Journal of Risk and Financial Management

Research

18 pages, 1556 KiB

Open AccessArticle

The Effects of Climate Change to Weather-Related Environmental Hazards: Interlinkages of Economic Factors and Climate Risk

by George Halkos and Argyro Zisiadou

J. Risk Financial Manag. 2023, 16(5), 264; https://doi.org/10.3390/jrfm16050264 - 5 May 2023

Cited by 3 | Viewed by 1857

Abstract

Climate change has become an increasingly intense global phenomenon in recent years. A great number of researchers support the idea that climate change is strongly connected to some environmental hazards, and specifically, those correlated to extreme weather events. Following the Paris Agreement, and [...] Read more.

Climate change has become an increasingly intense global phenomenon in recent years. A great number of researchers support the idea that climate change is strongly connected to some environmental hazards, and specifically, those correlated to extreme weather events. Following the Paris Agreement, and due to the increased concern regarding climate change impacts, several indices have been established. The Climate Change Performance Index (CCPI) includes 59 countries and the EU, which cumulatively emit 92% of global greenhouse gases (GHGs), while the Global Climate Risk Index (CRI) analyzes to what extend countries have been affected by impacts of weather-related loss events. Both indices provide annual scores to each country and rank them based on those scores indicating the existing environmental situation. Our main purpose is to examine whether there is an interconnection between those two indices as well as testify whether economic growth is a great contributor to country’s environmental performance and as a result to climate risk. Using a sample of the reported countries for the year 2019, the latest reported year for both indices, and following a cross-sectional econometric analysis, we provide evidence regarding the connection of CCPI and CRI by using graphs, mapping visualization and econometric estimations in order to draw lines between indices. Moreover, we examine the interlinkages, and we estimate the influence caused by socio-economic factors and emissions levels per country. We provide evidence regarding the high-ranked and low-ranked countries and how they perform not only to an environmental base, but also to an economic base. Regarding the major finding, based on our analysis, no proven causality between CRI and CCPI was observed. Economic growth appears to have a significant impact on CRI but not on the CCPI, for the year 2019, while population density has an impact on both indices. Regarding greenhouse gas emissions, the econometric estimations provide evidence of significance for CRI but not for CCPI. An in-depth understanding of the current situation as well as of the factors affecting the climate conditions will give us the needed elements in order to minimize the adverse impact, if not improve the current situation. It is well known and stated that climate action should be taken so that we bequeath a safer and more sustainable planet to the next generations. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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24 pages, 8003 KiB

Open AccessArticle

Portfolio Volatility Estimation Relative to Stock Market Cross-Sectional Intrinsic Entropy

by Claudiu Vințe and Marcel Ausloos

J. Risk Financial Manag. 2023, 16(2), 114; https://doi.org/10.3390/jrfm16020114 - 11 Feb 2023

Viewed by 2255

Abstract

Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market indices, or other portfolios is of great importance to professional fund managers and individual investors alike. Our research uses the cross-sectional intrinsic entropy (CSIE) [...] Read more.

Selecting stock portfolios and assessing their relative volatility risk compared to the market as a whole, market indices, or other portfolios is of great importance to professional fund managers and individual investors alike. Our research uses the cross-sectional intrinsic entropy (CSIE) model to estimate the cross-sectional volatility of the stock groups that can be considered together as portfolio constituents. The CSIE market volatility estimate is based on daily traded prices—open, high, low, and close (OHLC)—along with the daily traded volume for symbols listed on the considered market. In our study, we benchmark portfolio volatility risks against the volatility of the entire market provided by the CSIE and the volatility of market indices computed using longitudinal data. This article introduces CSIE-based betas to characterise the relative volatility risk of the portfolio against market indices and the market as a whole. We empirically prove that, through CSIE-based betas, multiple sets of symbols that outperform the market indices in terms of rate of return while maintaining the same level of risk or even lower than the one exhibited by the market index can be discovered, for any given time interval. These sets of symbols can be used as constituent stock portfolios and, in connection with the perspective provided by the CSIE volatility estimates, to hierarchically assess their relative volatility risk within the broader context of the overall volatility of the stock market. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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13 pages, 852 KiB

Open AccessArticle

Using Variable Slope Total Derivative Estimations to Pick between and Improve Macro Models

by Jonathan Leightner

J. Risk Financial Manag. 2022, 15(6), 267; https://doi.org/10.3390/jrfm15060267 - 14 Jun 2022

Cited by 1 | Viewed by 1480

Abstract

Using the same data set, a researcher can obtain very different reduced form estimates just by assuming different macroeconomic models. Reiterative Truncated Projected Least Squares (RTPLS) or Variable Slope Generalized Least Squares (VSGLS) can be used to estimate total derivatives that are not [...] Read more.

Using the same data set, a researcher can obtain very different reduced form estimates just by assuming different macroeconomic models. Reiterative Truncated Projected Least Squares (RTPLS) or Variable Slope Generalized Least Squares (VSGLS) can be used to estimate total derivatives that are not model dependent. These estimates can be used to pick between competing macro models, improve current models, or create new models. A selected survey of RTPLS estimates in the literature reveals several common patterns: (1) as income inequality has surged around the world, the effect of changes in government spending (G), exports (X), and money supply (M-1) on Gross Domestic Product (GDP) have plummeted, (2) decreases in G, X, and M-1 cause GDP to fall more than equal increases in G, X, and M-1 cause GDP to rise, and (3) unusually large increases in G and M-1 cause their effect on GDP to plummet. These common patterns fit with a global glut of savings hypothesis, which predicts that an increase in savings will not cause an increase in production expanding investment. An appropriate model could be built around the idea that investors have a choice between investing to increase production or investing to earn rent or interest. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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15 pages, 1237 KiB

Open AccessArticle

Vague Pension Future: Empirical Evidence from the Israeli Radical Privatized Market

by Ishay Wolf and Smadar Levi

J. Risk Financial Manag. 2022, 15(5), 207; https://doi.org/10.3390/jrfm15050207 - 30 Apr 2022

Viewed by 2654

Abstract

We examine the future benefits of the Israeli privatized pension system, which is considered as a model of transition to funded pension systems worldwide. This research is based on an extensive database obtained from one of the largest traditional private funds in the [...] Read more.

We examine the future benefits of the Israeli privatized pension system, which is considered as a model of transition to funded pension systems worldwide. This research is based on an extensive database obtained from one of the largest traditional private funds in the market. The results paint a concerning picture regarding the adequacy of benefits and quality of life in old age. Israel’s radical privatized pension model signals a warning to other nations. We show that, even with high returns, most individuals cannot handle the magnitude of financial and labor risks accumulated during their career and retirement. We recommend more balanced government intervention as well as the use of risk-sharing mechanisms such as providing minimum pension guarantee and strengthening the unfunded social security pillar. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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21 pages, 1865 KiB

Open AccessArticle

Good Practice Principles in Modelling Defined Contribution Pension Plans

by Kevin Dowd and David Blake

J. Risk Financial Manag. 2022, 15(3), 108; https://doi.org/10.3390/jrfm15030108 - 26 Feb 2022

Cited by 2 | Viewed by 2183

Abstract

We establish 16 good practice principles for modelling defined contribution pension plans. These principles cover the following issues: model specification and calibration; modelling quantifiable uncertainty; modelling member choices; modelling member characteristics, such as occupation and gender; modelling plan charges; modelling longevity risk; modelling [...] Read more.

We establish 16 good practice principles for modelling defined contribution pension plans. These principles cover the following issues: model specification and calibration; modelling quantifiable uncertainty; modelling member choices; modelling member characteristics, such as occupation and gender; modelling plan charges; modelling longevity risk; modelling the post-retirement period; integrating the pre- and post-retirement periods; modelling additional sources of income, such as the state pension and equity release; modelling extraneous factors, such as unemployment risk, activity rates, taxes and welfare entitlements; scenario analysis and stress testing; periodic updating of the model and changing assumptions; and overall fitness for purpose. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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21 pages, 1067 KiB

Open AccessArticle

Stimulating Non-Energy Exports in Trinidad and Tobago: Evidence from a Small Petroleum-Exporting Economy Experiencing the Dutch Disease

by Roger Hosein, Leera Boodram and George Saridakis

J. Risk Financial Manag. 2022, 15(1), 36; https://doi.org/10.3390/jrfm15010036 - 13 Jan 2022

Cited by 3 | Viewed by 2887

Abstract

The motivation for this study hinges around the fact that Trinidad and Tobago (T&T) is suffering from the Dutch disease which inadvertently hinders the growth of non-energy exports. This paper examines measures that can be adopted for a small petroleum-exporting economy to dampen [...] Read more.

The motivation for this study hinges around the fact that Trinidad and Tobago (T&T) is suffering from the Dutch disease which inadvertently hinders the growth of non-energy exports. This paper examines measures that can be adopted for a small petroleum-exporting economy to dampen the effect of Dutch disease by promoting non-energy trade. This paper is novel and contributes to the literature in using panel data for the T&T case, as it investigates the effect of a devaluation of the TT dollar in order to stimulate non-energy exports (a combination of agriculture and manufacturing trade). Note that previous studies would have examined the Marshall–Lerner condition on the aggregate trade balance which is heavily influenced by energy revenues. The panel autoregressive distributed lag (ARDL) method is used for ten of T&T’s main trading partners for the period 1991 to 2019 to establish findings. The results show that the Marshall–Lerner condition does not hold for aggregate trade in the long run, as expected. However, when non-energy trade is isolated, it is found that a devaluation of the TT dollar does have a positive impact on non-energy trade and the Marshall–Lerner condition holds. Other measures are also recommended to stimulate non-energy exports in the long run. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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23 pages, 1517 KiB

Open AccessArticle

Determinants of Bank Profitability in CEE Countries: Evidence from GMM Panel Data Estimates

by Alexandra Horobet, Magdalena Radulescu, Lucian Belascu and Sandra Maria Dita

J. Risk Financial Manag. 2021, 14(7), 307; https://doi.org/10.3390/jrfm14070307 - 5 Jul 2021

Cited by 26 | Viewed by 7572

Abstract

Given the high resilience of the Central and Eastern Europe (CEE) banking sectors during the last financial crisis and their major role in the CEE region in financing the economy and supporting the high growth rates achieved there, our paper investigates the determinants [...] Read more.

Given the high resilience of the Central and Eastern Europe (CEE) banking sectors during the last financial crisis and their major role in the CEE region in financing the economy and supporting the high growth rates achieved there, our paper investigates the determinants of banking profitability in the CEE banking sectors based on a Generalized Method of Methods (GMM) approach using data between 2009 and 2018. We have selected determinants from the macroeconomic factors and from the financial-banking specific factors using a two-step GMM method. Our findings demonstrate that unemployment rate, inflation, budget balance, non-governmental credit, non-performing loan rates, concentration rate and capitalization rate negatively impact on the banking profitability in the CEE banking sectors. According to these findings, some policy recommendations were elaborated. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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14 pages, 709 KiB

Open AccessArticle

Italexit and the Impact of Immigrants from Italy on the Italian Labor Market

by Mihaela Simionescu

J. Risk Financial Manag. 2021, 14(1), 14; https://doi.org/10.3390/jrfm14010014 - 1 Jan 2021

Cited by 3 | Viewed by 3407

Abstract

Considering the recent debates regarding Brexit and the potential negative effects of immigrants on Italian labor market, the main aim of this paper is to assess the impact of immigrants from Italy on the labor market of this country using econometric techniques. Based [...] Read more.

Considering the recent debates regarding Brexit and the potential negative effects of immigrants on Italian labor market, the main aim of this paper is to assess the impact of immigrants from Italy on the labor market of this country using econometric techniques. Based on these results, one answer regarding the potential exit of Italy from the EU (Italexit) because of the immigration issue is provided. According to a Johansen co-integration test, there was not any long-run relationship between the number of EU immigrants from Italy and the variation of unemployment rate in the period from 1990 to 2019. The estimations based on Bayesian ridge regressions indicated that the number of EU immigrants did not affect labor cost index in business economy, manufacturing or industry, construction and services in the period 2001–2019. The variation in employed immigrants from Italy in the period 2008–2019 depends on changes in risk of poverty or social exclusion, housing cost overburden rate, exports of goods and services, inflation and tax rate on low wage earners and adult participation in learning. Full article

(This article belongs to the Special Issue Macroeconomic Modelling)

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