The Experts below are selected from a list of 11610 Experts worldwide ranked by ideXlab platform
Avanidhar Subrahmanyam - One of the best experts on this subject based on the ideXlab platform.
-
index Option Trading activity and market returns
Management Science, 2021Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives play an informational role? Weekly index put order flow on the International Securities Exchange positively and robustly predicts weekly S&P 500 index returns. T...
-
The Informational Role of Index Option Trading
Social Science Research Network, 2017Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives capture informed Trading? We show that net buying pressure in index put Options traded on the International Securities Exchange (ISE) positively and robustly predicts SP specifically in index futures and the ETF on the index, as well as order flow in the underlying index. The contrarian nature of return prediction from Option order flow (net put buying predicts a higher index return) suggests that market makers who take the other side of the Option orders have private information, and set quotes to attract orders from outside customers and brokers. Supporting the notion that market makers lower spreads to attract Trading when they have information, we find that the predictive ability of put order flow for index Options is higher when puts are more liquid.
Dmitriy Muravyev - One of the best experts on this subject based on the ideXlab platform.
-
index Option Trading activity and market returns
Management Science, 2021Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives play an informational role? Weekly index put order flow on the International Securities Exchange positively and robustly predicts weekly S&P 500 index returns. T...
-
The Informational Role of Index Option Trading
Social Science Research Network, 2017Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives capture informed Trading? We show that net buying pressure in index put Options traded on the International Securities Exchange (ISE) positively and robustly predicts SP specifically in index futures and the ETF on the index, as well as order flow in the underlying index. The contrarian nature of return prediction from Option order flow (net put buying predicts a higher index return) suggests that market makers who take the other side of the Option orders have private information, and set quotes to attract orders from outside customers and brokers. Supporting the notion that market makers lower spreads to attract Trading when they have information, we find that the predictive ability of put order flow for index Options is higher when puts are more liquid.
-
Option Trading costs are lower than you think
Social Science Research Network, 2016Co-Authors: Dmitriy Muravyev, Neil D PearsonAbstract:Conventional estimates of the costs of taking liquidity in equity Options markets are large. This presents a puzzle, which we resolve by taking seriously the implication of models of dynamic limit order markets that the bid-ask midpoint can be a poor proxy for the true value of a security, conditional on the occurrence of a trade. Changes in Option prices can be predicted using publically available information, and a large proportion of Option trades exploit this high-frequency predictability to take liquidity at low cost, buying and selling immediately before Option prices are expected to change. Conventional measures of effective spreads and price impact do not account for this execution timing but can be adjusted to do so. For the average trade, effective spreads that take account of trade timing are one-third smaller than the conventionally measured effective spreads; for trades that reflect execution timing, they are four times smaller. Conventional measures of price impact overstate it by a factor of more than two. These findings have striking implications for the profitability of Options Trading strategies that involve taking liquidity. Our main results are robust to recent changes in Option market structure.
Tarun Chordia - One of the best experts on this subject based on the ideXlab platform.
-
index Option Trading activity and market returns
Management Science, 2021Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives play an informational role? Weekly index put order flow on the International Securities Exchange positively and robustly predicts weekly S&P 500 index returns. T...
-
The Informational Role of Index Option Trading
Social Science Research Network, 2017Co-Authors: Tarun Chordia, Alexander Kurov, Dmitriy Muravyev, Avanidhar SubrahmanyamAbstract:Do order flows in index derivatives capture informed Trading? We show that net buying pressure in index put Options traded on the International Securities Exchange (ISE) positively and robustly predicts SP specifically in index futures and the ETF on the index, as well as order flow in the underlying index. The contrarian nature of return prediction from Option order flow (net put buying predicts a higher index return) suggests that market makers who take the other side of the Option orders have private information, and set quotes to attract orders from outside customers and brokers. Supporting the notion that market makers lower spreads to attract Trading when they have information, we find that the predictive ability of put order flow for index Options is higher when puts are more liquid.
Bobby S Sriniivasan - One of the best experts on this subject based on the ideXlab platform.
-
utilizing a neural logic expert system in currency Option Trading
Expert Systems With Applications, 1995Co-Authors: Quah Tongseng, C.l. Tan, H.h. Teh, Bobby S SriniivasanAbstract:Abstract International currency market weathers all forms of worldwide current affairs and governmental economics statistics releases. Such news causes fluctuations in demands and supplies for major currencies. In order to gain from currency Tradings, a trader has to gauge, sometimes guess using gut feelings, the likely market movement, and act accordingly. In this paper, a neural network-based expert decision support system for assisting users in making currency Option Trading decisions is presented. By utilizing neural network technology in its inference engine, the system is able to learn new knowledge and refine its inference strategy through usage. Furthermore, it can change its reasoning strategies according to different users, thus realizing the idea of personalized logic system.
Ghulam Sarwar - One of the best experts on this subject based on the ideXlab platform.
-
the informational role of Option Trading volume in equity index Options markets
Review of Quantitative Finance and Accounting, 2005Co-Authors: Ghulam SarwarAbstract:This paper examines the dynamic relations between future price volatility of the S&P 500 index and Trading volume of S&P 500 Options to explore the informational role of Option volume in predicting the price volatility. The future volatility of the index is approximated alternatively by implied volatility and by EGARCH volatility. Using a simultaneous equation model to capture the volume-volatility relations, the paper finds that strong contemporaneous feedbacks exist between the future price volatility and the Trading volume of call and put Options. Previous Option volumes have a strong predictive ability with respect to the future price volatility. Similarly, lagged changes in volatility have a significant predictive power for Option volume. Although the volume-volatility relations for individual volatility and volume terms are somewhat different under the two volatility measures, the results on the predictive ability of volume (volatility) for volatility (volume) are broadly similar between the implied and EGARCH volatilities. These findings support the hypothesis that both the information- and hedge-related Trading explain most of the Trading volume of equity index Options.