Some results on quadratic hedging with insider trading

We consider the hedging problem in an arbitrage-free incomplete financial market, where there are two kinds of investors with different levels of information about the future price evolution, described by two filtrations F and G=F∨σ(G) where G is a given r.v. representing the additional information. We focus on two types of quadratic approaches to hedge a given square-integrable contingent claim: local risk minimization (LRM) and mean-variance hedging (MVH). By using initial enlargement of filtrations techniques, we solve the hedging problem for both investors and compare their optimal strategies under both approaches.

In particular, for LRM, we show that for a large class of additional non trivial r.v.s G both investors will pursue the same locally risk minimizing portfolio strategy and the cost process of the ordinary agent is just the projection on F of that of the insider. For the MVH approach, we study also some general stochastic volatility model, including Hull and White, Heston and Stein and Stein models. In this more specific setting and for r.v.s G which are measurable with respect to the filtration generated by the volatility process, we obtain an expression for the insider optimal strategy in terms of the ordinary agent optimal strategy plus a process admitting a simple feedback-type representation.     

Mean-Variance Hedging Under Multiple Defaults Risk

We solve a mean-variance hedging problem in an incomplete market where multiple defaults can occur. For this purpose, we use a default-density modeling approach. The global market information is formulated as a progressive enlargement of a default-free Brownian filtration, and the dependence of the default times is modelled using a conditional density hypothesis. We prove the quadratic form of each value process between consecutive default times and recursively solve systems of coupled quadratic backward stochastic differential equations (BSDEs). We demonstrate the existence of these solutions using BSDE techniques. Then, using a verification theorem, we prove that the solutions of each subcontrol problem are related to the solution of our global mean-variance hedging problem. As a byproduct, we obtain an explicit formula for the optimal trading strategy. Finally, we illustrate our results for certain specific cases and for a multiple defaults case in particular.     

期权组合最优套期保值模型及实证研究

根据实际投资中投资者可以选择不同到期日、不同敲定价格的期权组合进行套期保值的现实,本文建立了二次效用函数下期权组合最优动态套期保值模型,证明了该模型最优解存在的唯一性,并在协方差矩阵可逆和不可逆两种情形下分别给出了期权最优头寸的显式表达式。在50ETF价格先升后降、先降后升、下降和上升四种情形下,对上证50ETF期权的多种期权组合套期保值问题进行实证分析。研究结果表明:不同到期日不同敲定价格的看跌期权组合具有较好的套期保值效果。本文的研究为选择期权组合进行套期保值和解决展期期权套期保值问题提供了借鉴。     

对数正态随机波动率期权局部风险最小定价与风险对冲

随机波动率模型是著名的Black-Scholes模型的推广,该模型描述的市场是不完备的,相应期权的定价与保值和投资者的风险态度有关．本文假设标的资产波动率为对数正态过程,根据局部风险最小准则,运用梯度算子方法,得到了欧式看涨期权的局部风险最小定价及套期保值策略的显式解．     

The role of index bonds in universal currency hedging

This study examines the demand for index bonds and their role in hedging risky asset returns against currency risks in a complete market where equity is not hedged against inflation risk. Avellaneda's uncertain volatility model with non-constant coefficients to describe equity price variation, forward price variation, index bond price variation and rate of inflation, together with Merton's intertemporal portfolio choice model, are utilized to enable an investor to choose an optimal portfolio consisting of equity, nominal bonds and index bonds when the rate of inflation is uncertain. A hedge ratio is universal if investors in different countries hedge against currency risk to the same extent. Three universal hedge ratios (UHRs) are defined with respect to the investor's total demand for index bonds, hedging risky asset returns (i.e. equity and nominal bonds) against currency risk, which are not held for hedging purposes. These UHRs are hedge positions in foreign index bond portfolios, stated as a fraction of the national market portfolio. At equilibrium all the three UHRs are comparable to Black's corrected equilibrium hedging ratio. The Cameron-Martin-Girsanov theorem is applied to show that the Radon-Nikodym derivative given under a P -martingale, the investor's exchange rate (product of the two currencies) is a martingale. Therefore the investors can agree on a common hedging strategy to trade exchange rate risk irrespective of investor nationality. This makes the choice of the measurement currency irrelevant and the hedge ratio universal without affecting their values.     

Multi-period minimax hedging strategies

Option pricing and hedging under transaction costs are of major importance to marketmakers and investors. In this paper we present the basic minimax strategy which determines the optimum number of shares that minimizes the worst-case potential hedging error under transaction costs for the next period. We present two extensions of this strategy. The first extension is the two-period minimax where the worst case is defined over a two-period setting. The objective function of the basic minimax strategy is augmented to include the hedging error for the second period. The second extension is the variable minimax strategy where early rebalancing is triggered by the minimax hedging error. Simulation results suggest that the basic minimax strategy and its two extensions are superior in performance to delta hedging and that the variable minimax strategy is superior to both the basic and the two-period strategies. This result is due to the opportunity provided by the variable minimax strategy to rebalance early. The greatest amount of business for traded options is done for at-the-money options; in this paper, we have concluded that the minimax strategies are particularly suitable for managing the risk of such options. In the Appendix, we present the minimax algorithm used for the implementation of these strategies.     

Sentiment lost: the effect of projecting the pricing kernel onto a smaller filtration set

Abstract

This paper provides a theoretical analysis on the impacts of using a suboptimal information set for the estimation of the pricing kernel and, more in general, for the validity of the fundamental theorems of asset pricing. While inferring the risk-neutral measure from options data provides a naturally forward-looking estimate, extracting the real world measure from historical returns is only partially informative, thus suboptimal with respect to investors’ future beliefs. As a consequence of this disalignment, the two measures no longer share the same nullset, thus distorting the investors’ risk premium and the validity of the pricing measure. From a probabilistic viewpoint, the missing beliefs are totally unaccessible stopping times on the coarser filtration set, so that an absolutely continuous strict local martingale, once projected on it, becomes continuous with jumps. Some empirical examples complete the paper.     

Unit-linked life insurance policies: Optimal hedging in partially observable market models

In this paper we investigate the hedging problem of a unit-linked life insurance contract via the local risk-minimization approach, when the insurer has a restricted information on the market. In particular, we consider an endowment insurance contract, that is a combination of a term insurance policy and a pure endowment, whose final value depends on the trend of a stock market where the premia the policyholder pays are invested. To allow for mutual dependence between the financial and the insurance markets, we use the progressive enlargement of filtration approach. We assume that the stock price process dynamics depends on an exogenous unobservable stochastic factor that also influences the mortality rate of the policyholder. We characterize the optimal hedging strategy in terms of the integrand in the Galtchouk–Kunita–Watanabe decomposition of the insurance claim with respect to the minimal martingale measure and the available information flow. We provide an explicit formula by means of predictable projection of the corresponding hedging strategy under full information with respect to the natural filtration of the risky asset price and the minimal martingale measure. Finally, we discuss applications in a Markovian setting via filtering.     

Hedging-based utility risk measure customized for individual investors

This paper proposes a hedging-based utility risk measure (HBU) customized for individual investors requiring a comprehensive risk assessment for financial products. We show that HBU is a convex risk measure and if the utility has constant relative risk aversion, HBU is coherent. Roughly speaking, HBU is the opposite of a generalized utility indifference price and it depends on claimants' utility and hedging instruments accessible to them. We present HBU's qualities and provide two examples, explaining HBU's relevance.     

Mean‐variance hedging with basis risk

Basis risk arises in a number of financial and insurance risk management problems when the hedging assets do not perfectly match the underlying asset in a hedging program. Notable examples in insurance include the hedging for longevity risks, weather index–based insurance products, variable annuities, etc. In the presence of basis risk, a perfect hedging is impossible, and in this paper, we adopt a mean‐variance criterion to strike a balance between the expected hedging error and its variability. Under a time‐dependent diffusion model setup, explicit optimal solutions are derived for the hedging target being either a European option or a forward contract. The solutions are obtained by a delicate application of the linear quadratic control theory, the method of backward stochastic differential equation, and Malliavin calculus. A numerical example is presented to illustrate our theoretical results and their interesting implications.     

基于Copula-ECM-GARCH模型的农产品期货套期保值绩效研究

Copula函数具有可以准确刻画变量间的相依结构、精准描述金融时间序列"尖峰厚尾"分布特点的良好统计性质.针对传统计量模型在计算套期保值比率时存在的局限性,利用Copula函数描述变量的尾部相关性,并结合ECM-GARCH模型,对大豆、小麦、玉米三种国内农产品期货进行套期保值研究,分别计算最优的套期保值比率及其绩效,并...     

需求和汇率风险下的全球供应链汇率风险对冲策略

在下游零售商同时面临市场需求风险和汇率风险的背景下,研究了汇率风险对冲(外汇期货对冲)策略在全球供应链运作及风险管理中的作用。在无/有对冲策略两种情形下分别构建了上游制造商和下游零售商的动态博弈模型,并求解了均衡结果。两种情形下的均衡结果显示,汇率风险对冲策略可以提高供应链系统订货量、增加零售商收益的期望值和确定性等价量、增加供应链系统的总收益。进一步讨论了有对冲策略的情形下,两类外生风险对供应链均衡决策变量和盈利性的影响方式。结果表明,汇率风险对冲策略对汇率风险起到了有效的隔离作用,避免了供应链下游的汇率风险向上游企业传递,并能实现供应链收益与风险的权衡。     

期货套期保值C VaR风险的敏感度分析

把条件风险价值应用于期货组合套期保值的风险管理,分析条件风险价值对期货部位的敏感性.在一般的概率分布下,分空头套期保值和多头套期保值两种情况,导出期货组合套期保值的条件风险价值关于套期比的一阶和二阶变化率,并研究其经济意义.投资者可以根据条件风险价值的敏感度增减期货头寸,把握好用于套期保值的期货量,帮助投资者管理套期保值风险.     

期货市场中持仓量及参与者对资产价格的影响研究

本文通过建立一个期货市场的均衡模型,提出在具有套保需求和有限风险承受能力的前提下,期货价格能够预测未来资产价格变动的方向,持仓量能够辅助预测未来资产价格变动的剧烈程度;此外,市场中不知情投机者具有风险调整市场收益的作用,不知情套保者的参与能够稳定市场。对于持仓量是否能够辅助预测未来资产价格变动的剧烈程度,本文利用中国商品期货市场数据进行了实证检验,结果表明与理论研究的结论一致。     

基于风险约束的套期保值模型及沪深300股指实证研究

提出利用风险价值VaR建立套期保值资产组合的风险约束.以套期保值资产组合收益最大为目标,以控制套期保值资产组合风险为约束,建立了基于风险约束的套期保值模型.该模型在有效控制风险的基础上,可以大幅提高套期保值资产组合的收益.对沪深300股指现货和期货的数据进行了实证分析,对比了现有研究的最小二乘((OLS)、向量自回归(VAR)、向量误差修正(VEC)三种模型以及本文建立的基于风险约束的期货套期保值模型.样本内检验结果表明,本模型比现有研究模型的收益有大幅提高,平均增加81.6%.同时并没有失去对风险的控制,与现有研究模型只有5.32%的差别.对于样本外检验,模型在控制风险和提高收益两个方面都要优于现有研究模型.模型比现有研究模型平均可提高收益21.4%,平均降低风险3.61%.     

从投资情绪角度看股票市场流动性——来自B股向境内居民开放的研究

我们借鉴行为方面的模型,即投资情绪的变化会影响股票市场的流动性,从而影响股票的未来收益。在卖空限制条件下市场高流动性预示市场充斥着非理性投资者。本文通过中国股市具备卖空限制和2001年2月B股向境内居民开放前后B股投资主体(投资情绪)发生变化这一自然事件,实证分析了B股市场向境内居民开放后,投资者情绪变化引起市场流动性增加,对股票预期收益的流动性溢价影响也由开放前的不显著变化为显著。     

Supply chain network equilibrium with strategic financial hedging using futures

In this paper, we develop a network equilibrium model for supply chain networks with strategic financial hedging. We consider multiple competing firms that purchase multiple materials and parts to manufacture their products. The supply chain firms’ procurement activities are exposed to commodity price risk and exchange rate risk. The firms can use futures contracts to hedge the risks. Our research studies the equilibrium of the entire network where each firm optimizes its own operation and hedging decisions. We use variational inequality theory to formulate the equilibrium model, and provide qualitative properties. We provide analytical results for a special case with duopolistic competition, and use simulations to study an oligopolistic case. The analytical and simulation studies reveals interesting managerial insights.     

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.     

Utility indifference pricing and hedging for structured contracts in energy markets

In this paper we study the pricing and hedging of structured products in energy markets, such as swing and virtual gas storage, using the exponential utility indifference pricing approach in a general incomplete multivariate market model driven by finitely many stochastic factors. The buyer of such contracts is allowed to trade in the forward market in order to hedge the risk of his position. We fully characterize the buyer’s utility indifference price of a given product in terms of continuous viscosity solutions of suitable nonlinear PDEs. This gives a way to identify reasonable candidates for the optimal exercise strategy for the structured product as well as for the corresponding hedging strategy. Moreover, in a model with two correlated assets, one traded and one nontraded, we obtain a representation of the price as the value function of an auxiliary simpler optimization problem under a risk neutral probability, that can be viewed as a perturbation of the minimal entropy martingale measure. Finally, numerical results are provided.     

Dynamic asset allocation with event risk,transaction costs and predictable returns

We examine the interplay between event risk, transaction costs and predictability on the dynamic asset allocation of an investor with discrete trading opportunities. The model is calibrated to the U.S. stock market and a Gauss–Hermite quadrature approach is used to solve the investor’s dynamic optimization problem. Numerical scenarios are examined to show the impact of event risk on asset allocations, hedging demands, no-trading regions, and certainty equivalent returns. It is found that event risk shrinks hedging demand. Neglecting event risk can also lead to sizeable certainty equivalent return losses.