Beyond risk-based portfolios: balancing performance and risk contributions in asset allocation

Asset allocation using a new Performance/Risk Contribution measure improves the performance of risk-based portfolios     

Momentum investing and the asset allocation decision

This study examines the active asset allocation decisions of Australian multisector fund managers to determine whether active fund managers engage in momentum strategies. We find evidence supporting the existence of momentum investing in active asset allocation strategies. This evidence exists in the Australian Equities, Australian Fixed Interest and Listed Property asset classes. Interestingly, balanced funds adopt contrarian strategies in the International Equities asset class. We also examine whether there is any association between a fund's market timing skill and the execution of momentum strategies. Our results show that fund managers with no market timing skill are momentum investors.     

An analysis of risk-based asset allocation and portfolio insurance strategies

This paper compares traditional portfolio insurance strategies with modern risk-based dynamic asset allocation strategies within a currency portfolio context for reserve management. Given the objective of preserving reserve value, the evaluation of the hedging performances of various strategies focuses on four perspectives regarding, in particular, the return distribution of the hedged portfolio. In terms of the Sharpe Ratio, the constant proportional portfolio insurance is the best performer due to having the lowest volatility, while the Value at Risk strategy based upon the normal distribution is the worst due to its having the smallest return. From the perspective that the return distribution of the hedged portfolio is shifted to the right, the synthetic put performs the best, with the expected shortfall strategy the second best. In terms of the cumulative portfolio return across years, the expected shortfall strategy using the historical distribution ranks first, as a result of its participation in upward markets. Furthermore, the expected shortfall-based strategy results in a lower turnover within the investment horizon, thereby saving transaction costs.     

Intertemporal asset allocation: A comparison of methods

This paper compares two recent Monte Carlo methods advocated for the computation of optimal portfolio rules. The candidate methods are the approach based on Monte Carlo with Malliavin Derivatives (MCMD) proposed by Detemple, Garcia and Rindisbacher [Detemple et al., 2003. A Monte-Carlo method for optimal portfolios. Journal of Finance 58, 401–406] and the approach based on Monte Carlo with regression (MCR) of Brandt, Goyal, Santa-Clara and Stroud [Brandt et al., 2003. A simulation approach to dynamic portfolio choice with an application to learning about return predictability. Working paper, Wharton School]. Our comparisons are carried out in the context of various intertemporal portfolio choice problems with two assets, a risky asset and a riskless asset, and different configurations of the state variables. The specifications studied include a linear model with a single state variable admitting an exact solution and a non-linear model with two state variables that requires a purely numerical resolution. The accuracies of the candidate methods are compared. We provide, in particular, efficiency plots displaying the speed–accuracy trade-off for various selections of the relevant simulation and discretization parameters. MCMD is shown to dominate in all the settings considered.     

资产周期特性与保险公司资产配置策略

在竞争激烈的保险市场上,作为盈利的两大支柱之一,保险公司资产管理的能力日趋重要,而保险公司资产配置是保险资产管理的核心,其研究意义就显得尤为重要。本文首先给出保险资产配置的意义与总体原则,然后从保险资金的来源和特性入手,在详细分析了美国、中国不同经济周期和市场周期下大类资产风险收益特性的基础之上,给出保险公司资产负债管理和资产配置的战略决策建议。     

Timing and diversification: A state-dependent asset allocation approach

Abstract

The influence of changing economic environment leads the distribution of stock market returns to be time-varying. A conditionally optimal investment hence requires a dynamic adjustment of asset allocation. In this context, this paper examines the improvement in portfolio performance by simulating portfolio strategies that are conditioned on the Markov regime switching behaviour of stock market returns. Including a memory effect eliminates the empirical shortcoming of discrete state models, namely that they produce a standard and an extreme state in stock returns. So far, this has prevented the regimes from being used as a valuable conditioning variable. Based on a discrete state indicator variable, is presented evidence of considerable performance improvement relative to the static model due to optimal shifting between aggressive and well diversified portfolio structures.     

International asset allocation for incompletely-informed investors

This study explains the home bias puzzle by examining the effect of information quality on the asset allocation decisions. Our calibration results based on MSCI data indicate that in order to hedge for the changing quality of the information, when updating their estimates of expected returns of foreign assets, those agents who are partially informed and relatively more conservative will tend to hold fewer foreign assets than completely-informed agents. Furthermore, the magnitude of home bias in the portfolio of partially-informed agents decreases with the precision of their estimates and the instantaneous correlation between the returns of the home and foreign assets.     

A multivariate model of strategic asset allocation

We develop an approximate solution method for the optimal consumption and portfolio choice problem of an infinitely long-lived investor with Epstein–Zin utility who faces a set of asset returns described by a vector autoregression in returns and state variables. Empirical estimates in long-run annual and post-war quarterly U.S. data suggest that the predictability of stock returns greatly increases the optimal demand for stocks. The role of nominal bonds in long-term portfolios depends on the importance of real interest rate risk relative to other sources of risk. Long-term inflation-indexed bonds greatly increase the utility of conservative investors.     

Capital allocation for credit portfolios with kernel estimators

Determining the contributions of sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often, economic capital is measured as the Value-at-Risk (VaR) of the portfolio loss distribution. For many of the credit portfolio risk models used in practice, the VaR contributions then have to be estimated from Monte Carlo samples. In the context of a partly continuous loss distribution (i.e. continuous except for a positive point mass on zero), we investigate how to combine kernel estimation methods with importance sampling to achieve more efficient (i.e. less volatile) estimation of VaR contributions.     

Optimal portfolios and Heston's stochastic volatility model: an explicit solution for power utility

Given an investor maximizing utility from terminal wealth with respect to a power utility function, we present a verification result for portfolio problems with stochastic volatility. Applying this result, we solve the portfolio problem for Heston's stochastic volatility model. We find that only under a specific condition on the model parameters does the problem possess a unique solution leading to a partial equilibrium. Finally, it is demonstrated that the results critically hinge upon the specification of the market price of risk. We conclude that, in applications, one has to be very careful when exogenously specifying the form of the market price of risk.     

Multi-period stochastic optimization models for dynamic asset allocation

Institutional investors manage their strategic asset mix over time to achieve favorable returns subject to various uncertainties, policy and legal constraints, and other requirements. One may use a multi-period portfolio optimization model in order to determine an optimal asset mix. The concept of scenarios is typically employed for modeling random parameters in a multi-period stochastic programming model, and scenarios are constructed via a tree structure. Recently, an alternative stochastic programming model with simulated paths was proposed by Hibiki [Hibiki, N., 2001b. A hybrid simulation/tree multi-period stochastic programming model for optimal asset allocation. In: Takahashi, H. (Ed.), The Japanese Association of Financial Econometrics and Engineering. JAFEE Journal 89–119 (in Japanese); Hibiki, N., 2003. A hybrid simulation/tree stochastic optimization model for dynamic asset allocation. In: Scherer, B. (Ed.), Asset and Liability Management Tools: A Handbook for Best Practice, Risk Books, pp. 269–294], and it is called a hybrid model. The advantage of the simulated path structure compared to the tree structure is to give a better accuracy to describe uncertainties of asset returns. In this paper, we compare the two types of multi-period stochastic optimization models, and clarify that the hybrid model can evaluate and control risk better than the scenario tree model using some numerical tests. According to the numerical results, an efficient frontier of the hybrid model with the fixed-proportion strategy dominates that of the scenario tree model when we evaluate them on simulated paths. Moreover, optimal solutions of the hybrid model are more appropriate than those of the scenario tree model.     

Active fund management: Global asset allocation funds

We examine the value of active fund management of global asset allocation funds. We use unique daily data and a modified Sharpe's [Sharpe, W., 1992. Asset allocation: management style and performance measurement. Journal of Portfolio Management 18, 7–19] Return-Based Style Analysis method to create a three-index model. We introduce an alternative method derived from Sharpe to calculate attribution returns that measure active fund management performance. Our results suggest that a sample of global asset allocation funds add value for investors. To determine the estimation ability of our model and the implications for estimated asset allocation decisions, we report historical and cross-sectional root mean square errors, which give positive indications of reliability.     

Strategic asset allocation for a country: the Norwegian case

This paper develops a simple strategic asset allocation model for a country with non-tradable assets and liabilities. Contemporaneous correlation does not capture the long-term relationship between the non-tradable items and the financial assets. I apply cointegration and duration matching to better identify the long-term relationship. The model is applied to the case of Norway. Simulations suggest that Norway should implement a strategy which entails a higher proportion (than today’s strategy) invested in stocks. Although the new strategy is superior in several criteria and as Norway reforms its social security system, there is still considerable risk that Norway will fail to meet its liabilities.      

Equity risk versus retirement adequacy: asset allocation solutions for KiwiSaver

New Zealand's KiwiSaver superannuation system operates with a conservatively low asset allocation towards equity investments. Evidence suggests ‘conservative’ portfolios are riskier than portfolios holding more growth assets when considering shortfall risk. This study employs stochastic simulation to determine the optimal asset allocation to improve the balance of probabilities for retirement adequacy. The findings show that KiwiSaver default funds are excessively conservative, preventing investors from reaching their retirement goals. Increasing the asset allocation to equities across the range of available KiwiSaver funds is the only solution to significantly improve retirement adequacy in New Zealand given the low contribution rates observed.     

The alpha factor asset pricing model: A parable

Recent empirical studies use the returns of attribute-sorted portfolios of common stocks as if they represent risk factors in an asset pricing model. If the attributes are chosen following an empirically observed relation to the cross-section of stock returns, such portfolios will appear to be useful risk factors, even when the attributes are completely unrelated to risk. We illustrate this result using a parable and argue that the moral of the story is important in practice.     

Dynamic factor Value-at-Risk for large heteroskedastic portfolios

We propose a methodology that can efficiently measure the Value-at-Risk (VaR) of large portfolios with time-varying volatility and correlations by bringing together the established historical simulation framework and recent contributions to the dynamic factor models literature. We find that the proposed methodology performs well relative to widely used VaR methodologies, and is a significant improvement from a computational point of view.     

Modeling asset market volatility in a small market:: Accounting for non-synchronous trading effects

The use of GARCH modeling in empirical finance has so far to a great extent been restricted to larger asset markets. This paper considers whether the GARCH framework can be used on a smaller, less liquid market. In particular, selected stocks on the Vancouver Stock Exchange, a smaller market in Canada, are examined. Modeling return volatility in the standard GARCH framework and returns as autoregressive fails to remove significant serial correlation in the mean. The results indicate that once the parameters are adjusted for non-synchronous trading effects, GARCH can also be successful in modeling stochastic volatility on smaller markets. Persistence in both the mean and variance are eliminated with these adjustments. In addition, for some stocks, volumes add explanatory power for explaining return volatility.     

Risk aversion measures: comparing attitudes and asset allocation

Households' reported willingness to take financial risk is compared to the riskiness of their portfolios, measured as risky assets to wealth. Overall, their portfolio allocations are reliable indicators of attitudes toward risk, demonstrating an understanding of their relative level of risk taking. Multivariate regression analysis using multiply imputed data from the 1989 Survey of Consumer Finances indicates that households generally exhibit decreasing relative risk aversion. Further, investment in risky assets is significantly related to socioeconomic factors, attitude toward risk taking, desire to leave an estate and expectations about the adequacy of Social Security and pension income.