportunities with regards to portfolio strategy. Interpretation of these vehicles as return enhancers or risk diversifiers can lead to very different approaches in portfolio construction. Equally indeterminate is the extent to which liquid alternatives substitute for hedge funds, that is, do liquid alternatives and hedge funds have similar risk exposures. A fundamental concern is that an investor does not overpay for exposures more cheaply accessed in liquid format as opposed to the typically more expensive limited partnership format. We present a general approach for dealing with this challenge that divides the components among beta, alternative beta (a mix of alpha and beta for liquid alternatives), and complementary beta (neither alpha nor beta for hedge funds). Our approach holds steady the amount of beta in the alternative beta portfolio (liquid alternatives portfolio), and it minimizes the amount of beta and alternative beta in the complementary beta portfolio (hedge fund portfolio). Our approach is indifferent with respect to the exact shape of the returns distribution.
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Article
Investment Horizon Risk and Volatility Metrics
We re-examine the literatures’ disparate conclusions that stock returns are more (less) volatile over longer investment horizons. We claim that the commonly employed variance ratio is incapable of generally determining whether investment risk increases with investment horizon. We demonstrate that the use of effective returns and standard deviation ratios have significantly different results compared to continuous return variance ratios. Using basic return generating processes and standard deviations, plus a recent well-specified study, we find stocks are less volatile over short to long horizons but are more volatile over very long horizons. The conclusions are consistent with some research for very long horizons but inconsistent in short to long horizons.
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Article
The Impact of Costs on Recent Target Date Fund Performance
Target date funds (TDFs) are rapidly becoming a common means to prepare for retirement. Given the swelling demand for these funds, this research is a timely look at TDFs’ most recent decade. As of March 2016, 518 TDFs have been in existence for over ten years, providing a good sample period by which to assess their performance. Analysis of the entire universe of TDFs with ten years of data reveals that a significant factor in differentiating between better and worse TDF investment performance is their expenses and loads. Among the TDFs with the lowest 25% of expenses, we find significantly better returns without an appreciable impact on standard deviation of returns or beta. Selecting TDFs without loads increases both returns and risk measures. Risk-adjusted returns using standard deviation, negative return variance, or beta all demonstrate the value of avoiding high expenses and load/commission fees.
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Case Study
Pricing for Survival in the Biopharma Industry: A Case Study of Acthar Gel and Questcor Pharmaceuticals
Recent cases of aggressive pricing behavior in the biopharmaceutical industry have raised serious concerns among payers and policymakers about industry ethics. However, these cases should not be confused with price increases motivated by challenging business conditions that ultimately lead to greater investment in R&D and improved patient access to therapeutics. We study the example of Questcor Pharmaceuticals, which was forced to choose between increasing the price of an effective drug in 2007 and ceasing production and shutting down. We consider Questcor’s journey from inception to its acquisition in 2014, analyze the factors leading up to the price hike of its main revenue generator, Acthar Gel, and discuss its resulting impact on patients after 2007. A counterfactual financial simulation of the company’s prospects in the case where prices were not increased shows that Questcor would have become insolvent between 2008 and 2010.
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Book Review
Behavioral Risk Management: Managing the Psychology that Drives Decisions and Influences Operational Risk
“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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Survey & Crossover
Machine Learning in Finance: The Case of Deep Learning for Option Pricing
“Surveys& Crossovers” This section provides surveys of the literature in investment management or short papers exemplifying advances in finance that arise from the confluence with other fields. This section acknowledges current trends in technology, and the cross-disciplinary nature of the investment management business, while directing the reader to interesting and important recent work.
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Practitioner's Digest
Practitioner’s Digest • Vol. 15, No. 4
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.