Nonconstant optimal hedge ratio estimation and nested hypotheses tests

1994 ◽  
Vol 14 (5) ◽  
pp. 619-635 ◽  
Author(s):  
Kevin P. McNew ◽  
Paul L. Fackler
Keyword(s):  
Ratio Estimation ◽  
Hedge Ratio ◽  
Optimal Hedge

scholarly journals Optimal Hedge Ratio estimation: GARCH (1,1) approach, a new model

2017 ◽  
Vol 3 (6) ◽  
Author(s):  
A. García ◽  
J. Rositas ◽  
M. H. Badii
Keyword(s):  
Ratio Estimation ◽  
Hedge Ratio ◽  
New Model ◽  
Gold Futures ◽  
Optimal Hedge

Abstract. An estimation of the Optimal Hedge Ratio on future markets is developed. The methodology incorporates forecasting the volatility and correlation of the spot and future prices using a GARCH (1,1) model, and under these estimations compute the optimal hedge ratio. This document shows a clear example of the methodology, using gold futures to hedge the risk exposure.Key words: GARCH (1,1), hedge Ratio estimationResumen. Se desarrolla una estimación óptima de Hedge Ratio en los mercados del futuro. La metodología se basa en incorporar el pronostico de volatilidad y la correlación entre el precio del momento y del futuro usando el GARCH (1,1). Este documento demuestra un ejemplo claro de la metodología, utilizando el oro en el futuro para proteger el riesgo.Palabras Claves: Estimación de Hedge Ratio, GARCH (1,1)

Optimal Hedge Ratio Estimation and Effectiveness Using ARCD

2007 ◽  
Author(s):  
Eleftheria S. Kostika ◽  
Raphael N. Markellos
Keyword(s):  
Ratio Estimation ◽  
Hedge Ratio ◽  
Optimal Hedge

Optimal Hedge Ratio Estimation and Effectiveness Using ARCD

2012 ◽  
Vol 32 (1) ◽  
pp. 41-50 ◽  
Author(s):  
Eleftheria Kostika ◽  
Raphael N. Markellos
Keyword(s):  
Ratio Estimation ◽  
Hedge Ratio ◽  
Optimal Hedge

scholarly journals Generalized Optimal Hedge Ratio Estimation

1989 ◽  
Vol 71 (4) ◽  
pp. 858-868 ◽  
Author(s):  
Robert J. Myers ◽  
Stanley R. Thompson
Keyword(s):  
Ratio Estimation ◽  
Hedge Ratio ◽  
Optimal Hedge

Optimal Hedge Ratio and Hedging Effectiveness in Stock Futures Market: Evidence from National Stock Exchange, India

2019 ◽  
Vol 118 (3) ◽  
pp. 137-152
Author(s):  
A. Shanthi ◽  
R. Thamilselvan
Keyword(s):  
Banking Sector ◽  
Stock Exchange ◽  
Research Work ◽  
Futures Market ◽  
Least Square ◽  
Time Varying ◽  
Hedge Ratio ◽  
Hedging Effectiveness ◽  
Out Of Sample ◽  
Optimal Hedge

The major objective of the study is to examine the performance of optimal hedge ratio and hedging effectiveness in stock futures market in National Stock Exchange, India by estimating the following econometric models like Ordinary Least Square (OLS), Vector Error Correction Model (VECM) and time varying Multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) model by evaluating in sample observation and out of sample observations for the period spanning from 1st January 2011 till 31st March 2018 by accommodating sixteen stock futures retrieved through www.nseindia.com by considering banking sector of Indian economy. The findings of the study indicate both the in sample and out of sample hedging performances suggest the various strategies obtained through the time varying optimal hedge ratio, which minimizes the conditional variance performs better than the employed alterative models for most of the underlying stock futures contracts in select banking sectors in India. Moreover, the study also envisage about the model selection criteria is most important for appropriate hedge ratio through risk averse investors. Finally, the research work is also in line with the previous attempts Myers (1991), Baillie and Myers (1991) and Park and Switzer (1995a, 1995b) made in the US markets

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