Valuing the option to invest in an incomplete market

This paper considers the impact of entrepreneurial risk aversion and incompleteness on investment timing and the value of the option to invest. A risk averse entrepreneur faces the irreversible decision of when to pay a cost in order to receive a one-off investment payoff. The uncertainty associated with the investment payoff can be partly offset by hedging, but the remaining unhedgeable risk is idiosyncratic. Nested within our incomplete set-up is the complete model of McDonald and Siegel (Q J Econ 101:707–727, 1986) which assumes investment payoffs are perfectly spanned by traded assets. We find risk aversion and idiosyncratic risk erode option value and lower the investment threshold. Our main finding is that there is a parameter region within which the complete and incomplete models give differing investment signals. In this region, the option is never exercised (and investment never occurs) in the complete model, whereas the entrepreneur exercises the option in the incomplete setting. Strikingly, this parameter region corresponds to a negative implicit dividend yield on the payoff, and so this exercise behavior contrasts with conventional wisdom of Merton (Bell J Econ Manage 4:141–183, 1973) for complete markets. Finally, in this parameter region, increased volatility speeds-up investment and option values are not strictly convex in project value, in sharp contrast to the conclusion of standard real options models. The author thanks George Constantinides, Graham Davis, Jerome Detemple, Avinash Dixit, David Hobson, Stewart Hodges, Bart Lambrecht, Andrew Lyasoff, Robert McDonald, Pierre Mella-Barral, Jianjun Miao, Bob Nau (ES discussant), Gordon Sick, James Smith, Stathis Tompaidis, Elizabeth Whalley and Zvi Wiener for their comments. The author also thanks seminar participants at the University of Texas at Austin (2004), Kings College London, the Cornell Finance Workshop, the Oxford-Princeton Finance Workshop, the BIRS Finance Workshop (2004), the Eighth Annual Real Options conference, the Bachelier Finance Society Third World Congress (2004), Princeton University, Boston University, the Fields Institute Toronto, QMF 2004, Warwick Business School, and the Econometric Society Winter Meetings (2006). First version: July, 2004.     

Estimating structural credit risk models when market prices are contaminated with noise

In this paper, sequential estimation on hidden asset value and model parameter estimation is implemented under the Black–Cox model. To capture short‐term autocorrelation in the stock market, we assume that market noise follows a mean reverting process. For estimation, Bayesian methods are applied in this paper: the particle filter algorithm for sequential estimation of asset value and the generalized Gibbs and multivariate adapted Metropolis methods for model parameters estimation. The first simulation study shows that sequential hidden asset value estimation using both option price and equity price is more efficient than estimation using equity price alone. The second simulation study shows that, by applying the generalized Gibbs sampling and multivariate adapted Metropolis methods, model parameters can be estimated successfully. In an empirical analysis, the stock market noise for firms with more liquid stock is estimated as having smaller volatility. Copyright © 2015 John Wiley & Sons, Ltd.     

Ruin probability for Lévy risk process compounded by geometric Brownian motion

In this paper, we assume that the surplus of an insurer follows a Lévy risk process and the insurer would invest its surplus in a risky asset, whose prices are modeled by a geometric Brownian motion. It is shown that the ruin probabilities (by a jump or by oscillation) of the resulting surplus process satisfy certain integro-differential equations.      

Dynamic investment strategies with demand-side and cost-side risks

Investments in cost reductions are critical for the long run success of companies that operate in dynamic and stochastic market environments. This paper studies optimal investment in cost reductions as a real option under the assumption that a single firm faces two different sources of risk, stochastic demand and input prices. We derive optimal investment strategies for a monopoly as well as a firm in a perfectly competitive market and show that in case of high marginal costs, cost reductions take place earlier in competitive than in monopoly markets. While the existence of an option to invest in cost reductions increases firm value it also increases a firm’s systematic risk. Risk can be smaller in a monopolistic than in a competitive industry.     

Worst-case portfolio optimization with proportional transaction costs

We study optimal asset allocation in a crash-threatened financial market with proportional transaction costs. The market is assumed to be either in a normal state, in which the risky asset follows a geometric Brownian motion, or in a crash state, in which the price of the risky asset can suddenly drop by a certain relative amount. We only assume the maximum number and the maximum relative size of the crashes to be given and do not make any assumptions about their distributions. For every investment strategy, we identify the worst-case scenario in the sense that the expected utility of terminal wealth is minimized. The objective is then to determine the investment strategy which yields the highest expected utility in its worst-case scenario. We solve the problem for utility functions with constant relative risk aversion using a stochastic control approach. We characterize the value function as the unique viscosity solution of a second-order nonlinear partial differential equation. The optimal strategies are characterized by time-dependent free boundaries which we compute numerically. The numerical examples suggest that it is not optimal to invest any wealth in the risky asset close to the investment horizon, while a long position in the risky asset is optimal if the remaining investment period is sufficiently large.     

含不动产项目的保险公司再保险-投资策略

站在保险公司管理者的角度,考虑存在不动产项目投资机会时保险公司的再保险-投资策略问题.假定保险公司可以投资于不动产项目、风险证券和无风险证券,并通过比例再保险控制风险,目标是最小化保险公司破产概率并求得相应最佳策略,包括:不动产项目投资时机、再保险比例以及投资于风险证券的金额.运用混合随机控制-最优停时方法,得到最优值函数及最佳策略的显式解.结果表明,当且仅当其盈余资金多于某一水平(称为投资阈值)时保险公司投资于不动产项目.进一步的数值算例分析表明:(a)不动产项目投资的阈值主要受项目收益率影响而与投资金额无明显关系,收益率越高则投资阈值越低;(b)市场环境较好(牛市)时项目的投资阈值降低;反之,当市场环境较差(熊市)时投资阈值提高.     

Optimal risk sharing under distorted probabilities

We study optimal risk sharing among n agents endowed with distortion risk measures. Our model includes market frictions that can either represent linear transaction costs or risk premia charged by a clearing house for the agents. Risk sharing under third-party constraints is also considered. We obtain an explicit formula for Pareto optimal allocations. In particular, we find that a stop-loss or deductible risk sharing is optimal in the case of two agents and several common distortion functions. This extends recent result of Jouini et al. (Adv Math Econ 9:49–72, 2006) to the problem with unbounded risks and market frictions.      

Gain�Closs based convex risk limits in discrete-time trading

We present an approach for pricing and hedging in incomplete markets, which encompasses other recently introduced approaches for the same purpose. In a discrete time, finite space probability framework conducive to numerical computation we introduce a gain–loss ratio based restriction controlled by a loss aversion parameter, and characterize portfolio values which can be traded in discrete time to acceptability. The new risk measure specializes to a well-known risk measure (the Carr–Geman–Madan risk measure) for a specific choice of the risk aversion parameter, and to a robust version of the gain–loss measure (the Bernardo–Ledoit proposal) for a specific choice of thresholds. The result implies potentially tighter price bounds for contingent claims than the no-arbitrage price bounds. We illustrate the price bounds through numerical examples from option pricing.     

Risk averse asymptotics in a Black–Scholes market on a finite time horizon

We consider the optimal investment and consumption problem in a Black–Scholes market, if the target functional is given by expected discounted utility of consumption plus expected discounted utility of terminal wealth. We investigate the behaviour of the optimal strategies, if the relative risk aversion tends to infinity. It turns out that the limiting strategies are: do not invest at all in the stock market and keep the rate of consumption constant!     

Option pricing under residual risk and imperfect hedging

This paper is concerned in the option pricing in a discrete time incomplete market. We emphasize the interplay between option pricing and residual risk as well as imperfect hedging. It has been shown that the value of a European option satisfies a hyperbolic, rather than parabolic, partial differential equation. The closed-form solution for this hyperbolic equation has been obtained, which will collapse to the Black–Scholes formula as the time scaling converges to zero.