scholarly journals Cross-Hedging Portfolios in Emerging Stock Markets: Evidence for the LATIBEX Index

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2736
Author(s):  
Pablo Urtubia ◽  
Alfonso Novales ◽  
Andrés Mora-Valencia
Keyword(s):  
Latin American ◽  
International Market ◽  
Futures Market ◽  
Alternative Possibilities ◽  
Futures Contracts ◽  
Garch Models ◽  
Conditional Moments ◽  
Emerging Stock Markets ◽  
Asymmetric Garch ◽  
Cross Hedging

We consider alternative possibilities for hedging spot positions on the FTSE LATIBEX Index, the index of the only international market exclusively for Latin American firms that is denominated by the euro. Since there is not a futures market on the index, it is unclear whether a relatively successful hedge can be found. We explore the plausibility of employing futures on four stock market indices: EUROSTOXX 50, S&P500, BOVESPA, and IPC, and simulate the results that could be obtained by a hedge position based on either unconditional or conditional second order moments estimated from different asymmetric GARCH models. Several criteria for hedging effectiveness suggest that futures contracts on BOVESPA should be preferred, and that a salient reduction in risk can be achieved over the unhedged LATIBEX portfolio. The evidence in favor of a better performance of conditional moments is very clear, without significant differences among the alternative GARCH specifications.

scholarly journals Forecasting Volatility of Energy Commodities: Comparison of GARCH Models with Support Vector Regression

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 6
Author(s):  
Marcin Fałdziński ◽  
Piotr Fiszeder ◽  
Witold Orzeszko
Keyword(s):  
Support Vector Regression ◽  
Absolute Error ◽  
Futures Contracts ◽  
Support Vector ◽  
Garch Models ◽  
Forecasting Performance ◽  
Asymmetric Garch ◽  
Heating Oil ◽  
Forecasting Volatility ◽  
Forecasting Errors

We compare the forecasting performance of the generalized autoregressive conditional heteroscedasticity (GARCH) -type models with support vector regression (SVR) for futures contracts of selected energy commodities: Crude oil, natural gas, heating oil, gasoil and gasoline. The GARCH models are commonly used in volatility analysis, while SVR is one of machine learning methods, which have gained attention and interest in recent years. We show that the accuracy of volatility forecasts depends substantially on the applied proxy of volatility. Our study confirms that SVR with properly determined hyperparameters can lead to lower forecasting errors than the GARCH models when the squared daily return is used as the proxy of volatility in an evaluation. Meanwhile, if we apply the Parkinson estimator which is a more accurate approximation of volatility, the results usually favor the GARCH models. Moreover, it is difficult to choose the best model among the GARCH models for all analyzed commodities, however, forecasts based on the asymmetric GARCH models are often the most accurate. While, in the class of the SVR models, the results indicate the forecasting superiority of the SVR model with the linear kernel and 15 lags, which has the lowest mean square error (MSE) and mean absolute error (MAE) among the SVR models in 92% cases.

EFFECTIVE CROSS HEDGING: EVIDENCE FROM PHYSICAL CRUDE PALM OIL AND ITS INTER-RELATED AGRICULTURAL FUTURES CONTRACTS

2018 ◽  
Vol 17 (2) ◽  
pp. 123
Author(s):  
Noryati Ahmad ◽  
Ahmad Danial Zainudin ◽  
Fahmi Abdul Rahim ◽  
Catherine S F Ho
Keyword(s):  
Palm Oil ◽  
Futures Contracts ◽  
Crude Palm Oil ◽  
Oil Futures ◽  
Futures Contract ◽  
Agricultural Futures ◽  
Cross Hedging ◽  
Optimal Hedge ◽  
Excessive Speculation ◽  
Chicago Board Of Trade

Since its establishment, Crude Palm Oil futures contract (FCPO) has been used to directly hedge its physical crude palm oil (CPO). However, due to the excessive speculation activities on crude palm oil futures market, it has been said to be no longer an effective hedging tool to mitigate the price risk of its underlying physical market. This triggers the need for market players to find possible alternatives to ensure that the hedging role can be executed effectively. Thus this investigation attempts to examine whether other inter-related grains and oil seed futures contracts could serve as effective cross-hedging mechanisms for the CPO. Weekly data of inter-related futures contracts from Chicago Board of Trade (CBOT) and Dalian Commodity Exchange (DCE) are employed to cross hedge the physical crude palm oil prices. The study starts from 2006 until 2016. Empirical results indicate that FCPO is still the best futures contract for hedging purposes while Chicago Soybean (CBOTBO) provides second best alternative if cross-hedging is considered. Keywords: Crude palm oil, Crude palm oil futures, Cross Hedging, Optimal Hedge Ratio, Effective Hedging

Learning for infinitely divisible GARCH models in option pricing

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Fumin Zhu ◽  
Michele Leonardo Bianchi ◽  
Young Shin Kim ◽  
Frank J. Fabozzi ◽  
Hengyu Wu
Keyword(s):  
Option Pricing ◽  
Stock Returns ◽  
Bayesian Learning ◽  
Space Structure ◽  
Estimation Methods ◽  
Garch Models ◽  
Learning Approaches ◽  
Infinitely Divisible ◽  
Asymmetric Garch ◽  
Non Gaussian

AbstractThis paper studies the option valuation problem of non-Gaussian and asymmetric GARCH models from a state-space structure perspective. Assuming innovations following an infinitely divisible distribution, we apply different estimation methods including filtering and learning approaches. We then investigate the performance in pricing S&P 500 index short-term options after obtaining a proper change of measure. We find that the sequential Bayesian learning approach (SBLA) significantly and robustly decreases the option pricing errors. Our theoretical and empirical findings also suggest that, when stock returns are non-Gaussian distributed, their innovations under the risk-neutral measure may present more non-normality, exhibit higher volatility, and have a stronger leverage effect than under the physical measure.

Re-Examining the Nifty Returns after the First Decade of Derivative Trading in Indian Capital Market Using Non-Linear Asymmetric GARCH Models

2012 ◽  
Vol 3 (4) ◽  
pp. 29-52 ◽  
Author(s):  
Sunita Narang
Keyword(s):  
Capital Market ◽  
Garch Models ◽  
Conditional Heteroskedasticity ◽  
Indian Market ◽  
Total Period ◽  
Dummy Variable ◽  
Asymmetric Garch ◽  
Indian Stock Market ◽  
Surrogate Index ◽  
The Impact

This article examines the Indian stock market for conditional volatility using symmetric and asymmetric GARCH (Generalized Autoregressive Conditional Heteroskedasticity) variants with reference to a comprehensive period of 20 years from July 3, 1990 to November 30, 2010 using S&P CNX Nifty. The impact of future trading on Nifty return and volatility is assessed using dummy variable in total period and using Log (Open Interest of Nifty futures) in post-derivative period. Along with the period of two decades the analysis has also been done on a sub-period of a decade from 1995 to 2005 with NiftyJunior as surrogate index as it had no derivatives during this period. The results show that the PGARCH model is best suited to Indian market conditions.

scholarly journals Holiday effects in the South African futures market

1998 ◽  
Vol 29 (3) ◽  
pp. 119-133 ◽  
Author(s):  
C. F. Smit ◽  
E. V.D.M. Smit
Keyword(s):  
South African ◽  
Futures Market ◽  
Weekend Effect ◽  
Futures Contracts ◽  
The South ◽  
Futures Contract ◽  
Holiday Effect ◽  
Holiday Effects ◽  
Daily Returns ◽  
Local Research

International and local research in share markets offered evidence of a holiday effect. Pre-holiday mean returns are significantly higher than on other trading days. The holiday effect cannot be separated from the weekend effect, as holidays which fall on Fridays and Mondays also influence the weekend analysis. Both these effects exist in their own right. Research on international futures markets supports the existence of a holiday effect. The present study investigates the holiday effect on daily returns of the All Gold Near Futures contract, the All Industrial Near Futures contract and the All Share Near Futures contract in the South African futures market. A distinction is made between pre-holidays, post-holidays and non-holidays. None of the near futures contracts exhibit a significant holiday effect, although signs of a holiday effect are present. It is further shown that the month-end effect is not strongly influenced by the holiday effect. It is also concluded that the pre-holiday effects are not large enough to be exploited on an on-going basis in the South African futures market.

Clustering in the futures market: Evidence from S&P 500 futures contracts

2004 ◽  
Vol 24 (5) ◽  
pp. 413-428 ◽  
Author(s):  
Adam L. Schwartz ◽  
Bonnie F. Van Ness ◽  
Robert A. Van Ness
Keyword(s):  
Futures Market ◽  
Futures Contracts
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