scholarly journals Reevaluating hedging performance

2006 ◽  
Vol 26 (7) ◽  
pp. 677-702 ◽  
Author(s):  
John Cotter ◽  
Jim Hanly
Keyword(s):  
Hedging Performance

Beta hedging: performance measures, momentum weighting and rebalancing effects

2019 ◽  
Author(s):  
Daniel Nadler ◽  
Anatoly B. Schmidt
Keyword(s):  
Performance Measures ◽  
Hedging Performance

Hedging performance of GNMA futures under rising and falling interest rates

1983 ◽  
Vol 3 (4) ◽  
pp. 403-413 ◽  
Author(s):  
Joanne Hill ◽  
Joseph Liro ◽  
Thomas Schneeweis
Keyword(s):  
Interest Rates ◽  
Hedging Performance

Tail Risk Hedging Performance: Measuring What Counts

2021 ◽  
Author(s):  
Linda Chang ◽  
Jeremie Holdom ◽  
Vineer Bhansali
Keyword(s):  
Tail Risk ◽  
Risk Hedging ◽  
Hedging Performance

Risk Management with KOSDAQ50 Index Futures Markets

2003 ◽  
Vol 11 (2) ◽  
pp. 51-79
Author(s):  
Gyu Hyeon Mun ◽  
Jeong Hyo Hong
Keyword(s):  
Garch Model ◽  
Minimum Variance ◽  
Price Risk ◽  
Risk Minimization ◽  
Index Futures ◽  
Hedging Strategies ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Sample Data ◽  
Hedging Performance

This paper studies hedging strategies that use the KOSDAQ50 index futures to hedge the price risk of the KOSDAQ50 index spot portfolio. This study uses the minimum variance hedge model and bivariate ECT-GARCH (1,1) model as hedging models, and analyzes their hedging performances. The sample period covers from January 31, 2001 to December 31, 2002. The most important findings may be summarized as follows. First, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios of the risk-minimization tend to be higher than those of GARCH model. Second, for the in-sample data, hedging effectiveness of GARCH model is higher than that of the risk-minimization, while for the out-of-sample data, hedging effectiveness of the risk-minimization with constant hedge ratios is not far behind the GARCH model in its hedging performance. Third, the hedging performance of KOSDAQ50 index futures is lower than that of KOSPI200 index futures, but higher than that of KTB futures. In conclusion, in the KOSDAQ50 index market, investors are encouraged to use the simple risk-minimization model to hedge the price risk of KOSDAQ50 spot portfolios.

An empirical investigation of the GARCH option pricing model: Hedging performance

2003 ◽  
Vol 23 (12) ◽  
pp. 1191-1207 ◽  
Author(s):  
Haynes H. M. Yung ◽  
Hua Zhang
Keyword(s):  
Option Pricing ◽  
Empirical Investigation ◽  
Pricing Model ◽  
Option Pricing Model ◽  
Hedging Performance

Interest rate volatility, trading volume, and the hedging performance of T-bond and GNMA futures—A note

1985 ◽  
Vol 5 (2) ◽  
pp. 273-286 ◽  
Author(s):  
Shantaram P. Hegde ◽  
Kenneth P. Nunn
Keyword(s):  
Interest Rate ◽  
Trading Volume ◽  
Interest Rate Volatility ◽  
Hedging Performance

Do investor sentiment, weather and catastrophe effects improve hedging performance? Evidence from the Taiwan options market

2016 ◽  
Vol 37 ◽  
pp. 35-51 ◽  
Author(s):  
Chih-Yuan Yang ◽  
Ling-Jhen Jhang ◽  
Chia-Chien Chang
Keyword(s):  
Investor Sentiment ◽  
Options Market ◽  
Hedging Performance

A note on hedging performance and portfolio effects

1990 ◽  
Vol 10 (2) ◽  
pp. 201-204 ◽  
Author(s):  
Da-Hsiang Donald Lien
Keyword(s):  
Hedging Performance
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