Strategies for Improving V-KOSPI 200 Index

2019 ◽  
Vol 27 (1) ◽  
pp. 1-47
Author(s):  
Tae-Hun Kang
Keyword(s):  
Time Frame ◽  
Options Market ◽  
Direct Solution ◽  
Market Making ◽  
Index Options ◽  
Market Prices ◽  
Target Time ◽  
Variability Level ◽  
Index Option

The study examines not only the methods for eliminating stale or abnormal prices but also strategies for enhancing liquidity in the KOSPI 200 index options market, for compensating the defects of V-KOSPI 200. First, introducing market making scheme in the KOSPI 200 options market can be the direct solution to prevent temporary fluctuations and spikes of the index arising from abnormal orders and to alleviate unnatural low variability (level) of the index through decreasing the use of stale market prices (model prices). Second, if weekly options underlying KOSPI 200 index are available for trading and investor interest in the weeklys are surged, Korea Exchange can enhance V-KOSPI 200 to include series of KOSPI 200 weekly options. The inclusion for at least 5~6 weekly options available for trading allow V-KOSPI 200 to be calculated with KOSPI 200 index option series that most precisely match the 30-day target time-frame for expected volatility that the Index is intended to represent. Along with these strategies for enhancing liquidity in the KOSPI 200 index options market, the study suggests the methodology which can prevents temporary fluctuations and spikes of the index by substituting stale or abnormal prices for normal prices.

Is volatility risk priced in the KOSPI 200 index options market?

2009 ◽  
Vol 29 (9) ◽  
pp. 797-825 ◽  
Author(s):  
Sun-Joong Yoon ◽  
Suk Joon Byun
Keyword(s):  
Options Market ◽  
Index Options ◽  
Volatility Risk

Pairs Trading In The index Options Market

2021 ◽  
Author(s):  
Marianna Brunetti ◽  
Roberta De Luca
Keyword(s):  
Options Market ◽  
Pairs Trading ◽  
Index Options

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.

Storage Options and Sizing for Utility Scale Integration of Wind Energy Plants

Solar Energy ◽  
2005 ◽  
Author(s):  
Allan E. Ingram
Keyword(s):  
Energy Storage ◽  
Wind Energy ◽  
Storage System ◽  
Electric Energy ◽  
Time Frame ◽  
Market Prices ◽  
Electric Energy Storage ◽  
Design Engineers ◽  
Scale Integration ◽  
Utility Scale

Electric energy storage has been discussed as an option for increasing the marketability of wind energy facilities by reducing output variation. Utility scale wind plants face economic exposure to tariff charges for output variation as well as depending on volatile market prices for success. Wind speed variability and associated changes in wind plant output raise specific challenges to design engineers sizing electric energy storage systems. Evaluation of prospective Wind/Storage applications depends on the characteristics of individual wind plant output and the choice of storage technology. Energy storage options range from traditional lead acid batteries and pumped hydro storage to recently commercialized electrochemical flow battery systems. Selection and sizing of energy storage for wind plants vary with the time frame for each application. Different time frames correspond with the utility definitions of regulation, load shaping and load factoring. Results from a storage system model are presented that differentiate appropriate storage system sizes for these applications.

scholarly journals ON THE RELATIONSHIP OF IMPLIED, REALIZED AND HISTORICAL VOLATILITY: EVIDENCE FROM NSE EQUITY INDEX OPTIONS

2014 ◽  
Vol 15 (5) ◽  
pp. 915-934 ◽  
Author(s):  
Puja Padhi ◽  
Imlak Shaikh
Keyword(s):  
Instrumental Variable ◽  
Implied Volatility ◽  
Return Volatility ◽  
Volatility Forecasting ◽  
Variable Technique ◽  
Index Options ◽  
Equity Index ◽  
Relationship Of ◽  
Index Option ◽  
The Relationship

This study examines the information content of implied volatility, using the options of the underlying S&P CNX Nifty index. In this study, implied, historical and realized volatilities are calculated using non-overlapping monthly at-the-money samples. The study covers the period from introduction of options on the derivative segment of NSE, June 2001 to May 2011. The results reveal that call and put implied volatility of S&P CNX Nifty index option does contain information about future realized return volatility. This study accounts for the problem of error-in-variable and controls for it by using the instrumental variable technique. In the 2SLS estimation, the Hausman H-statistic shows that call implied volatility is measured with error. Hence, 2SLS coefficients are more consistent than the OLS estimates. Results of this study might prove to be helpful to the volatility traders in volatility forecasting and option pricing.

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