Portfolio Choice and Trading in a Large 401(k) Plan

The Cross-Section of Equity Returns in Emerging Markets

Recent research has noted that the change in the shape of the yield curve can serve as a proxy for economic activity and contains economic information not present in other explanatory variables. This article extends previous research by examining the combined effect of changes in the shape of the yield curve (yield pattern) and term spread on ex ante equity returns. We find specific yield patterns do affect future equity returns, that changes in the expected long rate is a significant factor, and that, when conditioned on the change in yield curve, the term spread is time variant and significant in specific yield pattern environments and insignificant in others. Specifically, we find that average ex ante equity returns are significant and positive when the yield pattern shows signs of the expected long rate declining. In addition, we find the efficacy of the conditional term spread to predict future equity returns increased after 1980. Our results are consistent with the Expectation Theory of interest rat...

Independent Institutional Investors and Equity Returns

A large body of empirical evidence suggests that beliefs systematically deviate from perfect rationality. Much of the evidence implies that economic agents tend to form forecasts that are excessively influenced by recent changes. We present a parsimonious quasi-rational model that we call natural expectations, which falls between rational expectations and (naïve) intuitive expectations. (Intuitive expectations are formed by running growth regressions with a limited number of right-hand-side variables, and this leads to excessively extrapolative beliefs in certain classes of environments). Natural expectations overstate the long-run persistence of economic shocks. In other words, agents with natural expectations turn out to form beliefs that don't sufficiently account for the fact that good times (or bad times) won't last forever. We embed natural expectations in a simple dynamic macroeconomic model and compare the simulated properties of the model to the available empirical evidence. The model's predictions match many patterns observed in macroeconomic and financial time series, such as high volatility of asset prices, predictable up-and-down cycles in equity returns, and a negative relationship between current consumption growth and future equity returns.

Decomposing Value Globally

Because the 60–40 allocation is very simple to implement (subject to rebalancing rules)—and because it has generated strong absolute and relative risk-adjusted returns over time (i.e., it had a significantly higher Sharpe ratio than did an allocation to either equities or bonds alone)—it has long been a benchmark asset allocation method for endowment and pension fund managers. Thus, it is likely that endowment and pension funds will perform well if the 60–40 allocation performs well (and vice versa). This article provides evidence that the drivers of US equity market returns have changed over time. Specifically, while equity returns are more rate driven in earlier periods (i.e., lower rates are better for equities), they are more economically driven in more recent periods (i.e., a stronger economy is more compatible with equities). Therefore, if the US economy remains sluggish and rates are still low, the 60–40 allocation is likely to perform more poorly in the future than in the past, and, by extension, so are endowment and pension funds. <b>TOPICS:</b>Foundations &amp; endowments, portfolio theory, portfolio construction, performance measurement <b>Key Findings</b> ▪ In the future, endowment and pension fund returns will be primarily driven by the performance of risk assets. It follows that endowment and pension funds will only be able to achieve their objectives if the future environment is favorable to equities. An analysis of recent years’ returns reveals that the only environment in which equities are expected to perform well in the future is one of sustained strong economic growth coupled with accommodative monetary policy. In the absence of such an environment, endowments and pension funds may be unable to sustain planned spending levels. ▪ Individual investors’ future asset allocation choices will necessarily involve real trade-offs. In the past, the 60-40 allocation generated equity-like returns with bond-like volatility, so investors who chose the 60-40 allocation had ‘it all’: high returns and low volatility. However, in the future, the 60-40 allocation will likely generate sharply lower volatility but also meaningfully lower returns, relative to a 100% equity allocation. Investors focused on reducing risk may still find the 60-40 allocation useful, but investors with funding needs and higher returns targets will need to increase their allocation to risk assets. ▪ Individual investors allocating to illiquid risk assets need to be aware that endowments and pension funds will likely significantly increase their allocations to illiquid risk assets in an attempt to achieve their required returns. The magnitude of these institutional inflows may lead to lower returns for illiquid risk assets, as is often the case when large amounts of capital chase a more limited opportunity set.

PurposeThis study aims to investigate the association between Muslim individuals’ portfolio allocation choice and Islamic religiosity (levels and dimensions), controlling for risk tolerance and sociodemographic factors.Design/methodology/approachThe study uses primary data collected via survey questionnaires from a sample of 751 Muslim working individuals in Kuala Lumpur, Malaysia. Owing to the ordinal nature of the dependent variable, which reflects the levels of proportions of risky assets in portfolios, the data were analyzed using an ordered probit regression model.FindingsThe findings reveal that Islamic religiosity levels in general were insignificantly related to portfolio allocation, but that two dimensions of religiosity (virtue and obligation) significantly impact the allocations of risky assets in the portfolio. The higher the level of virtue, the lower the propensity to allocate risky assets into the portfolio. On the contrary, the higher the level of obligation, the higher the propensity to allocate risky assets in the portfolio. Meanwhile, individuals with higher risk tolerance, income and education levels show greater propensity to allocate risky assets in the portfolio.Research limitations/implicationsThe sample is restricted to Muslims in Kuala Lumpur; hence, the findings are not easily generalized to Muslim investors in general. Findings may differ between Muslims across the world, so future research needs to expand from a country specific to an international analysis. In addition, future studies could include other determinants of portfolio allocation, such as financial literacy.Practical implicationsThe findings of this study may assist financial planners and policymakers to better understand the drivers of portfolio allocation among their Muslim clients.Originality/valueWhile other studies have tended to focus on the impact of religiosity on the holdings of specific financial assets, such as Islamic bank accounts or Takaful, the present study explores the effect of Islamic religiosity dimensions on the allocations of risky assets in the portfolio. The study also develops an ordinal measure of portfolio allocation and makes a methodological contribution by using an ordered probit regression analysis.

Who Are Informed? The Evidence from Institutional Trades

Political Risk, Economic Risk and Financial Risk

We use data from the PSID to investigate how households' portfolio allocations change in response to wealth fluctuations. Persistent habits, consumption commitments, and subsistence levels can generate time-varying risk aversion with the consequence that when the level of liquid wealth changes, the proportion a household invests in risky assets should also change in the same direction. In contrast, our analysis shows that the share of liquid assets that households invest in risky assets is not affected by wealth changes. Instead, one of the major drivers of households' portfolio allocation seems to be inertia: households rebalance only very slowly following inflows and outflows or capital gains and losses.

Canner, Mankiw and Weil (1997) point out that the popular financial advisors on portfolio allocation among cash, bonds and stocks appear not to follow the mutual-fund separation theorem and call the inconsistency between separation theorem and popular financial advice ”an asset allocation puzzle.” For solving the asset allocation puzzle, we provide an analysis of the optimal dynamic asset allocation strategy for a long-horizon investor who has nontraded assets under an economic environment with stochastic investment opportunities and incomplete financial markets. We propose another distinguishing hedging component of the dynamic asset allocation for the stock index fund: the human capital hedging component, the hedging demand which characterizes the demand arising from the desire to hedge against changes in the labor income in contrast to Merton (1973). When we incorporate nontraded assets with intertemporal hedging, we can solve the asset allocation puzzle successfully.

Strategic Asset Allocation and Markov Regime Switch with GARCH Model

The shape of the volatility smirk has significant cross-sectional predictive power for future equity returns. Stocks exhibiting the steepest smirks in their traded options underperform stocks with the least pronounced volatility smirks in their options by 10.9% per year on a risk-adjusted basis. This predictability persists for at least 6 months, and firms with the steepest volatility smirks are those experiencing the worst earnings shocks in the following quarter. The results are consistent with the notion that informed traders with negative news prefer to trade out-of-the-money put options, and that the equity market is slow in incorporating the information embedded in volatility smirks.

Where Experience Matters: Asset Allocation and Asset Pricing with Opaque and Illiquid Assets

In spite of theoretical benefits, Markowitz mean-variance (MV) optimized portfolios often fail to meet practical investment goals of marketability, usability, and performance, prompting many investors to seek simpler alternatives. Financial experts Richard and Robert Michaud demonstrate that the limitations of MV optimization are not the result of conceptual flaws in Markowitz theory but unrealistic representation of investment information. What is missing is a realistic treatment of estimation error in the optimization and rebalancing process. The text provides a non-technical review of classical Markowitz optimization and traditional objections. The authors demonstrate that in practice the single most important limitation of MV optimization is oversensitivity to estimation error. Portfolio optimization requires a modern statistical perspective. Efficient Asset Management, Second Edition uses Monte Carlo resampling to address information uncertainty and define Resampled Efficiency(TM) (RE) technology. RE optimized portfolios represent a new definition of portfolio optimality that is more investment intuitive, robust, and provably investment effective. RE rebalancing provides the first rigorous portfolio trading, monitoring, and asset importance rules, avoiding widespread ad hoc methods in current practice. The Second Edition resolves several open issues and misunderstandings that have emerged since the original edition. The new edition includes new proofs of effectiveness, substantial revisions of statistical estimation, extensive discussion of long-short optimization, and new tools for dealing with estimation error in applications and enhancing computational efficiency. RE optimization is shown to be a Bayesian-based generalization and enhancement of Markowitz’s solution. RE technology corrects many current practices that may adversely impact the investment value of trillions of dollars under current asset management. RE optimization technology may also be useful in other financial optimizations and more generally in multivariate estimation contexts of information uncertainty with Bayesian linear constraints. Michaud and Michaud’s new book includes numerous additional proposals to enhance investment value including Stein and Bayesian methods for improved input estimation, the use of portfolio priors, and an economic perspective for asset-liability optimization. Applications include investment policy, asset allocation, and equity portfolio optimization. A final chapter includes practical advice for avoiding simple portfolio design errors. A simple global asset allocation problem illustrates portfolio optimization techniques. The presentation is intuitive, rigorous and informed with institutional management experience to appeal to investment management executives, consultants, fund trustees, brokers, academics, and anyone seeking to stay abreast of the future of investment technology. With its important implications for investment practice, Efficient Asset Management’s highly intuitive yet rigorous approach to defining optimal portfolios will appeal to investment management executives, consultants, brokers, and anyone seeking to stay abreast of current investment technology. Through practical examples and illustrations, Michaud and Michaud update the practice of optimization for modern investment management.