scholarly journals Information Content of Options Trading Volume for Future Volatility: Evidence from the Taiwan Options Market

2008 ◽  
Author(s):  
Chuang-Chang Chang ◽  
Pei-Fang Hsieh ◽  
Yaw-Huei Wang
Keyword(s):  
Information Content ◽  
Trading Volume ◽  
Options Market ◽  
Options Trading

Trading in the Options Market around Financial Analysts’ Consensus Revisions

2014 ◽  
Vol 49 (3) ◽  
pp. 725-747 ◽  
Author(s):  
Darren K. Hayunga ◽  
Peter P. Lung
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Trading Volume ◽  
Financial Analysts ◽  
Options Market ◽  
Sample Analysis ◽  
Consensus Recommendation ◽  
Out Of Sample ◽  
Correct Direction ◽  
Options Trading

AbstractThis article investigates the options market around a revision in the financial analysts’ consensus recommendation. The results demonstrate that options investors trade in the correct direction of the upcoming revision approximately 3 days prior to the announcement. We find this behavior in option-implied prices, implied volatilities, and options trading volume. Tests confirm that the options market leads the stock market before the financial analysts’ revision. Moreover, using all firms with outstanding options, an out-of-sample analysis produces a profitable zero-cost trading strategy net of transaction costs based on the relative valuations between the synthetic and the underlying equity security.

The Information Content of the VIX Options Trading Volume

2021 ◽  
Author(s):  
Chen Gu ◽  
Xu Guo ◽  
Alexander Kurov ◽  
Raluca Stan
Keyword(s):  
Information Content ◽  
Trading Volume ◽  
Vix Options ◽  
Options Trading

Volatility Forecast Incorporating Investors’ Sentiment and its Application in Options Trading Strategies: A Behavioural Finance Approach at Nifty 50 Index

2020 ◽  
Vol 24 (2) ◽  
pp. 217-227
Author(s):  
Kelvin Mutum
Keyword(s):  
Decision Making ◽  
Investor Sentiment ◽  
Trading Strategies ◽  
Percentage Error ◽  
Forecasting Model ◽  
Decision Making Process ◽  
Options Market ◽  
Volatility Forecasting ◽  
Behavioural Finance ◽  
Options Trading

The present study was to examine whether the performance of options trading strategies can be improved if volatility forecasting incorporating investors’ sentiment was incorporated in the decision-making process at the Indian options market. The study adopted the multiple-factor model to build the Indian volatility forecasting model. The benchmark forecasting model (BMF) includes absolute daily returns (|RA|), daily high–low range (HLR) and daily realized volatility (RV). The proxies of investors’ sentiment considered in the study were India volatility index (IVIX), advance decline ratio (ADR), put-call open interest (PCOI) and their changes. The results of the causality and regression test indicate that investors’ sentiment and their changes should be included in the forecasting model. Mean absolute percentage error (MAPE) indicates that 15-day holding period shows the minimum error. Straddle strategies were simulated 15 days ahead before the options maturity date base on the direction of the forecast for different volatility forecasting models. The simulation result shows that the options trading performance might be improved if volatility forecasting incorporating investor sentiment, particularly IVIX, was incorporated in the decision-making process at the Indian options market. From the behavioural finance point of view, the study bridges the gap between options trading, volatility forecasting and information content of investors’ sentiment at the Indian financial market.

scholarly journals Predictability of OTC Option Volatility for Future Stock Volatility

2020 ◽  
Vol 12 (12) ◽  
pp. 5200
Author(s):  
Jungmu Kim ◽  
Yuen Jung Park
Keyword(s):  
Information Content ◽  
Unbiased Estimator ◽  
Implied Volatility ◽  
Realized Volatility ◽  
Stock Index ◽  
Options Market ◽  
Over The Counter ◽  
Index Options ◽  
Stock Volatility ◽  
Future Realized Volatility

This study explores the information content of the implied volatility inferred from stock index options in the over-the-counter (OTC) market, which has rarely been studied in the literature. Using OTC calls, puts, and straddles on the KOSPI 200 index, we find that implied volatility generally outperforms historical volatility in predicting future realized volatility, although it is not an unbiased estimator. The results are more apparent for options with shorter maturity. However, while implied volatility has strong predictability during normal periods, historical volatility is superior to implied volatility during a period of crisis due to the liquidity contraction of the OTC options market. This finding suggests that the OTC options market can play a role in conveying important information to predict future volatility.

Sign in / Sign up

Export Citation Format

Share Document