Tests of CBOE Options Market Efficiency and Arbitrage Opportunities Based on Options Pricing Mathematical Models

2020 ◽  
Author(s):  
Ziye Huang ◽  
Xiyue Wu ◽  
Zehan Duan
Keyword(s):  
Mathematical Models ◽  
Market Efficiency ◽  
Options Pricing ◽  
Options Market ◽  
Arbitrage Opportunities

Arbitrage Profitability of Box Spreads in the KOSPI200 Options Market

2006 ◽  
Vol 14 (2) ◽  
pp. 109-137
Author(s):  
Jae Ha Lee ◽  
Deok Hee Hahn
Keyword(s):  
Market Efficiency ◽  
Execution Time ◽  
Options Market ◽  
Small Discrepancy ◽  
Arbitrage Opportunities ◽  
Over Time

This study explores the arbitrage profitability of box spread strategies to test the KOSPI200 options market efficiency. using minute-by-minute data for the December 2003 - June 2004 period. The sample consists of 39.445 and 38.318 observations for small discrepancy and large discrepancy in exercise prices. respectively. In the case of credit box spreads, there were 681 (2%) and 2.293 (6%) arbitrage observations for small and large discrepancies, while debit box spreads showed 831 (2%) and 3.098 (8%) observations for small and large discrepancies. In general, mean profit and median profit were different, and the arbitrage profit varied over time. The time to option expiration did not impact the arbitrage profit. Also, the arbitrage profit of box spreads was significantly higher on Fridays for large discrepancy, and it varied across weekdays except the case of small-discrepancy debit box spread. Both arbitrage opportunities and profits substantially decreased as execution time increased. Our overall results suggest that the KOSPI200 options market has been efficient.

scholarly journals Determinants of Violations in the SET50 Index Options Pricing Relationships: Put-Call-Futures Parity and Box Spread Tests

2018 ◽  
Vol 14 (3) ◽  
pp. 1 ◽  
Author(s):  
Woradee Jongadsayakul
Keyword(s):  
Transaction Costs ◽  
Risk Premium ◽  
Tobit Model ◽  
Options Pricing ◽  
Options Market ◽  
Index Options ◽  
Exercise Price ◽  
Daily Data ◽  
Before And After ◽  
Contract Specification

Although SET50 Index Options, the only option product on Thailand Futures Exchange, has been traded since October 29, 2007, it has faced the liquidity problem. The SET50 Index Options market must offer a risk premium to compensate investors for liquidity risk. It may cause violations in options pricing relationships. This research therefore uses daily data from October 29, 2007 to December 30, 2016 to compare the violations in SET50 Index Options pricing relationships before and after change in contract specification on October 29, 2012 and investigate determinants of these violations using Tobit model. Two tests of SET50 Index Options pricing relationships, Put-Call-Futures Parity and Box Spread, are employed. The test results of Put-Call-Futures Parity show that the percentage and baht amount of violations in many cases are greater in the period before the modification of SET50 Index Options. Without transaction costs, we also see more Box Spread violations before contract adjustment. However, after taking transaction costs into account, there are more percentage and baht amount of Box Spread violations in the later time period. The estimation of Tobit model shows that the violation sizes of both Put-Call-Futures Parity and Box Spread, excluding transaction costs, depend on the liquidity of SET50 Index Options market measured by option moneyness and open interest. The SET50 Index Options contract specification, especially exercise price, also significantly affects the size of violations, though the direction of a relationship is not cleared.

Profiting from arbitrage and odds biases of the European football gambling market

2013 ◽  
Vol 7 (2) ◽  
pp. 41-70 ◽  
Author(s):  
Anthony Costa Constantinou ◽  
Norman Elliott Fenton
Keyword(s):  
Market Efficiency ◽  
Arbitrage Opportunities ◽  
European Football ◽  
Gambling Market ◽  
Common Misconceptions

A gambling market is usually described as being inefficient if there are one or more betting strategies that generate profit, at a consistent rate, as a consequence of exploiting market flaws. This paper examines the online European football gambling market based on 14 European football leagues over a period of seven years, from season 2005/06 to 2011/12 inclusive, and takes into consideration the odds provided by numerous bookmaking firms. Contrary to common misconceptions, we demonstrate that the accuracy of bookmakers' odds has not improved over this period. More importantly, our results question market efficiency by demonstrating high profitability on the basis of consistent odds biases and numerous arbitrage opportunities.

Test on the Profit of Pairs Trading Strategy Using KOSPI200 Regular and Mini Options

2018 ◽  
Vol 26 (1) ◽  
pp. 115-151
Author(s):  
Woo–baik Lee
Keyword(s):  
The Other ◽  
Sample Period ◽  
Options Market ◽  
Pairs Trading ◽  
Elapsed Time ◽  
High Profit ◽  
Arbitrage Opportunities ◽  
Arbitrage Trading ◽  
Arbitrage Opportunity ◽  
Price Spread

The KOSPI200 mini option introduced in July 2015 is the derivative of which trading multiplier is reduced to one-fifth of the regular options. This study explored the pairs trading opportunities arising from the price spread between the KOSPI200 regular options and the mini options during the sample period from August 2015 to March 2016 and measured the profits of pairs trading. The main results are summarized as follows. First, the most frequency of pairs trading with high profit was observed for in-the-money options. On the other hands, the frequency of pairs trading opportunities is low and the profit is relatively small for out-of (at)-the money options. Second, for in-the-money options, arbitrage opportunities were captured every three minutes on an average, but the elapsed time between arbitrage opportunity opportunities on out-of-the money options exceeded 10 minutes on average. Third, pairs trading opportunities occur uniformly throughout the day, but profit tends to increase in the afternoon than in the morning. This indicates that price efficiency in options market deteriorates and profit of arbitrage trading with price disparity is higher in the afternoon than that of the morning trading. In addition, the profitability of pairs trading with low liquidity was cross-sectionally higher than those with high liquidity.

Ensuring More Is Better: On the Simultaneous Application of Stock and Options Data to Estimate the GARCH Options Pricing Model

2018 ◽  
Keyword(s):  
Option Pricing ◽  
Stock Prices ◽  
Options Pricing ◽  
Asymptotic Result ◽  
Option Prices ◽  
Options Market ◽  
Pricing Model ◽  
Simultaneous Application ◽  
Option Values ◽  
Option Pricing Model

The most common approach in fitting option pricing models to market data is first to make an assumption about the underlying asset’s returns process and then develop an option pricing model for that process that is tested against market option prices. The returns process is estimated from historical data, option values are computed, and then compared against a cross-section of prices from the options market. Unfortunately, this often does not work well, and plainly it is inefficient in its use of the data. However, efforts to combine returns data from the asset market and prices from the options market into a single estimation have also not had much success. In this article, Chang, Cheng, and Fuh propose a new procedure to combine data from both markets in the estimation, in which options are assumed to be subject to random pricing noise relative to model values. The additional slack gives the estimator better ability to match prices in both markets. The article contrasts the performance of the full model approach with an approach that only uses stock prices or options prices to fit an option pricing model based on an underlying GARCH process. The value of the combined approach is demonstrated both theoretically as an asymptotic result in the model and also in a Monte Carlo simulation.

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