Alejandro Bernales

The Success of Option Listings

We examine a number of unexplored factors that affect the ex-post adoption rates of newly listed stock options. We show that a variety of measures of information asymmetries for underlying stocks predict option adoption rates. This occurs even when we control for factors that have been found to be significant in earlier literature, such as stock volatility and volume. However, option listings induce a reduction in the strength of the information asymmetries in the underlying stock. Further, option bid-ask spreads start from low initial levels and increase over time, which is consistent with a modest initial aggressiveness of informed investors.Keywords: Stock options; option listings; asymmetric information; adoption rates; option volume, open interest. JEL Codes: D82; G10; G14; O31.Series:IGIER Working Paper SeriesWe examine unexplored factors that affect the ex-post adoption rates of newly listed stock options. We show that a variety of measures of information asymmetries concerning underlying stocks predict option adoption rates. These predictive relationships are robust after including factors that have been found to be significant in earlier literature, such as stock volatility and volume. Moreover, we report that not only do information asymmetries prior to option listings forecast a successful listing, but also that successful listings themselves end up reducing ex-post the extent of the information asymmetries affecting a stock.

Learning and Index Option Returns

ABSTRACT Little is known about the economic sources that may generate the abnormal returns observed in put index options. We show that the learning process followed by investors may be one such source. We develop an equilibrium model under partial information in which a rational Bayesian learner prices put option contracts. Our model generates put option returns similar to the empirical returns of S&P 500 put index options. This result is not obtained when we analyze alternative setups of the model in which no learning process exists.

Thinly traded securities and risk management

Thinly traded securities exist in both emerging and well developed markets. However, plausible estimations of market risk measures for portfolios with infrequently traded securities have not been explored in the literature. We propose a methodology to calculate market risk measures based on the Kalman filter which can be used on incomplete datasets. We implement our approach in a fixed-income portfolio within a thin trading environment. However, a similar approach may be also applied to other markets with thinly traded securities. Our methodology provides reliable market risk measures in portfolios with infrequent trading.