A dynamic model of active portfolio management with benchmark orientation

This paper studies optimal dynamic portfolios for investors concerned with the performance of their portfolios relative to a benchmark. Assuming that asset returns follow a multi-linear factor model similar to the structure of Ross (1976) [Ross, S., 1976. The arbitrage theory of the capital asset pricing model. Journal of Economic Theory, 13, 342–360] and that portfolio managers adopt a mean tracking error analysis similar to that of Roll (1992) [Roll, R., 1992. A mean/variance analysis of tracking error. Journal of Portfolio Management, 18, 13–22], we develop a dynamic model of active portfolio management maximizing risk adjusted excess return over a selected benchmark. Unlike the case of constant proportional portfolios for standard utility maximization, our optimal portfolio policy is state dependent, being a function of time to investment horizon, the return on the benchmark portfolio, and the return on the investment portfolio. We define a dynamic performance measure which relates portfolio’s return to its risk sensitivity. Abnormal returns at each point in time are quantified as the difference between the realized and the model-fitted returns. Risk sensitivity is estimated through a dynamic matching that minimizes the total fitted error of portfolio returns. For illustration, we analyze eight representative mutual funds in the U.S. market and show how this model can be used in practice.     

Multivariate utility maximization with proportional transaction costs

We present an optimal investment theorem for a currency exchange model with random and possibly discontinuous proportional transaction costs. The investor’s preferences are represented by a multivariate utility function, allowing for simultaneous consumption of any prescribed selection of the currencies at a given terminal date. We prove the existence of an optimal portfolio process under the assumption of asymptotic satiability of the value function. Sufficient conditions for this include reasonable asymptotic elasticity of the utility function, or a growth condition on its dual function. We show that the portfolio optimization problem can be reformulated in terms of maximization of a terminal liquidation utility function, and that both problems have a common optimizer.     

Risk aversion and the dynamics of optimal liquidation strategies in illiquid markets

We consider the infinite-horizon optimal portfolio liquidation problem for a von Neumann–Morgenstern investor in the liquidity model of Almgren (Appl. Math. Finance 10:1–18, 2003). Using a stochastic control approach, we characterize the value function and the optimal strategy as classical solutions of nonlinear parabolic partial differential equations. We furthermore analyze the sensitivities of the value function and the optimal strategy with respect to the various model parameters. In particular, we find that the optimal strategy is aggressive or passive in-the-money, respectively, if and only if the utility function displays increasing or decreasing risk aversion. Surprisingly, only few further monotonicity relations exist with respect to the other parameters. We point out in particular that the speed by which the remaining asset position is sold can be decreasing in the size of the position but increasing in the liquidity price impact.      

Collective mental accounting: an integrated behavioural portfolio selection model for multiple mental accounts

We propose a behavioural portfolio selection model called collective mental accounting (CMA), which integrates all mental sub-portfolios (mental accounts) in one mathematical model. Moreover, this study contributes to the literature of behavioural portfolio selection in three further ways: first, the CMA model can determine the proportions of wealth allocated to each mental sub-portfolio with and without input from the investor. Second, unlike other mental accounting models (MA), in CMA it is possible to define constraints on total asset holdings such as short-selling, and cardinality constraints. Third, in order to make CMA more tractable and mathematically elegant, we obtain a semi-definite programming representation of the model. We also present a numerical example to investigate the effects of short-selling constraints as well as to compare the portfolio recommendations, utility functions, feasibility, and optimality of the CMA and MA models. The results reveal that although both models’ solutions are mean-variance efficient, CMA outperforms MA in terms of behavioural efficient frontier and utility functions.     

Modern portfolio management with conditioning information

This paper studies models in which active portfolio managers utilize conditioning information unavailable to their clients to optimize performance relative to a benchmark. We derive explicit solutions for the optimal strategies with multiple risky assets, with or without a risk-free asset, and consider various constraints on portfolio risks or weights. The optimal strategies feature a mean–variance efficient component (to minimize portfolio variance), and a hedging demand for the benchmark portfolio (to maximize correlation with the benchmark). A currency portfolio example shows that the optimal strategies improve the measured performance by 53% out of sample, compared with portfolios ignoring conditioning information.     

Investing for the Long-run in European Real Estate

We calculate optimal portfolio choices for a long-horizon, risk-averse investor who diversifies among European stocks, bonds, real estate, and cash, when excess asset returns are predictable. Simulations are performed for scenarios involving different risk aversion levels, horizons, and statistical models capturing predictability in risk premia. Importantly, under one of the scenarios, the investor takes into account the parameter uncertainty implied by the use of estimated coefficients to characterize predictability. We find that real estate ought to play a significant role in optimal portfolio choices, with weights between 12 and 44%. Under plausible assumptions, the welfare costs of either ignoring predictability or restricting portfolio choices to traditional financial assets only are found to be in the order of 150–300 basis points per year. These results are robust to changes in the benchmarks and in the statistical framework.      

Dynamic Portfolio Choice with Parameter Uncertainty and the Economic Value of Analysts' Recommendations

We derive a closed-form solution for the optimal portfolio ofa nonmyopic utility maximizer who has incomplete informationabout the alphas or abnormal returns of risky securities. Weshow that the hedging component induced by learning about theexpected return can be a substantial part of the demand. Usingour methodology, we perform an "ex ante" empirical exercise,which shows that the utility gains resulting from optimal allocationare substantial in general, especially for long horizons, andan "ex post" empirical exercise, which shows that analysts’recommendations are not very useful. (JEL C61, G11, G24)     

Investment decisions when utility depends on wealth and other attributes

The problem of optimal investment under a multivariate utility function allows for an investor to obtain utility not only from wealth, but other (possibly correlated) attributes. In this paper we implement multivariate mixtures of exponential (mixex) utility to address this problem. These utility functions allow for stochastic risk aversions to differing states of the world. We derive some new results for certainty equivalence in this context. By specifying different distributions for stochastic risk aversions, we are able to derive many known, plus several new utility functions, including models of conditional certainty equivalence and multivariate generalisations of HARA utility, which we call dependent HARA utility. Focusing on the case of asset returns and attributes being multivariate normal, we optimise the asset portfolio, and find that the optimal portfolio consists of the Markowitz portfolio and hedging portfolios. We provide an empirical illustration for an investor with a mixex utility function of wealth and sentiment.     

An empirical analysis of intertemporal asset pricing models with transaction costs and habit persistence

In intertemporal asset pricing models, transaction costs are usually neglected. In this paper we explicitly incorporate transaction costs in these models and analyze to what extent this extension is helpful in explaining the cross-section of expected returns. An empirical analysis using CRSP data on size-based portfolios examines the role of the transaction costs and shows that incorporating such costs in the consumption-based model with power utility does not yield very satisfactory results. However, the introduction of habit persistence substantially improves the model. We find rather strong evidence of habit persistence in monthly consumption data. The plots of the models' pricing errors indicate that an intertemporal asset pricing model with transaction costs and habit persistence explains the cross-sectional variation in the portfolio returns quite accurately.     

Optimal portfolios with a positive lower bound on final wealth

We consider the determination of optimal portfolios under a lower bound on the final wealth. Possible applications range from capital guarantee strategies over life insurance investment where part of the benefit is a guaranteed return on capital to continuous-time mean-variance problems with a strictly positive lower bound. Our solution method consists of transforming the original problem into a portfolio problem without a positive lower bound but a transformed utility function and a modified initial wealth.     

In which financial markets do mutual fund theorems hold true?

The mutual fund theorem (MFT) is considered in a general semimartingale financial market S with a finite time horizon T, where agents maximize expected utility of terminal wealth. The main results are:

A market model with medium/long-term effects due to an insider

In this article, we consider a modification of the Karatzas–Pikovsky model of insider trading. Specifically, we suppose that the insider agent influences the long/medium-term evolution of Black–Scholes type model through the drift of the stochastic differential equation. We say that the insider agent is using a portfolio leading to a partial equilibrium if the following three properties are satisfied: (a) the portfolio used by the insider leads to a stock price which is a semimartingale under his/her own filtration and his/her own filtration enlarged with the final price; (b) the portfolio used by the insider is optimal in the sense that it maximises the logarithmic utility for the insider when his/her filtration is fixed; and (c) the optimal logarithmic utility in (b) is finite. We give sufficient conditions for the existence of a partial equilibrium and show in some explicit models how to apply these general results.     

Revisiting asset pricing under habit formation in an overlapping-generations economy

By incorporating habit formation into an overlapping-generations economy, we show that the middle-aged consumers’ savings decision has a substantial impact on the equity premium. The higher incentive for savings for the middle-aged, resulting from the habit formation preference, causes an even higher demand for bonds and a lower demand for equity, which eventually generates a lower risk-free rate and a higher required return for holding equity than does the framework of non-habit forming models. Calibration results verify that the habit formation setting, together with an OLG framework is capable of yielding lower bond returns and higher equity returns than the standard CRRA utility models, and the borrowing constraint imposed on the young-aged consumers amplifies the positive effect of habit formation on the equity premium. The findings imply that habit formation preferences within the overlapping-generations framework under the borrowing-constrained economy can provide a more improved explanation of the equity premium puzzle.     

Asset allocation: How much does model choice matter?

This paper analyzes the optimal portfolio decision of a CRRA investor in models with stochastic volatility and stochastic jumps. The investor follows a buy-and-hold strategy in the stock, the money market account, and one additional derivative. We show that both the type of the model and the structure of the risk premia have a significant impact on the optimal portfolio, on the utility gain from having access to derivatives, and on whether the investor prefers to trade OTM or ATM options. We also show that model mis-specification results in significant utility losses. Omitting jumps in volatility can be devastating, in particular if the investor chooses the seemingly optimal OTM put options. A misestimation of the structure of the risk premia has a less devastating effect, but can still lead to a loss of around 4% in the annual certainty equivalent return.     

Size and Value Anomalies under Regime Shifts

This paper finds strong evidence of time-variations in the jointdistribution of returns on a stock market portfolio and portfoliostracking size- and value effects. Mean returns, volatilitiesand correlations between these equity portfolios are found tobe driven by underlying regimes that introduce short-run markettiming opportunities for investors. The magnitude of the premiaon the size and value portfolios and their hedging propertiesare found to vary across regimes. Regimes are shown to havea large impact both on the optimal asset allocation—especiallyunder rebalancing—and on investors' utility. Regimes alsohave a considerable impact on hedging demands, which are positivewhen the investor starts from more favorable regimes and negativewhen starting from bad states. Recursive out-of-sample forecastingexperiments show that portfolio strategies based on models thataccount for regimes dominate single-state benchmarks.     

A Factor Allocation Approach to Optimal Bond Portfolio

This paper proposes a new method to a bond portfolio problem in a multi-period setting. In particular, we apply a factor allocation approach to constructing the optimal bond portfolio in a class of multi-factor Gaussian yield curve models. In other words, we consider a bond portfolio problem in terms of a factors’ allocation problem. Thus, we can obtain clear interpretation about the relation between the change in the shape of a yield curve and dynamic optimal strategy, which is usually hard to be obtained due to high correlations among individual bonds. We first present a closed form solution of the optimal bond portfolio in a class of the multi-factor Gaussian term structure model. Then, we investigate the effects of various changes in the term structure on the optimal portfolio strategy through series of comparative statics.     

Optimal portfolio choice in the bond market

We consider the Merton problem of optimal portfolio choice when the traded instruments are the set of zero-coupon bonds. Working within a Markovian Heath–Jarrow–Morton model of the interest rate term structure driven by an infinite-dimensional Wiener process, we give sufficient conditions for the existence and uniqueness of an optimal trading strategy. When there is uniqueness, we provide a characterization of the optimal portfolio as a sum of mutual funds. Furthermore, we show that a Gauss–Markov random field model proposed by Kennedy [Math. Financ. 4, 247–258(1994)] can be treated in this framework, and explicitly calculate the optimal portfolio. We show that the optimal portfolio in this case can be identified with the discontinuities of a certain function of the market parameters.     

习惯形成下的最优货币政策

著名的弗里德曼规则指出,最优货币政策可以通过设置名义利率等于0来实现。本文构造了基于习惯形成的最优货币政策模型,并使用主方法求解了模型。本文的研究表明,当家庭的效用函数偏好具有习惯形成的特点时,弗里德曼规则仍然成立。