Dynamic pairs trading using the stochastic control approach

We propose a model for analyzing dynamic pairs trading strategies using the stochastic control approach. The model is explored in an optimal portfolio setting, where the portfolio consists of a bank account and two co-integrated stocks and the objective is to maximize for a fixed time horizon, the expected terminal utility of wealth. For the exponential utility function, we reduce the problem to a linear parabolic partial differential equation which can be solved in closed form. In particular, we exhibit the optimal positions in the two stocks.     

Cross-sectional tests of asset pricing models with full-rank mimicking portfolios

In the standard tests of asset pricing models, factor risk premia are estimated on a test asset span so that models are tested with degrees of freedom reduced by the number of factors. Risk premia of traded factors can be further restricted to be equal to their expected returns, but such restrictions cannot be imposed on models with nontraded factors, which may create a problem of testing without full restrictions or on unequal asset spans across models. We propose a full-rank mimicking portfolio approach by projecting nontraded factors onto a combined span of test assets and benchmark traded factors. Under the Hansen-Jagannathan distance framework, we demonstrate that full-rank mimicking portfolios can provide improved power and fair performance comparison against a benchmark model in both specification and model comparison tests.     

Performance evaluation with portfolio holdings information

This paper surveys recent academic research that uses portfolio holdings to evaluate the performance of an asset manager. These approaches mitigate the benchmark-choice problem of Roll (1978), as well as providing a much more precise attribution of the sources of manager returns. Although originally developed with U.S. data, recent papers have applied these approaches to European, Asian, and Australian equity managers. All surveyed approaches can be integrated into the Brinson, Hood, and Beebower (1986) attribution method, if we allow the composition of the benchmark portfolio to evolve through time according to the observed portfolio holdings of an asset manager.     

The long-run performance of initial public offerings: Stochastic dominance criteria

We examine the long-run performance of initial public offerings (IPOs) using the idea of stochastic dominance. The analysis is a first attempt using a non-event study methodology to evaluate long-horizon performance. We find that there is no first-order stochastic dominance relation between the IPO portfolio and the benchmark of a broad index or a portfolio including either small size or low book-to-market stocks. However, those benchmarks second-order stochastically dominate the IPO portfolio. When using a portfolio including both small size and low book-to-market stocks as benchmark, there is a clear dominance of the IPO portfolio over the benchmark for both orders. Our findings generally imply that the question of assessing portfolio performance between IPO firms and benchmark portfolios depends critically on the specific construction or the cumulative distribution function of the benchmark portfolios. The empirical results also potentially explain the extent of sample dependent results in the literature.     

Optimal strategy for a fund manager with option compensation

I consider the problem of portfolio optimization for a manager whose compensation is given by the sum of a constant and a variable term. The constant term is a fixed percentage of the managed funds that is payed to the manager independently of his performance. The variable term is a premium that is proportional to the profit earned by the manager over a benchmark at a certain evaluation date. I find the optimal strategy and the optimal portfolio value in the Black–Scholes setting when the benchmark is a linear combination of the risky asset and the money market account.     

Performance measurement and best-practice benchmarking of mutual funds: combining stochastic dominance criteria with data envelopment analysis

We propose a method for mutual fund performance measurement and best-practice benchmarking, which endogenously identifies a dominating benchmark portfolio for each evaluated mutual fund. Dominating benchmarks provide information about efficiency improvement potential as well as portfolio strategies for achieving them. Portfolio diversification possibilities are accounts for by using Data Envelopment Analysis (DEA). Portfolio risk is accounted for in terms of the full return distribution by utilizing Stochastic Dominance (SD) criteria. The approach is illustrated by an application to US based environmentally responsible mutual funds.     

Long-term wealth growth portfolio allocation under parameter uncertainty: A non-conservative robust approach

The Kelly portfolio, which is documented to have the highest wealth growth rate of any other portfolio in the long run, has highly risky and unstable performance in the short term. This paper offers a hybrid approach to address this problem by integrating the concept of ridge regression and shrinkage estimation into a robustly modified Kelly portfolio. The proposed approach is a two-stage optimization process that not only takes into account the effect of estimation error but also solves the notoriously conservative problem introduced by the robust optimization method. By extending the worst-case scenarios considered by the robust Kelly portfolio, our approach significantly improves its out-of-sample performance without compromising risk reduction. In an extensive out-of-sample analysis with simulated and empirical data sets, we also characterize the impacts of the robustness level and the length of the rolling window on the final result. Moreover, we conduct a comparative study to confirm the validity of the proposed approach, and our model allows the investor to have a better risk-return trade-off than other traditional models.     

Market insurance and endogenous saving with multiple loss states

The standard one-period model for insurance demand does not consider the interaction between the present and the future. Reflecting this observation, we analyze intertemporal insurance demand and saving in a two-period model with multiple loss states. When an individual has no access to a capital market, we first find that an actuarially fair premium does not guarantee full insurance in general, unlike in the standard approach. Income stream and discount factors are also important in determining insurance demand. Second, insurance is neither an inferior good nor a Giffen good. Third, an increase in concavity of the utility function does not always lead to an increase in insurance demand. The current income level and changes in downside risk aversion affect insurance demand. When the individual has access to a capital market, we further have the following observations. Fourth, an actuarially fair premium leads to full insurance. Fifth, insurance is an inferior good and can be a Giffen good under decreasing absolute risk aversion (DARA). An increase in the interest rate leads to a lower insurance demand and a higher saving when the relative risk aversion is less than unity. Lastly, an increase in concavity of the utility function leads to an increase in insurance demand and a decrease in saving. In conjunction, our findings point to the fact that the standard results are not obtainable if insurance demand is considered in isolation from the capital market.     

Selecting a discrete portfolio

We study the problem of selecting an optimal portfolio out of a finite set of available assets. Assets are characterized by their expected returns and the covariance matrix, and investors are assumed to have a mean–variance utility, that is, their utility function is linear in the mean and variance of the portfolio they hold.When assets are negatively correlated, or even when a slightly more general condition is satisfied, we provide an algorithm for selecting an optimal portfolio. We illustrate the usefulness of this algorithm by some comparative statics result. When assets can be positively correlated, we deliver a negative result regarding the existence of useful algorithms for selecting an optimal portfolio.     

Portfolio choice in the model of expected utility with a safety-first component

Decisions in Economics and Finance - The standard problem of portfolio choice between one risky and one riskless asset is analyzed in the model of expected utility with a safety-first component...     

内部收益保证下养老基金的最优资产配置

研究内部收益保证下DC型养老基金的最优资产配置问题。利用鞅方法，在HJM利率期限结构下求得了最优资产配置的显性解。结论表明最优投资策略分为四部分：投机策略、利率套期保值策略、基准组合的复制策略及一揽予债券卖空策略。最后对最优策略的动态行为进行了数值分析。     

A Conditional Single Index model with Local Covariates for detecting and evaluating active portfolio management

The intercept of standard Single Index and Conditional Single Index models, the so-called alpha, is often used to evaluate the long-run performance of managed portfolios. However, this measure is not always appropriate for detecting the presence and impact of active management strategies. Based on the conditional factor models literature, we introduce a Conditional Single Index model where the time-varying alpha and beta parameters depend only on the past history of the underlying portfolio returns and of the benchmark returns. The dynamics of the parameters have two components: the first describes the long-term behaviour of the alpha and beta, whereas the second is associated with the short-term performance of the underlying portfolio. The interpretation of parameters allows the identification of portfolio managers who implement active management strategies. An application on a set of 1300 U.S. mutual funds shows how widespread active management is on the U.S. market.     

Bayesian forecasting and portfolio decisions using dynamic dependent sparse factor models

We extend the recently introduced latent threshold dynamic models to include dependencies among the dynamic latent factors which underlie multivariate volatility. With an ability to induce time-varying sparsity in factor loadings, these models now also allow time-varying correlations among factors, which may be exploited in order to improve volatility forecasts. We couple multi-period, out-of-sample forecasting with portfolio analysis using standard and novel benchmark neutral portfolios. Detailed studies of stock index and FX time series include: multi-period, out-of-sample forecasting, statistical model comparisons, and portfolio performance testing using raw returns, risk-adjusted returns and portfolio volatility. We find uniform improvements on all measures relative to standard dynamic factor models. This is due to the parsimony of latent threshold models and their ability to exploit between-factor correlations so as to improve the characterization and prediction of volatility. These advances will be of interest to financial analysts, investors and practitioners, as well as to modeling researchers.     

Is small beautiful? Size effects of volatility spillovers for firm performance and exchange rates in tourism

This paper examines the size effects of volatility spillovers for firm performance and exchange rates with asymmetry in the Taiwan tourism industry. The analysis is based on two conditional multivariate models, BEKK–AGARCH and VARMA–AGARCH, in the volatility specification. Daily data from 1 July 2008 to 29 June 2012 for 999 firms are used, which covers the Global Financial Crisis. The empirical findings indicate that there are size effects on volatility spillovers from the exchange rate to firm performance. Specifically, the risk for firm size has different effects from the three leading tourism sources to Taiwan, namely USA, Japan, and China. Furthermore, all the return series reveal quite high volatility spillovers (at over 60%) with a one-period lag. The empirical results show a negative correlation between exchange rate returns and stock returns. However, the asymmetric effect of the shock is ambiguous, owing to conflicts in the significance and signs of the asymmetry effect in the two estimated multivariate GARCH models. The empirical findings provide financial managers with a better understanding of how firm size is related to financial performance, risk and portfolio management strategies that can be used in practice.     

Optimal consumption and portfolio rules with intertemporally dependent utility of consumption

In the usual consumption portfolio problem, lifetime utility is assumed to be time-additive. This assumption has been criticized for failing to capture important intertemporal dependencies in utility such as intertemporal risk aversion and habit formation. This paper studies the consumption portfolio problem for a class of intertemporally dependent utility functions.     

A Stein-type shrinkage estimator of the covariance matrix for portfolio selections

The covariance matrix plays a crucial role in portfolio optimization problems as the risk and correlation measure of asset returns. An improved estimation of the covariance matrix can enhance the performance of the portfolio. In this paper, based on the Cholesky decomposition of the covariance matrix, a Stein-type shrinkage strategy for portfolio weights is constructed under the mean-variance framework. Furthermore, according to the agent’s maximum expected utility value, a portfolio selection strategy is proposed. Finally, simulation experiments and an empirical study are used to test the feasibility of the proposed strategy. The numerical results show our portfolio strategy performs satisfactorily.     

Approximating exact expected utility via portfolio efficient frontiers

Expected utility theory is nowadays accepted as the standard for rational choice among risky assets. However, as Harry Markowitz recently pointed out, the problem of how the maximum expected utility along the risk–return portfolio efficient frontiers approximates the exact maximum expected utility is still open. This paper shows that some popular risk–return models are actually able to approximate expected utility maximization with respect to classical and new distance measures. It also analyzes the ability of the whole risk–return efficient frontiers to approximate the exact one. Our empirical analysis is based on recent publicly available real-world data sets.     

The more the merrier? Network portfolio size and innovation performance in Nigerian firms

A positive relationship between firms' networking activities and innovativeness has been consistently established in the literature on innovation. However, studies considering different innovation types, and on developing countries are scarce. This paper addresses questions concerning the relationship between networking strategies and innovativeness of firms, using innovation survey data on Nigerian firms. Quantile regression is applied to trace the link between portfolio size and innovation at different levels of innovative success. The results show a positive relationship between a firm's innovation performance and the size of its networking portfolio. This relationship varies across different innovation types and with increasing innovation performance. The findings suggest that the widely accepted portfolio approach to external search for knowledge is not necessarily always the best—its utility depends on the firm's current level of innovative success. This poses a challenge for open innovation.     

Arbitrage concepts under trading restrictions in discrete-time financial markets

In a discrete-time setting, we study arbitrage concepts in the presence of convex trading constraints. We show that solvability of portfolio optimization problems is equivalent to absence of arbitrage of the first kind, a condition weaker than classical absence of arbitrage opportunities. We center our analysis on this characterization of market viability and derive versions of the fundamental theorems of asset pricing based on portfolio optimization arguments. By considering specifically a discrete-time setup, we simplify existing results and proofs that rely on semimartingale theory, thus allowing for a clear understanding of the foundational economic concepts involved. We exemplify these concepts, as well as some unexpected situations, in the context of one-period factor models with arbitrage opportunities under borrowing constraints.     

均值方差偏好和下方风险控制下的动态投资组合决策模型

本文在均值方差框架下，研究了下方风险控制下的动态投资组合问题。在目标函数中考虑了投资组合的最坏结果，利用标准的期权定价理论，给出了最优投资策略的解析式。该投资策略等价于一个关于“资产”最小二阶矩组合的欧式看跌期权和无风险资产的组合，而且两基金分离定理仍然成立。