Arbitrage opportunities, liquidity provision, and trader types in an index option market

2019 ◽  
Vol 40 (3) ◽  
pp. 279-307
Author(s):  
Chin‐Ho Chen ◽  
Junmao Chiu ◽  
Huimin Chung
Keyword(s):  
Liquidity Provision ◽  
Arbitrage Opportunities ◽  
Index Option ◽  
Option Market

Deviations from Put-Call Parity and Volatility Prediction: Evidence from the Taiwan Index Option Market

2014 ◽  
Vol 34 (12) ◽  
pp. 1122-1145 ◽  
Author(s):  
Chin-Ho Chen ◽  
Huimin Chung ◽  
Shu-Fang Yuan
Keyword(s):  
Index Option ◽  
Option Market

Implied Volatility of the KOSPI 200 Index Option Market

2015 ◽  
Vol 23 (4) ◽  
pp. 517-541
Author(s):  
Dam Cho
Keyword(s):  
Financial Crisis ◽  
Trading Volume ◽  
Implied Volatility ◽  
Spot Price ◽  
Strike Price ◽  
Market Pricing ◽  
Put Options ◽  
The Difference ◽  
Index Option ◽  
Option Market

This paper analyzes implied volatilities (IVs), which are computed from trading records of the KOSPI 200 index option market from January 2005 to December 2014, to examine major characteristics of the market pricing behavior. The data includes only daily closing prices of option transactions for which the daily trading volume is larger than 300 contracts. The IV is computed using the Black-Scholes option pricing model. The empirical findings are as follows; Firstly, daily averages of IVs have shown very similar behavior to historical volatilities computed from 60-day returns of the KOSPI 200 index. The correlation coefficient of IV of the ATM call options to historical volatility is 0.8679 and that of the ATM put options is 0.8479. Secondly, when moneyness, which is measured by the ratio of the strike price to the spot price, is very large or very small, IVs of call and put options decrease days to maturity gets longer. This is partial evidence of the jump risk inherent in the stochastic process of the spot price. Thirdly, the moneyness pattern showed heavily skewed shapes of volatility smiles, which was more apparent during the global financial crises period from 2007 to 2009. Behavioral reasons can explain the volatility smiles. When the moneyness is very small, the deep OTM puts are priced relatively higher due to investors’ crash phobia and the deep ITM calls are valued higher due to investors’ overconfidence and confirmation biases. When the moneyness is very large, the deep OTM calls are priced higher due to investors’ hike expectation and the deep ITM puts are valued higher due to overconfidence and confirmation biases. Fourthly, for almost all moneyness classes and for all sub-periods, the IVs of puts are larger than the IVs of calls. Also, the differences of IVs of deep OTM put ranges minus IVs of deep OTM calls, which is known to be a measure of crash phobia or hike expectation, shows consistent positive values for all sub-periods. The difference in the financial crisis period is much bigger than in other periods. This suggests that option traders had a stronger crash phobia in the financial crisis.

CHANCE DISCOVERY IN STOCK INDEX OPTION AND FUTURES ARBITRAGE

2005 ◽  
Vol 01 (03) ◽  
pp. 435-447 ◽  
Author(s):  
EDWARD TSANG ◽  
SHERI MARKOSE ◽  
HAKAN ER
Keyword(s):  
Historical Data ◽  
Stock Index ◽  
Domain Experts ◽  
Programming Tool ◽  
Promising Tool ◽  
Arbitrage Opportunities ◽  
Out Of Sample ◽  
Computer Scientists ◽  
The One ◽  
Index Option

The prices of the option and futures of a stock both reflect the market's expectation of futures changes of the stock's price. Their prices normally align with each other within a limited window. When they do not, arbitrage opportunities arise: an investor who spots the misalignment will be able to buy (sell) options on the one hand, and sell (buy) futures on the other and make risk-free profits. Historical data suggest that option and futures prices on the LIFFE Market do not align occasionally. Arbitrage chances are rare. Besides, they last for seconds only before the market adjusts itself. The challenge is not only to discover such chances, but to discover them ahead of other arbitragers. In the past, we have introduced EDDIE as a genetic programming tool for forecasting. This paper describes EDDIE-ARB, a specialization of EDDIE, for forecasting arbitrage opportunities. As a tool, EDDIE-ARB was designed to enable economists and computer scientists to work together to identify relevant independent variables. Trained on historical data, EDDIE-ARB was capable of discovering rules with high precision. Tested on out-of-sample data, EDDIE-ARB out-performed a naive ex ante rule, which reacted only when misalignments were detected. This establishes EDDIE-ARB as a promising tool for arbitrage chances discovery. It also demonstrates how EDDIE brings domain experts and computer scientists together.

Informed trading in the index option market: The case of KOSPI 200 options

2008 ◽  
Vol 28 (12) ◽  
pp. 1118-1146 ◽  
Author(s):  
Hee-Joon Ahn ◽  
Jangkoo Kang ◽  
Doojin Ryu
Keyword(s):  
Informed Trading ◽  
Index Option ◽  
Option Market
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