scholarly journals Pricing and Informational Efficiency of the MIB30 Index Options Market. An Analysis with High Frequency Data

2003 ◽  
Author(s):  
Gianluca Cassese ◽  
Massimo Guidolin
Keyword(s):  
High Frequency ◽  
High Frequency Data ◽  
Informational Efficiency ◽  
Options Market ◽  
Frequency Data ◽  
Index Options

Stock Price Jumps and News Sentiment: A Case of Investor Overreaction

2018 ◽  
Vol 11 (2) ◽  
pp. 20-37
Author(s):  
Vinay Kumar Apparaju ◽  
Ashwani Kumar ◽  
Ritu Yadav
Keyword(s):  
High Frequency ◽  
Stock Price ◽  
Strong Form ◽  
High Frequency Data ◽  
Options Market ◽  
Frequency Data ◽  
Innovative Method ◽  
Investor Behaviour ◽  
News Sentiment ◽  
The Impact

The research paper develops an understanding on how news based sentiment capture investor behaviour reflected in price jumps in stock markets. It compares the impact on two models of stock price jumps; the non-parametric model proposed by BNS and the wavelet based method. The study is also a perspective on the semi strong form of market efficiencyUsing the high frequency data from the stock and options market along with the actual high frequency news data from Bloomberg, the two alternative methodologies of jumps have been tested. In addition, options trades have been simulated to see whether profits can be earned from the news sentiment captured by jumps.Methodologically, jumps based on wavelets were found to be better related  with the news sentiment compared to the BNS method. Also,   the news sentiment based jumps were found to present opportunities in the simulated trades that could be exploited for earning profits suggesting that investors overreact.The paper uses an innovative method for computation of the news based sentiment. To the best of our knowledge, the paper is the first to evaluate jumps and news sentiment using the actual news data. A perspective on the semi strong form of market efficiency is presented, that too by departing from the event study based models. 

scholarly journals Efficiency of S&P CNX Nifty Index Option of the National Stock Exchange (NSE), India, using Box Spread Arbitrage Strategy

2014 ◽  
Vol 15 (3) ◽  
pp. 269 ◽  
Author(s):  
G. P. Girish ◽  
Nikhil Rastogi
Keyword(s):  
High Frequency ◽  
Stock Exchange ◽  
Estimation Error ◽  
High Frequency Data ◽  
Frequency Data ◽  
Index Options ◽  
Time Period ◽  
Arbitrage Strategy ◽  
Computational Simplicity ◽  
Index Option

Box spread is a trading strategy in which one simultaneously buys and sells options having the same underlying asset and time to expiration, but different exercise prices. This study examined the efficiency of European style S&P CNX Nifty Index options of National Stock Exchange, (NSE) India by making use of high-frequency data on put and call options written on Nifty (Time-stamped transactions data) for the time period between 1st January 2002 and 31st December 2005 using box-spread arbitrage strategy. The advantages of box-spreads include reduced joint hypothesis problem since there is no consideration of pricing model or market equilibrium, no consideration of inter-market non-synchronicity since trading box spreads involve only one market, computational simplicity with less chances of mis-specification error, estimation error and the fact that buying and selling box spreads more or less replicates risk-free lending and borrowing. One thousand three hundreds and fifty eight exercisable box-spreads were found for the time period considered of which 78 Box spreads were found to be profitable after incorporating transaction costs (32 profitable box spreads were identified for the year 2002, 19 in 2003, 14 in 2004 and 13 in 2005) The results of our study suggest that internal option market efficiency has improved over the years for S&P CNX Nifty Index options of NSE India.     

Forecasting Exchange Rate Realized Volatility Through Decomposition Using High-Frequency Data

2017 ◽  
Author(s):  
Rim mname Lamouchi ◽  
Russell mname Davidson ◽  
Ibrahim mname Fatnassi ◽  
Abderazak Ben mname Maatoug
Keyword(s):  
Exchange Rate ◽  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Frequency Data
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