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.

Hedging Strategies with the KTB Futures

2002 ◽  
Vol 10 (2) ◽  
pp. 25-56
Author(s):  
Jae Ha Lee ◽  
Han Deog Hui
Keyword(s):  
Garch Model ◽  
Corporate Bond ◽  
Price Sensitivity ◽  
Risk Minimization ◽  
Hedging Strategies ◽  
Daily Data ◽  
Bond Portfolio ◽  
Hedge Ratios ◽  
Out Of Sample ◽  
The Garch Model

This study explores hedging strategies that use the KTB futures to hedge the price risk of the KTB spot portfolio. The study establishes the price sensitivity, risk-minimization, bivariate GARCH (1,1) models as hedging models, and analyzes their hedging performances. The sample period covers from September 29, 1999 to September 18, 2001. Time-matched prices at 11:00 (11:30) of the KTB futures and spot were used in the analysis. The most important findings may be summarized as follows. First, while the average hedge ration of the price sensitivity model is close to one, both the risk-minimization and GARCH model exhibit hedge ratios that are substantially lower than one. Hedge ratios tend to be greater for daily data than for weekly data. Second, for the daily in-sample data, hedging effectiveness is the highest for the GARCH model with time-varying hedge ratios, but the risk-minimization model with constant hedge ratios is not far behind the GARCH model in its hedging performance. In the case of out-of-sample hedging effectiveness, the GARCH model is the best for the KTB spot portfolio, and the risk-minimization model is the best for the corporate bond portfolio. Third, for daily data, the in-sample hedge shows a better performance than the out-of-sample hedge, except for the risk-minimization hedge against the corporate bond portfolio. Fourth, for the weekly in-sample hedges, the price sensitivity model is the worst and the risk-minimization model is the best in hedging the KTB spot portfolio. While the GARCH model is the best against the KTB +corporate bond portfolio, the risk-minimization model is generally as good as the GARCH model. The risk-minimization model performs the best for the weekly out-of-sample data, and the out-of-sample hedges are better than the in-sample hedges. Fifth, while the hedging performance of the risk-minimization model with daily moving window seems somewhat superior to the traditional risk-minimization model when the trading volume increased one year after the inception of the KTB futures, on the average the traditional model is better than the moving-window model. For weekly data, the traditional model exhibits a better performance. Overall, in the Korean bond markets, investors are encouraged to use the simple risk-minimization model to hedge the price risk of the KTB spot and corporate bond portfolios.

HEDGING EFFECTIVENESS OF CROSS-LISTED NIFTY INDEX FUTURES

2019 ◽  
Vol 19 (02) ◽  
pp. 1950011
Author(s):  
K. KIRAN KUMAR ◽  
SHREYA BOSE
Keyword(s):  
Variance Reduction ◽  
Stock Exchange ◽  
Conditional Correlation ◽  
Index Futures ◽  
Hedging Strategies ◽  
Hedging Effectiveness ◽  
Maximum Variance ◽  
Daily Data ◽  
Hedge Ratios ◽  
Autoregressive Conditional Heteroscedasticity

This paper investigates the hedging effectiveness of cross-listed Nifty Index futures and compares the performance of constant and dynamic optimal hedging strategies. We use daily data of Nifty index traded on the National Stock Exchange (NSE), India and cross-listed Nifty futures traded on the Singapore Stock Exchange (SGX) for a period of six years from July 15, 2010 to July 15, 2016. Various competing forms of Multivariate Generalised Autoregressive Conditional Heteroscedasticity (MGARCH) models, such as Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC), have been employed to capture the time-varying volatility. The results clearly depict that dynamic hedge ratios outperform traditional constant hedge ratios with the DCC–GARCH model being the most efficient with maximum variance reduction from the unhedged portfolio.

Examining the Hedging Effectiveness of Futures Contracts over Pre and Post Financial Crisis Period: Evidence from National Stock Exchange of India

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Kapil Gupta ◽  
Mandeep Kaur
Keyword(s):  
Financial Crisis ◽  
Stock Exchange ◽  
Futures Contracts ◽  
Price Risk ◽  
Hedge Ratio ◽  
Crisis Period ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Time Invariant

Present study examines the efficiency of futures contracts in hedging unwanted price risk over highly volatile period i.e. June 2000 - December 2007 and January 2008 – June 2014, pre and post-financial crisis period, by using S&PC NXNIFTY, CNXIT and BANKNIFTY for near month futures contracts. The hedge ratios have been estimated by using five methods namely Ederingtons Model, ARMA-OLS, GARCH (p,q), EGARCH (p,q) and TGARCH (p,q). The study finds that hedging effectiveness increased during post crisis period for S&PC NXNIFTY and BANKNIFTY. However, for CNXIT hedging effectiveness was better during pre-crisis period than post crisis. The study also finds that time-invariant hedge ratio is more efficient than time-variant hedge ratio.

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%.

scholarly journals Hedging effectiveness for international index futures markets

2018 ◽  
Vol 32 (1) ◽  
pp. 149-159
Author(s):  
Alexandros Koulis ◽  
George Kaimakamis ◽  
Christina Beneki
Keyword(s):  
Futures Markets ◽  
Futures Contracts ◽  
Index Futures ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
The Usa ◽  
Conventional Models ◽  
Market Indexes

Abstract This paper investigates the hedging effectiveness of the International Index Futures Markets using daily settlement prices for the period 4 January 2010 to 31 December 2015. Standard OLS regressions, Error Correction Model (ECM), as well as Autoregressive Distributed Lag (ARDL) cointegration model are employed to estimate corresponding hedge ratios that can be employed in risk management. The analyzed sample consists of daily closing market rates of the stock market indexes of the USA and the European futures contracts. The findings indicate that the time varying hedge ratios, if estimated through the ARDL model, are more efficient than the fixed hedge ratios in terms of minimizing the risk. Additionally, there is evidence that the comparative advantage of advanced econometric approaches compared to conventional models is enhanced further for capital markets within peripheral EU countries

Do higher order moments of return distribution provide better decisions in minimum-variance hedging? Evidence from US stock index futures

2019 ◽  
Vol 45 (2) ◽  
pp. 240-265
Author(s):  
Yang (Greg) Hou ◽  
Mark Holmes
Keyword(s):  
Minimum Variance ◽  
Jel Classification ◽  
Higher Order ◽  
Stock Index ◽  
Stock Index Futures ◽  
Return Distribution ◽  
Higher Order Moments ◽  
Index Futures ◽  
Hedging Strategies ◽  
Skewness And Kurtosis

Using daily S&P 500 spot index and index futures data, this article examines the effects of conditional skewness and kurtosis parameters of a skew-Student density function on dynamic minimum-variance hedging strategies. We find an important role for autoregressive marginal skewness and joint kurtosis in risk management. While static higher order moments improve reductions in variance of hedged portfolios over the case of normality, the inclusion of an autoregressive component significantly extends these improvements. This occurs in both tranquil and tumultuous periods. Furthermore, when transaction costs are considered, taking into account variations of higher order moments retains the best performance. JEL Classification: G11, G13

scholarly journals Optimal Hedging Strategies for Natural Gas

2020 ◽  
Vol 12 (8) ◽  
pp. 1
Author(s):  
Changfeng Zhou ◽  
Huan Cai
Keyword(s):  
Natural Gas ◽  
Crude Oil ◽  
Financial Risk ◽  
Natural Gas Market ◽  
Hedging Strategies ◽  
Hedging Effectiveness ◽  
Hedge Ratios ◽  
Asset Portfolio ◽  
Gas Market ◽  
Optimal Hedge

This study examines the optimal hedge performance between natural gas market and crude oil, ECO, gold and US-bonds markets. To calculate optimal hedge ratios and hedging effectiveness, we apply several multivariate volatility models, namely CCC, DCC, cDCC and bayesDCC. The empirical results show that crude oil is the best asset to hedge natural gas followed by gold and ECO. This is a new result relative to the existing literature on natural gas prices. Additionally, we find that the bayesDCC model has the best performance on optimal hedge ratios (OHRs) calculation in terms of hedging effectiveness. Our findings will hold important financial risk management implications and asset portfolio for those invest in natural gas market.

Hedging and Optimal Hedge Ratios for International Index Futures Markets

2009 ◽  
Vol 12 (04) ◽  
pp. 593-610 ◽  
Author(s):  
Cheng-Few Lee ◽  
Kehluh Wang ◽  
Yan Long Chen
Keyword(s):  
Futures Markets ◽  
Minimum Variance ◽  
Stock Index ◽  
Stock Index Futures ◽  
Hedge Ratio ◽  
Index Futures ◽  
Static Hedging ◽  
Hedge Ratios ◽  
Optimal Hedge ◽  
Mean Variance

This empirical study utilizes four static hedging models (OLS Minimum Variance Hedge Ratio, Mean-Variance Hedge Ratio, Sharpe Hedge Ratio, and MEG Hedge Ratio) and one dynamic hedging model (bivariate GARCH Minimum Variance Hedge Ratio) to find the optimal hedge ratios for Taiwan Stock Index Futures, S&P 500 Stock Index Futures, Nikkei 225 Stock Index Futures, Hang Seng Index Futures, Singapore Straits Times Index Futures, and Korean KOSPI 200 Index Futures. The effectiveness of these ratios is also evaluated. The results indicate that the methods of conducting optimal hedging in different markets are not identical. However, the empirical results confirm that stock index futures are effective direct hedging instruments, regardless of hedging schemes or hedging horizons.

scholarly journals Research on the Hedge Ratio of China's Crude Oil Futures — Based on DCC-GARCH Model

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Hao Du
Keyword(s):  
Crude Oil ◽  
Variance Reduction ◽  
Garch Model ◽  
Leverage Effect ◽  
Risk Minimization ◽  
Oil Futures ◽  
Hedge Ratio ◽  
Hedge Ratios ◽  
Crude Oil Futures ◽  
Research Objects

Crude oil plays an important role in economic development. This paper chooses China’s crude oil futures and crude oil actuals as the research objects, and builds the DCC-GARCH model to study the hedge ratio under the risk minimization standard. The hedge ratios obtained from the DCC-GARCH model will be compared with those obtained from OLS, B-VAR and VECM models. The empirical results prove that: China’s crude oil futures and actuals have a significant reverse “leverage effect”; China’s crude oil futures have a variance reduction of more than 70% under all models; the DCC-GARCH model achieves the best hedging performance in the four models.

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