Uncovering risk transmission between socially responsible investments, alternative energy investments and the implied volatility of major commodities

Shahid, Muhammad Naeem; Azmi, Wajahat; Ali, Mohsin; Islam, ‪Muhammad Umar; Rizvi, Syed Aun R.

doi:10.1016/j.eneco.2023.106634

Cited by 23 publications

(3 citation statements)

References 53 publications

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“…Further, Szczepanska-Przekota (2021) explored the impact of cryptocurrencies on economic conditions of different markets, and found that investors perceive the cryptocurrency market as more risky as compared to equity markets. Shahid et al (2023) explored the interconnectedness and risk transmission across global financial markets and assessed the portfolio diversification potential of socially responsible investments using DCC-GARCH and VAR-GARCH models. Their findings indicated negative correlation between traditional volatility indices and socially responsible investment indices.…”

Section: Literature Reviewmentioning

confidence: 99%

Interconnectedness of Cryptocurrency Uncertainty Indices with Returns and Volatility in Financial Assets during COVID-19

Asiri,

Alnemer,

Bhatti

2023

JRFM

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This paper investigates the dynamic relationship between cryptocurrency uncertainty indices and the movements in returns and volatility across spectrum of financial assets, comprising cryptocurrencies, precious metals, green bonds, and soft commodities. It employs a Time-Varying Parameter Vector Autoregressive (TVP-VAR) connectedness approach; the analysis covers both the entire sample period spanning August 2015 to 31 December 2021 and the distinct phase of COVID-19 pandemic. The findings of the study reveal the interconnectedness of returns within these asset classes during the COVID-19 pandemic. In this context, cryptocurrency uncertainty indices emerge as influential transmitters of shocks to other financial asset categories and it significantly escalates throughout the crisis period. Additionally, the outcomes of the study imply that during times of heightened uncertainty, exemplified by events such as the COVID-19 pandemic, the feasibility of portfolio diversification for investors might be constrained. Consequently, the amplified linkages between financial assets through both forward and backward connections could potentially compromise financial stability. This research sheds light on the impact of cryptocurrency uncertainty on the broader financial market, particularly during periods of crisis. The findings have implications for investors and policymakers, emphasizing the need for a comprehensive understanding of the interconnectedness of financial assets and the potential risks associated with increased interdependence. By recognizing these dynamics, stakeholders can make informed decisions to enhance financial stability and manage portfolio risk effectively.

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Section: Literature Reviewmentioning

confidence: 99%

Interconnectedness of Cryptocurrency Uncertainty Indices with Returns and Volatility in Financial Assets during COVID-19

Asiri,

Alnemer,

Bhatti

2023

JRFM

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“…The volatility of the financial market is an important indicator for measuring the degree of price fluctuations of financial assets, which plays a very important role in practical applications such as investment decision making [1], asset pricing [2], and risk management [3]. Therefore, the construction of a more accurate volatility estimation and forecasting model has very important theoretical value and application significance.…”

Section: Introductionmentioning

confidence: 99%

On Stock Volatility Forecasting under Mixed-Frequency Data Based on Hybrid RR-MIDAS and CNN-LSTM Models

Ma,

Hong,

Song

2024

Mathematics

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Most of the deep-learning algorithms on stock price volatility prediction in the existing literature use data such as same-frequency market indicators or technical indicators, and less consider mixed-frequency data, such as macro-data. Compared with the traditional model that only inputs the same-frequency data such as technical indicators and market indicators, this study proposes an improved deep-learning model based on mixed-frequency big data. This paper first introduces the reserve restricted mixed-frequency data sampling (RR-MIDAS) model to deal with the mixed-frequency data and, secondly, extracts the temporal and spatial features of volatility series by using the parallel model of CNN-LSTM and LSTM, and finally utilizes the Optuna framework for hyper-parameter optimization to achieve volatility prediction. For the deep-learning model with mixed-frequency data, its RMSE, MAE, MSLE, MAPE, SMAPE, and QLIKE are reduced by 18.25%, 14.91%, 30.00%, 12.85%, 13.74%, and 23.42%, respectively. This paper provides a more accurate and robust method for forecasting the realized volatility of stock prices under mixed-frequency data.

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“…Further, the study also recommends switching to RE usage with the view to mitigating greenhouse gas emissions. Similarly, Pata (2018) andShahid et al (2023), investigated urbanization, industrialization and carbon emissions in Turkey context.…”

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confidence: 99%

The Role of Green Energy Technologies Development, Carbon Finance, Carbon Tax and Economic Growth on Environmental Conditions in ASEAN Countries

Yunikewaty,

Siswahyudi

2023

IJEEP

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Green technology and carbon finance have the potential to greatly add significance towards traditional financing practices related to carbon emissions because of information based nature, Thus, exploration of green technologies and carbon finance assist economies in the formulation of effective policies. By employing the panel data of ASEAN economies from 2011-2019, the study used CUP-FM and CUP-BC methods to empirically analyze the said relationship. The outcomes of the study revealed that green technologies, carbon finance, carbon taxes, economic growth decrease GHG emissions. It implies that the synergetic effect of green technologies, carbon finance, carbon tax and economic growth play an essential role in improving environmental conditions. Consequently, ASEAN region can reshape the policies by integrating green technologies and carbon finance and also looks into country’s local condition to improve the urban environmental efficiency, hence, achieving carbon neutralization goal.

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Uncovering risk transmission between socially responsible investments, alternative energy investments and the implied volatility of major commodities

Cited by 23 publications

References 53 publications

Interconnectedness of Cryptocurrency Uncertainty Indices with Returns and Volatility in Financial Assets during COVID-19

Interconnectedness of Cryptocurrency Uncertainty Indices with Returns and Volatility in Financial Assets during COVID-19

On Stock Volatility Forecasting under Mixed-Frequency Data Based on Hybrid RR-MIDAS and CNN-LSTM Models

The Role of Green Energy Technologies Development, Carbon Finance, Carbon Tax and Economic Growth on Environmental Conditions in ASEAN Countries

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