Equity market implied volatility and energy prices: A double threshold GARCH approach

Cochran, Steven J.; Mansur, Iqbal; Odusami, Babatunde

doi:10.1016/j.eneco.2015.05.013

Cited by 8 publications

(4 citation statements)

References 26 publications

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“…In addition to the relationship between VIX and US stock market returns, Cochran et al (2015) use fuel oil, gasoline and natural gas futures prices returns data for 1999-2013, and find that natural gas futures returns and changes in VIX are positively correlated. However, changes in VIX are negatively correlated for heating oil and gasoline, suggesting that the returns on natural gas, contrary to the returns on the other two commodities, are more able to withstand volatility in stock markets.…”

Section: Vix Literature Reviewmentioning

confidence: 98%

“…Previous studies have suggested that, although VIX is not necessarily able to predict accurately the returns variability, the information it provides serves as a valuable reference to investors, so that cannot be ignored when examining the risk-return relationship. Cochran et al (2015) noted that the impact of VIX can be felt not only in the stock market, but also in returns in spot commodity and futures markets.…”

Section: Implied Volatilitymentioning

confidence: 99%

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Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK

Chang

Hsieh

McAleer

2018

JRFM

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As stock market indexes are not tradeable, the importance and trading volume of Exchange-Traded Funds (ETFs) cannot be understated. ETFs track and attempt to replicate the performance of a specific index. Numerous studies have demonstrated a strong relationship between the S&P500 Composite Index and the Volatility Index (VIX), but few empirical studies have focused on the relationship between VIX and ETF returns. The purpose of the paper is to investigate whether VIX returns affect ETF returns by using vector autoregressive (VAR) models to determine whether daily VIX returns with different moving average processes affect ETF returns. The ARCH-LM test shows conditional heteroskedasticity in the estimation of ETF returns, so that the Diagonal BEKK (named after Baba, Engle, Kraft and Kroner) model is used to accommodate multivariate conditional heteroskedasticity in the VAR estimates of ETF returns. Daily data on ETF returns that follow different stock indexes in the USA and Europe are used in the empirical analysis, which is presented for the full data set, as well as for the three sub-periods Before, During, and After the Global Financial Crisis. The estimates show that daily VIX returns have: (1) significant negative effects on European ETF returns in the short run; (2) stronger significant effects on single-market ETF returns than on European ETF returns; and (3) lower impacts on the European ETF returns than on S&P500 returns. For the European markets, the estimates of the mean equations tend to differ between the whole sample period and the sub-periods, but the estimates of the matrices A and B in the Diagonal BEKK model are quite similar for the whole sample period and at least two of the three sub-periods. For the US Markets, the estimates of the mean equations also tend to differ between the whole sample period and the sub-periods, but the estimates of the matrices A and B in the Diagonal BEKK model are very similar for the whole sample period and the three sub-periods.

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Section: Vix Literature Reviewmentioning

confidence: 98%

Section: Implied Volatilitymentioning

confidence: 99%

Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK

Chang

Hsieh

McAleer

2018

JRFM

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“…More specifically, the VIX is calculated by looking at the midpoints of the real-time S&P 500 option bid and ask prices. Cochran et al (2015) studied equity market implied volatility and energy prices, they found that natural gas can withstand considerably more variation in the VIX index as compared to other energy products. For energy portfolio investment, the impact of uncertainties on energy prices is studied by VIX Index, results suggest that negative dependence exists between uncertainty changes and energy returns (Ji, et al, 2018).…”

Section: Volatility Index Vixmentioning

confidence: 99%

The Impact of Financial, Economic and Environmental Factors on Energy Efficiency, Intensity, and Dependence: The Moderating Role of Governance and Institutional Quality

Ijaz

Chughtai

2022

IJEEP

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Economies are under serious pressure to sustain themselves due to globalization, focusing simply on economic growth and operational efficiency will not yield the desired sustainable financial and economic position for economies. Management of energy efficiency and reducing the energy dependence and intensity is the core objective for the economy and achievement of the above objective financial, economic, and environmental factors need to be studied. Economic wellbeing critically depends on the efficient use of energy and which type of governance mechanism is in place will also define the ways toward energy efficiency. A better understanding of the relationship will help the economies to fulfill their energy needs efficiently, realize developmental goals, and overcome environmental issues. This study examines the relationship between financial, economic, and environmental factors with energy efficiency, intensity, and dependency with moderating role of governance including institutional quality and governance index for belt and road initiative countries. The core objective of the study is to analyze which financial, economic, and environmental factors serve well in the management of energy efficiency, intensity, and dependence issues and how various dynamics of governance policies including market structure moderate the above-mentioned relationship. For this secondary data is used from world development indicators, market insiders, and Chicago Board Options Exchange (CBOE) data. This research will help the researchers and practitioners to achieve long-term economic, financial, and environmental sustainability. The proposed model predicts that 0.44% change in Total Factor Energy Productivity measure of Energy Efficiency, 0.03% changes in Energy use/Purchasing Power Parity ratio measure of Energy Intensity, and 9.63% changes in Energy Reserves/Energy Production ratio measure of Energy Dependence. Results also reveal that environmental factors including Rural population, Urbanization, Co2 emission, energy use, and energy production will contribute most to achieving sustainable economic growth.

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“…In recent times, for speculative and investment purposes, funds have increased interest in energy commodities, i.e., oil and natural gas. Due to the commoditization of energy markets, Cochran et al [47] argue of the "volatility-generating processes and, in particular, the extent to which these processes are influenced by equity market volatility." In the aftermath of the economic crisis, the European Commission has strengthened the financial regulation on energy trade, with the aim of steadying the financial markets and constraining the volatility in energy price.…”

Section: Public Energy-efficiency Gapmentioning

confidence: 99%

Financing the (Environmental) Quality of Cities with Energy Efficiency Investments

Caneparo

2020

Sustainability

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The purpose of the paper is to study the financing models in order to drive the large amount of financial resources, already allocated for energy efficiency, to improve the quality of cities. These resources are being deployed worldwide by both public and private financial institutions. Energy efficiency is usually managed at the scale of the buildings, i.e., consumption reduction (heating, lighting, etc.). The study methodology is to review energy-efficiency finance (EEF) models, and assess them using multiple case studies. At the same time, the ownership of cities’ spaces is studied across public-private space management, as an effective methodology to bridge the gap between public and investor finance. The comparative analysis of the case studies suggests a paradigm shift in the definition of energy efficiency, not just in terms of the buildings, but instead also the local urban environment with its feedbacks on the quality of urban living. The practical implications are innovative EEF models, such as those being reviewed, which may be: (1) analytical, to assess the environment at the scale of blocks or neighbourhoods; (2) financial, to fund the specific scale; (3) relating to policy, to support and encourage. In recent years, support for urban regeneration is becoming particularly relevant, given the budget constraints of most public administrations and the conjunctural shortening of private partnerships.

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Equity market implied volatility and energy prices: A double threshold GARCH approach

Cited by 8 publications

References 26 publications

Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK

Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK

The Impact of Financial, Economic and Environmental Factors on Energy Efficiency, Intensity, and Dependence: The Moderating Role of Governance and Institutional Quality

Financing the (Environmental) Quality of Cities with Energy Efficiency Investments

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