A note on convergence of an approximate hedging portfolio with liquidity risk

When the underlying asset price depends on activities of traders, hedging errors include costs due to the illiquidity of the underlying asset and the size of this cost can be substantial. Cetin et al. (2004), Liquidity risk and arbitrage pricing theory, Finance and Stochastics, 8(3), 311-341, proposed a hedging strategy that approximates the classical Black–Scholes hedging strategy and produces zero liquidity costs. Here, we compute the rate of convergence of the final value of this hedging portfolio to the option payoff in case of a European call option; i.e. we see how fast its hedging error converges to zero. The hedging strategy studied here is meaningful due to its simple liquidity cost structure and its smoothness relative to the classical Black–Scholes delta.     

Discrete–time delta hedging and the Black–Scholes model with transaction costs

The paper deals with the problem of discrete–time delta hedging and discrete-time option valuation by the Black–Scholes model. Since in the Black–Scholes model the hedging is continuous, hedging errors appear when applied to discrete trading. The hedging error is considered and a discrete-time adjusted Black–Scholes–Merton equation is derived. By anticipating the time sensitivity of delta in many cases the discrete-time delta hedging can be improved and more accurate delta values dependent on the length of the rebalancing intervals can be obtained. As an application the discrete-time trading with transaction costs is considered. Explicit solution of the option valuation problem is given and a closed form delta value for a European call option with transaction costs is obtained.     

Quadratic hedging for sequential claims with random weights in discrete time

We study a quadratic hedging problem for a sequence of contingent claims with random weights in discrete time. We obtain the optimal hedging strategy explicitly in a recursive representation, without imposing the non-degeneracy (ND) condition on the model and square integrability on hedging strategies. We relate the general results to hedging under random horizon and fair pricing in the quadratic sense. We illustrate the significance of our results in an example in which the ND condition fails.     

Risk-minimizing hedging strategies under restricted information: The case of stochastic volatility models observable only at discrete random times

We consider a market where the price of the risky asset follows a stochastic volatility model, but can be observed only at discrete random time points. We determine a local risk minimizing hedging strategy, assuming that the information of the agent is restricted to the observations of the price at its random jump times. Stochastic filtering also comes into play when computing the hedging strategy in the given situation of restricted information.     

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.     

广义δ规避策略下的两值期权定价研究

在离散时间场合和不存在交易成本假设下,提出了期权定价的平均自融资极小方差规避策略,得到了含有残差风险的两值看涨期权价格满足的偏微分方程和相应的两值期权定价公式。通过用数值分析来比较新的期权定价模型与经典的期权定价模型,发现投资者的风险偏好和标度对期权定价有重要影响。由此说明,考虑残差风险对两值期权定价研究具有重要的理论和实际意义。     

离散条件下标的资产带跳的德尔塔对冲误差研究

讨论了离散条件下的德尔塔对冲以及含泊松跳跃的布莱克—休斯模型下期权的定价问题.在布莱克—休斯模型中对冲被假设为连续发生的,当应用于离散的交易时,对冲误差就产生了.考虑到对冲误差,得出一种离散条件下标的资产带泊松跳跃的修正的布莱克—休斯方程和依赖再对冲区间长度的更精确的德尔塔值.     

广义δ规避策略下的两值期权定价研究

在离散时间场合和不存在交易成本假设下,提出了期权定价的平均自融资极小方差规避策略,得到了含有残差风险的两值看涨期权价格满足的偏微分方程和相应的两值期权定价公式。通过用数值分析来比较新的期权定价模型与经典的期权定价模型,发现投资者的风险偏好和标度对期权定价有重要影响。由此说明,考虑残差风险对两值期权定价研究具有重要的理论和实际意义。     

On optimal partial hedging in discrete markets

The paper considers arbitrage-free discrete markets representing them in the form of scenario trees. Two well-known problems of quantile hedging and hedging with minimal risk of shortfall are analysed. Methods of solving these problems are discussed. The dynamic programming algorithm is used to build the hedging strategy.     

Minimizing coherent risk measures of shortfall in discrete‐time models with cone constraints

The paper studies the problem of minimizing coherent risk measures of shortfall for general discrete‐time financial models with cone‐constrained trading strategies, as developed by Pham and Touzi. It is shown that the optimal strategy is obtained by super‐hedging a contingent claim, which is represented as a Neyman–Pearson‐type random variable.     

Hedging Large Portfolios of Options in Discrete Time*

The problem studied is that of hedging a portfolio of options in discrete time where underlying security prices are driven by a combination of idiosyncratic and systematic risk factors. It is shown that despite the market incompleteness introduced by the discrete time assumption, large portfolios of options have a unique price and can be hedged without risk. The nature of the hedge portfolio in the limit of large portfolio size is substantially different from its continuous time counterpart. Instead of linearly hedging the total risk of each option separately, the correct portfolio hedge in discrete time eliminates linear as well as second and higher order exposures to the systematic risk factors only. The idiosyncratic risks need not be hedged, but disappear through diversification. Hedging portfolios of options in discrete time thus entails a trade‐off between dynamic and cross‐sectional hedging errors. Some computations are provided on the outcome of this trade‐off in a discrete‐time Black–Scholes world.     

Information on jump sizes and hedging

We study a hedging problem in a market where traders have various levels of information. The exclusive information available only to informed traders is modelled by a diffusion process rather than discrete arrivals of new information. The asset price follows a jump–diffusion process and an information process affects jump sizes of the asset price. We find the local risk minimization hedging strategy of informed traders. Numerical examples as well as their comparison with the Black–Scholes strategy are provided via Monte Carlo.     

L 2 -discrete hedging in a continuous-time model

In the setting of the Black-Scholes option pricing market model, the seller of a European option must trade continuously in time. This is, of course, unrealistic from the practical viewpoint. He must then follow a discrete trading strategy. However, it does not seem natural to hedge at deterministic times regardless of moves of the spot price. In this paper, it is supposed that the hedger trades at a fixed number N of rebalancing (stopping) times. The problem (P^N) of selecting the optimal hedging times and ratios which allow one to minimize the variance of replication error is considered. For given N rebalancing, the discrete optimal hedging strategy is identified for this criterion. The problem (P^N) is then transformed into a multidimensional optimal stopping problem with boundary constraints. The restrictive problem (P^N _BS) of selecting the optimal rebalancing for the same criterion is also considered when the ratios are given by Black-Scholes. Using the vector-valued optimal stopping theory, the existence is shown of an optimal sequence of rebalancing for each one of the problems (P^N) and (P^N _BS). It also shown BS that they are asymptotically equivalent when the number of rebalances becomes large and an optimality criterion is stated for the problem (P^N). The same study is made when more realistic restrictions are imposed on the hedging times. In the special case of two rebalances, the problem (P² _BS) is solved and the problems (P² _BS) and (P²) are transformed into two optimal stopping problems. This transformation is useful for numerical purposes.     

最小方差准则下一个未定权益的近似对冲

本文研究了不完备的离散时间股票市场下未定权益的定价的对冲问题.利用在最小方差准则下选择概率测度Q或权重函数LN来求最优投资组合的方法,给出了离散时间情况下的鞅表示定理,在最小方差准则下提供一个简单的方法来近似对冲一个未定权益或一个欧氏期权.     

Loss analysis of a life insurance company applying discrete-time risk-minimizing hedging strategies

The present paper investigates the net loss of a life insurance company issuing equity-linked pure endowments in the case of periodic premiums. Due to the untradability of the insurance risk which affects both the in- and outflow side of the company, the issued insurance claims cannot be hedged perfectly. Furthermore, we consider an additional source of incompleteness caused by trading restrictions, because in reality the hedging of the contingent claims is more likely to occur at discrete times. Based on Møller [Møller, T., 1998. Risk-minimizing hedging strategies for unit-linked life insurance contracts. Astin Bull. 28, 17–47], we particularly examine the situation, where the company applies a time-discretized risk-minimizing hedging strategy. Through an illustrative example, we observe numerically that only a relatively small reduction in ruin probabilities is achieved with the use of the discretized originally risk-minimizing strategy because of the accumulated extra duplication errors caused by discretizing. However, the simulated results are highly improved if the hedging model instead of the hedging strategy is discretized. For this purpose, Møller’s [Møller, T., 2001. Hedging equity-linked life insurance contracts. North Amer. Actuarial J. 5 (2), 79–95] discrete-time (binomial) risk-minimizing strategy is adopted.     

Hedging guarantees in variable annuities under both equity and interest rate risks

Effective hedging strategies for variable annuities are crucial for insurance companies in preventing potentially large losses. We consider discrete hedging of options embedded in guarantees with ratchet features, under both equity (including jump) risk and interest rate risk. Since discrete hedging and the underlying model considered lead to an incomplete market, we compute hedging strategies using local risk minimization. Our results suggest that risk minimization hedging, under a joint model for the underlying and interest rate, leads to effective risk reduction. Moreover, hedging with standard options is superior to hedging with the underlying when both equity and interest rate risks are appropriately modeled.     

A multi-stage financial hedging approach for the procurement of manufacturing materials

This paper addresses the problem of mitigating procurement risk that arises from volatile commodity prices by proposing a hedging strategy within a multi-stage time frame. The proposed multi-stage hedging strategy requires a commodity futures position to be correctly initialised and rebalanced with adequate volumes of short/long positions, so as to reduce the volatility in the total procurement cost that would otherwise be generated by varying commodity spot prices. The novelty in the approach is the introduction of the rebalancing of commodity futures position at defined intermediate stages. To obtain an efficient or near optimal multi-stage hedging strategy, a discrete-time stochastic control model (DSCM) is developed. Numerical experiments and Monte Carlo simulation are used to show that the proposed multi-stage hedging strategy compares favourably with the minimal-variance hedge and the one-stage hedge. A close-form optimal solution is also presented for the case when procurement volume and price are independent.     

Barndorff-Nielsen and Shephard model: oil hedging with variance swap and option

In this paper the Barndorff-Nielsen and Shephard (BN-S) model is implemented to find an optimal hedging strategy for the oil commodity from the Bakken, a new region of oil extraction that is benefiting from fracking technology. The model is analyzed in connection to the quadratic hedging problem and some related analytical results are developed. The results indicate that oil can be optimally hedged with the use of a combination of options and variance swaps. Theoretical results related to the variance process are established and implemented for the analysis of the variance swap. In this paper we also determined the optimal amount of the underlying oil commodity that has to be held for minimizing the hedging error. The model and analysis are used to numerically analyze hedging decisions for managing price risk in Bakken oil commodities. From the numerical results, a number of important features of the usefulness of the Barndorff-Nielsen and Shephard model are illustrated.

     

On Carr and Lee’s Correlation Immunization Strategy

In their seminal work Robust Replication of Volatility Derivatives, Carr and Lee show how to robustly price and replicate a variety of claims written on the quadratic variation of a risky asset under the assumption that the asset’s volatility process is independent of the Brownian motion that drives the asset’s price. Additionally, they propose a correlation immunization strategy that minimizes the pricing and hedging error that results when the correlation between the risky asset’s price and volatility is non-zero. In this paper, we show that the correlation immunization strategy is the only strategy among the class of strategies discussed in Carr and Lee's paper that results in real-valued hedging portfolios when the correlation between the asset’s price and volatility is non-zero. Additionally, we perform a number of Monte Carlo experiments to test the effectiveness of Carr and Lee’s immunization strategy. Our results indicate that the correlation immunization method is an effective means of reducing pricing and hedging errors that result from a non-zero correlation.