Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of Schöbel and Zhu (1999) by including stochastic interest rates. Moreover, we allow all driving model factors to be instantaneously correlated with each other, i.e. we allow for a general correlation structure between the instantaneous interest rates, the volatilities and the underlying stock returns. As insurance products often incorporate long-term exposures, they are typically more sensitive to changes in the interest rates, volatility and currencies. Therefore, having the flexibility to correlate the underlying asset price with both the stochastic volatility and the stochastic interest rates, yields a realistic model which is of practical importance for the pricing and hedging of such long-term contracts. We show that European options, typically used for the calibration of the model to market prices, and forward starting options can be priced efficiently and in closed-form by means of Fourier inversion techniques. We extensively discuss the numerical implementation of these pricing formulas, allowing for a fast and accurate valuation of European and forward starting options. The model will be especially useful for the pricing and risk management of insurance contracts and other exotic derivatives involving long-term maturities.     

Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility

We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of Schöbel and Zhu (1999) by including stochastic interest rates. Moreover, we allow all driving model factors to be instantaneously correlated with each other, i.e. we allow for a general correlation structure between the instantaneous interest rates, the volatilities and the underlying stock returns. As insurance products often incorporate long-term exposures, they are typically more sensitive to changes in the interest rates, volatility and currencies. Therefore, having the flexibility to correlate the underlying asset price with both the stochastic volatility and the stochastic interest rates, yields a realistic model which is of practical importance for the pricing and hedging of such long-term contracts. We show that European options, typically used for the calibration of the model to market prices, and forward starting options can be priced efficiently and in closed-form by means of Fourier inversion techniques. We extensively discuss the numerical implementation of these pricing formulas, allowing for a fast and accurate valuation of European and forward starting options. The model will be especially useful for the pricing and risk management of insurance contracts and other exotic derivatives involving long-term maturities.     

A Stochastic Programming Model for Currency Option Hedging

In this paper we use a stochastic programming approach to develop currency option hedging models which can address problems with multiple random factors in an imperfect market. The portfolios considered in our model are rebalanced at the end of each time period, and reinvestments are allowed during the hedging process. These sequential decisions (reinvestments) are based on the evolution of random parameters such as exchange rates, interest rates, etc. We also allow the inclusion of a variety of instruments in the hedging portfolio, including short term derivative securities, short term options, and futures. These instruments help generate strategies that provide good liquidity and low trade intensity. One of the important features of the model is that it incorporates constraints on sensitivity measures such as Delta and Gamma. By ensuring that these hedge parameters track a desired trajectory (e.g., the parameters of a target option), the new model provides investment strategies that are robust with respect to the perturbations measured by Delta and Gamma. In order to manage the explosion of scenarios due to multiple random factors, we incorporate sampling within a scenario aggregation algorithm. We illustrate that when compared with other myopic hedging methods in imperfect markets, the new stochastic programming model can provide better performance. Our examples also illustrate stochastic programming as a practical computational tool for realistic hedging problems.     

Computational methods for incentive option valuation

Employing stochastic programming, we provide a general framework for option pricing based on marginal bid/ask price valuation. It is applied to numerical analysis of options with European and American style exercise using a double binary tree. Incentive options are valued considering hedging restrictions and other market frictions, such as transaction and short position costs, and different borrowing and lending rates. The framework also includes correlated labor income. The possibility of partial sales is analyzed using ask price functions. Without friction costs and labor income, our model is the discrete-time equivalent of Ingersoll (J Bus 79:453–487, 2006). When labor income and/or market frictions are present, or a fraction of options is sold, the option values are materially different compared to Ingersoll (J Bus 79:453–487, 2006).

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Analytical valuation of catastrophe equity options with negative exponential jumps

A catastrophe put option is valuable in the event that the underlying asset price is below the strike price; in addition, a specified catastrophic event must have happened and influenced the insured company. This paper analyzes the valuation of catastrophe put options under deterministic and stochastic interest rates when the underlying asset price is modeled through a Lévy process with finite activity. We provide explicit analytical formulas for evaluating values of catastrophe put options. The numerical examples illustrate how financial risks and catastrophic risks affect the prices of catastrophe put options.     

Pricing currency options under two-factor Markov-modulated stochastic volatility models

This article investigates the valuation of currency options when the dynamic of the spot Foreign Exchange (FX) rate is governed by a two-factor Markov-modulated stochastic volatility model, with the first stochastic volatility component driven by a lognormal diffusion process and the second independent stochastic volatility component driven by a continuous-time finite-state Markov chain model. The states of the Markov chain can be interpreted as the states of an economy. We employ the regime-switching Esscher transform to determine a martingale pricing measure for valuing currency options under the incomplete market setting. We consider the valuation of the European-style and American-style currency options. In the case of American options, we provide a decomposition result for the American option price into the sum of its European counterpart and the early exercise premium. Numerical results are included.     

Hybrid Lévy Models: Design and Computational Aspects

ABSTRACT

A hybrid model is a model, where two markets are studied jointly such that stochastic dependence can be taken into account. Such a dependence is well known for equity and interest rate markets on which we focus here. Other pairs can be considered in a similar way. Two different versions of a hybrid approach are developed. Independent time-inhomogeneous Lévy processes are used as the drivers of the dynamics of interest rates and equity. In both versions, the dynamics of the interest rate side is described by an equation for the instantaneous forward rate. Dependence between the markets is generated by introducing the driver of the interest rate market as an additional term into the dynamics of equity in the first version. The second version starts with the equity dynamics and uses a corresponding construction for the interest rate side. Dependence can be quantified in both cases by a single parameter. Numerically efficient valuation formulas for interest rate and equity derivatives are developed. Using market quotes for liquidly traded assets we show that the hybrid approach can be successfully calibrated.     

Time Charters with Purchase Options in Shipping: Valuation and Risk Management

Abstract

The article studies the valuation and optimal management of Time Charters with Purchase Options (T/C–POPs), which is a specific type of asset lease with embedded options that is common in shipping markets. T/C–POPs are economically significant and sometimes account for more than half of the stock market value of listed shipping companies.

The main source of risk in markets for maritime transportation is the freight rate, and we therefore specify a single-factor continuous time model for the dynamic evolution of freight rates that allows us to price a wide variety of freight rate-related derivatives including various forms of T/C–POPs using contingent claims valuation techniques. Our model allows for the derivation of closed valuation formulas for some simple freight rate derivatives, whereas the more complex ones are analysed using numerical (finite difference) procedures. We accompany our theoretical results with illustrative numerical examples as we proceed.     

Accounting for risk aversion in derivatives purchase timing

We study the problem of optimal timing to buy/sell derivatives by a risk-averse agent in incomplete markets. Adopting the exponential utility indifference valuation, we investigate this timing flexibility and the associated delayed purchase premium. This leads to a stochastic control and optimal stopping problem that combines the observed market price dynamics and the agent??s risk preferences. Our results extend recent work on indifference valuation of American options, as well as the authors?? first paper (Leung and Ludkovski, SIAM J Finan Math 2(1) 768?C793, 2011). In the case of Markovian models of contracts on non-traded assets, we provide analytical characterizations and numerical studies of the optimal purchase strategies, with applications to both equity and credit derivatives.     

Swing options in commodity markets: a multidimensional Lévy diffusion model

We study valuation of swing options on commodity markets when the commodity prices are driven by multiple factors. The factors are modeled as diffusion processes driven by a multidimensional Lévy process. We set up a valuation model in terms of a dynamic programming problem where the option can be exercised continuously in time. Here, the number of swing rights is given by a total volume constraint. We analyze some general properties of the model and study the solution by analyzing the associated HJB-equation. Furthermore, we discuss the issues caused by the multi-dimensionality of the commodity price model. The results are illustrated numerically with three explicit examples.     

Generalised soft binomial American real option pricing model (fuzzy–stochastic approach)

The stochastic discrete binomial models and continuous models are usually applied in option valuation. Valuation of the real American options is solved usually by the numerical procedures. Therefore, binomial model is suitable approach for appraising the options of American type. However, there is not in several situations especially in real option methodology application at to disposal input data of required quality. Two aspects of input data uncertainty should be distinguished; risk (stochastic) and vagueness (fuzzy). Traditionally, input data are in a form of real (crisp) numbers or crisp-stochastic distribution function. Therefore, hybrid models, combination of risk and vagueness could be useful approach in option valuation. Generalised hybrid fuzzy–stochastic binomial American real option model under fuzzy numbers (T-numbers) and Decomposition principle is proposed and described. Input data (up index, down index, growth rate, initial underlying asset price, exercise price and risk-free rate) are in a form of fuzzy numbers and result, possibility-expected option value is also determined vaguely as a fuzzy set. Illustrative example of equity valuation as an American real call option is presented.     

Risk-neutral valuation of participating life insurance contracts in a stochastic interest rate environment

Over the last years, the valuation of life insurance contracts using concepts from financial mathematics has become a popular research area for actuaries as well as financial economists. In particular, several methods have been proposed of how to model and price participating policies, which are characterized by an annual interest rate guarantee and some bonus distribution rules. However, despite the long terms of life insurance products, most valuation models allowing for sophisticated bonus distribution rules and the inclusion of frequently offered options assume a simple Black–Scholes setup and, more specifically, deterministic or even constant interest rates.We present a framework in which participating life insurance contracts including predominant kinds of guarantees and options can be valuated and analyzed in a stochastic interest rate environment. In particular, the different option elements can be priced and analyzed separately. We use Monte Carlo and discretization methods to derive the respective values.The sensitivity of the contract and guarantee values with respect to multiple parameters is studied using the bonus distribution schemes as introduced in [Bauer, D., Kiesel, R., Kling, A., Ruß, J., 2006. Risk-neutral valuation of participating life insurance contracts. Insurance: Math. Econom. 39, 171–183]. Surprisingly, even though the value of the contract as a whole is only moderately affected by the stochasticity of the short rate of interest, the value of the different embedded options is altered considerably in comparison to the value under constant interest rates. Furthermore, using a simplified asset portfolio and empirical parameter estimations, we show that the proportion of stock within the insurer’s asset portfolio substantially affects the value of the contract.     

A Convenient Way to Characterize Equivalent Martingale Measures in Incomplete Markets

It is an empirical fact that the (empirically) relevant models for asset prices often describe markets that are incomplete in terms of their underlying assets, yielding many possible equivalent martingale measures under the no-arbitrage assumption. By using actual derivative prices, i.e., prices as observed in the market, additional information about the empirically relevant equivalent martingale measures might be obtained. In order to be able to process such information easily one needs a convenient way to represent all possible equivalent martingale measures in relation to derivative prices. In this paper we present such a convenient characterization. Conceptually, our characterization is not different from existing characterizations using, for example, Radon–Nikodym derivatives of martingale measures with respect to objective probabilities, but our characterization offers some advantages. The main advantage is that pricing derivatives is split up into two steps. The first step is solving a related complete markets pricing problem. This is a well-studied problem, so that it can easily be solved generally. In the second step a weighted average of the first step complete markets price must be calculated. Pricing under different equivalent martingale measures in the original market only differs with respect to the second step. The empirically relevant weighting can be determined by confronting the theoretical with the actually observed prices. As a byproduct we obtain a new and natural definition of idiosyncratic risk, which we show to be in line with the use of this term in the literature.To illustrate the ideas we discuss several examples. Among others we obtain the Hull–White formula for options on assets with stochastic volatility under close to minimal conditions that (for example) do not rely on a specification of the processes in terms of Itô diffusion.we relax the assumption of no-correlation between asset prices and volatilities in the Hull–White framework; we consider the case where the stochastic volatility does bear a risk-premium; we discuss pricing under stochastic interest rates; and we consider square-root type processes. All these pricing problems, and many more, can conveniently be handled using the approach based on our characterization of the equivalent martingale measures in continuous time markets that are incomplete in the underlying assets.     

An analytic valuation method for multivariate contingent claims with regime-switching volatilities

In this paper, we provide an analytic valuation method for European-type contingent claims written on multiple assets in a stochastic market environment. We employ a two-state Markov regime-switching volatility in order to reflect stochastically changing market conditions. The method is developed by exploiting the probability density of the occupation time for which the underlying asset processes are in a certain regime during a time period. In order to show its usefulness, we derive analytic valuation formulas for quanto options and exchange options with two underlying assets, as examples.     

Optimal bidding of a virtual power plant on the Spanish day-ahead and intraday market for electricity

We develop a multi-stage stochastic programming approach to optimize the bidding strategy of a virtual power plant (VPP) operating on the Spanish spot market for electricity. The VPP markets electricity produced in the wind parks it manages on the day-ahead market and on six staggered auction-based intraday markets. Uncertainty enters the problem via stochastic electricity prices as well as uncertain wind energy production. We set up the problem of bidding for one day of operation as a Markov decision process (MDP) that is solved using a variant of the stochastic dual dynamic programming algorithm. We conduct an extensive out-of-sample comparison demonstrating that the optimal policy obtained by the stochastic program clearly outperforms deterministic planning, a pure day-ahead strategy, a benchmark that only uses the day-ahead market and the first intraday market, as well as a proprietary stochastic programming approach developed in the industry. Furthermore, we study the effect of risk aversion as modeled by the nested Conditional Value-at-Risk as well as the impact of changes in various problem parameters.     

Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches

We demonstrate how the problem of determining the ask price for electricity swing options can be considered as a stochastic bilevel program with asymmetric information. Unlike as for financial options, there is no way for basing the pricing method on no-arbitrage arguments. Two main situations are analyzed: if the seller has strong market power he/she might be able to maximize his/her utility, while in fully competitive situations he/she will just look for a price which makes profit and has acceptable risk. In both cases the seller has to consider the decision problem of a potential buyer – the valuation problem of determining a fair value for a specific option contract – and anticipate the buyer’s optimal reaction to any proposed strike price. We also discuss some methods for finding numerical solutions of stochastic bilevel problems with a special emphasis on using duality gap penalizations.     

上证50股指期货、ETF期权与ETF市场的价格发现能力对比分析

比较基于上证50指数的股指期货、ETF期权与现货ETF市场的价格发现能力,选取5分钟高频数据进行实证分析,并将暴涨暴跌行情与全样本区间进行了对比分析。首先,采用买权卖权等价理论反推期权价格隐含的现货价格;其次,运用向量误差修正模型,结合广义脉冲响应函数等分析方法研究市场间价格的领先滞后关系;最后,运用广义信息共享模型量化各个市场的价格发现贡献度。结果表明:在不同区间中,期货市场均领先其他市场至少5分钟;从长期来看,期货在价格发现中的贡献度最大,期权次之;在暴涨区间中,ETF的价格发现贡献度最大,期货次之;在暴跌区间中,期权的价格发现贡献度最大,期货次之。     

Contingent claim valuation in a market with different interest rates

The problem of contingent claim valuation in a market with a higher interest rate for borrowing than for lending is discussed. We give results which cover especially the European call and put options. The method used is based on transforming the problem to suitable auxiliary markets with only one interest rate for borrowing and lending and is adapted from a paper of Cvitanic and Karatzas (1992) where the authors study constrained portfolio problems.     

A Pricing Model for American Options with Gaussian Interest Rates

In this paper we introduce a new methodology to price American put options under stochastic interest rates. We derive an analytic approximation that can be evaluated very fast and is fairly accurate. The method uses the so-called forward risk adjusted measure to derive analytic prices. We show that for American puts the correlation between the stock price and the interest rate has different influences on European option values and early exercise premiums.