scholarly journals On the Optimal Dynamic Hedging with Nonferrous Metals

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Eric Martial Etoundi Atenga
Keyword(s):  
Nonferrous Metals ◽  
Multivariate Garch ◽  
Metal Exchange ◽  
London Metal Exchange ◽  
Volatility Spillovers ◽  
Lead Zinc ◽  
Optimal Dynamic ◽  
Multivariate Garch Models ◽  
Copper Aluminum

This paper employs multivariate GARCH to model conditional correlations and to examine volatility spillovers and hedging possibilities with nonferrous metals traded on the London Metal Exchange (LME) market. Three different multivariate GARCH models (diagonal, CCC and DCC) are employed and contrasted. The nonferrous metals studied are copper, aluminum, tin, lead, zinc and nickel and span the period from January 6, 2000 to February 29, 2016. The multivariate DCC GARCH framework is found to fit the data in an appropriate design and provides results showing the strongest evidence of long-term persistence volatility spillovers between lead and aluminum. We also find that the Hurst exponents given by the R/S method are on average 0.94, indicating the existence of a strong degree of long-range dependence in conditional volatilities. On average, the cheapest hedge is a long position in lead and a short position in nickel. The most expensive hedge is long nickel and short copper.

scholarly journals Empirical Analysis of “Volatilitysurprise” between Dollar Exchange Rate and CRB Commodity Future Markets

2016 ◽  
Vol 8 (9) ◽  
pp. 117
Author(s):  
Ching-Chun Wei
Keyword(s):  
Exchange Rate ◽  
Multivariate Garch ◽  
Garch Models ◽  
Suitable Model ◽  
Dollar Exchange Rate ◽  
Short And Long Term ◽  
Multivariate Garch Models ◽  
Commodity Future ◽  
Equity Index

This paper used the five multivariate GARCH models (including BEKK, CCC, DCC, VARMA-CCC and VARMA-DCC) to analyze the mean and volatility interaction of volatility surprise between US dollar exchange and CRB future index (including agricultural, energy, commodity and precious metal equity index). The empirical findings exhibit that significant own short and long-term persistence effects and the cross-markets volatility surprise spillover short and long-term persistence effects between dollar exchange rate and CRB commodity future equity index markets in five multivariate GARCH models. Besides that, the residual diagnostic test indicated that VARMA-DCC models is the best suitable model to modeling the dollar exchange rate with CRB commodity equity index.

Tech advances will bolster long-term copper demand

2019 ◽  
Keyword(s):  
Environmental Protection ◽  
Environmental Protection Agency ◽  
Copper Price ◽  
Metal Exchange ◽  
London Metal Exchange ◽  
Protection Agency ◽  
Content Type ◽  
Copper Producer ◽  
The Us

Subject The copper market. Significance The copper price has picked up by nearly 9% this year after weakening unexpectedly through 2018, losing 17.5%. Unusually, the slide was accompanied by metal inventories dropping steadily on the London Metal Exchange, Comex and Shanghai Metals Exchange. Stocks peaked at 900 kilotonnes (kt) in March 2018 before plummeting by 65% to start the year at the lowest since 2014. This rare combination of falling inventories and weakening prices has yet to find a viable explanation. Impacts Zambian import duties on concentrate has prompted 366 kt of capacity to be shutdown, reducing supply on the market. Boosting the outlook for US output, the US Environmental Protection Agency has approved Hudbay’s 112-kt-per-year Rosemont mine in Arizona. Chilean miner Codelco is spending 4.9 billion dollars to mine underground at Chuquicamata, aiming to extend operations by 40 years. Indonesia, the ninth largest copper producer, is to redirect output towards local smelters; it has cut annual export quotas by 25-75%.

scholarly journals Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models

2020 ◽  
Vol 5 (1) ◽  
pp. 123-133
Author(s):  
Hongjun Zeng
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
Volatility Spillovers ◽  
Stock Market Return ◽  
Monthly Return ◽  
Multivariate Garch Models ◽  
Linkage Effects

This article examines the linkage and volatility spillover among Chinese Stock Market Monthly Return and Investor Sentiment, investigating the effect dynamic links of various investor sentiment indicators and Chinese stock market return volatility. Employing the DCC and BEKK GARCH, we find investor sentiment is to some extent linked to the yield fluctuations of the Chinese stock market, but the volatility spillover is relatively weak. In the test period (2005-2020), we observe that several indicators do not explain their linkage effects with CSI 300 index of return fluctuations and volatility spillovers well, with no indicators can reflect both of these effects. Most indicators are linkage with the CSI 300 index, especially consumer confidence index (CCI), new investor account openings last month (NIA) and the volume of transactions last month (TURN) have significant linkage effects with the CSI 300 index. We also find that only the CCI index has a one-way volatility spillover on the CSI 300 index, and the CSI 300 index has no volatility spillover on any indicator.

scholarly journals Testing the conditional correlations and volatility spillovers between US and ASEAN Islamic stock markets: A Multivariate GARCH Analysis

2015 ◽  
Vol 2 (1) ◽  
pp. 029
Author(s):  
Muhammad Rizky Prima Sakti
Keyword(s):  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Time Varying ◽  
Foreign Investors ◽  
Volatility Spillovers ◽  
The Us ◽  
Conditional Correlations ◽  
Multivariate Garch Models ◽  
Empirical Design

This study examines the conditional correlations and volatility spillovers between the US and ASEAN Islamic stock markets. The empirical design uses MSCI (Morgan Stanley Capital International) Islamic indexes as it adopted stringent restriction to include companies in sharia list. By using a three multivariate GARCH models (BEKK, diagonal VECH, and CCC model), we find evidence of returns and volatility spillovers from the US to the ASEAN Islamic stock markets. However, as the estimated time-varying conditional correlations and volatilities indicate there is still a room for diversification benefits, particularly in the single markets. The Islamic MSCI of Thailand, Indonesia, and Singapore are less correlate to the US MSCI Islamic index. The implication is that foreign investors may benefit from the reduction of risk by adding the Islamic stocks in those countries.

scholarly journals Modeling Mediterranean Stock Markets Volatility with Univariate and Multivariate Approaches

2021 ◽  
Vol 16 ◽  
pp. 457-468
Author(s):  
Saoussan Bouchareb ◽  
Mohamed Salah Chiadmi ◽  
Fouzia Ghaiti
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Stock Markets ◽  
Multivariate Garch ◽  
Garch Models ◽  
Volatility Spillovers ◽  
Daily Data ◽  
Multivariate Approaches ◽  
Multivariate Garch Models

In our study we use the univariate and multivariate GARCH models to analyze the volatility behavior of the daily data of four Mediterranean stock markets (Morocco, Turkey, Spain, and France) spanning the period 2000-2020. We find a strong evidence of persisting of volatility in each of these markets. Results also indicate that both the univariate and the multivariate approaches capture well the ARCH and GARCH effects. We analyze the conditional covariances, and co-volatility spillovers between the Moroccan stock market and the three other Mediterranean stock markets. In order to study co-volatility spillovers, our work is built on the diagonal BEKK model especially the conditional covariances.

scholarly journals Um Estudo Empírico da Dinâmica da Correlação do Retorno das Ações do Brasil

2019 ◽  
Vol 16 (4) ◽  
pp. 635 ◽  
Author(s):  
Hudson Chaves Costa ◽  
Sabino Da Silva Porto Junior ◽  
Gabrielito Menezes
Keyword(s):  
Structural Breaks ◽  
Statistical Tests ◽  
Multivariate Garch ◽  
Garch Models ◽  
Conditional Correlation ◽  
Temporal Series ◽  
Largest Eigenvalues ◽  
Multivariate Garch Models ◽  
Long Term Trend

This article examines empirically the behavior of the correlation between the return of shares listed on the BMF& BOVESPA over the period from 2000 to 2015. To this end, we use multivariate GARCH models introduced by Bollerslev (1990) to remove the temporal series of arrays of conditional correlation of returns of stocks. With the temporal series of the largest eigenvalues of matrices of correlation estimated conditional, we apply statistical tests (unit root, structural breaks and trend) to verify the existence of stochastic trend or deterministic to the intensity of the correlation between the returns of the shares represented by eigenvalues. Our results confirm that both in times of crises at national and international turbulence, there is greater correlation between the actions. However, we did not find any long-term trend in time series of the largest eigenvalues of matrices of correlation conditional.

scholarly journals Analysis of the factors influencing the price of aluminum on the world market

Mechanik ◽  
2017 ◽  
Vol 90 (7) ◽  
pp. 565-567
Author(s):  
Agata Wzorek ◽  
Oleksandr Ivashchuk ◽  
Łukasz Wzorek
Keyword(s):  
World Market ◽  
Metal Exchange ◽  
London Metal Exchange ◽  
Factors Influencing ◽  
World Markets ◽  
The World ◽  
Short And Long Term

The article analyzes world prices on the aluminum market in the 20th and 21st centuries, with particular attention to the last five years. The factors influencing the price of this metal have been identified, as well as the factors that influence the short and long term aluminum price forecasts in the world markets, including the London Metal Exchange.

Volatility Modelling of Chinese Stock Market Monthly Return and Investor Sentiment Using Multivariate GARCH Models

2020 ◽  
Vol 5 (1) ◽  
pp. 123-133
Author(s):  
Hongjun Zeng
Keyword(s):  
Stock Market ◽  
Investor Sentiment ◽  
Multivariate Garch ◽  
Volatility Spillover ◽  
Chinese Stock Market ◽  
Volatility Spillovers ◽  
Stock Market Return ◽  
Monthly Return ◽  
Multivariate Garch Models ◽  
Linkage Effects

This article examines the linkage and volatility spillover among Chinese Stock Market Monthly Return and Investor Sentiment, investigating the effect dynamic links of various investor sentiment indicators and Chinese stock market return volatility. Employing the DCC and BEKK GARCH, we find investor sentiment is to some extent linked to the yield fluctuations of the Chinese stock market, but the volatility spillover is relatively weak. In the test period (2005-2020), we observe that several indicators do not explain their linkage effects with CSI 300 index of return fluctuations and volatility spillovers well, with no indicators can reflect both of these effects. Most indicators are linkage with the CSI 300 index, especially consumer confidence index (CCI), new investor account openings last month (NIA) and the volume of transactions last month (TURN) have significant linkage effects with the CSI 300 index. We also find that only the CCI index has a one-way volatility spillover on the CSI 300 index, and the CSI 300 index has no volatility spillover on any indicator.

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