Index Option Prices and Stock Market Momentum

2004 ◽  
Vol 77 (4) ◽  
pp. 835-874 ◽  
Author(s):  
Kaushik Amin ◽  
Joshua D. Coval ◽  
H. Nejat Seyhun
Keyword(s):  
Stock Market ◽  
Option Prices ◽  
Index Option

scholarly journals Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk

2020 ◽  
pp. 1-27
Author(s):  
Peter Christoffersen ◽  
Mathieu Fournier ◽  
Kris Jacobs ◽  
Mehdi Karoui
Keyword(s):  
Risk Premium ◽  
Risk Premia ◽  
Factor Models ◽  
Option Prices ◽  
Variance Risk Premium ◽  
Market Return ◽  
Price Of Risk ◽  
Variance Risk ◽  
Index Option

Abstract We show that the prices of risk for factors that are nonlinear in the market return can be obtained using index option prices. The price of coskewness risk corresponds to the market variance risk premium, and the price of cokurtosis risk corresponds to the market skewness risk premium. Option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An analysis of factor models with coskewness risk indicates that the new estimates of the price of risk improve the models’ performance compared with regression-based estimates.

Informed Trading in the Stock Market and Option-Price Discovery

2020 ◽  
pp. 1-40 ◽  
Author(s):  
Pierre Collin-Dufresne ◽  
Vyacheslav Fos ◽  
Dmitry Muravyev
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Implied Volatility ◽  
Common Knowledge ◽  
Option Price ◽  
Price Volatility ◽  
Informed Trading ◽  
Flow Dynamics ◽  
Option Prices ◽  
Market Makers

Abstract When activist shareholders file Schedule 13D filings, the average stock-price volatility drops by approximately 10%. Prior to filing days, volatility information is reflected in option prices. Using a comprehensive sample of trades by Schedule 13D filers that reveals on what days and in what markets they trade, we show that on days when activists accumulate shares, option-implied volatility decreases, implied volatility skew increases, and implied volatility time slope increases. The evidence is consistent with a theoretical model where it is common knowledge that informed trading occurs only in the stock market and market makers update option prices based on stock-price and order-flow dynamics.

Do the Option Prices Forecast Spot Price? Evidence from the KOSPI 200 Index Option Market

2011 ◽  
Vol 19 (3) ◽  
pp. 251-280
Author(s):  
Byungwook Choi
Keyword(s):  
Implied Volatility ◽  
Parametric Method ◽  
Trading Strategy ◽  
Stock Index ◽  
Rate Of Return ◽  
Spot Price ◽  
Option Prices ◽  
Daily Rate ◽  
Risk Neutral ◽  
Index Option

This study investigates a forecasting power of volatility curvatures and risk neutral densities implicit in KOSPI 200 option prices by analyzing minute by minute historical index option intraday trading data from January of 2007 to January of 2011. We begin by estimating implied volatility functions and risk neutral price densities based on non-parametric method every minute and by calculating volatility curvature and skewness premium. We then compare the daily rate of return of the signal following trading strategy that we buy (sell) a stock index when the volatility curvature or skewness premium increases (decreases) with that of an intraday buy-and-hold strategy that we buy a stock index on 9:05AM and sell it on 2:50PM. We found that the rate of return of the signal following trading strategy was significantly higher than that of the intraday buy-and-hold strategy, which implies that the option prices have a strong forecasting power on the direction of stock market. Another finding is that the information contents of option prices disappear after three or four minutes.

Futures and Option Prices After the Stock Market Close: Evidence from the Korean Markets

2008 ◽  
Vol 16 (2) ◽  
pp. 95-125
Author(s):  
Jae Ha Lee ◽  
Sang Soo Kwon
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Return Volatility ◽  
Option Prices ◽  
Option Markets ◽  
Option Returns ◽  
Time Zones ◽  
The Impact

In the KOSPI2oo futures and option markets. additional fifteen minutes (15 : 00∼15 개5) after the underlying stock market close are given tor the adjustments of the futures and option positions. During the first five minutes. 15: 00∼15 : 05. a continuous auction trading is made. while the trading at a single clearing price is made for the remaining ten minutes. 15: 05∼15: 15. Previous studies focused on the synchronous trading in terms of transaction time in the analysis of the lead-lag relationship. truncating the futures and option data during 15 : 00∼15 : 15. In this article. we explore how the KOSPI2oo futures and option returns for the extra fifteen minutes impact the next day's KOSPI200 cash returns, We also examine the lead-lag relationship during the reggular trading hours (9 : 00∼15 : 00) and the impact of the cash returns during 14 : 20∼15 : 00 on futures and option returns during 15 : 00∼15: 15. Our main findings are summarized as follows. First. the KOSPI200 futures and option returns during 15 : 00∼15 : 15 lead the close-to-open KOSPI200 cash return, even though the trading volume and return volatility during 15: 00∼15: 15 are lower relative to the regular stock market session (9 : 00∼15: 00). The impact of the futures and option returns on the cash return lasts hlK) minutes and one minute‘ repectively. after the next day open. Second. the option return during the continuous auction trading session (15 : 00∼ 15 : 05) leads the close-to-open cash return. while the futures return of trading at a single clearing price during 15 : 05∼15 : 10 impacts the close-to-open cash return. Third, we found that the lead-lag relationships among the KOSPI200 futures, option, and cash returns are not constant during the reg비ar stock market session‘ In partieular. the impact of the KOSPI200 cash ret un during 14 : 40∼15 : 00 on the futures and option retuns for the 15 : 00∼15: 15 Interval is much stronger. compared with other time zones. Finally. the KOSPI200 cash return during the last ten minutes of trading at a Single clearing price (14 : 50∼15 : 00). significantly impacts the option return during 15: 00∼15: 05. while there is no impact on the futures return (15 : 00∼15: 15).

Artificial neural network model of the hybrid EGARCH volatility of the Taiwan stock index option prices

2008 ◽  
Vol 387 (13) ◽  
pp. 3192-3200 ◽  
Author(s):  
Chih-Hsiung Tseng ◽  
Sheng-Tzong Cheng ◽  
Yi-Hsien Wang ◽  
Jin-Tang Peng
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Stock Index ◽  
Option Prices ◽  
Artificial Neural ◽  
Index Option

Option prices and stock market momentum: evidence from China

2018 ◽  
Vol 18 (9) ◽  
pp. 1517-1529 ◽  
Author(s):  
Jianping Li ◽  
Yanzhen Yao ◽  
Yibing Chen ◽  
Cheng-Few Lee
Keyword(s):  
Stock Market ◽  
Option Prices

A Tractable Framework for Option Pricing with Dynamic Market Maker Inventory and Wealth

2019 ◽  
Vol 55 (4) ◽  
pp. 1117-1162
Author(s):  
Mathieu Fournier ◽  
Kris Jacobs
Keyword(s):  
Stochastic Volatility ◽  
Risk Premium ◽  
Reduced Form ◽  
Market Maker ◽  
Option Prices ◽  
Stochastic Volatility Models ◽  
Variance Risk Premium ◽  
Volatility Models ◽  
Variance Risk ◽  
Index Option

We develop a tractable dynamic model of an index option market maker with limited capital. We solve for the variance risk premium and option prices as a function of the asset dynamics and market maker option holdings and wealth. The market maker absorbs end users’ positive demand and requires a more negative variance risk premium when she incurs losses. We estimate the model using returns, options, and inventory and find that it performs well, especially during the financial crisis. The restrictions imposed by nested existing reduced-form stochastic-volatility models are strongly rejected in favor of the model with a market maker.

scholarly journals Option Implied Stock Buy-Side and Sell-Side Market Depths

Risks ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 108
Author(s):  
Tsai
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Price Impact ◽  
Option Prices ◽  
Bear Market ◽  
Market Depth ◽  
Price Impacts ◽  
Event Date ◽  
Trading Activities ◽  
The Difference

This paper investigates option valuation when the underlying market suffers from illiquidity of price impact. Using option data, I infer trading activities and price impacts on the buy side and the sell side in the stock market from option prices across maturities. The finding displays that the stock market is active when the stock prices plummet, but becomes silent after the market crashes. In addition, the difference of option implied price impacts between the buy side and the sell side, which indicates asymmetric liquidity, increases with the time to maturity, especially on the day of the market crisis. Moreover, investors have different perspectives on the future liquidity after liquidity shocks when they are in a bull market or in a bear market according to the option implied price impact (or market depth) curves. I also calibrate three market indices simultaneously and reach the same conclusion that the three markets become erratic on the event date and calm down in the aftermath.

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