scholarly journals Statistical Arbitrage with Mean-Reverting Overnight Price Gaps on High-Frequency Data of the S&P 500

2019 ◽  
Vol 12 (2) ◽  
pp. 51 ◽  
Author(s):  
Johannes Stübinger ◽  
Lucas Schneider
Keyword(s):  
High Frequency ◽  
Test Procedure ◽  
Research Area ◽  
High Frequency Data ◽  
Frequency Data ◽  
Stock Selection ◽  
Deep Dive ◽  
Statistical Arbitrage ◽  
Jump Diffusion Model ◽  
Arbitrage Strategy

This paper develops a fully-fledged statistical arbitrage strategy based on a mean-reverting jump–diffusion model and applies it to high-frequency data of the S&P 500 constituents from January 1998–December 2015. In particular, the established stock selection and trading framework identifies overnight price gaps based on an advanced jump test procedure and exploits temporary market anomalies during the first minutes of a trading day. The existence of the assumed mean-reverting property is confirmed by a preliminary analysis of the S&P 500 index; this characteristic is particularly significant 120 min after market opening. In the empirical back-testing study, the strategy delivers statistically- and economically-significant returns of 51.47 percent p.a.and an annualized Sharpe ratio of 2.38 after transaction costs. We benchmarked our trading algorithm against existing quantitative strategies from the same research area and found its performance superior in a multitude of risk-return characteristics. Finally, a deep dive analysis shows that our results are consistently profitable and robust against drawdowns, even in recent years.

NONPARAMETRIC ESTIMATION FOR SECOND-ORDER JUMP-DIFFUSION MODEL IN HIGH FREQUENCY DATA

2017 ◽  
Vol 65 (04) ◽  
pp. 1033-1063 ◽  
Author(s):  
YUPING SONG
Keyword(s):  
High Frequency ◽  
Jump Diffusion ◽  
Small Sample ◽  
Second Order ◽  
Stock Index ◽  
High Frequency Data ◽  
Monte Carlo Experiment ◽  
Frequency Data ◽  
Sample Paths ◽  
Jump Diffusion Model

We provide the nonparametric estimators of the infinitesimal coefficients of the second-order continuous-time models with discontinuous sample paths of jump-diffusion models. Under the mild conditions, we obtain the weak consistency and the asymptotic normality of the estimators. A Monte Carlo experiment demonstrates the better small-sample performance of these estimators. In addition, the estimators are illustrated empirically through stock index of Shanghai Stock Exchange in high frequency data.

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.     

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