Cross‐region and cross‐sector asset allocation with regimes

Cross‐region and cross‐sector asset allocation decisions are one of the most fundamental issues in international equity portfolio management. Equity returns exhibit higher volatilities and correlations, and lower expected returns, in bear markets compared to bull markets. However, static mean–variance analysis fails to capture this salient feature of equity returns. We accommodate the nonlinearity of returns using a regime switching model across both regions and sectors. The regime‐dependent asset allocation potentially adds value to the traditional static mean–variance allocation. In addition, optimal allocation across sectors provide greater benefits compared to international diversification, which is characterized by higher returns, lower risks, lower correlations with the world market and a higher Sharpe ratio.     

Dynamic correlations and volatility effects in the Balkan equity markets

This paper investigates the presence of time-varying comovements, volatility implications and dynamic correlations in major Balkan and leading mature equity markets, in order to provide quantified responses to international asset allocation decisions. Since asset returns and correlation dynamics are critical inputs in asset pricing, portfolio management and risk hedging, emphasis is placed on the respective (constant and dynamic) equity market correlations produced by alternative multivariate GARCH forms, the Constant Conditional Correlation and the Asymmetric Dynamic Conditional Correlation models. The Balkan stock markets are seen to exhibit time-varying correlations as a peer group, although correlations with the mature markets remain relatively modest. In conjunction with sensitivity analysis on the asymmetric variance–covariance matrix, active portfolio diversification to the Balkan equity markets indicates to potentially improve investors’ risk-return trade-off.     

The impact of risk-based regulation on European insurers’ investment strategy

This paper examines the impact of Solvency II on the attainability of target returns, the attainability of portfolio efficiency and the asset allocation of European insurers. I start with a brief introduction to the Solvency II Directive, focusing on the rules for calculating solvency capital requirements (SCR) according to the Solvency II standard formula. The subsequent numerical analysis includes several portfolio optimizations focusing on six relevant asset classes for the 1993–2017 time period. I derive optimal portfolios with respect to the Solvency II capital requirements, with respect to conventional risk measures, and I combine both optimization problems. My results show that the capital requirements according to Solvency II are not adequately calibrated. Nevertheless, due to a solid equity base, the majority of European insurers are still able to attain high target returns and mean-variance-efficiency. However, undercapitalized insurers are not able to hold risk-optimal allocations of equities, real estate and hedge funds any longer. In an environment of very low interest rates, these insurers may also face difficulties obtaining their target returns. To the best of my knowledge, this is the first paper to explicitly incorporate the solvency capital requirement as a numerical constraint into the insurers’ portfolio optimization problem. As a result, my approach first provides insights about the attainable target return and the asset weights as a direct function of insurers’ equity.     

TACTICAL ASSET ALLOCATION: CAN IT WORK?

Market events of the past ten years have sparked an interest in tactical asset allocation. In the current study we develop and test a model that incorporates currently available information into the tactical asset allocation process. The model provides an estimate of the probabilities that the upcoming market period will be bullish or bearish. Logit analysis is employed to determine which of the various timely and readily available data significantly affect these probabilities. These estimated probabilities are used to suggest the optimal allocations of funds over time between the risk-free asset and the market portfolio. Then, several timing strategies are compared with a buy-and-hold portfolio. An asset allocation strategy based on the probabilities assigned by the logit model appears to achieve greater terminal wealth with less variability of returns. Similar results are obtained for both an initial sample (1962–76 in our model) and a holdout sample (1977–88).     

Disappointment aversion and the equity premium puzzle: new international evidence

Drawing upon the seminal study of Ang, Bekaert, and Liu [2005. “Why Stock May Disappoint?” Journal of Financial Economics 76 (3): 471–508], we incorporate disappointment aversion (DA, that is, aversion to outcomes that are worse than prior expectations) within a simple theoretical portfolio-choice model. Based on the results of this model, we then empirically address the portfolio allocation problem of an investor who chooses between a risky and a risk-free asset using international data from 19 countries. Our findings strongly support the view that DA leads investors to reduce their exposure to the stock market (i.e. DA significantly depresses the portfolio weights on equities in all cases considered). Overall, our study shows that in addition to risk aversion, DA plays an important role in explaining the equity premium puzzle around the world.     

Focusing on the worst state for robust investing

Despite its shortcomings, the Markowitz model remains the norm for asset allocation and portfolio construction. A major issue involves sensitivity of the model's solution to its input parameters. The prevailing approach employed by practitioners to overcome this problem is to use worst-case optimization. Generally, these methods have been adopted without incorporating equity market behavior and we believe that an analysis is necessary. Therefore, in this paper, we present the importance of market information during the worst state for achieving robust performance. We focus on the equity market and find that the optimal portfolio in a market with multiple states is the portfolio with robust returns and observe that focusing on the worst market state provides robust returns. Furthermore, we propose alternative robust approaches that emphasize returns during market downside periods without solving worst-case optimization problems. Through our analyses, we demonstrate the value of focusing on the worst market state and as a result find support for the value of worst-case optimization for achieving portfolio robustness.     

Asset Trading Volume with Dynamically Complete Markets and Heterogeneous Agents

Trading volume of infinitely lived securities, such as equity, is generically zero in Lucas asset pricing models with heterogeneous agents. More generally, the end‐of‐period portfolio of all securities is constant over time and states in the generic economy. General equilibrium restrictions rule out trading of equity after an initial period. This result contrasts the prediction of portfolio allocation analyses that portfolio rebalancing motives produce nontrivial trade volume. Therefore, other causes of trade must be present in asset markets with large trading volume.     

Constructing inverse factor volatility portfolios: A risk-based asset allocation for factor investing

In this study, we investigate risk-based asset allocation approaches for factor investing strategies by constructing a multifactor portfolio based on the inverse weighting method. We propose the inverse factor volatility (IFV) strategy, which is the simplified variant of a factor risk parity, assuming constant factor correlation. In IFV portfolio construction, the portfolio's weights are determined by using scaled inverse factor volatility treated as a proxy for a targeted exposure in the optimization. Based on daily stock and index returns on global markets from 2002 to the end of 2017, we implemented the empirical analysis of IFV portfolios among three stock markets: Japan, Euro, and the US. The results obtained reveal that the IFV portfolios significantly outperformed market capitalization weighted portfolios by successfully acquiring factor risk premiums.     

Normative portfolio theory

In this paper, we correct the adverse impact of estimation risk on both portfolio weights and performance with two new equity allocation methods we implement with estimation-free and estimated ex-ante returns. Portfolios with estimation-free ex-ante returns and systematic-to-unsystematic risk weights have statistically higher Sharpe ratios than both similar portfolios with estimated ex-ante returns and 1/N′th portfolios. Optimal portfolio methods with well-behaved weights guide investors in a way not hitherto possible (normative portfolio theory).     

Why stocks may disappoint

We provide a formal treatment of both static and dynamic portfolio choice using the Disappointment Aversion preferences of Gul (1991. Econometrica 59(3), 667–686), which imply asymmetric aversion to gains versus losses. Our dynamic formulation nests the standard CRRA asset allocation problem as a special case. Using realistic data generating processes, we find reasonable equity portfolio allocations for disappointment averse investors with utility functions exhibiting low curvature. Moderate variation in parameters can robustly generate substantial cross-sectional variation in portfolio holdings, including optimal non-participation in the stock market.     

Monetary policy and portfolio rebalancing: Evidence from European equity mutual funds

In this study, we provide empirical evidence on the portfolio rebalancing of European equity mutual funds following both conventional (CMP) and unconventional monetary policies (UMP). We use 1772 equity mutual funds’ portfolio holdings over the period 2002Q4–2016Q4. This level of granularity allows us to characterise the funds’ asset allocation in different portfolio dimensions: the size, style, currency, and domicile of the stocks, and managers’ preferred investment strategies. Using a panel fixed effect estimator, our results support the existence of portfolio rebalancing across equity categories following UMP. European equity mutual funds’ assets are, on average, reallocated towards mid-cap, and core stocks and developing economies, and shifted away from small-cap and value stocks and home as well as developed countries. Furthermore, mutual funds seem to concentrate on their preferred and historical investment strategies. These two results suggest that managers are more willing to invest in safer and familiar stocks following UMP announcements thereby decreasing the risk of asymmetry of information. We finally show that the funds size, returns volatility and expense ratio affect the strength of the rebalancing.     

PORTFOLIO OPTIMIZATION UNDER TRACKING ERROR AND WEIGHTS CONSTRAINTS

The performance of active portfolio managers who must comply with a weights constraint is often assessed against a benchmark. The weights constraint is common as the funds are committed by their own prospectus to a minimum (or maximum) portfolio concentration. We characterize the optimal asset allocation and analyze the implications of the weights constraint on the manager's performance and on the relevance of the information ratio. We obtain that because of the weights constraint, at the optimum, the information ratio often decreases when the manager is free to deviate more from the benchmark.     

Multi-asset portfolio optimization and out-of-sample performance: an evaluation of Black–Litterman,mean-variance,and naïve diversification approaches

The Black–Litterman model aims to enhance asset allocation decisions by overcoming the problems of mean-variance portfolio optimization. We propose a sample-based version of the Black–Litterman model and implement it on a multi-asset portfolio consisting of global stocks, bonds, and commodity indices, covering the period from January 1993 to December 2011. We test its out-of-sample performance relative to other asset allocation models and find that Black–Litterman optimized portfolios significantly outperform naïve-diversified portfolios (1/N rule and strategic weights), and consistently perform better than mean-variance, Bayes–Stein, and minimum-variance strategies in terms of out-of-sample Sharpe ratios, even after controlling for different levels of risk aversion, investment constraints, and transaction costs. The BL model generates portfolios with lower risk, less extreme asset allocations, and higher diversification across asset classes. Sensitivity analyses indicate that these advantages are due to more stable mixed return estimates that incorporate the reliability of return predictions, smaller estimation errors, and lower turnover.     

Evaluating Liquidation Strategies for Insurance Companies

In this article, we examine liquidation strategies and asset allocation decisions for property and casualty insurance companies for different insurance product lines. We propose a cash‐flow‐based liquidation model of an insurance company and analyze selling strategies for a portfolio with liquid and illiquid assets. Within this framework, we study the influence of different bid‐ask spread models on the minimum capital requirement and determine a solution set consisting of an optimal initial asset allocation and an optimal liquidation strategy. We show that the initial asset allocation, in conjunction with the appropriate liquidation strategy, is an important tool in minimizing the capital committed to cover claims for a predetermined ruin probability. This interdependence is of importance to insurance companies, stakeholders, and regulators.     

Myopic loss aversion,reference point,and money illusion

We use the portfolio selection model presented in He and Zhou [Manage. Sci., 2011, 57, 315–331] and the NYSE equity and US treasury bond returns for the period 1926–1990 to revisit Benartzi and Thaler’s myopic loss aversion theory. Through an extensive empirical study, we find that in addition to the agent’s loss aversion and evaluation period, his reference point also has a significant effect on optimal asset allocation. We demonstrate that the agent’s optimal allocation to equities is consistent with market observation when he has reasonable values of degree of loss aversion, evaluation period and reference point. We also find that the optimal allocation to equities is sensitive to these parameters. We then examine the implications of money illusion for asset allocation. Finally, we extend the model to a dynamic setting.     

Value-at-risk capital requirement regulation,risk taking and asset allocation: a mean–variance analysis

In this study, the mean–variance framework is employed to analyze the impact of the Basel value-at-risk (VaR) market risk regulation on the institution's optimal investment policy, the stockholders’ welfare, as well as the tendency of the institution to change the risk profile of the held portfolio. It is shown that with the VaR regulation, the institution faces a new regulated capital market line, which induces resource allocation distortion in the economy. Surprisingly, only when a riskless asset is available does VaR regulation induce the institution to reduce risk. Otherwise, the regulation may induce higher risk, accompanied by asset allocation distortion. On the positive side, the regulation implies an upper bound on the risk the institution takes and it never induces the firm to select an inefficient portfolio. Moreover, when the riskless asset is available, tightening the regulation always increases the amount of maintained eligible capital and decreases risk.     

Portfolio and welfare consequences of debt market dominance

The ability to issue debt that pays in units of the domestic good leads a country to accumulate a large and negative net foreign asset position while maintaining a positive position in equity. This debt market advantage also helps to explain the weak relationship between the real exchange rate and relative consumption. Our stylized model matches the key facts about the U.S. international portfolio, the U.S. real exchange rate, and explains nearly 50% of the observed variation in the valuation effects. We find that taxing bond market transactions increases the volatility of the exchange rate, capital flows and allocations. In contrast, taxing equity positions stabilizes the exchange rate and capital flows while having little impact on the allocation. Lastly, the paper describes a global solution method for portfolio problems under incomplete markets.     

Efficient Post-Retirement Asset Allocation

Abstract

To examine post-retirement asset allocation, an extension to the classic Markowitz risk-return framework is suggested. Assuming that retirees make constant (real dollar) annual withdrawals from their portfolios, reward and risk measures are defined to be the mean and standard deviation of wealth remaining at end of life. Asset returns and time of death are both treated as random variables. Assuming constant lifetime asset allocation, the risk and reward measures can be evaluated analytically, and an efficient frontier can be determined. Life annuities can be used to extend the left-hand (low-risk) side of the efficient frontier. The desired level of wealth at end of life can be used to choose a desirable portfolio on the efficient frontier. The desirable portfolio strongly depends on the withdrawal rate. It is suggested (although not proven) that asset allocations strategies that vary with age do not add efficiency in this model, and asset allocation strategies that vary with wealth can add efficiency.     

Portfolio implications of systemic crises

Systemic crises can have grave consequences for investors in international equity markets, because they cause the risk-return trade-off to deteriorate severely for a longer period. We propose a novel approach to include the possibility of systemic crises in asset allocation decisions. By combining regime switching models with Merton [Merton, R.C., 1969. Lifetime portfolio selection under uncertainty: The continuous time case. Review of Economics and Statistics 51, 247–257]-style portfolio construction, our approach captures persistence of crises much better than existing models. Our analysis shows that incorporating systemic crises greatly affects asset allocation decisions, while the costs of ignoring them is substantial. For an expected utility maximizing US investor, who can invest globally these costs range from 1.13% per year of his initial wealth when he has no prior information on the likelihood of a crisis, to over 3% per month if a crisis occurs with almost certainty. If a crisis is taken into account, the investor allocates less to risky assets, and particularly less to the crisis prone emerging markets.     

公共养老储备基金资产配置比较研究与启示——基于挪威、法国、爱尔兰、新西兰四国公共养老储备基金比较分析

公共养老储备基金的资产配置策略是以储备基金的营运目标为导向制定的。设定基准投资组合、分散化的全球资产配置、重视新兴市场与社会责任投资、再平衡策略与动态资产配置策略并重等成为近年来各国共公告养老储备基金资产配置的主要特征。基于全国社会保障基金的投资实践,文章提出了制定差异化的资产配置策略以实现不同阶段目标,投资监管模式和资产配置策略同步创新以实现投资监管与投资实践良性互动,加快资产配置策略的全球布局以实现区域经济套利和人口红利套利,注重储备基金的责任投资导向、凸显养老金绿色投资功能的改革建议。