基于极端损失约束的均值-方差投资组合选择研究

将极端损失约束引入投资组合选择问题研究,构建了极端损失约束的均值一方差投资组合模型,通过拉格朗日乘数法,得到了最优投资组合策略及有效边界的解析解,并就投资策略运用方面进行了实证分析结果表明:在方差一均值坐标中有效边界与经典的均值一方差模型的有效边界形状是一致的,但极端损失约束越紧,有效前沿越向方差一均值坐标的右侧移动;在传统均值-方差模型中加入极端损失约束可以改善投资组合的业绩表现,相对于等权组合策略和最小方差策略而言,适当的极端损失约束可以给投资者带来最好的投资业绩。     

国际分散化投资对中国超额外汇储备投资的启示——基于1999~2012年世界主要股市与大宗商品历史数据的实证研究

本文基于世界主要股市与大宗商品1999.1-2012.11的历史数据,运用Markowits均值方差模型构建了我国超额外汇储备的国际分散化投资的有效边界,研究了在满足我国国内投资的风险条件下,寻找我国超额外汇储备的国际分散化投资的有效组合,最后以此为基础提出了基于我国国情的政策建议.     

国际分散化投资对中国超额外汇储备投资的启示——基于1999～2012年世界主要股市与大宗商品历史数据的实证研究

本文基于世界主要股市与大宗商品1999.1-2012.11的历史数据,运用Markowits均值方差模型构建了我国超额外汇储备的国际分散化投资的有效边界,研究了在满足我国国内投资的风险条件下,寻找我国超额外汇储备的国际分散化投资的有效组合,最后以此为基础提出了基于我国国情的政策建议。     

基于均值——方差模型的云南特色股票研究

Markowitz均值——方差模型是用于研究投资者如何通过合理的资金分配来达到既定收益下,风险最小化问题.本文采用该模型,基于投资优化组合的理论对云南省内地的特色股票做投资组合分析,通过对五支股票数据的统计分析,得到在预期收益既定的条件下,投资风险最小时的最优投资组合。同时,根据这五支股票的投资权重进一步精选出三支股票,并计算出了最优的投资权重。     

多货币债券定价的跳跃扩散模型随机路径分析

针对同一债券特别是主权债券以不同币种发行时所产生的违约信用风险进行研究,同时关注回收率对汇率形成的影响。研究认为：以远期汇率为对冲工具的组合无效,而同时考虑违约及不违约情况的期望汇率定价是一个有效选择。在这一理念基础上,研究还讨论了确定期望汇率的分析框架,并利用跳跃扩散模型复制策略进行风险对冲,然后对不同币种债券定价,最后利用蒙特卡洛技术模拟汇率生成的随机路径。     

关于最优资本配置模型研究的文献综述

资本配置的优化问题一直是学界研究的热点,传统的马科维茨均值方差模型在提出之后,被广泛的应用于投资组合的选择和资本配置。国内外学者受其启发,开始在该理论的基础上对最优资本配置模型进行优化与改良,得到了相当丰富的研究成果。本文整理了最优资本配置模型的研究文献,涉及的较为典型的模型除了传统的均值方差模型外,还有损失最小化模型、MV模型和尾均值—方差模型,在对这些模型进行比较分析的基础上本文提出了未来研究中仍需改进的三个方面。     

基于投资约束条件的企业年金最优投资组合研究

利用马科维兹的均值-方差模型,在目前我国企业年金投资约束条件的前提下测算四种主要投资工具在不同投资组合下的收益率和风险。研究表明:在现有年金投资约束条件下,从企业年金投资组合的安全性和收益率出发,国债和企业债券两者之间企业债券更优;两种以上投资工具的组合更能分散风险;投资组合中必须要选择股票投资;股票投资占比越高,企业年金投资组合的收益率越大。     

招商中证白酒基金的投资组合合理性——基于一般原则和最优原则

投资管理的核心就是组合投资。好的投资组合可以降低投资风险,获得更好的投资收益。本文基于风险与收益相匹配的一般原则和最优原则,来判断招商中证白酒基金的合理性,以期透视该基金的投资组合是否获得风险与收益的最大化。     

我国股市行业投资组合及启示—基于Markowitz资产选择的E-V模型

本文根据马克维茨的资产组合理论,以我国股市现存的行业布局和估值现状为研究背景,系统分析了行业配置的可行组合和有效组合,并在有效组合的基础上,以分散投资方式考察了投资比例变动对收益和风险的影响。统计结论在肯定收益和风险对等性的前提下,指出由于我国行业间估值关联度高且区间波动大,影响了分散投资的效果,此外,完全市场化投资并非最优投资选择。     

基于均值-方差模型的我国企业年金基金海外投资研究

我国企业年金基金进行市场化运营以来,始终被封锁于国门之内,由于投资范围的局限,非市场风险一直未得到充分分散。本研究利用国内外债券市场和股票市场的投资工具,充分考虑风险偏好与政府设定投资限制等因素对海外投资份额的影响,通过马克维茨的均值-方差模型模拟出不同投资限额和风险偏好下的最优投资比例,论证企业年金基金可以通过海外投资获得更多的多样化效益,并在剖析宏观经济形势的基础上,结合实证结果,     

The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics

This paper investigates the role of stochastic volatility and return jumps in reproducing the volatility dynamics and the shape characteristics of the Korean Composite Stock Price Index (KOSPI) 200 returns distribution. Using efficient method of moments and reprojection analysis, we find that stochastic volatility models, both with and without return jumps, capture return dynamics surprisingly well. The stochastic volatility model without return jumps, however, cannot fully reproduce the conditional kurtosis implied by the data. Return jumps successfully complement this gap. We also find that return jumps are essential in capturing the volatility smirk effects observed in short-term options.

Quadratic hedging in affine stochastic volatility models

We determine the variance-optimal hedge for a subset of affine processes including a number of popular stochastic volatility models. This framework does not require the asset to be a martingale. We obtain semiexplicit formulas for the optimal hedging strategy and the minimal hedging error by applying general structural results and Laplace transform techniques. The approach is illustrated numerically for a Lévy-driven stochastic volatility model with jumps as in Carr et al. (Math Finance 13:345–382, 2003).      

Risky asset pricing based on safety first fund management

We study a portfolio selection model based on Kataoka's safety-first criterion (KSF model in short). We assume that the market is complete but without risk-free asset, and that the returns are jointly elliptically distributed. With these assumptions, we provide an explicit analytical optimal solution for the KSF model and obtain some geometrical properties of the efficient frontier in the plane of probability risk degree z _α and target return r _α. We further prove a two-fund separation and tangency portfolio theorem in the spirit of the traditional mean-variance analysis. We also establish a risky asset pricing model based on risky funds that is similar to Black's zero-beta capital asset pricing model (CAPM, for short). Moreover, we simplify our risky asset pricing model using a derivative risky fund as a reference for market evaluation.     

ESO compensation: The roles of default risk, employee sentiment, and insider information

This paper derives a pricing model for employee stock options (ESO) that includes default risk and considers employee sentiment. Using ESO data from 1992 to 2004, the study finds that the average executive's subjective value is about 55% of the Black-Scholes value. Only employees who over-estimate firm returns (or insiders who know that the firm is under-valued) by about 10% per annum will prefer ESOs over cash compensation. Our model also shows that work incentives offered by ESOs may be far lower than those implied by Black-Scholes but that ESOs may induce less risk-taking behavior, contrary to typical moral hazard arguments. Findings may impact relevant accounting regulations as well as compensation decisions.     

Calibration and hedging under jump diffusion

A jump diffusion model coupled with a local volatility function has been suggested by Andersen and Andreasen (2000). By generating a set of option prices assuming a jump diffusion with known parameters, we investigate two crucial challenges intrinsic to this type of model: calibration of parameters and hedging of jump risk. Even though the estimation problem is ill-posed, our results suggest that the model can be calibrated with sufficient accuracy. Two different strategies are explored for hedging jump risk: a semi-static approach and a dynamic technique. Simulation experiments indicate that each of these methods can sharply reduce risk exposure. JEL Classification G12 · G13     

Shortage function and portfolio selection: On some special cases and extensions

The shortage function has recently been introduced in portfolio selection theory for measuring efficiency. In this paper we focuss on the case of shortselling. We show that, in such a case, the shortage function can be computed in closed form. Some issues concerning duality are also analyzed. We also analyze the case of a riskless asset.     

Pairs trading with a mean-reverting jump–diffusion model on high-frequency data

This paper develops a pairs trading framework based on a mean-reverting jump–diffusion model and applies it to minute-by-minute data of the S&P 500 oil companies from 1998 to 2015. The established statistical arbitrage strategy enables us to perform intraday and overnight trading. Essentially, we conduct a three-step calibration procedure to the spreads of all pair combinations in a formation period. Top pairs are selected based on their spreads’ mean-reversion speed and jump behaviour. Afterwards, we trade the top pairs in an out-of-sample trading period with individualized entry and exit thresholds. In the back-testing study, the strategy produces statistically and economically significant returns of 60.61% p.a. and an annualized Sharpe ratio of 5.30, after transaction costs. We benchmark our pairs trading strategy against variants based on traditional distance and time-series approaches and find its performance to be superior relating to risk–return characteristics. The mean-reversion speed is a main driver of successful and fast termination of the pairs trading strategy.