The role of long memory in hedging effectiveness

2008 ◽  
Vol 52 (6) ◽  
pp. 3075-3082 ◽  
Author(s):  
Jerry Coakley ◽  
Jian Dollery ◽  
Neil Kellard
Keyword(s):  
Long Memory ◽  
Hedging Effectiveness

scholarly journals HOW EFFECTIVE IS FUTURES AS AN INSTRUMENT OF HEDGING AGAINST PRICE RISK? -A STUDY BASED ON SPOT AND FUTURE PRICES OF GOLD

2016 ◽  
Vol 4 (9) ◽  
pp. 143-150
Author(s):  
Shafeeque Muhammad ◽  
Thomachan
Keyword(s):  
Spot Market ◽  
Futures Market ◽  
Price Risk ◽  
Time Varying ◽  
Risk Hedging ◽  
Hedging Effectiveness ◽  
Cash Market ◽  
Hedge Ratios ◽  
Opposite Position

This paper examines the role of commodity futures market as an instrument of hedging against price risk. Hedging is the practice of offsetting the price risk in a cash market by taking an opposite position in the futures market. By taking a position in the futures market, which is opposite to the position held in the spot market, the producer can offset the losses in the latter with the gains in the former. Both static and time varying hedge ratios have been calculated using VECM-MGARCH model. Variance of return from hedge portfolio has been found to be low. Further hedging effectiveness has been observed to be around 12%.

Volatility forecasts: the role of asymmetric and long-memory dynamics and regional evidence

2007 ◽  
Vol 17 (17) ◽  
pp. 1421-1430 ◽  
Author(s):  
Twm Evans ◽  
David G. McMillan
Keyword(s):  
Long Memory

Intraday return inefficiency and long memory in the volatilities of forex markets and the role of trading volume

2018 ◽  
Vol 506 ◽  
pp. 433-450 ◽  
Author(s):  
Syed Jawad Hussain Shahzad ◽  
Jose Areola Hernandez ◽  
Waqas Hanif ◽  
Ghulam Mujtaba Kayani
Keyword(s):  
Long Memory ◽  
Trading Volume

Incentive mechanisms and hedging effectiveness – an experimental study

2018 ◽  
Vol 8 (3) ◽  
pp. 332-352 ◽  
Author(s):  
Lu Zhang ◽  
Difang Wan ◽  
Wenhu Wang ◽  
Chen Shang ◽  
Fang Wan
Keyword(s):  
Behavioral Finance ◽  
Design Theory ◽  
Futures Market ◽  
Incentive Mechanisms ◽  
Content Type ◽  
Hedging Effectiveness ◽  
Exploratory Experiment ◽  
Long Term Impact ◽  
Brokerage Firms

PurposeThe purpose of this paper is to analyze the role of four different incentives in improving hedging effectiveness and propose an alternative regulatory mechanism for China’s futures market.Design/methodology/approachThe research method that this study uses is a laboratory experiment, and this study follows the basic norms of experimental research. In addition, this paper designs and conducts a game experiment between hedgers and futures brokerage firms (FBFs) under different incentive mechanisms.FindingsBy analyzing the experimental data, it is found that compared with other incentive mechanisms, hedgers’ willingness to hedge and FBFs’ regulatory intention are both significantly higher for the dynamic linkage updating mechanism, indicating that hedgers have a stronger willingness to follow their hedging plan, and FBFs are more responsible for their regulatory behaviors. Additionally, the dynamic linkage updating mechanism has a long-term impact on effective hedging in the futures market.Research limitations/implicationsThe findings suggest that the dynamic linkage updating mechanism is beneficial for effectively restricting both hedgers’ over-speculation and FBFs’ regulatory slack and improving the hedging efficiency of the futures market.Practical implicationsTo solve the problem of inefficient hedging in China’s futures market, i.e., hedgers’ over-speculation and FBFs’ passive collusion with hedgers, the regulators of China’s futures market should reform the existing incentives and adopt a dynamic linkage updating mechanism to encourage all the participants to actively improve hedging effectiveness.Originality/valueThis paper analyzes and verifies, for the first time, the role of the dynamic linkage updating mechanism in the investing behaviors of hedgers and the regulatory behaviors of future brokerage firms. The futures market experiment that was designed and used in this study is a pioneering and exploratory experiment that applies game theory and mechanism design theory to the field of behavioral finance.

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