Conditional currency hedging

I propose a simple and robust approach to hedge currency risk that can be directly applied by international investors in diverse asset classes. Compared to current mean-variance approaches, it is robust to overfitting and thus better anticipates risk-minimizing currency positions for global equity, bond, and commodity investors out of sample. Furthermore, correlations among currencies, equities, and commodities can be predicted by lagged implied foreign exchange volatility. This allows investors to dynamically adjust their hedges, resulting in significantly lower risk compared to other hedging alternatives while maintaining or even improving Sharpe ratio, particularly during crisis periods.     

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Abstract

In this paper a continuous-time model of a reinsurance market is presented, which contains the principal components of uncertainty transparent in such a market: Uncertainty about the time instants at which accidents take place, and uncertainty about claim sizes given that accidents have occurred.

Due to random jumps at random time points of the underlying claims processes, the absence of arbitrage opportunities is not sufficient to give unique premium functionals in general. Market preferences are derived under a necessary condition for a general exchange equilibrium. Information constraints are found under which premiums of risks are determined. It is demonstrated how general reinsurance treaties can be uniquely split into proportional contracts and nonproportional ones.

Several applications to reinsurance markets are given, and the results are compared to the corresponding theory of the classical one-period model of a reinsurance syndicate.

This paper attempts to reach a synthesis between the classical actuarial risk theory of insurance, in which virtually no economic reasoning takes place but where the net reserve is represented by a stochastic process, and the theory of partial equilibrium price formation at the heart of the economics of uncertainty.     

Robust optimal strategies for an insurer with reinsurance and investment under benchmark and mean-variance criteria

In this paper, an ambiguity-averse insurer (AAI) whose surplus process is approximated by a Brownian motion with drift, hopes to manage risk by both investing in a Black–Scholes financial market and transferring some risk to a reinsurer, but worries about uncertainty in model parameters. She chooses to find investment and reinsurance strategies that are robust with respect to this uncertainty, and to optimize her decisions in a mean-variance framework. By the stochastic dynamic programming approach, we derive closed-form expressions for a robust optimal benchmark strategy and its corresponding value function, in the sense of viscosity solutions, which allows us to find a mean-variance efficient strategy and the efficient frontier. Furthermore, economic implications are analyzed via numerical examples. In particular, our conclusion in the mean-variance framework differs qualitatively, for certain parameter ranges, with model-uncertainty robustness conclusions in the framework of utility functions: model uncertainty does not always result in an agent deciding to reduce risk exposure under mean-variance criteria, opposite to the conclusions for utility functions in Maenhout and Liu. Our conclusion can be interpreted as saying that the mean-variance problem for the AAI explains certain counter-intuitive investor behaviors, by which the attitude to risk exposure, for an AAI facing model uncertainty, depends on positive past experience.     

Who gains and who loses on stock markets? Risk preferences and timing matter

This paper uses an agent-based multi-asset model to examine the effect of risk preferences and optimal rebalancing frequency on performance measures while tracking profit and risk-adjusted return. We focus on the evolution of portfolios managed by heterogeneous mean-variance optimizers with a quadratic utility function under different market conditions. We show that patient and risk-averse agents are able to outperform aggressive risk-takers in the long-run. Our findings also suggest that the trading frequency determined by the optimal tolerance for the deviation from portfolio targets should be derived from a tradeoff between rebalancing benefits and rebalancing costs. In a relatively calm market, the absolute range of 6% to 8% and the complete-way back rebalancing technique outperforms others. During particular turbulent periods, however, none of the existing rebalancing techniques improves tax-adjusted profits and risk-adjusted returns simultaneously.     

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.     

Investment Guide to Yunnan

Yunnan Province is located on the southwest boundary of the People＇s Republic of China,spanning approximately 394,000 square kilometers,which accounts for 4.1% of the total area of China.The south part of the province is on the belt of the Tropic of Cancer.The average altitude is around 2,000 meters above sea level,with highest point at 6,740 meters and the lowest 76.4 meters above sea level.About 84% of the entire province is mountainous region,10% is plateau and hilly land and 6% area is basin and valley.     

THE ROLE OF LOGISTICS IN MARKET ORIENTATION

In today's increasingly competitive environment, survival depends on two key aspects of being market‐oriented ‐ understanding the external environment and executing decisions based on that understanding. Logistics personnel are uniquely positioned to play a key role in creating and maintaining a market‐oriented organization as they are progressively gaining more responsibilities in integrating cross‐functional processes and implementing supply chain strategies. This paper explores how logisticians participate in market orientation behaviors and how a market‐oriented logistics function impacts logistics and business performance. Based on a qualitative field research study involving in‐depth interviews with seventeen logistics personnel that draws and builds upon the logistics, market orientation, knowledge management, organizational behavior, information processing, and strategic management literatures, a theoretical model of logistics market orientation and its effect on logistics and business performance is developed and propositions are presented. Findings highlight logistics' central role in generating, disseminating, reaching a shared interpretation of, and responding to market intelligence.     

CONTINUOUS-TIME MEAN-VARIANCE PORTFOLIO SELECTION WITH BANKRUPTCY PROHIBITION

A continuous-time mean-variance portfolio selection problem is studied where all the market coefficients are random and the wealth process under any admissible trading strategy is not allowed to be below zero at any time. The trading strategy under consideration is defined in terms of the dollar amounts, rather than the proportions of wealth, allocated in individual stocks. The problem is completely solved using a decomposition approach. Specifically, a (constrained) variance minimizing problem is formulated and its feasibility is characterized. Then, after a system of equations for two Lagrange multipliers is solved, variance minimizing portfolios are derived as the replicating portfolios of some contingent claims, and the variance minimizing frontier is obtained. Finally, the efficient frontier is identified as an appropriate portion of the variance minimizing frontier after the monotonicity of the minimum variance on the expected terminal wealth over this portion is proved and all the efficient portfolios are found. In the special case where the market coefficients are deterministic, efficient portfolios are explicitly expressed as feedback of the current wealth, and the efficient frontier is represented by parameterized equations. Our results indicate that the efficient policy for a mean-variance investor is simply to purchase a European put option that is chosen, according to his or her risk preferences, from a particular class of options.     

Mean-Variance Hedging for Stochastic Volatility Models

In this paper we discuss the tractability of stochastic volatility models for pricing and hedging options with the mean-variance hedging approach. We characterize the variance-optimal measure as the solution of an equation between Doléans exponentials; explicit examples include both models where volatility solves a diffusion equation and models where it follows a jump process. We further discuss the closedness of the space of strategies.     

银行信贷资产证券化信用风险度量及传染研究——基于修正KMV模型和MST算法的实证

精准科学地度量和描述信用风险及传染机制有利于银行信贷资产证券化的高效健康发展和货币市场系统性风险的防范.运用修正KMV模型测度银行信贷资产证券化产品在不同时期的信用风险,并采用最小生成树(MST)算法考察银行间信用风险的传染机制.结果显示:政策性银行和大型商业银行发行的产品在各个时期信用风险均处于较低水平;股份制银行、城商行和农商行发行的产品违约率前期略高于前两类银行,但后期明显下降;后三类银行位于银行股票收益率网络的中心位置,具有传递信息和维系网络稳定的重要作用.