Portfolio management with stochastic interest rates and inflation ambiguity

We solve, in closed form, a stock-bond-cash portfolio problem of a risk- and ambiguity-averse investor when interest rates and the inflation rate are stochastic. The expected inflation rate is unobservable, but the investor can learn about it from observing realized inflation and stock and bond prices. The investor is ambiguous about the inflation model and prefers a portfolio strategy which is robust to model misspecification. Ambiguity about the inflation dynamics is shown to affect the optimal portfolio fundamentally different than ambiguity about the price dynamics of traded assets, for example the optimal portfolio weights can be increasing in the degree of ambiguity aversion. In a numerical example, the optimal portfolio is significantly affected by the learning about expected inflation and somewhat affected by ambiguity aversion. The welfare loss from ignoring learning or ambiguity can be considerable.     

Islamic and conventional portfolios optimization under investor sentiment states: Bayesian vs Markowitz portfolio analysis

This paper investigates the portfolio optimization under investor’s sentiment states of Hidden Markov model and over a different time horizon during the period 2004–2016. To compare the efficient portfolios of the Islamic and the conventional stock indexes, we have employed two approaches: the Bayesian and Markowitz mean-variance. Our findings reveal that the Bayesian efficient frontier of Islamic and conventional stock portfolios is affected by the investor’s sentiment state and the time horizon. Our findings also indicate that the investor’s sentiment regimes change the Islamic and the conventional optimal diversified portfolios.Moreover, the results show that the potential diversification benefits seem to be more important when using the Bayesian approach than when applying the Markowitz approach. This finding is valid for the bearish, depressed, bullish and calm states in Islamic stock markets. However, the diversification of potential portfolios is significant only for the bullish and the bubble states in the conventional financial markets.The findings of the study provided additional evidence for investors to exploit googling investor sentiment states to evaluate the portfolio performance and make an optimal portfolio allocation.     

Herd behaviour & investor sentiment: Evidence from UK mutual funds

The aims of this paper are to detect evidence of institutional investor herding behaviour and examine the role that investor sentiment plays in institutional investor herding behaviour. The herding behaviour is investigated by examining the dispersion of time varying beta of UK open-end and closed-end funds. The study finds evidence of fund managers' herding behaviour, which suggests they are likely to herd on market portfolio, size, and value factors. UK market-wide investor sentiment index is used for investigating the effects of investor sentiment on institutional herding behaviour. We find a unidirectional investor sentiment effect on the herding of UK mutual fund managers. We also reveal that the sentiment factors affecting UK open-end and closed-end fund managers herding behaviour are different due to the differences in fund structure.     

Intermediated Investment Management

Intermediaries such as financial advisers serve as an interface between portfolio managers and investors. A large fraction of their compensation is often provided through kickbacks from the portfolio manager. We provide an explanation for the widespread use of intermediaries and kickbacks. Depending on the degree of investor sophistication, kickbacks are used either for price discrimination or aggressive marketing. We explore the effects of these arrangements on fund size, flows, performance, and investor welfare. Kickbacks allow higher management fees to be charged, thereby lowering net returns. Competition among active portfolio managers reduces kickbacks and increases the independence of advisory services.     

How suboptimal are linear sharing rules?

The objective of this paper is to analyze criteria for portfolio choice when two investors are forced to invest in a common portfolio and share the proceeds by a linear sharing rule. A similar situation with many investors is typical for defined contribution pension schemes. The restriction implies two sources of suboptimal investment decisions as seen from each of the two investors individually. One is the suboptimal choice of portfolio, the other is the forced linear sharing rule. We measure the combined consequence for each investor by their respective loss in wealth equivalent. We show that significant losses can arise when investors are diverse in their risk attitude. We also show that an investor with a low degree of risk aversion, like the logarithmic or the square root investor, often applied in portfolio choice models, can either inflict or be subject to severe losses when being forced to participate in such a common investment pool.     

The Role of Learning in Dynamic Portfolio Decisions

This paper analyzes the effect of uncertainty about the mean return on the risky asset on the portfolio decisions of an investor who has a long investment horizon. Building on the earlier work of Detemple (1986), Dothan and Feldman (1986), and Gennotte (1986), it is shown that the possibility of future learning about the mean return on the risky asset induces the investor to take a larger or smaller position in the risky asset than she would if there were no learning, the direction of the effect depending on whether the investor is more or less risk tolerant than the logarithmic investor whose portfolio decisions are unaffected by the possibility of future learning. Numerical calculations show that uncertainty about the mean return on the market portfolio has a significant effect on the portfolio decision of an investor with a 20 year horizon if her assessment of the market risk premium is based solely on the Ibbotson and Sinquefield (1995) data.     

Selecting a portfolio with skewness: Recent evidence from US,European, and Latin American equity markets

Polynomial goal programming, in which investor preferences for skewness can be incorporated, is utilized to determine the optimal portfolio from Latin American, US and European capital markets. The empirical findings suggest that the incorporation of skewness into an investor’s portfolio decision causes a major change in the resultant optimal portfolio. The empirical evidence indicates that investors do trade expected return of the portfolio for skewness.     

Portfolio selection with skewness: A multiple-objective approach

In the presence of skewness, the portfolio selection entails considering competing and conflicting objectives, such as maximizing both its expected returns and skewness, and minimizing its risk for decreasing absolute risk-aversion investors. Since it is unlikely that a portfolio can solve the multiple-objectives problem simultaneously, a portfolio selection must depend on the investor's preference among objectives. This article shows that investor preference can be incorporated into a polynomial goal programming problem from which a portfolio selection with skewness is determined. An inefficient mean-variance portfolio may be optimal in the mean-variance-skewness content. The features of applying polynomial goal programming in portfolio selection are 1) the existence of an optimal solution, 2) the flexibility of the incorporation of investor preference, and 3) the relative simplicity of computational requirements.     

Optimal Bond Portfolio for Investors with Long Time Horizons

We study the optimal bond portfolio for an investor with long time horizonusing Japanese interest rate data. A simple one-factor term structure modelis used for our numerical example. The optimal portfolio is computed using thetechnique of stochastic flows and Monte Carlo simulation. The hedgingportfolio is not negligible and the mean variance portfolio is very sensitiveto parameter values. The optimal portfolio is highly leveraged for a typicalparameter value. The investor holds a zero-coupon bond because of the lowerbound restriction on investor's wealth. The lower bound constraint may makethe optimal portfolio more realistic.     

A Simulation Approach to Dynamic Portfolio Choice with an Application to Learning About Return Predictability

We present a simulation-based method for solving discrete-timeportfolio choice problems involving non-standard preferences,a large number of assets with arbitrary return distribution,and, most importantly, a large number of state variables withpotentially path-dependent or non-stationary dynamics. The methodis flexible enough to accommodate intermediate consumption,portfolio constraints, parameter and model uncertainty, andlearning. We first establish the properties of the method forthe portfolio choice between a stock index and cash when thestock returns are either iid or predictable by the dividendyield. We then explore the problem of an investor who takesinto account the predictability of returns but is uncertainabout the parameters of the data generating process. The investorchooses the portfolio anticipating that future data realizationswill contain useful information to learn about the true parametervalues.     

Dynamic optimal portfolio choice in a jump-diffusion model with investment constraints

We consider the dynamic portfolio choice problem in a jump-diffusion model, where an investor may face constraints on her portfolio weights: for instance, no-short-selling constraints. It is a daunting task to use standard numerical methods to solve a constrained portfolio choice problem, especially when there is a large number of state variables. By suitably embedding the constrained problem in an appropriate family of unconstrained ones, we provide some equivalent optimality conditions for the indirect value function and optimal portfolio weights. These results simplify and help to solve the constrained optimal portfolio choice problem in jump-diffusion models. Finally, we apply our theoretical results to several examples, to examine the impact of no-short-selling and/or no-borrowing constraints on the performance of optimal portfolio strategies.     

Robust Portfolio Rules and Asset Pricing

I present a new approach to the dynamic portfolio and consumptionproblem of an investor who worries about model uncertainty (inaddition to market risk) and seeks robust decisions along thelines of Anderson, Hansen, and Sargent (2002). In accordancewith max-min expected utility, a robust investor insures againstsome endogenous worst case. I first show that robustness dramaticallydecreases the demand for equities and is observationally equivalentto recursive preferences when removing wealth effects. Unlikestandard recursive preferences, however, robustness leads toenvironment-specific "effective" risk aversion. As an extension,I present a closed-form solution for the portfolio problem ofa robust Duffie-Epstein-Zin investor. Finally, robustness increasesthe equilibrium equity premium and lowers the risk-free rate.Reasonable parameters generate a 4% to 6% equity premium.     

Portfolio optimization with a defaultable security

In this paper we derive a closed-form solution for a representative investor who optimally allocates her wealth among the following securities: a credit-risky asset, a default-free bank account, and a stock. Although the inclusion of a credit-related financial product in the portfolio selection is more realistic, no closed-form solutions to date are given in the literature when a recovery value is considered in the event of a default. While most authors have assumed some recovery scheme in their initial model set up, they do not address the portfolio problem with a recovery when a default actually occurs. Given the tractability of the recovery of market value, we solved the optimal portfolio problem for the representative investor whose utility function is a Constant Relative Risk Aversion utility function. We find that the investor will allocate larger fraction of wealth to the defaultable security as long as the default-event risk is priced. These results are very intuitive and reasonable since it indicates that if the default risk premium is not priced properly the investor purchases less defaultable securities.     

Does the Failure of the Expectations Hypothesis Matter for Long‐Term Investors?

We solve the portfolio problem of a long‐run investor when the term structure is Gaussian and when the investor has access to nominal bonds and stock. We apply our method to a three‐factor model that captures the failure of the expectations hypothesis. We extend this model to account for time‐varying expected inflation, and estimate the model with both inflation and term structure data. The estimates imply that the bond portfolio of a long‐run investor looks very different from the portfolio of a mean‐variance optimizer. In particular, time‐varying term premia generate large hedging demands for long‐term bonds.     

Portfolio selection with mental accounts and delegation

Das et al. (2010) develop an elegant framework where an investor selects portfolios within mental accounts but ends up holding an aggregate portfolio on the mean-variance frontier. This investor directly allocates the wealth in each account among available assets. In practice, however, investors often delegate the task of allocating wealth among assets to portfolio managers who seek to beat certain benchmarks. Accordingly, we extend their framework to the case where the investor allocates the wealth in each account among portfolio managers. Our contribution is threefold. First, we provide an analytical characterization of the existence and composition of the optimal portfolios within accounts and the aggregate portfolio. Second, we present conditions under which such portfolios are not on the mean-variance frontier, and conditions under which they are. Third, we show that the aforementioned analytical characterization is also applicable within the framework of Das et al. and thus improves upon their numerical approach.     

An Exact Solution to a Dynamic Portfolio Choice Problem under Transactions Costs

The presence of any friction in financial markets qualitatively changes the nature of the optimization problem faced by an investor. It requires one to either act or do nothing, an issue which, of course, does not arise in frictionless situations. The investor considered here accumulates wealth without consuming until some terminal point in time when he consumes all. His objective is to maximize the expected utility derived from that terminal consumption. We postpone the terminal point far into the future to obtain a stationary portfolio rule. The portfolio policy is in the form of two control barriers between which portfolio proportions are allowed to fluctuate. We show how to calculate them.     

Learning about Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation

This paper examines the effects of uncertainty about the stock return predictability on optimal dynamic portfolio choice in a continuous time setting for a long-horizon investor. Uncertainty about the predictive relation affects the optimal portfolio choice through dynamic learning, and leads to a state-dependent relation between the optimal portfolio choice and the investment horizon. There is substantial market timing in the optimal hedge demands, which is caused by stochastic covariance between stock return and dynamic learning. The opportunity cost of ignoring predictability or learning is found to be quite substantial.     

Foreign institutional investors,information asymmetries,and asset valuation in emerging markets

This study investigates the effects of information asymmetries and asset valuation model differences (investor heterogeneity) between foreign and domestic investors on their distinct portfolio holdings in an emerging market setting. I argue that information asymmetry and investor heterogeneity views significantly interact in explaining the different asset allocation decisions of foreign and domestic investors. Employing a large dataset from Turkey, the findings suggest that both information asymmetry and investor heterogeneity view play a key role in explaining the investment decisions of different investor groups. Specifically, different from domestic investors, foreign investors are more likely to invest in firms with a higher global market performance which supports the investor heterogeneity view. However, this relationship only holds for firms with high information asymmetries. The difference in valuation models between foreign and domestic investors converge when asymmetric information problems between these investor groups weaken. This study contributes to the international finance literature by providing a new explanation of why foreign and domestic investors invest in different assets.     

Investor attention,firm-specific characteristic,and momentum: A case of the Korean stock market

This study examines the sources of negative momentum profits by combining investor attention and the properties of common and firm-specific factors. We choose the Korean stock market as a good case to characterize the negative momentum profits identified in Asia. In both portfolio and stock analyses, a method is devised to generate return data involving the property of each common and firm-specific factor within stock groups by investor attention. This study found significant negative momentum profits within the stock group with high investor attention. This momentum effect is highly dependent on the reversed performance of the past loser portfolio, not the continued performance of the past winner portfolio, and this reversal is strongly attributable to the properties of firm-specific factors, and not those of common factors. These results are robustly consistent regardless of changes in empirical design and the consideration of influence factors, market dynamics, and other stock markets.     

Portfolio selections under mean-variance preference with multiple priors for means and variances

We study portfolio selections under mean-variance preference with multiple priors for means and variances. We introduce two types of multiple priors, the priors for means and the priors for variances of risky asset returns. As our framework, in the absence of a risk-free asset, the global minimum-variance portfolio is optimal when the investor is extremely ambiguity averse with respect to means, and the equally weighted portfolio is optimal when the investor is extremely ambiguity averse with respect to variances.