The Information Content of Implied Volatilities and Model-Free Volatility Expectations

The Information Content of Implied Volatilities and Model-Free Volatility Expectations
Author: Stephen J. Taylor
Publisher:
Total Pages: 64
Release: 2008
Genre:
ISBN:

The volatility information content of stock options for individual firms is measured using option prices for 149 U.S. firms during the period from January 1996 to December 1999. Volatility forecasts defined by historical stock returns, at-the-money (ATM) implied volatilities and model-free (MF) volatility expectations are compared for each firm. The recently developed model-free volatility expectation incorporates information across all strike prices, and it does not require the specification of an option pricing model.Our analysis of ARCH models shows that, for one-day-ahead estimation, historical estimates of conditional variances outperform both the ATM and the MF volatility estimates extracted from option prices for more than one-third of the firms. This result contrasts with the consensus about the informational efficiency of options written on stock indices; several recent studies find that option prices are more informative than daily stock returns when estimating and predicting index volatility. However, for the firms with the most actively traded options, we do find that the option forecasts are nearly always more informative than historical stock returns. When the prediction horizon extends until the expiry date of the options, our regression results show that the option forecasts are more informative than forecasts defined by historical returns for a substantial majority (86%) of the firms. Although the model-free (MF) volatility expectation is theoretically more appealing than alternative volatility estimates and has been demonstrated to be the most accurate predictor of realized volatility by Jiang and Tian (2005) for the Samp;P 500 index, the results for our firms show that the MF expectation only outperforms both the ATM implied volatility and the historical volatility for about one-third of the firms. The firms for which the MF expectation is best are not associated with a relatively high level of trading in away-from-the-money options.

Predicting Volatility and the Information Content of Informed Traders in an Option Market

Predicting Volatility and the Information Content of Informed Traders in an Option Market
Author: Teng-Ching Huang
Publisher:
Total Pages: 38
Release: 2015
Genre:
ISBN:

We investigate the impact of information trading on predicting variation of implied volatility. First, we find that informed traders do trade in the index options market. The predicting biases of implied volatilities on the realized volatility are correlated with the information trading. Second, we find that delta market depth and bid-ask spread are correlated with the predicting variations in implied volatilities. Moreover, the difference between realized and implied volatility, bid-ask spread, and delta market depth are the determinants of price discovery in the option market. Third, the intraday patterns in realized volatility exhibit an inverse J-shape, which induces forecasting biases in implied volatilities. Finally, based on the performance of the volatility trading strategy, the result does not support efficient market hypothesis.

The Forecasting Performance of German Stock Option Densities

The Forecasting Performance of German Stock Option Densities
Author: Ben R. Craig
Publisher:
Total Pages: 34
Release: 2007
Genre:
ISBN:

In this paper the authors estimate risk-neutral densities (RND) for the largest euro-area stock market (the index of which is the German DAX), reporting their statistical properties, and evaluating their forecasting performance. The authors have applied an innovative test procedure to a new, rich, and accurate data set. They have two main results. First, They have recorded strong negative skewness in the densities. Second, they find evidence for a significant difference between the actual density and the risk-neutral density, leading to the conclusion that market participants were surprised by the extent of both the rise and the fall of the DAX.

Handbook of Evidence Based Management Practices in Business

Handbook of Evidence Based Management Practices in Business
Author: Satyendra Kumar Sharma
Publisher: Taylor & Francis
Total Pages: 725
Release: 2023-05-25
Genre: Business & Economics
ISBN: 1000935159

This book is a collection of selected high-quality research papers presented at the 4th International Conference on Evidence-Based Management (ICEBM) 2023, held at Birla Institute of Technology & Science, Pilani, Rajasthan, India, during February 24–25, 2023. It has 76 chapters written by various scholars focusing on evidence-based management practices in different functional areas of management with the application of theory and empirical techniques. This book will be helpful to practitioners, academics, scholars, and policymakers.

ICIDC 2022

ICIDC 2022
Author: Zuriati Ahmad Zukarnain
Publisher: European Alliance for Innovation
Total Pages: 2599
Release: 2022-10-13
Genre: Computers
ISBN: 1631903691

The 2022 International Conference on Information Economy, Data Modeling and Cloud Computing (ICIDC 2022) was successfully held in Qingdao, China from June 17 to 19, 2022. Under the impact of COVID-19, ICIDC 2022 was held adopting a combination of online and offline conference. During this conference, we were greatly honored to have Prof Datuk Dr Hj Kasim Hj Md Mansur from Universiti Malaysia Sabah, Malaysia to serve as our Conference Chairman. And there were 260 individuals attending the conference. The conference agenda was composed of keynote speeches, oral presentations, and online Q&A discussion. The proceedings of ICIDC 2022 cover various topics, including Big Data Finance, E-Commerce and Digital Business, Modeling Method, 3D Modeling, Internet of Things, Cloud Computing Platform, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication. Data modeling allows us to obtain the dynamic change trend of various indicator data, so how to use big data information to model and study the development trend of economic operation plan is of great significance. And that is exactly the purpose of this conference, focusing on the application of big data in the economic field as well as conducting more profound research in combination with cloud computing.