scholarly journals An Empirical Analysis of Oil and Stock Markets’ Volatility Based on the DGC-MSV-t Model

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jing Zhang ◽  
Ya-Ming Zhuang ◽  
Jia-Bao Liu
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Crude Oil ◽  
Spillover Effect ◽  
Stochastic Volatility Model ◽  
Oil Price ◽  
Stock Index ◽  
Spot Prices ◽  
Volatility Model ◽  
Multivariate Stochastic Volatility

We investigate the spillover effect between crude oil future prices, crude oil spot prices, and stock index by using the multivariate stochastic volatility model. These tests between each market show the significant Granger causes of spillover effect. More and more evidences show that the crude oil price has been affected by other financial markets. The oil future played an important role in the energy market. WTI and Brent oil future have more spillover effect than INE oil future. The result shows that S&P stock market is more sensitive to the oil price than Shanghai stock market. The cross-market spillover effect we found can give some advices for the investor of oil and stock market. DIC test shows that DGC-MSV-t is considered effective and more accurate.

scholarly journals Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

2013 ◽  
Vol 45 (02) ◽  
pp. 545-571 ◽  
Author(s):  
F. E. Benth ◽  
L. Vos
Keyword(s):  
Stochastic Volatility ◽  
Simulation Method ◽  
Energy Markets ◽  
Stochastic Volatility Model ◽  
Spot Price ◽  
Leverage Effect ◽  
Order Structure ◽  
Spot Prices ◽  
Volatility Model ◽  
Multivariate Stochastic Volatility

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

scholarly journals Volatility Spillover Effect of International Crude Oil Futures and China-Russia Stock Market: A Multivariate BEKK-GARCH Model Based on Wavelet Multiresolution Analysis

2019 ◽  
Vol 11 (1) ◽  
pp. 183
Author(s):  
Maoguo Wu ◽  
Daimin Lu
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Explanatory Power ◽  
Composite Index ◽  
Spillover Effect ◽  
Stock Index ◽  
Oil Futures ◽  
Crude Oil Futures ◽  
Futures Price ◽  
Volatility Spillover Effect

The increasingly prominent strategic position of crude oil determines its high impact on macro-economy. The value of crude oil is reflected in the price of crude oil futures. Stock market is the barometer of macro economy. To what extent does international crude oil futures price affect stock market? China and Russia are the biggest importer and exporter of crude oil, respectively. Crude oil is of strategic value to both countries. This study empirically investigates the volatility spillover effect of international crude oil futures and China-Russia stock market from April 24th, 2015 to April 20th, 2018, based on the data of international crude oil futures prices, China-Russia stock market composite index, and industry stock index. The empirical results show that there is a short-term relationship between China-Russia stock market composite index and international crude oil futures price. The international crude oil futures price has a greater explanatory power to Russian RTS index, but a smaller explanatory power to Shanghai composite index. All industry stock indices are cointegrated with international crude oil futures prices. Except for China industry and Russia energy, the adjustment coefficient of international crude oil futures price on stock index volatility of other industries is insignificant. This study mainly studies the relationship between international crude oil futures price and the comprehensive stock index and industry stock index of China and Russia, and compares the impact of international crude oil futures price on the stock market of the largest importer and the largest exporter of crude oil to explore the linkage between crude oil futures price and stock market, and puts forward policy implications based on the empirical results.

scholarly journals Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

2013 ◽  
Vol 45 (2) ◽  
pp. 545-571 ◽  
Author(s):  
F. E. Benth ◽  
L. Vos
Keyword(s):  
Stochastic Volatility ◽  
Simulation Method ◽  
Energy Markets ◽  
Stochastic Volatility Model ◽  
Spot Price ◽  
Leverage Effect ◽  
Order Structure ◽  
Spot Prices ◽  
Volatility Model ◽  
Multivariate Stochastic Volatility

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

Analysis of Stock Volatility Clustering Using ANN

2015 ◽  
Vol 28 (2) ◽  
pp. 32-45 ◽  
Author(s):  
Manish Kumar ◽  
Santanu Das ◽  
Sneha Govil
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Model Building ◽  
Stochastic Volatility Model ◽  
Propagation Model ◽  
Stock Index ◽  
Support Vector ◽  
Stock Volatility ◽  
Volatility Model ◽  
Artificial Neural

The model building theories broadly categorize the stock index forecasting models into two broad categories: Based on statistical theory consisting models such as Stochastic Volatility model (SV) and General Autoregressive Conditional Heteroskedasticity (GARCH) whereas other one based on artificial intelligence based models, such as artificial neural network (ANN), the support vector machine (SVM) and technique used for optimization such as particle swarm optimization (PSO). In existing literature, many of the statistical models when compared with artificial neural network models were outperformed by these models. This paper analyses stock volatility using ANN models as Multilayer perceptron with back propagation model and Radial Basis function.

Thanks, neighbor! Stock market experience around significant European tax cuts

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huabing Wang ◽  
Anne Macy
Keyword(s):  
Stock Market ◽  
Spillover Effect ◽  
Abnormal Returns ◽  
The Other ◽  
Stock Index ◽  
Corporate Tax ◽  
Cross Sectional ◽  
Content Type ◽  
Study Approach ◽  
Tax Cuts

PurposeThis paper analyzes the effect of corporate tax cuts on the competitiveness of the tax-cutting countries and neighbor countries.Design/methodology/approachThis study utilizes four significant corporate tax reforms among the OECD countries in Europe that offer a one-time tax cut of 6% or more. The short-term event study approach examines the stock index reactions for both the tax-cutting countries and the other countries. Multivariate fixed-effect regressions are employed to study the cross-sectional variations in the non-tax-cut countries.FindingsThis paper finds positive excess returns for Slovakia and Germany around the tax-cut passage. Multivariate analysis of stock market reactions of the non-tax-cutting countries reveals some evidence supporting both the positive spillover effect and the negative competitive loss effect. More advanced countries are more likely to experience higher abnormal returns, while higher tax countries are more likely to suffer lower abnormal returns. Other factors identified that might have influenced the effect of a foreign tax cut include the existing trade flows with the tax-cutting countries, whether the country has a common currency and the export orientation of the economy.Research limitations/implicationsThe findings are subject to sample-size issues. The lack of results for the other two countries is due to complicating events, as suggested by the further investigation of concurrent news events around the event days.Practical implicationsThe simultaneous analysis of the reform countries and the other countries in the region suggests that policymakers need to consider the relative positioning of their country vs the other countries in terms of economic development and current tax burdens when determining the optimal policy for their country or to respond to the tax policy changes in the other countries.Originality/valueThis study offers empirical evidence regarding the effect of corporate tax changes on competitiveness through the lens of stock markets' reactions, which depend on the net results of the spillover gain vs the competitive loss.

scholarly journals The Nexus between Stock Returns of Oil Companies and Oil Price Fluctuations after Heavy Oil Upgrading: Toward Theoretical Progress

Economies ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 71 ◽  
Author(s):  
Sedighi ◽  
Mohammadi ◽  
Fard ◽  
Sedighi
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Returns ◽  
Petroleum Industry ◽  
Oil Industry ◽  
Oil Price ◽  
Investment Policies ◽  
Price Fluctuations ◽  
Oil Companies ◽  
Petroleum Companies

This study attempts to discover the nexus between crude oil price fluctuation after heavy oil upgrading and stock returns of petroleum companies in the U.S. Stock Exchange for the years 2008 to 2018. One of the methods of upgrading heavy crude oil is to extract asphaltene from crude oil. Considering the Asphaltene Removal (AR) as a factor in the nexus between oil price and the stock market is an innovation in the literature of energy finance. Asphaltenes cause many problems in the petroleum industry, which increases the cost of oil production and reduces the financial efficiency of oil companies. The AR is certainly one of the significant matters of the oil industry and can affect the price of oil. Therefore, changes in the price of oil can influence the price of oil company stocks. Hence, changes in stock prices will certainly affect the stock returns of oil companies. In an effort to solve this puzzle, the four financial models were employed to explore the nexus between oil price fluctuations and stock returns. The analysis of the results demonstrated that the oil price fluctuations caused by the removal of asphaltenes influence the stock returns of petroleum companies. Eventually, the theoretical hypothesis was confirmed by considering the USA as a case study. The outcomes of this investigation are a theoretical progression in areas related to the petroleum industry and the stock market that could lead to the adoption of new investment policies in the petroleum industry including investing in new procedures to manage and decrease the costs and time of the AR process, which would result in the advancement of petroleum companies. In fact, we have introduced a modern investment strategy in the oil industry aimed at reducing oil production costs, improving financial statements and increasing the stock returns of petroleum companies. Eventually, we will present new investment policies in the oil industry that can lead to economic growth and development of financial markets especially stock market, derivatives market, futures exchange, commodities exchange, as well as bond market.

The optimal thermal causal path analysis on the relationship between international crude oil price and stock market

Kybernetes ◽  
2018 ◽  
Vol 47 (6) ◽  
pp. 1242-1261 ◽  
Author(s):  
Can Zhong Yao ◽  
Peng Cheng Kuang ◽  
Ji Nan Lin
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Markets ◽  
Oil Prices ◽  
Oil Price ◽  
Chinese Stock Market ◽  
Crude Oil Price ◽  
Content Type ◽  
Crude Oil Prices ◽  
Causal Path

Purpose The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets. Design/methodology/approach The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method. Findings The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices. Originality/value China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

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