Investment Volatility Research Articles

Oil shocks and volatility of green investments: GARCH-MIDAS analyses

This study examines how market volatility of five green investments (Standard & Poor's - S&P [Green bond select index and Green bond index] and Morgan Stanley Capital International - MSCI [Global alternative energy index, Global pollution prevention index, and Global green building index]) respond to oil shocks; using the Generalized Autoregressive Conditional Heteroscedasticity with Mixed Data Sampling (GARCH-MIDAS) modelling framework. We employ Baumeister and Hamilton's decomposed oil shocks: economic activity shocks, oil consumption demand shocks, oil inventory demand shocks, and oil supply shocks; each in their original levels, as well as their negatively and positively disaggregated levels. Our findings show homogeneous and heterogeneous responses of green investments volatility to variants of oil shocks. Asymmetry effect is also evidenced, given the differences between the estimated effect of positive and negative oil shocks on the volatility of green investments.

A Systematic Literature Review of Volatility and Risk Management on Cryptocurrency Investment: A Methodological Point of View

In this study, we explore the research published from 2009 to 2021 and summarize what extant literature has contributed in the last decade to the analysis of volatility and risk management in cryptocurrency investment. Our samples include papers published in journals ranked across different fields in ABS ranked journals. We conduct a bibliometric analysis using VOSviewer software and perform a literature review. Our findings are presented in terms of methodologies used to model cryptocurrencies’ volatility and also according to their main findings pertaining to volatility and risk management in those assets and using them in portfolio management. Our research indicates that the models that consider the Markov-switching regime seem to be more consensual among the authors, and that the best machine learning technique performances are hybrid models that consider the support vector machines (SVM). We also argue that the predictability of volatility, risk reduction, and level of speculation in the cryptocurrency market are improved by the leverage effects and the volatility persistence.

Is interest rate uncertainty a predictor of investment volatility? evidence from the wild bootstrap likelihood ratio approach

Is interest rate uncertainty a predictor of investment volatility? evidence from the wild bootstrap likelihood ratio approach

The impact of political risk on FDI exit decisions

Do political risks drive exit decisions by multinational companies (MNC)? What mechanisms can protect a multinational subsidiary in a host country that is characterized by weak institutions and high political risks? Using multinational plant-level data for Russia in the period 2000-2016 and applying the Cox proportional hazard model, we find significant effects from elevated host-country political risk when we compare the year of entry to the year of exit. MNCs are particularly sensitive to problems associated with law, order, and social conditions in Russia and the presence of the military in politics in the home country. Institutional similarity does not reduce the hazard of exits, and MNCs from high-risk countries exit less when home-country risk increases. Subsidiaries from countries that have imposed sanctions on Russia are less likely to exit, though sanctions interact with host-country risks, making them more severe. Being large and being part of a greenfield project help subsidiaries to build resistance against host-country political risks. These findings provide empirical evidence that support our conclusions regarding foreign direct investment volatility in countries with high risk.

Analysis of Korea’s Green Technology Policy and Investment Trends for the Realization of Carbon Neutrality: Focusing on CCUS Technology

In 2008, the Republic of Korea announced the Low Carbon Green Growth vision as the national growth engine. This Green Growth vision invested in developing state-of-the-art green technologies to minimize greenhouse gas and pollutant emissions. Following a change in administration, Korean green technologies were re-categorized into six core technologies for climate change response in 2014, and ten core technologies for carbon-neutrality in 2021. The government proposed the realization of an inclusive green state in the 3rd Five-Year Green Growth Plan announced in 2019. Following the Green New Deal announced in 2020, green technology policies and investments continue, with the declaration of 2050 carbon neutrality. In the past two years, government policies from the 2050 Carbon Neutrality Strategy to the 2050 Carbon-Neutral Scenario consider Carbon Capture Utilization and Storage (CCUS) as an important technology to reduce CO2 and meet carbon-neutral goals. This study examines major green technology policy trends, focusing on CCUS, beginning with the Green Growth era in 2008 to today. R&D investment costs related to green technology during the green growth period and CCUS-related investment costs over the past 10 years (2011–2020) are utilized in statistical analyses (correlation, trend) to investigate and analyze investment volatility in green and CCUS technologies related to climate change. Finally, the study will provide basic information for establishing CCUS-related R&D policies, which will continue to increase in achieving carbon neutrality.

The investment volatility-dampening role of foreign aid in poor sub-Saharan African countries

Sustained investment is required for economic growth. Investment however often experiences severe volatility in poor countries, making spending plans difficult to formulate, and diminishing growth potentials. Foreign aid serves as an important source of complementary financing for sustained investment. This paper thus studies the effect of aid inflows on total investment volatility in 19 heavily indebted poor sub-Saharan African countries over the period 1980–2018. Employing the cross-sectionally augmented distributed lag (CS-DL) estimation technique for long-run coefficients in dynamic heterogeneous panels with cross-sectional dependence along with bootstrap panel causality testing, we show that aid has an inverse relationship with investment volatility. We thus conclude that aid can be viewed as a dampening factor for investment volatility in poor countries. We also show that the ability of sudden reductions in aid inflows to trigger investment volatility is bigger than the ability of sudden increases in aid inflows to lower investment volatility.

The financing of uncertain future investments

PurposeThe purpose of this study is to investigate the effects of two important financing sources, debt and cash, on a firm’s investment decisions and explores the intertemporal impact of this financing on future investment volatility.Design/methodology/approachThis paper first reports our results using ordinary least squares (OLS) estimation and then employ an instrumental variable (IV) strategy which addresses potential endogeneity that arises from future investment volatility on current capital structure and cash levels.FindingsThis paper finds firms with low levels of debt or high levels of cash experience higher future investment volatility, and the probability of large future investment increases with high cash levels. This study’s findings are economically important; for example, a one-standard-deviation increase from the mean of debt ratio implies an approximate 7.8% decrease in future investment volatility; and a one-standard-deviation increase from the mean of a firm’s cash level leads to a 47% increase in the probability of a large investment in the next year.Originality/valueThe findings of this study help firms understand the impact of their present financing decisions on the plausibility of their future investments. This paper contributes to the literature by making both novel and confirmatory findings. This paper was structured to include confirmatory findings for two reasons. First, this paper uses different methods to construct investment volatility and the related investment spike. Second, and more importantly, the hypotheses are interrelated and communicate how firms plan for and execute against uncertain future investments. Growth options are ephemeral, and the hypotheses structure provides a guideline for how a firm finances future growth options.

Free riding and insurer carbon-linked investment

The paper develops a two-insurer contingent claim framework to evaluate their equities. One insurer conducts carbon-linked investment, while the other conducts conventional (non-carbon-linked) investment. The free-riding issue becomes essential because of the carbon-emission externality. We show that the life insurance policyholders are free riders when either the return of carbon-linked or the conventional investment increases. But the cost burden of policyholder protection is the reduced insurer interest margin. The results also apply to the increased carbon-linked investment volatility and the different coronavirus COVID-19 impacts on the two-insurer interest margins. In the soundness test, we show that insurance stability at the cost of insurer profits is less significant when the carbon-linked investor's barrier increases. Free riding would be intimately relevant to insurance and carbon-emission environments in the barrier option model.

ОЦЕНКА ВОЛАТИЛЬНОСТИ ИНВЕСТИЦИЙ В ТЕХНОЛОГИЧЕСКИЕ ИННОВАЦИИ ПРЕДПРИЯТИЙ КИТАЯ

Modern development of China is not possible without the support of technological innovations of its individual enterprises. However, the continuous growth of investment in innovation has not led to a proper increase in the innovative level of Chinese enterprises. The object of the study is the innovation activities of enterprises in China. The subject of the study is the volatility of investment in innovation. The aim of the study is to substantiate the impact of investment volatility in the technological innovation of Chinese enterprises in strategic emerging industries. The objectives of the study are to assess the impact of investment volatility in the technological innovation of Chinese enterprises at different stages of the life cycle. The following research methods have been used: analysis, synthesis, analogy, statistical methods. In recent years, there has been an increase in investment volatility in the technological innovation. However, according to a number of Chinese scholars, the unsustainability of enterprises' investment in innovation will eventually lead to an increase in the level of these innovations. The assumptions made by scientists need to be verified. Within the framework of the article, the influence of investments’ volatility in the technological innovations at different stages of the life cycle of Chinese enterprises has been studied. The causes are determined and the various consequences of volatility at different stages of the life cycle of enterprises are considered. It has been established that volatility has a positive effect on the innovation of enterprises in the growth stage, at the mature stage it has a slight stimulating effect, and it has no effect at the stage of decline. The negative deterrent effect of state subsidies for innovation on the volatility of investments at all stages of the life cycle of enterprises is noted

Climate change investing and COVID-19: evidence from return volatility

This study investigates the impact of COVID-19 on the volatility of climate-related investments in India. The study evaluates the certainty of investments related to climate change in India. The GARCH (1, 1) model is employed on the CARBONEX index of India. The author has found evidence of increasing volatility due to COVID-19. Also, a large degree of volatility persistency has been exhibited by S&P BSE CARBONEX due to COVID-19. In conclusion of the study, the author discovered that during COVID-19, a rise of 145.75% in unconditional variance was seen.

Option Volatility Investment Strategy: The Combination of Neural Network and Classical Volatility Prediction Model

This study focuses on the volatility prediction and option volatility investment. By investigating the traditional Volatility Prediction Model and machine learning algorithms, this study tries to merge these two aspects together. This work setup a bridge of previous financial studies and machine learning studies by proposing an algorithm integrating neural network and three traditional volatility models, called “Quantile based neural network and model integration combination algorithm.” The algorithm effectively lowers the volatility prediction error (measured by root of mean square error, shorted for RMSE: 0.319724) and beat the Wavenet (RMSE: 0.44) which is the benchmark and surpasses integrated model (RMSE: 0.348346) in test set. In terms of option investment strategy, this paper constructs a CSI 300 index option portfolio which hedges the underlying asset price risk and exposes the volatility risk. Then propose the “Option strategy of volatility prediction with dynamic thresholds.” With the new algorithm above, the strategy improves the return‐risk ratio in test set (measured by Sharpe ratio: 1.99–2.07).

Prices Volatility and Hedging Strategy: Evidence of The Green Stock in Moscow Exchange

The aim of this study is to investigate the presence of fractal structure in the Moscow Exchange green stocks, and to propose a hedging strategy for the investors. We use the daily returns MRSV index for the period from 9/22/2020 to 01/06/2022. The Hurst exponent, wave analysis, and wavelet shrinkage estimator were applied. Our results show that the daily returns of MRSV index follow a fractal pricing paradigm. The volatility of MRSV index returns is confined to support and resistance levels (+2%, -2%), This result is due to speculation behavior in Moscow Exchange. To hedge against price volatility investors should buy the put options when the returns of MRSV index fall below the support level -2%.

The Impact of Innovation Investment Volatility on Technological Innovation of Enterprises in Different Life Cycles

Empirical findings from the impact of innovation investment volatility on enterprise technological innovation are mixed. Based on the punctuated equilibrium theory, this study explores the impact of innovation investment volatility on enterprise technological innovation in different life cycles and whether innovation subsidy has expected effects on enterprises’ technological innovation. By using the 205 Chinese listed enterprises in strategic emerging industries from 2010 to 2019 as the research sample, the results show that the innovation investment volatility has a positive impact on technological innovation of enterprise in the growing stage, while it has no significant effect on enterprise technological innovation in the mature and declining stages. In addition, the negative moderating effect of innovation subsidy on the relationship between innovation investment volatility and technological innovation is the most significant for enterprises in the growing stage, weakly significant for enterprises in the mature stage, and insignificant for enterprises in the declining stage.

Hedging on the Hill: Does Political Hedging Reduce Firm Risk?

We examine whether firms’ political hedging activities are effective at mitigating political risk. Focusing on the risk induced by partisan politics, we measure political hedging as the degree to which firms’ political connections are balanced across Republican and Democratic candidates. We find that greater political hedging is associated with reduced stock return volatility, particularly during periods of higher policy uncertainty. Similarly, greater political hedging is associated with reduced crash risk, investment volatility, and earnings volatility. Moreover, the reduction in earnings volatility appears to relate to both a firm’s taxes and its operating activities, as we find that greater political hedging is associated with reduced cash effective tax rate volatility and pretax income volatility. We further find investors are better able to anticipate future earnings for firms that engage in political hedging, suggesting that political hedging helps improve firms’ information environments. Lastly, we perform an event study using President Obama’s Clean Power Plan. We find that on the days this policy proposal was debated in Congress, energy and utility firms experienced heightened intraday return volatility (relative to other firms and nonevent days). However, this heightened volatility is mitigated for energy and utility firms that are more politically hedged. Overall, we conclude that political hedging is an effective risk management tool that helps mitigate firm risk. This paper was accepted by Suraj Srinivasan, accounting.

Foreign Direct Investment and Output Volatility Nexus: A Global Analysis

Volatility in output growth remains a genuine concern around the globe because of its detrimental effects on growth, poverty and welfare. In the realm of output volatility, the role of FDI and its consistency is particularly important and worth considering. This article examines the role of FDI inflows and specifically the instability in it on output growth volatility using a panel dataset of 141 world economies for the period 1971–2017. The study employs a variety of estimation techniques like pooled ordinary least squares (POLS), LS fixed effects (FE), LS random effects (RE), two stage least squares (2SLS) and generalised methods of moments (GMM). Findings of the study suggest that FDI acts as the volatility reducing factor, whereas uncertainty in it increases output volatility. On the policy front, this study recommends policies that not only encourage FDI inflows but also ensure the inflows to be more consistent and stable. Our results are robust corresponding to various above-mentioned estimation techniques and sensitivity analysis. JEL Codes: C23, E32, F21

Ethical and unethical investments under extreme market conditions

This study investigates the time-varying volatility and risk measures of ethical and unethical investments. We apply the Bayesian Markov-switching generalized autoregressive conditional heteroscedasticity (MS-GARCH) approach to compute the value-at-risk (VaR) and expected shortfall (ES) of ethical and unethical indices returns, which allows for detecting the differences between ethical and unethical investments. The innovative finding of our study is that ethical investments are less affected during global financial crises compared with unethical and conventional investments. The policy implication of this study is that investors should consider ethical investments as a hedging asset for their portfolios during extreme market conditions.

The Venture Capital Market in a Pandemic: Realities of Time and Future Prospects

The subject of the research is the financial mechanism of the modern venture investment market under conditions of uncertainty and the requirements of accelerated innovative development. The study aims to analyze the impact of the pandemic on the sustainability of the institutional behavior of venture capital investment in the global and Russian markets. The authors apply such scientific methods as sampling, grouping, comparison, analogy, analysis, generalization, systemic-structural approach to assessing the development of the subject of research. The paper analyses the role of venture investment in the successful promotion of innovations using the example of the world’s leading companies in 2016–2021. Successful examples of venture investment are presented. The study investigates the impact of the pandemic and lockdown on the level of volatility, composition and dynamics of venture capital investments in 2020– 2021. The authors conclude that the pandemic has an impact on the sectoral redistribution of investments in favor of venture investments in medicine, biotechnology, the sector of information and communication technologies and solutions for business, education, healthcare, on market polarization (covid-negative, covid-positive, covid-neutral), on reducing the role of state funds and Russian accelerators, while increasing the interest and scale of participation of private institutions (foreign investors, business angels, syndicated angel investment), to increase of the volume of the Russian venture capital market by increasing the average ticket size despite the reduction in their number, to strengthen the practice reproduction of their own ecosystems by corporate institutions, to popularize venture capital investment deals in terms of mergers and acquisitions. Prospects for researching the venture capital market are associated with the constant attention to high-tech covid-positive projects, with the growth of transactions in the early stages, due to the increase in the number of professional communities, with the pinpoint development of specific tasks of an investor or corporation by accelerators, with venture investment of companies with the subsequent entry of the project into their own ecosystem, with the improvement of the state’s restrictive measures aimed at a clear institutionalization of professional activities and increasing the financial stability of participants in the investment and innovation markets, with the stimulation of mechanisms for regional innovative development to attract capital to high-risk projects in the regions.

Macroeconomic Variables and Foreign Portfolio Investment Volatility in Nigeria

The study aims to check the impact of macroeconomic variables on foreign portfolio investment (FPI) volatility in Nigeria using time series data from January, 2014 to December, 2019 obtained from the Central Bank of Nigeria. The test revealed that previous month’s volatility in FPI, inflation rate and all share indexes were significant determinants of FPI volatility in Nigeria. Based on the findings, it was recommended among other things that these factors that influence foreign portfolio investment oscillation should be regulated by the appropriate government agencies to ensure more serene investment clime.

Assessing the Impact of Outbreaks on Malaysian Listed Property Companies in Mixed-Asset Portfolios

Abstract This paper assesses the impact of outbreaks from the perspective of volatility of Malaysian Listed Property Companies in mixed-asset portfolios, concentrating on periods of time between outbreaks. The real issue of this study is the health crisis that has troubled institutional investors, as it has already significantly impacted the returns on investments. Investors need to be better informed on the impact of health outbreaks on investments in order to minimize their impact. To assess the impact of the outbreaks, the GARCH method has been employed to examine the dynamic volatility of listed property companies in mixed-asset portfolios. The volatility level will give investors better information from point of view of the dynamics of volatility of the Malaysian listed property companies’ performance within mixed-asset portfolios. The findings show that listed property companies demonstrate high volatility compared to other mixed-asset portfolios during the periods of outbreaks. This indicates Malaysian listed property companies were the most volatile investment in mixed-asset portfolios. This empirical study will contribute significantly to institutional investors, especially in terms of the investment decision-making process during outbreaks.

The role of inventories for the propagation of aggregate fluctuations: lessons for Bulgaria (1999–2019)

PurposeIn this study, inventories are introduced as a productive input into a real-business-cycle (RBC) setup augmented with the government.Design/methodology/approachThe model is calibrated to Bulgarian data for the period 1999–2019. The quantitative importance of the presence of inventories is investigated.FindingsThe quantitative effect of inventories is found to be important: decreasing consumption volatility and increasing employment variability. Those results, however, are at the expense of decreasing wage volatility and increasing investment volatility, and generally worsening the contemporaneous correlations of the main variables with output.Originality/valueFluctuations in inventory levels matter for business cycle fluctuations in Bulgaria, which is a novel result. Still, there is a need for more research on the incorporation of inventories into RBC models to better fit the Bulgarian experience.