Volatile Analysis Research Articles

VeHIF current arcing, volatility and vegetation ignition development: An EMD based volatility analysis for earth-fault classification

Vegetation High Impedance Fault (VeHIF) events pose severe risks to public safety, wildlife, and forests. Overcurrent protection schemes generally cannot clear VeHIF events, which have previously resulted in bushfires. This research presents a VeHIF classification method based on the statistical variance analysis of volatility in the empirical mode decomposed feeder current. The author applied the proposed scheme to a dataset of 130 earth-faults with 100 % success rate and a mean classification time of 10 s (standard deviation of 14.32 s). While faster VeHIF fault classification should ideally be achieved, research findings show that faster classification speeds may not always be feasible or necessary. This finding relates to the fact that bushfire risk increases, when charring starts to spread over a branch with a breakout of flames. The present work further validates a positive pairwise correlation between a fault current's volatility and arcing, demonstrating the efficacy of High Frequency (HF) signals as reliable VeHIF volatility signatures.

Average and Risk-Return Analysis of Cryptocurrencies Using ARMA-GARCH Models

Cryptocurrency is a digital currency that is created through encrypted cryptography with complex algorithm and connected to each other on the blockchain system. Cryptocurrencies are widely used as investment instruments for financial assets like stocks. Similar to stocks, cryptocurrencies have a high risk – high returns characteristic, but the fluctuation of cryptocurrencies are more dynamic. Professional investors would do a volatility analysis of cryptocurrencies that potentially give the best returns. Returns assessment usually refers to the average value or expected return, while the estimated investment risk can be seen and analyzed from the volatility value. The study aimed to analyze the average and volatility of cryptocurrencies. This research was a case study done on five cryptocurrencies that are included at Top Gainers of 30 days update lists, in September 2022. The period is January 1, 2019 – September 30, 2022. The ARMA-GARCH models using three types of GARCH models, those are SGARCH(1,1), IGARCH(1,1), and TGARCH(1,1) were used for analysis. Based on the results of this research, the best ARMA-GARCH model for cryptocurrency Quant, XRP, Stellar, Monero, and Decred is ARMA(1,0)-SGARCH(1,1), ARMA(32,0)-TGARCH(1,1), ARMA(0,14)-SGARCH(1,1), ARMA(1,4)-TGARCH(1,1), and ARMA(1,0)-SGARCH(1,1). Best expected return with the lowest volatility value is owned by Monero (XMR). The research can be used by investors as a consideration in investing decision-making to cryptocurrencies.

Empirical Testing of Models of Autoregressive Conditional Heteroscedasticity Used for Prediction of the Volatility of Bulgarian Investment Funds

The relevance of the development is determined by the possibility of testing a complex analytical methodology for forecasting the daily volatility of Bulgarian investment funds, which will support the investment community in making adequate investment decisions. The used risk attribution quantification models GARCH (1.1), EGARCH (1.1), GARCH-M (1.1) and TGARCH (1.1) are adapted to predict the volatility of investment funds. The current development focuses on forecasting the risk concentration of investment funds (in Bulgaria) through the testing of complex, analytical and specialized models from the GARCH group. The object of the study includes quantitative analysis, estimation and forecasting of daily volatility through the models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty-two investment funds for the period from 13 July 2020 to 13 July 2023, where the results of the research show that according to three of the models GARCH, EGARCH and GARCH-M with the highest risk concentration the investment fund “Golden Lev Index 30” stands out. An exception to the thus formed trend is related to the TGARCH model in which the future conditional volatility is with the “EF Rapid” investment fund. When testing the models, we found that the GARCH model and the EGARCH model successfully optimize the regression parameters of the final equation for all analyzed investment funds, and as a result, valid forecasts are formed. In the case of the remaining two GARCH-M and TGARCH models, the impossibility of applicability of the model for some investment funds was found because of the optimization procedure, in which the parameters of the models have a value of zero. The present study is a unique mechanism for forecasting the daily volatility of Bulgarian investment funds, which further assists investors in risk assessment and is a prerequisite for making adequate and responsible investment decisions. The wide-spectrum toolkit of risk forecasting models allows their testing in investment funds with different risk natures (high-risk, balanced and low-risk). From a research point of view, in future research dedicated to modeling the risk attribution of investment funds, the analytical toolkit can be enriched with the following models: QGARCH, PGARCH, GJR-GARCH, IGARCH, SGARCH, AVGARCH, NGARCH and GAS. From a statistical point of view, we can apply the analyzed models to different probability distributions in order to describe the risky nature of investment funds.

Synthesis and study of properties of new oligoesters based on soybean oil as potential poly(vinyl chloride) plasticizers

AbstractNew compounds as potential poly(vinyl chloride) plasticizers based on soybean oil and oligoesters of adipic acid and different glycols by one‐pot transesterification are synthesized. In the first step of the plasticizer synthesis oligoesters of adipic acid and diethylene glycol, triethylene glycol, or dipropylene glycol are synthesized, and then in situ in the second step, a defined amount of soybean oil is introduced. By degradation of soybean oil with oligoesters, and transesterification reaction, different compounds are obtained. Their physicochemical properties are determined by NMR, SEC, DSC, TGA, and volatility analyses. The properties of synthesized plasticizers are compared with commercial products: monomeric (DEHP) and aliphatic oligoster of adipic acid and 1,3‐butanediol (H‐1).

Homogenizing microwave pyrolysis of oily sludge using nano-Fe3O4: volatile gas product analysis

ABSTRACT To improve the homogeneity of heating, the magnetic absorbing material Fe3O4 is considered to use in microwave pyrolysis of oily sludge. Therefore, the effect of Fe3O4 on the microwave pyrolysis of oily sludge is investigated based on gas volatile products. Thermogravimetric mass spectrometry result certifies that Fe3O4 will increase the weight-loss ratio from 13.0% to 14.1%. Also, the characteristic peak intensity of CO in gas products decreases from 5.41 × 10−10 A/g to 1.95 × 10−10 A/g, while H2O increases from 3.57 × 10−10 A/g to 7.32 × 10−10 A/g and CO2 increases from 6.87 × 10−10 A/g to 8.92 × 10−10 A/g. This is caused by the esterification of alcohols and esters and the reduction of Fe3O4 by CO. Based on the decrease in activation energy and enthalpy values of Stage II and IV, it infers that Fe3O4 catalyzes the pyrolysis process of oily sludge to some extent. Similarly, gas chromatography-mass spectrometry results show that Fe3O4 can make the types of gas products increase. Especially, the number of molecular species increases from 5 to 46 under 200–300 °C. Finally, a simple molecular dynamics simulation model is conducted, and the results are in agreement with the experimental results. This study shows that Fe3O4 improves the pyrolysis homogeneity and the pyrolysis efficiency also improves.

Income variability and agricultural policy

Objective: To compare producer income volatility under two types of policies (support prices and direct payments). Design/Methodology/Approach: Producer income is understood as the result of multiplying price by yield; therefore, income is the product of two random variables modeled with a lognormal distribution, accounting for the covariance. After the subtracting trend, the cyclical component is subjected to a volatile analysis under each policy studied. Results: Income volatility is systematically higher for support price programs than for the direct payment policy. Study Limitations/Implications: Government programs have recently taken up support prices again; therefore, income variability should be reviewed. Findings/Conclusions: Government programs aim to increase producer income by different means. However, they overlook possible volatility implications. By taking up support price programs again, producer income may be at risk of rebounding.

Microbiomics and volatile metabolomics-based investigation of changes in quality and flavor of oat (Avena sativa L.) silage at different stages.

This study aimed to analyze the fermentation quality, microbial community, and volatile metabolites of oat silage harvested at two different stages, while examining the correlation between microorganisms and volatile metabolites. Oats were harvested at two growth stages (pre-heading [PRH] and post-heading [POH] stages), followed by 90 days of natural fermentation, with 6 replicates per treatment. Pre- and post-silage samples were randomly selected for nutrient composition, fermentation parameters, microbial population, and high-throughput sequencing analysis. Volatile metabolomics analysis was also performed on samples after 90 days of fermentation to detect differences in flavor quality after silage. The effect of growth stage on the nutrient content of oats was significant, with pre-heading oats having higher crude protein and post-heading oats having higher water soluble carbohydrates content (p < 0.05). Following a 90-day fermentation period, the pH and ammonia nitrogen/total nitrogen levels in the PRH-90 (silage from pre-heading oats after 90 days of fermentation) group demonstrated a significant decrease (p < 0.05), whereas the lactic acid content was notably higher compared to the POH-90 (silage from post-heading oats after 90 days of fermentation) group (p <0.05). Lactiplantibacillus dominated in the PRH-90 group and Enterococcus dominated in the POH-90 group, with abundances of (> 86%) and (> 87%), respectively. The differential volatile metabolites of the two treatment groups were dominated by esters and terpenoids, and the differences in flavor were mainly concentrated in sweet, green, and fruity odors. The results of Kyoto encyclopedia of genes and genomes pathway enrichment analysis demonstrated three major metabolic pathways: phenylpropanoid biosynthesis, phenylalanine metabolism, and biosynthesis of secondary metabolites. Specific microorganisms were significantly correlated with flavor indicators and flavor metabolites. Lactiplantibacillus was significantly positively correlated with flavor substances indicating sweet and fruity flavors, contributing to good flavor, while Enterococcus was significantly and positively correlated with flavor substances indicating bad flavors. In summary, growth stage had significant effects on nutritional components, fermentation parameters and flavor quality of oats, with the fermentation process dominated by Lactiplantibacillus leading to good flavor, while the fermentation process dominated by Enterococcus led to the development of poor flavor.

PSVIII-23 Volatile Flavor Profile of Wet Pet Food Influences Canine and Feline Palatability Performance

Abstract Volatile flavor compounds as they relate to canine and feline palatability of wet pet food has yet to be established in the industry. The objectives of this study were to determine volatile compounds in wet pet food in diets that performed differently in palatability feeding studies. Five pairs of wet pet food diets (n = 3 feline; n = 2 canine) were obtained from separate manufacturing facilities and were selected based on palatability preference (P &amp;lt; 0.05, n = 3) or palatability parity (P &amp;gt; 0.05, n = 2). Volatile compounds were extracted using solid phase microextraction and analyzed via gas chromatography-mass spectrometry. Diets were analyzed in triplicate. Significance was determined at P &amp;lt; 0.05. Alcohols, aldehydes, and hydrocarbons comprised the main groups, and 58 total volatile compounds were identified. 1-octen-3-ol, an artifact of lipid oxidation, was found in all diets and was consistently greater (P &amp;lt; 0.05) in diets that were less preferred in palatability testing. A feline diet less preferred in palatability performance had increased concentrations (P &amp;lt; 0.05) of volatile compounds such as furfuryl alcohol and 2-pentyl furan, derived from both the Maillard reaction and thermal lipid degradation pathways, respectively. Conversely, a canine diet with palatability preference was greater (P &amp;lt; 0.05) in lipid degradation products such as 2-pentyl furan, 1-hexanol, and p-xylene. Overall, one set of diets had an increased (P &amp;lt; 0.05) production of Maillard reaction products including Strecker aldehydes, furans, and pyrazines whereas lipid degradation products were predominant in the second set. In conclusion, these data generally showed a significant difference (P &amp;lt; 0.05) in Maillard reaction and lipid degradation products in each pair of diets. Future studies are warranted to better understand how the volatile compound profile impacts palatability for canines and felines. Taken together, the results of this study suggest that volatile compound profile analysis could be utilized to further elucidate influencers of pet food palatability preferences.

Physicochemical Characteristics, Antioxidant Properties, Aroma Profile, and Sensory Qualities of Value-Added Wheat Breads Fortified with Post-Distillation Solid Wastes of Aromatic Plants

The influence of incorporation of post-distillation solid wastes of the aromatic plants (SWAP), oregano, rosemary, lemon balm, and spearmint into wheat breads at 1% and 2% levels on their physicochemical and sensorial properties, and antioxidant and volatile profiles were investigated. SWAP breads had darker crumbs and crust and greener crumbs compared to the control, but rather similar loaf specific volume and textural attributes (crust puncture test and crumb Texture Profile Analysis). Although the mold growth on bread crumb surface was not inhibited by SWAP presence, LC-DAD-MS revealed a large increase in terpenoids, like carnosic acid (all SWAP), carnosol (rosemary) and carvacrol (oregano), phenolic (rosmarinic and salvianolic) acids and flavonoids in bread with SWAP inclusion, leading to enhanced antioxidant capacity (ABST, DPPH and FRAP assays). The distinct aromatic plant flavors were detected in the fortified breads by trained assessors and confirmed by SPME-GC/MS volatile analysis, showing high levels of terpenoids in SWAP breads, like carvacrol (oregano), caryophyllene (rosemary and lemon balm), and carvone (spearmint), and rendering the 2% fortification unacceptable by consumers. Nevertheless, breads with 1% oregano or rosemary waste had similar control overall acceptability scores, indicating that SWAP can be a promising ingredient for developing antioxidant-enriched wheat breads.

Functional properties and flavor characteristics of milk from cows supplemented with jujube powder

Jujube has various functional properties and is a promising source of bioactive compounds and flavors. This study investigated the functional properties and flavor characteristics of milk from cows supplemented with jujube powder (JP). Here, milk volatile profiles and taste properties were analyzed by using an electronic nose and headspace solid-phase microextraction GC-MS. Compared with the control group, the total antioxidant capacity, 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulphonic free-radical-scavenging activity, lactoferrin, and IgG levels increased significantly in the JP group. Volatile flavor analysis indicated that ketone levels increased, acid abundance decreased, and toluene and dimethyl sulfone significantly increased in the JP group. Taste-profile analyses demonstrated that jujube supplementation altered the taste of the milk. In summary, dietary JP supplementation affects the volatile flavor composition and aroma of milk, as well as the bioactive components and antioxidant properties. These findings enhance our understanding of milk production using direct dietary supplementation to produce sustainable dairy products.

Effect of different drying methods on color difference, microorganisms and volatile metabolites profiles of Ganpu Tea

In this study, sunlight drying, low temperature drying and hot air drying were used to investigate the effects of different drying methods on color difference, microorganisms and volatile metabolites profiles of Ganpu Tea. The results suggested that the L*, a* and b* values of sunlight drying Ganpu Tea (GPTS) in the traditional drying process were significantly lower than those of low temperature drying Ganpu Tea (GPTL) and hot air drying Ganpu Tea (GPTH). It indicated that sunlight drying could decrease the lightness, redness and yellowness values compared with low temperature drying and hot air drying. 16S rDNA amplicon sequencing analysis showed that GPTS, compared with GPTL and GPTH, significantly increased the abundances of Cyanobacteria while significantly decreasing the abundances of Staphylococcus, Bacillus, Brevibacterium and Brachybacterium. At the genus level, Cyanobacteria was the core functional flora in GPTS, while Brevibacterium and Staphylococcus were the core functional flora in GPTL, and Bacillus was the core functional flora in GPTS. In addition, volatile metabolites profile analysis showed that GPTS significantly increased the volatile metabolites levels of Butanoic acid, 3-hexenyl ester, (E)- and Geranic acid compared with GPTL and GPTH. The research on the effects of different drying methods on the aroma, microorganisms and color of Ganpu tea would provide new strategies for improving the quality and enhancing the aroma of Ganpu Tea.

EXPLORANDO ADITIVOS PARA MEJORAR LA PRODUCCIÓN FERMENTATIVA DE BIOHIDRÓGENO

Dark fermentation appears as a promising strategy in the new energy landscape, as it enables the production of biohydrogen using a wide range of biomass substrates, thus also contributing to waste management. However, this process exhibits lower yields compared to conventional thermochemical processes for H2 production, such as reforming. To overcome this limitation, the use of additives has been explored to enhance microbial activity and increase dark fermentation yields. However, the application of additives remains limited in practice. This study aims to address this gap by examining the effects of three types of additives (zero-valent iron, activated carbon, and hydrochar) on dark fermentation and hydrogen generation. The results reveal that hydrochar shows the most promising outcomes, increasing H2 production by 20.3%, with the highest biohydrogen yield at 92 mLH2/g-glucose. Volatile fatty acid analysis reveals that butyric and acetic pathways are utilized for H2 production in this case. It is also important to consider the alkalinity of the feedstock, as high levels can increase the pH in the medium and promote methane (CH4) production as the main fermentation product instead of H2. When this occurs, Fe(0) NPs appear to be the additive that most favors methane generation, resulting in a 6.1% higher production compared to the control experiment. This confirms the interest in the use of certain additives in fermentative processes. Keywords: Activated carbon, Addition, Dark fermentation, Fe(0) nanoparticles, Green hydrogen, Hydrochar, VFA.

An Analysis of Volatility and Risk-Adjusted Returns of ESG Indices in Developed and Emerging Economies

The importance of Environmental, Social, and Governance (ESG) aspects in investment decisions has grown significantly in today’s volatile financial market. This study aims to answer the important question of whether investing in ESG-compliant companies is a better option for investors in both developed and emerging markets. This study assesses ESG investment performance in diverse regions, focusing on developed markets with high GDP, specifically the USA, Germany, and Japan, alongside emerging nations, India, Brazil, and China. We compare ESG indices against respective broad market indices, all comprising large and mid-cap stocks. This study employs a variety of risk-adjusted criteria to systematically compare the performance of ESG indices against broad market indices. The evaluation also delves into downside volatility, a crucial factor for portfolio growth. It also explores how news events impact ESG and market indices in developed and emerging economies using the EGARCH model. The findings show that, daily, there is no significant difference in returns between ESG and conventional indices. However, when assessing one-year rolling returns, ESG indices outperform the overall market indices in all countries except Brazil, exhibiting positive alpha and offering better risk-adjusted returns. ESG portfolios also provide more downside risk protection, with higher upside beta than downside beta in most countries (except the USA and India). Furthermore, negative news has a milder impact on the volatility of ESG indices in all of the studied countries except for Germany. This suggests that designing a portfolio based on ESG-compliant companies could be a prudent choice for investors, as it yields relatively better risk-adjusted returns compared to the respective market indices. Furthermore, there is insufficient evidence to definitively establish that the performance of ESG indices varies significantly between developed and emerging markets.

COVID-19 Pandemic and Indices Volatility: Evidence from GARCH Models

This study examines the impact of volatility on the returns of nine National Stock Exchange (NSE) indices before, during, and after the COVID-19 pandemic. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) modelling to analyse investor risk and the impact of volatility on returns. The study makes several contributions to the existing literature. First, it uses advanced volatility forecasting models, such as ARCH and GARCH, to improve volatility estimates and anticipate future volatility. Second, it enhances the analysis of index return volatility. The study found that the COVID-19 period outperformed the pre-COVID-19 and overall periods. Since the Nifty Realty Index is the most volatile, Nifty Bank, Metal, and Information Technology (IT) investors reaped greater returns during COVID-19 than before. The study provides a comprehensive review of the volatility and risk of nine NSE indices. Volatility forecasting techniques can help investors to understand index volatility and mitigate risk while navigating these dynamic indices.

HS-SPEM-GC-MS Analyses of Volatiles and Transcriptome Analysis of Camellia tetracocca in Response to Feeding by Empoasca onukii Matsuda

The tea leafhopper (Empoasca (Matsumurasca) onukii Matsuda, 1952) is the predominant pest infesting tea and causes significant losses in yield. Plants have evolved multiple defense responses to protect themselves from insect herbivores. Camellia tetracocca, a kind of ancient tea with local popularity, is unique to southwest China. This ancient tea is often attacked by the tea leafhopper. However, there are no relevant reports on changes in volatile components and defense signaling pathways after Camellia tetracocca has been attacked by E. onukii. To reveal changes in the responses of the volatile components of C. tetracocca to E. onukii, the headspace sampling technique and GC-MS were adopted to determine and analyze the volatiles. Furthermore, to unveil the defense mechanisms of C. tetracocca in response to E. onukii, transcriptome analysis was applied to damaged tea leaves and healthy leaves. The GC-MS analysis showed significant increases in the linalool and (E)-2-hexenal contents. The transcriptome analysis revealed a set of core pest-responsive genes (3074 upregulated and 5098 downregulated). Most of the enriched pest-responsive genes are mainly involved in plant hormone signal transduction photosynthesis, terpenoid backbone biosynthesis, alpha-linolenic acid metabolism, and the NF-κB signaling pathway. A conjoint analysis of the transcriptome and metabolome indicated that N2-acetylornithine, D-malic acid, theogallin, fucosyllactose, 5-caffeoylquinic acid, fumarprotocetraric acid, and arabinogalactose have a significant correlation with LOC114279735, LOC114317534, LOC114282078, LOC114317768, and LOC114263181. This study lays a foundation for further research on the breeding and cultivation of insect-resistant germplasm resources for C. tetracocca and on the promotion and development of the plant.

Numerical study for the combustion analysis of wood volatiles in porous radiant burner for the application of biomass cooking stove

This article presents a computational study of wood volatiles combustion in a two-layer porous radiant burner (PRB) at different power inputs (1–3 kW) and porosity ranges from 0.7 to 0.9 respectively. A 2-D computational model is designed to numerically solve the combustion of wood-volatiles and air. A finite volume technique is utilized to solve governing equations including; continuity equation, momentum equation, species transport equation, radiative transport equation, and gas and solid phases energy equations. The utilized model is validated with previous literature for a two-layer porous radiant burner and the deviation of comparison is found within the acceptable range. The results reveal that the higher temperature was found in the central part of the burner and the minimum at the circumference. The longitudinal temperature distribution along the central line ruled out the occurrence of flashbacks. Moreover, the transport species contours reveal that the maximum combustion reactions occur in the upper layer of the porous zone. Further, the radiation efficiency decreases with input power and increases with porosity. The maximum value of radiation efficiency is found 36% at 1 kW and porosity of 0.9. while the minimum is 26% found at 3 kW and porosity of 0.7. The overall assessment showed that the PRB-based cooking stove is capable for providing a desired temperature range and efficient radiation efficiency in the range of 1–3 kW of power input.

Optimization of volatile compound extraction on cooked meat using HS-SPME-GC-MS, and evaluation of diagnosis to meat species using volatile compound by multivariate data analysis

Meat and meat products are often adulterated deliberately with more than one species which have ethical concern and some health risk also. Hence species authentication is very necessary and flavor is an important attribute to identify meat species. This study aimed to optimize the volatile flavour compound extraction conditions, analysis, and species authentication from cooked beef, pork, and chicken using HS-SPME-GC-MS with multivariate analysis. The 50/30 μm DVB/CAR/PDMS fiber with 30 min extraction at 60 °C provides the best results. Fifty compounds were identified, of which aldehydes were the most abundant, followed by alcohols. PLS-DA plot & heatmap indicated that beef has a distinct flavor profile, whereas pork and chicken have little similarities. Most aldehydes were significantly different among the species (P < 0.05). Undecanal, 2-undecanone, 4-octanol, 2-undecenal, 1-octanol for beef; hexanal, 1-octen-3-ol, 4-methyl phenol, dodecane, undecane for pork and benzeneacetaldehyde for chicken can be used as discriminating biomarkers. Moreover, undecanal, hexanal, benzaldehyde, nonanal, benzeneacetaldehyde, 1-octanol, heptanol, and undecane significantly differed with high VIP (>1) scores. They played an important role in distinguishing the meat species. Thus, this method can be reliable and fastened to distinguish meat species and explore volatile profiles.

An Investigative Analysis of Volatility in the Cryptocurrency Market

The growing global fascination with cryptocurrencies has sparked heightened interest, driven by their pronounced market volatility. This particular study endeavors to assess the risk and rewards associated with four prominent cryptocurrencies, while also delving into an examination of their interrelationships and fluctuation patterns. The investigation is based on daily closing prices spanning from January 1, 2017, to June 30, 2022. To unravel the spillover and asymmetrical repercussions of volatility, we employ various models from the GARCH family, most notably the DCC GARCH and EGARCH models. In addition, Granger causality is harnessed to uncover any causal connections among these digital assets. The findings underscore a noteworthy spillover phenomenon between Bitcoin and Ethereum, the two foremost cryptocurrencies boasting the maximum market capitalization. This spillover effect manifests as symmetric volatility impacts, setting them apart from Litecoin and RIPPLE.

Spillovers across the Asian OPEC+ Financial Market

This research utilizes the Diebold and Yilmaz spillover model to examine the correlation between geopolitical events, natural disasters, and oil stock returns in Asian OPEC+ member countries. The study extends prior research by investigating the dynamics of the Asian OPEC+ oil market in light of recent exogenous events. The analysis commences by creating a self-generated Asian OPEC+ index, which demonstrates significant volatility, as indicated by GARCH (1, 1) model estimation. The results obtained from the Diebold and Yilmaz spillover test indicate that, on average, there is a moderate degree of connectedness among the variables. However, in the event of global-level shocks or shocks specifically affecting Asian OPEC+ countries, a heightened level of connectedness is found. Prominent instances of spillover events observed in the volatility analysis conducted during the previous decade include the COVID-19 pandemic, the conflict between Russia and Ukraine, and the Turkey earthquake of 2023. Based on the facts, it is recommended that investors take into account the potential risks linked to regions that are susceptible to natural calamities and geopolitical occurrences while devising their portfolios for oil stocks. The results further highlight the significance of integrating these aspects into investors’ decision-making procedures and stress the need for risk management tactics that consider geopolitical risks and natural disasters in the oil equity market.

Instability constraints and development traps: an empirical analysis of growth cycles and economic volatility in Latin America

Instability constraints and development traps: an empirical analysis of growth cycles and economic volatility in Latin America