Does Policy Uncertainty Affect Equity, Commodity, Interest Rates, and Currency Markets? Evidence From Cboe’s Volatility Index

Shaikh, Imlak

doi:10.3846/jbem.2020.13164

Cited by 14 publications

(5 citation statements)

References 38 publications

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“…Figure 4 shows the plot of absolute returns of DJSIUS with the EPU index; absolute returns are the crude measure of stocks’ volatility. It is seen that volatility appears to be very volatile following the EPU (Shaikh, 2020). Figure 5 also speaks a similar story presented in the previous graph; with a higher VIX level, sustainable stock exhibits more significant volatility.…”

Section: Data Sources Description and Preliminary Analysismentioning

confidence: 99%

On the relationship between policy uncertainty and sustainable investing

Shaikh

2021

JM2

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Purpose In recent times, sustainable investment gaining much attention within the investors’ community and it is broadly driven by environmental, social and governance (ESG) factors. This study aims to examine the ESG-based sustainability index and economic policy uncertainty (EPU). Design/methodology/approach Corporate sustainability assessment procedure yields Dow Jones sustainability indexes (DJSIUS) and ESG compliant firms become a member of such indexes. To uncover the effects of policy uncertainty as follows: the study considers EPU index, equity market policy uncertainty index, economic and political events for the period 2000–2017. The authors present the study using a conditional volatility framework. Findings The correlation between the DJSIUS and policy uncertainty appears to be negative and statistically significant. It is apparent from the results that policy uncertainty does contain important ESG factors that explain the sustainable investment in US firms. Moreover, the stock market boom, credit crunch, Lehman collapse and fiscal crises have shown significant adverse effects on the sustainability index. More importantly, it is seen that investors’ sustainable investing considers presidential election years for portfolio planning; the uncertainty associated with the election years has also shown a negative impact on the sustainable returns. Practical implications First, sustainability is essential for the long-term stakeholders’ wealth maximization under governments’ policy uncertainty such as constrained resources, demographic and climate-change-policy, societal expectations, public-policies, regulatory structure. Second, EPU creates new opportunities and risks for sustainable firms and sustainable investing. Originality/value The study is novel in which the authors present the effects of uncertainty on socially responsible investing.

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Section: Data Sources Description and Preliminary Analysismentioning

confidence: 99%

On the relationship between policy uncertainty and sustainable investing

Shaikh

2021

JM2

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“…Market risk is inherent in all investment activities. It can significantly impact the value of financial assets and liabilities (Odubuasi, Wilson-Oshilim, & Ifurueze, 2020;Shaikh, 2020). ii.…”

Section: Financial Risk Management Definition and Types Of Financial ...mentioning

confidence: 99%

Quantum computing and financial risk management: A theoretical review and implications

Mayokun Daniel Adegbola,

Ayodeji Enoch Adegbola,

Prisca Amajuoyi

et al. 2024

Comput. sci. IT res. j.

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This review paper examines the potential implications of quantum computing for financial risk management. It explores the fundamental principles of quantum computing, including qubits, superposition, and entanglement. It discusses its advantages over classical computing for risk assessment and mitigation. The paper outlines traditional approaches to financial risk management. It explores how quantum algorithms, such as quantum Monte Carlo methods and quantum annealing, can enhance these strategies. Challenges and barriers to adopting quantum computing in the financial industry are identified, along with future research directions. Ultimately, the paper highlights the transformative potential of quantum computing for improving risk management in today's complex financial markets. Keywords: Quantum Computing, Financial Risk Management, Qubits, Quantum Algorithms, Monte Carlo Simulations, Portfolio Optimisation.

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“…The US macroeconomic indicators such as "PPI, CPI, state employment, employment situations, labour turnover, and job openings, US export/imports, unemployment, real earnings, earnings of wages and salary, business employment dynamics and employment cost index" and their uncertainty play a significant role in the equity market and other markets (Shaikh, 2020). Cakan and Gupta (2017) modeled the impact of U.S. inflation and unemployment rate surprises on South African stock price volatility.…”

Section: Literature Review: Modeling Stock Returns Based On Economic Indicator's Surprisesmentioning

confidence: 99%

Modeling of EURO STOXX 50 index price returns based on industrial production surprises: basic and machine learning approach

Gasparėnienė¹,

Remeikienė²,

Sosidko³

et al. 2020

JESI

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There are a big number of researches which analyzing stock price returns. Some of them is based on fundamental analysis theory. Meanwhile other studies are based on efficient market hypotheses and financial behavior theories. However, there is not enough researches combining the characteristics of these theories into one. Such kind of researches in the scientific literature is usually referred to macroeconomic news, announcements, surprises, expectations studies. These studies examine not only the actual but also the predictive values of macroeconomic indicators announcements, normalizing them and thus creating absolutely a new surprise indicator. Purpose of this paper is modeling EURO STOXX 50 index price returns based on Industrial production surprise indicator. Empirical part shows that the best models for explaining EURO STOXX 50 index price returns was obtained at the 40 and 42 in different surprise indicator scenario. The coefficient of determination was obtained respectively 24.70% and 21,80%. Meanwhile applying machine learning method of artificial intelligence, a much more accurate models were obtained. The coefficient of determination respectively was 33,22% and 26,60%.

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Does Policy Uncertainty Affect Equity, Commodity, Interest Rates, and Currency Markets? Evidence From Cboe’s Volatility Index

Cited by 14 publications

References 38 publications

On the relationship between policy uncertainty and sustainable investing

On the relationship between policy uncertainty and sustainable investing

Quantum computing and financial risk management: A theoretical review and implications

Modeling of EURO STOXX 50 index price returns based on industrial production surprises: basic and machine learning approach

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