Options may have an effect on firm value because they help complete markets and stimulate informed trades. However, these benefits are likely to manifest themselves in active, rather than inactive, ...options markets. Supporting this observation, we find that firms with more options trading have higher values of Tobin's
q, after accounting for other determinants of value. Corporate investment in firms with greater options trading is more sensitive to stock prices. Options trading affects firm valuation more strongly in stocks with greater information asymmetry. These results indicate that options trading is positively associated with firm values as well as information production.
We present an approach to pricing European quanto options assuming that the underlying instruments follow a multivariate normal tempered stable (NTS) process. This allows for both fat-tailedness and ...asymmetric dependence between the returns on the underlying asset and the exchange rate. In an empirical application, we estimate the market and risk-neutral parameters for a quanto construction involving the Nikkei 225 index, as the underlying asset, and the Japanese yen and the US dollar exchange rate. While the Gaussian model is clearly rejected by the data, the NTS model cannot be rejected at any reasonable level. A calibration exercise demonstrates that the prices implied by the estimated NTS and the conventional Gaussian models differ substantially, with the NTS model yielding a superior performance as it better reflects the tail properties of the instruments involved.
Many financial assets, such as currencies, commodities, and equity stocks, exhibit both jumps and stochastic volatility, which are especially prominent in the market after the financial crisis. Some ...strategic decision making problems also involve American-style options. In this paper, we develop a novel, fast and accurate method for pricing American and barrier options in regime switching jump diffusion models. By blending regime switching models and Markov chain approximation techniques in the Fourier domain, we provide a unified approach to price Bermudan, American options and barrier options under general stochastic volatility models with jumps. The models considered include Heston, Hull–White, Stein–Stein, Scott, the 3/2 model, and the recently proposed 4/2 model and the α-Hypergeometric model with general jump amplitude distributions in the return process. Applications include the valuation of discretely monitored contracts as well as continuously monitored contracts common in the foreign exchange markets. Numerical results are provided to demonstrate the accuracy and efficiency of the proposed method.
This paper describes a practical algorithm based on Monte Carlo simulation for the pricing of multidimensional American (i.e., continuously exercisable) and Bermudan (i.e., discretely exercisable) ...options. The method generates both lower and upper bounds for the Bermudan option price and hence gives valid confidence intervals for the true value. Lower bounds can be generated using any number of primal algorithms. Upper bounds are generated using a new Monte Carlo algorithm based on the duality representation of the Bermudan value function suggested independently in Haugh and Kogan (2004) and Rogers (2002). Our proposed algorithm can handle virtually any type of process dynamics, factor structure, and payout specification. Computational results for a variety of multifactor equity and interest-rate options demonstrate the simplicity and efficiency of the proposed algorithm. In particular, we use the proposed method to examine and verify the tightness of frequently used exercise rules in Bermudan swaption markets.
Demand-Based Option Pricing Gârleanu, Nicolae; Pedersen, Lasse Heje; Poteshman, Allen M.
The Review of financial studies,
10/2009, Volume:
22, Issue:
10
Journal Article
Peer reviewed
Open access
We model demand-pressure effects on option prices. The model shows that demand pressure in one option contract increases its price by an amount proportional to the variance of the unhedgeable part of ...the option. Similarly, the demand pressure increases the price of any other option by an amount proportional to the covariance of the unhedgeable parts of the two options. Empirically, we identify aggregate positions of dealers and end-users using a unique dataset, and show that demand-pressure effects make a contribution to wellknown option-pricing puzzles. Indeed, time-series tests show that demand helps explain the overall expensiveness and skew patterns of index options, and cross-sectional tests show that demand impacts the expensiveness of single-stock options as well.
Utilizing frame duality and a FFT-based implementation of density projection we develop a novel and efficient transform method to price Asian options for very general asset dynamics, including regime ...switching Lévy processes and other jump diffusions as well as stochastic volatility models with jumps. The method combines continuous-time Markov chain approximation, with Fourier pricing techniques. In particular, our method encompasses Heston, Hull-White, Stein-Stein, 3/2 model as well as recently proposed Jacobi,
α
-Hypergeometric, and 4/2 models, for virtually any type of jump amplitude distribution in the return process. This framework thus provides a ‘
unified
’ approach to pricing Asian options in stochastic jump diffusion models and is readily extended to alternative exotic contracts. We also derive a characteristic function recursion by generalizing the Carverhill-Clewlow factorization which enables the application of transform methods in general. Numerical results are provided to illustrate the effectiveness of the method. Various extensions of this method have since been developed, including the pricing of barrier, American, and realized variance derivatives.
We use data on signed option volume to study which components of option volume predict stock returns and resolve the seemingly inconsistent results in the literature. We find no evidence that trades ...related to synthetic short positions in the underlying stocks contain more information than trades related to synthetic long positions. Purchases of calls that open new positions are the strongest predictor of returns, followed by call sales that close out existing purchased call positions. Overall, our results indicate that the role of options in providing embedded leverage is the most important channel why option trading predicts stock returns.
The VXX option market has grown in popularity alongside the VXX ETN market in activity and size of oustanding positions, yet there is no complete VXX option pricing model. This paper is the first to ...document and analyze the implied volatility (IV) curves of the VXX options market, by applying the methodology of Zhang and Xiang, providing a necessary benchmark for developing a VXX option pricing model. The IV curves of the VXX options market do not exhibit the typical smirk shape, as for S&P 500 options, but rather an upward-sloping almost linear curve.
This article presents a simple yet powerful new approach for approximating the value of American options by simulation. The key to this approach is the use of least squares to estimate the ...conditional expected payoff to the optionholder from continuation. This makes this approach readily applicable in path-dependent and multifactor situations where traditional finite difference techniques cannot be used. We illustrate this technique with several realistic examples including valuing an option when the underlying asset follows a jump-diffusion process and valuing an American swaption in a 20-factor string model of the term structure.
We study the cross-section of stock option returns by sorting stocks on the difference between historical realized volatility and at-the-money implied volatility. We find that a zero-cost trading ...strategy that is long (short) in the portfolio with a large positive (negative) difference between these two volatility measures produces an economically and statistically significant average monthly return. The results are robust to different market conditions, to stock risks-characteristics, to various industry groupings, to option liquidity characteristics, and are not explained by usual risk factor models.
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