This paper values American options on foreign assets in a stochastic interest rate economy using a two-point Geske and Johnson (1984) technique. The method requires the valuation of just two options: a European option and a twice-exercisable option. I first derive the risk-neutral distributions of asset prices under two forward risk-adjusted measures. Closed form solutions for European options on foreign assets are then obtained by applying these risk-neutral distributions. This article also provides analytic solutions for pricing twice exercisable options that are at most two-dimensional even though the valuation problem involves four risk factors at two exercise dates. I report the results of numerical evaluations of American option values using my method and show how they vary with the interest rate parameters. I also verify the accuracy of the proposed method by comparing with the benchmark values obtained from the least-square method of Longstaff and Schwartz (2001).

This paper generalizes and tightens Chen and Yeh's (2002) analytical upper bounds for American options under stochastic interest rates, stochastic volatility, and jumps, where American option prices are difficult to compute with accuracy. We first generalize Theorem 1 of Chen and Yeh (2002) and apply it to derive a tighter upper bound for American calls when the interest rate is greater than the dividend yield. Our upper bounds are not only tight, but also converge to accurate American call option prices when the dividend yield or strike price is small or when volatility is large. We then propose a general theorem that can be applied to derive upper bounds for American options whose payoffs depend on several risky assets. As a demonstration, we utilize our general theorem to derive upper bounds for American exchange options and American maximum options on two risky assets.

This paper utilizes the static hedge portfolio (SHP) approach of Derman et al. [Derman, E., Ergener, D., Kani, I., 1995. Static options replication. Journal of Derivatives 2, 78–95] and Carr et al. [Carr, P., Ellis, K., Gupta, V., 1998. Static hedging of exotic options. Journal of Finance 53, 1165–1190] to price and hedge American options under the Black-Scholes (1973) model and the constant elasticity of variance (CEV) model of Cox [Cox, J., 1975. Notes on option pricing I: Constant elasticity of variance diffusion. Working Paper, Stanford University]. The static hedge portfolio of an American option is formulated by applying the value-matching and smooth-pasting conditions on the early exercise boundary. The results indicate that the numerical efficiency of our static hedge portfolio approach is comparable to some recent advanced numerical methods such as Broadie and Detemple [Broadie, M., Detemple, J., 1996. American option valuation: New bounds, approximations, and a comparison of existing methods. Review of Financial Studies 9, 1211–1250] binomial Black-Scholes method with Richardson extrapolation (BBSR). The accuracy of the SHP method for the calculation of deltas and gammas is especially notable. Moreover, when the stock price changes, the recalculation of the prices and hedge ratios of the American options under the SHP method is quick because there is no need to solve the static hedge portfolio again. Finally, our static hedging approach also provides an intuitive derivation of the early exercise boundary near expiration.

This paper derives the pricing bounds of a currency cross-rate option using the option prices of two related dollar rates via a copula theory and presents the analytical properties of the bounds under the Gaussian framework. Our option pricing bounds are useful, because (1) they are general in the sense that they do not rely on the distribution assumptions of the state variables or on the selection of the copula function; (2) they are portfolios of the dollar-rate options and hence are potential hedging instruments for cross-rate options; and (3) they can be applied to generate bounds on deltas. The empirical tests suggest that there are persistent and stable relationships between the market prices and the estimated bounds of the cross-rate options and that our option pricing bounds (obtained from the market prices of options on two dollar rates) and the historical correlation of two dollar rates are highly informative for explaining the prices of the cross-rate options. Moreover, the empirical results are consistent with the predictions of the analytical properties under the Gaussian framework and are robust in various aspects.

This paper extends the seminal Cox-Ross-Rubinstein ((1979), CRR hereafter) binomial model to multiple assets. It differs from previous models in that it is derived under the complete market environment specified by Duffie and Huang (1985) and He (1990). The complete market assumption requires the number of states to grow linearly with the number of assets. However, the number of correlations grows at a faster rate, causing the CRR model to be indirectly extendable. We solve such a problem by recognizing that the fast growing correlation number is matched by the number of the angles of the edges of a hypercube spanned by the risky assets. As a result, we derive a solution that allows the number of equations to equal the number of risky assets and the riskless bond. The resulting tree structure hence provides the same intuition of pricing and hedging contingent claims as that provided by the CRR model. Finally, the proposed model is not only as easy to implement as the one-dimensional CRR model but also it is more memory efficient than the existing multi-factor lattice models.

This paper extends the static hedging portfolio (SHP) approach of Derman et al., 1995, Carr et al., 1998 to price and hedge American knock-in put options under the Black–Scholes model and the constant elasticity of variance (CEV) model. We use standard European calls (puts) to construct the SHPs for American up-and-in (down-and-in) puts. We also use theta-matching condition to improve the performance of the SHP approach. Numerical results indicate that the hedging effectiveness of a bi-monthly SHP is far less risky than that of a delta-hedging portfolio with daily rebalance. The numerical accuracy of the proposed method is comparable to the trinomial tree methods of Ritchken, 1995, Boyle and Tian, 1999. Furthermore, the recalculation time (the term is explained in Section 1) of the option prices is much easier and quicker than the tree method when the stock price and/or time to maturity are changed.

We examine whether investors can improve their investment opportunity sets through the addition of volatility-related assets into various groupings of benchmark portfolios. By first analyzing the weekly returns of three VIX-related assets over the period 1996–2008 and then applying mean–variance spanning tests, we find that adding VIX-related assets does lead to a statistically significant enlargement of the investment opportunity set for investors. Our empirical findings are robust and have two implications. First, there is scope for the further development of financial products relating to volatility indexes. Second, hedge fund managers can utilize VIX futures contracts or VIX-squared portfolios to enhance their equity portfolio performance, as measured by the Sharpe ratio.

In contrast to the constant exercise boundary assumed by Broadie and Detemple (1996) [Broadie, M., Detemple, J., 1996. American option valuation: New bounds, approximations, and comparison of existing methods. Review of Financial Studies 9, 1211–1250], we use an exponential function to approximate the early exercise boundary. Then, we obtain lower bounds for American option prices and the optimal exercise boundary which improve the bounds of Broadie and Detemple (1996). With the tight lower bound for the optimal exercise boundary, we further derive a tight upper bound for the American option price using the early exercise premium integral of Kim (1990) [Kim, I.J., 1990. The analytic valuation of American options. Review of Financial Studies 3, 547–572]. The numerical results show that our lower and upper bounds are very tight and can improve the pricing errors of the lower bound and upper bound of Broadie and Detemple (1996) by 83.0% and 87.5%, respectively. The tightness of our upper bounds is comparable to some best accurate/efficient methods in the literature for pricing American options. Moreover, the results also indicate that the hedge ratios (deltas and gammas) of our bounds are close to the accurate values of American options.

This paper develops a general equilibrium model and provides empirical support that the market volatility-of-volatility (VOV) predicts market returns and drives the time-varying volatility risk. In asset pricing tests with the market, volatility, and VOV as factors, the risk premium on VOV is statistically and economically significant and robust. Market and volatility risks are not priced in unconditional models, but, consistent with theory, their factor loadings, conditional on VOV, are priced. The pricing impact of VOV strengthens during market crashes, suggesting that VOV is particularly relevant during market turmoil, when investors demand increased compensation for VOV risk. (JEL G11, G12, G13)

We examine the impact of derivatives hedging on the spot market using accurate hedge ratios of covered warrants traded in the Taiwan Stock Exchange (TWSE). Results present significant positive abnormal returns and trading volumes before the announcement of a warrant’s issuance, and the effect is stronger when the hedging demand is larger. Moreover, a significantly positive relationship exists between stock return volatility and the price elasticity of hedging demand. Finally, we observe a significantly negative price effect upon the underlying stock after a call warrant has expired in-the-money due to the liquidation of hedging portfolios.