scholarly journals Regression-Based Variance Reduction Approach for Strong Approximation Schemes

Author(s):  
Denis Belomestny ◽  
Stefan Häfner ◽  
Mikhail Urusov
2016 ◽  
Vol 22 (1) ◽  
Author(s):  
Claude Le Bris ◽  
Frédéric Legoll ◽  
William Minvielle

AbstractWe adapt and study a variance reduction approach for the homogenization of elliptic equations in divergence form. The approach, borrowed from atomistic simulations and solid-state science


2019 ◽  
Vol 57 ◽  
pp. 101047 ◽  
Author(s):  
Ming-Hua Hsieh ◽  
Yi-Hsi Lee ◽  
So-De Shyu ◽  
Yu-Fen Chiu

2019 ◽  
Vol 18 (2) ◽  
pp. 131
Author(s):  
MANDEEP KAUR ◽  
KAPIL GUPTA

Present study attempts to investigate the impact of hedge horizon upon hedging effectiveness in Indian equity futures market by comparing hedging performance of near, next and far month futures contracts of NIFTY50 index and its 17 composite stocks. Hedging effectiveness has been measured using two approaches, namely, Variance Reduction approach and Risk-Return approach. The study finds that near month futures contracts are most effective when hedge effectiveness is measured using variance reduction approach, whereas, on the other hand, far month futures contracts are found to be most effective using risk-return approach. These results imply that for highly risk-averse investors (concerned with only minimization of risk), near month futures contracts enable effective hedging, whereas for less risk-averse investors (concerned with risk as well as return), far month futures contracts offer superior hedge effectiveness. The study also finds that coefficient of correlation between spot and futures returns is a significant factor affecting variance reduction of returns and bears direct relationship with it.


Sign in / Sign up

Export Citation Format

Share Document