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Options Data (option + data)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	100%

Selected Abstracts

A note on rational call option exercise

THE JOURNAL OF FUTURES MARKETS, Issue 5 2002
Malin Engström
Using Swedish equity option data, the rationality in the exercise of American call options is analyzed to see how well it complies with the theoretical exercise rules. Although the exercise behavior appears to be rational overall, several cases of both faulty exercise and failure to exercise are found. Almost a third of the early exercised calls are exercised at other times than predicted by theory. Several of these exercise decisions could potentially be explained by transaction costs, indicating that market frictions do affect the exercise behavior. However, over two thirds of the faulty exercises cannot be explained at all. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:471,482, 2002 [source]

Options and the Bubble

THE JOURNAL OF FINANCE, Issue 5 2006
ROBERT BATTALIO
ABSTRACT Many believe that a bubble existed in Internet stocks in the 1999 to 2000 period, and that short-sale restrictions prevented rational investors from driving Internet stock prices to reasonable levels. In the presence of such short-sale constraints, option and stock prices could decouple during a bubble. Using intraday options data from the peak of the Internet bubble, we find almost no evidence that synthetic stock prices diverged from actual stock prices. We also show that the general public could cheaply short synthetically using options. In summary, we find no evidence that short-sale restrictions affected Internet stock prices. [source]

Do Stock Prices and Volatility Jump?

THE JOURNAL OF FINANCE, Issue 3 2004
Option Prices, Reconciling Evidence from Spot
This paper examines the empirical performance of jump diffusion models of stock price dynamics from joint options and stock markets data. The paper introduces a model with discontinuous correlated jumps in stock prices and stock price volatility, and with state-dependent arrival intensity. We discuss how to perform likelihood-based inference based upon joint options/returns data and present estimates of risk premiums for jump and volatility risks. The paper finds that while complex jump specifications add little explanatory power in fitting options data, these models fare better in fitting options and returns data simultaneously. [source]

An empirical investigation of the GARCH option pricing model: Hedging performance

THE JOURNAL OF FUTURES MARKETS, Issue 12 2003
Haynes H. M. Yung
In this article, we study the empirical performance of the GARCH option pricing model relative to the ad hoc Black-Scholes (BS) model of Dumas, Fleming, and Whaley. Specifically, we investigate the empirical performance of the option pricing model based on the exponential GARCH (EGARCH) process of Nelson. Using S&P 500 options data, we find that the EGARCH model performs better than the ad hoc BS model both in terms of in-sample valuation and out-of-sample forecasting. However, the superiority of out-of-sample performance EGARCH model over the ad hoc BS model is small and insignificant except in the case of deep-out-of-money put options. The out-performance diminishes as one lengthens the forecasting horizon. Interestingly, we find that the more complicated EGARCH model performs worse than the ad hoc BS model in hedging, irrespective of moneyness categories and hedging horizons. For at-the-money and out-of-the-money put options, the underperformance of the EGARCH model in hedging is statistically significant. © 2003 Wiley Periodicals, Inc. Jrl Fut Mark 23:1191,1207, 2003 [source]