Journal of Risk and Financial Management

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19 pages, 795 KiB

Open AccessArticle

Eurozone Stock Market Reaction to Monetary Policy Interventions and Other Covariates

by Nikolaos Petrakis, Christos Lemonakis, Christos Floros and Constantin Zopounidis

J. Risk Financial Manag. 2022, 15(2), 56; https://doi.org/10.3390/jrfm15020056 - 26 Jan 2022

Cited by 5 | Viewed by 4032

Abstract

The joint effect of the global economic and sovereign debt crisis forced the European Central Bank (ECB) to apply conventional and non-standard expansionary monetary policy interventions in order to stabilize eurozone economies. We conducted a panel regression econometric analysis to study the influence [...] Read more.

The joint effect of the global economic and sovereign debt crisis forced the European Central Bank (ECB) to apply conventional and non-standard expansionary monetary policy interventions in order to stabilize eurozone economies. We conducted a panel regression econometric analysis to study the influence of euro area monetary authority policy interventions, along with two main macroeconomic variables and a sentiment indicator, on market equity returns of eurozone countries for the period January 2007 to December 2017. Our findings suggest that conventional and non-standard monetary policy innovations had a positive lagged impact on equity returns of euro area monetary markets. More specifically, interest rate cuts evenly influenced market indices while non-conventional actions mainly affected core eurozone countries that were less affected by the crisis. We also document a strong negative relationship between inflation rates and market returns. In addition, the sentiment indicator produces positive effects on returns because it contains information that is not incorporated into other macro variables. Full article

(This article belongs to the Special Issue Economic Forecasting)

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14 pages, 657 KiB

Open AccessArticle

Exports and Imports-Led Growth: Evidence from a Small Developing Economy

by Humnath Panta, Mitra Lal Devkota and Dhruba Banjade

J. Risk Financial Manag. 2022, 15(1), 11; https://doi.org/10.3390/jrfm15010011 - 1 Jan 2022

Cited by 12 | Viewed by 6331

Abstract

This paper examines equilibrium relationships and dynamic causality between economic growth, exports, and imports in Nepal using time-series data between 1965 and 2020. This research examines the impact of exports and imports on the economic growth of Nepal and documents empirical evidence in [...] Read more.

This paper examines equilibrium relationships and dynamic causality between economic growth, exports, and imports in Nepal using time-series data between 1965 and 2020. This research examines the impact of exports and imports on the economic growth of Nepal and documents empirical evidence in exports-led growth, imports-led growth, growth-led exports, and growth-led imports hypotheses in both the short and long run. The test results show no evidence favoring the exports-led growth and growth-led exports hypotheses in both the short and long run. However, the study finds evidence supporting the imports-led growth hypothesis in the short term and the growth-led imports hypothesis in the long term. Overall, this paper finds no evidence in favor of the notion that foreign trade supports the economic growth of Nepal in the long run. The research findings may have important implications for policymakers in Nepal. The paper contributes to trade and economic growth literature by investigating the relationship between exports, imports, capital, and gross domestic products in a small economy such as Nepal, where exports make a minimal and imports make an extensive contribution to gross domestic products by using cointegration and the vector error correction model. Full article

(This article belongs to the Special Issue Economic Forecasting)

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17 pages, 764 KiB

Open AccessArticle

The Time-Varying Relation between Stock Returns and Monetary Variables

by David G. McMillan

J. Risk Financial Manag. 2022, 15(1), 9; https://doi.org/10.3390/jrfm15010009 - 31 Dec 2021

Cited by 6 | Viewed by 3370

Abstract

The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes over time, and [...] Read more.

The nature of the relation between stock returns and the three monetary variables of interest rates (bond yields), inflation and money supply growth, while oft studied, is one that remains unclear. We argue that the nature of the relation changes over time, and this variation is largely driven by shocks, with a change in risk associated with each variable shifting the pattern of behaviour. We show a change in the correlation between each of the three variables with stock returns. Notably, a predominantly negative correlation with bond yields and inflation becomes positive, while the opposite is true for money supply growth. The shift begins with the bursting of the dotcom bubble but is exacerbated by the financial crisis. Results of predictive regressions for stock returns also indicate a switch in behaviour. Predominantly negative predictive power switches temporarily to positive around economic shocks. This suggests that higher yields, inflation and money growth typically depress returns but support the market during periods of stress. However, after the financial crisis, higher inflation and money growth exhibit persistent positive predictive power and suggest a change in the risk perception of higher values. Full article

(This article belongs to the Special Issue Economic Forecasting)

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27 pages, 1943 KiB

Open AccessArticle

Sticky Stock Market Analysts

by Ibrahim Filiz, Jan René Judek, Marco Lorenz and Markus Spiwoks

J. Risk Financial Manag. 2021, 14(12), 593; https://doi.org/10.3390/jrfm14120593 - 9 Dec 2021

Viewed by 2514

Abstract

Technological progress in recent years has made new methods available for making forecasts in a variety of areas. We examine the success of ex-ante stock market forecasts of three major stock market indices, i.e., the German Stock Market Index (DAX), the Dow Jones [...] Read more.

Technological progress in recent years has made new methods available for making forecasts in a variety of areas. We examine the success of ex-ante stock market forecasts of three major stock market indices, i.e., the German Stock Market Index (DAX), the Dow Jones Industrial Index (DJI), and the Euro Stoxx 50 (SX5E). We test whether the forecasts prove true when they reach their effective dates and are therefore suitable for active investment strategies. We revive the thoughts of the American sociologist William Fielding Ogburn, who argues that forecasters consistently underestimate the variability of the future. In addition, we draw on some contemporary measures of forecast quality (prediction-realization diagram, test of unbiasedness, and Diebold–Mariano test). We reveal that (a) unusual events are underrepresented in the forecasts, (b) the dispersion of the forecasts lags behind that of the actual events, (c) the slope of the regression lines in the prediction-realization diagram is <1, (d) the forecasts are highly biased, and (e) the quality of the forecasts is not significantly better than that of naïve forecasts. The overall behavior of the forecasters can be described as “sticky” because their forecasts adhere too strongly to long-term trends in the indices and are thus characterized by conservatism. Full article

(This article belongs to the Special Issue Economic Forecasting)

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17 pages, 5831 KiB

Open AccessArticle

Forecasting Stochastic Volatility Characteristics for the Financial Fossil Oil Market Densities

by Per Bjarte Solibakke

J. Risk Financial Manag. 2021, 14(11), 510; https://doi.org/10.3390/jrfm14110510 - 22 Oct 2021

Cited by 2 | Viewed by 1852

Abstract

This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets (Brent oil and WTI oil) for the period 2011–2021. The main objective is to make step ahead volatility predictions for the front month contracts followed by an implication discussion [...] Read more.

This paper builds and implements multifactor stochastic volatility models for the international oil/energy markets (Brent oil and WTI oil) for the period 2011–2021. The main objective is to make step ahead volatility predictions for the front month contracts followed by an implication discussion for the market (differences) and observed data dependence important for market participants, implying predictability. The paper estimates multifactor stochastic volatility models for both contracts giving access to a long-simulated realization of the state vector with associated contract movements. The realization establishes a functional form of the conditional distributions, which are evaluated on observed data giving the conditional mean function for the volatility factors at the data points (nonlinear Kalman filter). For both Brent and WTI oil contracts, the first factor is a slow-moving persistent factor while the second factor is a fast-moving immediate mean reverting factor. The negative correlation between the mean and volatility suggests higher volatilities from negative price movements. The results indicate that holding volatility as an asset of its own is insurance against market crashes as well as being an excellent diversification instrument. Furthermore, the volatility data dependence is strong, indicating predictability. Hence, using the Kalman filter from a realization of an optimal multifactor SV model visualizes the latent step ahead volatility paths, and the data dependence gives access to accurate static forecasts. The results extend market transparency and make it easier to implement risk management including derivative trading (including swaps). Full article

(This article belongs to the Special Issue Economic Forecasting)

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17 pages, 2191 KiB

Open AccessArticle

Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails

by Tamás Kiss, Hoang Nguyen and Pär Österholm

J. Risk Financial Manag. 2021, 14(11), 506; https://doi.org/10.3390/jrfm14110506 - 20 Oct 2021

Cited by 1 | Viewed by 1898

Abstract

In this paper, we analysed the heavy-tailed behaviour in the dynamics of housing-price returns in the United States. We investigated the sources of heavy tails by estimating autoregressive models in which innovations can be subject to GARCH effects and/or non-Gaussianity. Using monthly data [...] Read more.

In this paper, we analysed the heavy-tailed behaviour in the dynamics of housing-price returns in the United States. We investigated the sources of heavy tails by estimating autoregressive models in which innovations can be subject to GARCH effects and/or non-Gaussianity. Using monthly data from January 1954 to September 2019, the properties of the models were assessed both within- and out-of-sample. We found strong evidence in favour of modelling both GARCH effects and non-Gaussianity. Accounting for these properties improves within-sample performance as well as point and density forecasts. Full article

(This article belongs to the Special Issue Economic Forecasting)

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22 pages, 1080 KiB

Open AccessArticle

Variable Slope Forecasting Methods and COVID-19 Risk

by Jonathan Leightner, Tomoo Inoue and Pierre Lafaye de Micheaux

J. Risk Financial Manag. 2021, 14(10), 467; https://doi.org/10.3390/jrfm14100467 - 3 Oct 2021

Cited by 5 | Viewed by 1881

Abstract

There are many real-world situations in which complex interacting forces are best described by a series of equations. Traditional regression approaches to these situations involve modeling and estimating each individual equation (producing estimates of “partial derivatives”) and then solving the entire system for [...] Read more.

There are many real-world situations in which complex interacting forces are best described by a series of equations. Traditional regression approaches to these situations involve modeling and estimating each individual equation (producing estimates of “partial derivatives”) and then solving the entire system for reduced form relationships (“total derivatives”). We examine three estimation methods that produce “total derivative estimates” without having to model and estimate each separate equation. These methods produce a unique total derivative estimate for every observation, where the differences in these estimates are produced by omitted variables. A plot of these estimates over time shows how the estimated relationship has evolved over time due to omitted variables. A moving 95% confidence interval (constructed like a moving average) means that there is only a five percent chance that the next total derivative would lie outside that confidence interval if the recent variability of omitted variables does not increase. Simulations show that two of these methods produce much less error than ignoring the omitted variables problem does when the importance of omitted variables noticeably exceeds random error. In an example, the spread rate of COVID-19 is estimated for Brazil, Europe, South Africa, the UK, and the USA. Full article

(This article belongs to the Special Issue Economic Forecasting)

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17 pages, 371 KiB

Open AccessArticle

Industry, Firm, and Country Level Dynamics of Capital Structure: A Case of Pakistani Firms

by Idrees Liaqat, Muhammad Asif Khan, József Popp and Judit Oláh

J. Risk Financial Manag. 2021, 14(9), 428; https://doi.org/10.3390/jrfm14090428 - 7 Sep 2021

Cited by 8 | Viewed by 4001

Abstract

The capital structure appears to be one of the most researched and the most controversial areas in modern corporate finance. Prior literature on determinants of capital structure has concentrated on firm and country level factors by employing static modeling. Static modeling has certain [...] Read more.

The capital structure appears to be one of the most researched and the most controversial areas in modern corporate finance. Prior literature on determinants of capital structure has concentrated on firm and country level factors by employing static modeling. Static modeling has certain limitations, which do not allow companies to establish an optimum capital structure in line with economic uncertainty. This study makes a worthy contribution to the existing body of knowledge by filling the gap in the evolution of capital structure by employing a dynamic framework of the financial sector of Pakistan. In addition, the study brings into focus sectors’ importance in determining the firm’s financial behavior. Based on secondary financial sector data from 2006–2019, the article addresses the issues by employing two-step system generalized method of moments (GMM). The findings of the study validated the existence of dynamic capital structure across the financial sector of Pakistan and reinforced the substantial impact of sectors’ unique environment on leverage mechanism. The results are robust under alternative estimation approaches and offer useful policy implications. Full article

(This article belongs to the Special Issue Economic Forecasting)

24 pages, 562 KiB

Open AccessArticle

What Information in Financial Statements Could Be Used to Predict the Risk of Equity Investment?

by Min (Shirley) Liu

J. Risk Financial Manag. 2021, 14(8), 365; https://doi.org/10.3390/jrfm14080365 - 7 Aug 2021

Cited by 2 | Viewed by 2896

Abstract

Theoretically, accounting earnings could be used to estimate the intrinsic value of equity. If accounting earnings could be predicted accurately, then, so could be the value of equity, thereby, creating much less risk in equity investment. However, earnings surprises are common, and therefore [...] Read more.

Theoretically, accounting earnings could be used to estimate the intrinsic value of equity. If accounting earnings could be predicted accurately, then, so could be the value of equity, thereby, creating much less risk in equity investment. However, earnings surprises are common, and therefore so is the risk in equity investment. To quantify the risk in the investment implied from accounting earnings, I propose to use financial statements to construct abnormal sales growth rates (ABG) and abnormal changes in profit margins (ABPM) to measure the uncertainty embedded in the accounting earnings. I measure ABG (ABPM) as the difference between the current value of sales growth rate (profit margin) and its benchmark, a weighted value of the three preceding years’ sales growth rate (profit margin). Then, I quantify whether and to what extent the news of ABG and ABPM are material enough to change the expected earnings (proxied by analysts’ forecasted earnings revisions [FREV] and predicted unexpected earnings [UE], and future stock returns [SAR]). Fama–MacBeth regression results show that, together, solely ABPM and ABG could explain 8.2% (2.3%) (5.4%) of the variation of FREV (UE) (SAR). The risk-predictability of ABPM and ABG is robust to the presence of abnormal growth in net operating assets and accruals quality, which, suggested by previous literature, might influence unexpected earnings. Further contingent analyses indicate that the capital market reacts more strongly to the bad news embedded in the ABPM/ABG (with negative signs) than the good news in ABPM/ABG (with positive signs). Full article

(This article belongs to the Special Issue Economic Forecasting)

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18 pages, 446 KiB

Open AccessArticle

Cash Holding and Firm Value in the Presence of Managerial Optimism

by Ashfaq Habib, M. Ishaq Bhatti, Muhammad Asif Khan and Zafar Azam

J. Risk Financial Manag. 2021, 14(8), 356; https://doi.org/10.3390/jrfm14080356 - 4 Aug 2021

Cited by 7 | Viewed by 4488

Abstract

Cash holding is important for Chinese manufacturing firms coping with the increasing costs of financing and tough economic conditions. This study examines the impact of cash holding on the firm value of Chinese manufacturing businesses. We found evidence that a non-linear relationship exists [...] Read more.

Cash holding is important for Chinese manufacturing firms coping with the increasing costs of financing and tough economic conditions. This study examines the impact of cash holding on the firm value of Chinese manufacturing businesses. We found evidence that a non-linear relationship exists between cash holding and firm value in these companies. The study reveals that a higher level of cash holding in financially constrained firms negatively affects the firm value, while unconstrained firms with a less cash holding level have a better firm value. Finally, this research is enriched by implementing the novel measure of managerial optimism. Revealed is the interactive role of cash holding and optimism and how they affect firm value. The study concludes that managerial optimism influences a firm’s cash holding decisions, and this is more costly for unconstrained firms. Full article

(This article belongs to the Special Issue Economic Forecasting)

20 pages, 1662 KiB

Open AccessArticle

Modelling Systemically Important Banks vis-à-vis the Basel Prudential Guidelines

by M. Zulkifli Salim and Kevin Daly

J. Risk Financial Manag. 2021, 14(7), 295; https://doi.org/10.3390/jrfm14070295 - 26 Jun 2021

Cited by 5 | Viewed by 2871

Abstract

Our paper investigates Indonesia’s systemically important banks (SIBs) using theoretical approaches—CoVaR, marginal expected shortfall (MES), and SRISK—to compare with the Basel guidelines as benchmark. We use Indonesian banks’ market and supervisory data over the 2008–2019 period. The research aims to seek intertheoretical model [...] Read more.

Our paper investigates Indonesia’s systemically important banks (SIBs) using theoretical approaches—CoVaR, marginal expected shortfall (MES), and SRISK—to compare with the Basel guidelines as benchmark. We use Indonesian banks’ market and supervisory data over the 2008–2019 period. The research aims to seek intertheoretical model interaction and SIB ranking in concordance with the Basel guidelines as applied by a bank supervisor. The findings show that SRISK produced a more consistent ranking compared with CoVaR and MES. CoVaR and MES had higher intermodel correlation converted to 59% similarity in rankings. Further, all theoretical models are in line with the Basel guidelines, where the closest approximation is at 47%. The results indicate that policy makers could use scholarly models as validation tools and help improve supervision decision to identify systemically important institutions. Full article

(This article belongs to the Special Issue Economic Forecasting)

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13 pages, 691 KiB

Open AccessArticle

Tax Rates and Tax Revenues in the Context of Tax Competitiveness

by Martina Helcmanovská and Alena Andrejovská

J. Risk Financial Manag. 2021, 14(7), 284; https://doi.org/10.3390/jrfm14070284 - 22 Jun 2021

Cited by 6 | Viewed by 2904

Abstract

The diverse tax burdens and economic situations of EU member states are causing investors to relocate their investments to countries that offer better tax conditions and a better economic environment. The total amount of corporate tax revenue is therefore influenced by tax, macroeconomic [...] Read more.

The diverse tax burdens and economic situations of EU member states are causing investors to relocate their investments to countries that offer better tax conditions and a better economic environment. The total amount of corporate tax revenue is therefore influenced by tax, macroeconomic and other indicators. This paper assesses the importance of tax revenues and tax rates in the context of tax competitiveness in EU states. The aim of the paper is to determine the impact of selected indicators on corporate tax revenues in EU states for the period 2004 to 2019. The source data were drawn from the databases of the European Commission (2021) and The World Bank (2021). The set goal was complemented by an analysis of tax rates and subsequent comparison with corporate tax revenues. Multiple regression analysis was performed to achieve the goal. Two econometric models were compiled that followed the same variables, with the EU13 model dealing with the new member states and the EU15 model dealing with the old EU member states. The results showed that the variables statutory and average effective tax rate do not have a decisive influence on corporate tax revenues in either model. In the new states, the unemployment rate has the most statistically significant effect, while in the old countries GDP has the biggest effect. The result of this work is that there are differences between the new and old member states at different levels, which was ultimately reflected in the different impact of tax and macroeconomic indicators on corporate tax revenues. Full article

(This article belongs to the Special Issue Economic Forecasting)

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14 pages, 611 KiB

Open AccessArticle

Financial Contagion: A Tale of Three Bubbles

by Nathan Burks, Adetokunbo Fadahunsi and Ann Marie Hibbert

J. Risk Financial Manag. 2021, 14(5), 229; https://doi.org/10.3390/jrfm14050229 - 20 May 2021

Cited by 2 | Viewed by 3834

Abstract

The primary purpose of the study is to identify and measure the properties of asset bubbles, volatility clustering, and financial contagion during three recent financial market anomalies that originated in the U.S. and Chinese markets. In particular, we focus on the 2000 DotCom [...] Read more.

The primary purpose of the study is to identify and measure the properties of asset bubbles, volatility clustering, and financial contagion during three recent financial market anomalies that originated in the U.S. and Chinese markets. In particular, we focus on the 2000 DotCom Bubble, the 2008 Housing Crisis, and the 2015 Chinese Bubble. We employ three main empirical methods; the LPPL model to identify asset bubbles, the DCC-GARCH model to measure volatility clustering, and the Diebold-Yilmaz volatility spillover index to measure the level of financial contagion. We provide robust evidence that during the DotCom bubble there was very limited spillover between the S&P 500, the Shanghai, and the Shenzhen Composite Indexes. However, there was significantly more spillover effects in the two more recent crises, i.e., the Housing crisis and the 2015 Chinese Bubble. Together, these results highlight the fact that as financial markets have become more globalized, there are greater levels of volatility transmission and correspondingly fewer potential benefits from international diversification. Full article

(This article belongs to the Special Issue Economic Forecasting)

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23 pages, 3113 KiB

Open AccessArticle

Empirical Estimation of Intraday Yield Curves on the Italian Interbank Credit Market e-MID

by Anastasios Demertzidis and Vahidin Jeleskovic

J. Risk Financial Manag. 2021, 14(5), 212; https://doi.org/10.3390/jrfm14050212 - 8 May 2021

Cited by 1 | Viewed by 2642

Abstract

This paper introduces a major novelty: the empirical estimation of spot intraday yield curves based on tick-by-tick data on the Italian electronic interbank credit market (e-MID). To analyze the consequences of the recent financial crisis, we split the data into four periods, which [...] Read more.

This paper introduces a major novelty: the empirical estimation of spot intraday yield curves based on tick-by-tick data on the Italian electronic interbank credit market (e-MID). To analyze the consequences of the recent financial crisis, we split the data into four periods, which include events before, during, and after the recent financial crisis starting in 2007. Our first result is that, from a practical point of view, the intraday yield curve can be modeled by standard models for yield curves providing advantages for intraday trading on intraday interbank credit markets. Moreover, the estimates show that the systematic dynamics in the intraday yield curves during the turmoil were highly noticeable, resulting in a significantly better goodness-of-fit. Based on this fact, we infer that investors in the interbank credit market base their investment decisions on the effects of the intraday dynamics of intraday interest rates more intensively during a financial crisis. Therefore, the systematic impact on the e-MID appears to be stronger and econometric modeling of the intraday interest rate curve becomes even more attractive during a turmoil. Full article

(This article belongs to the Special Issue Economic Forecasting)

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18 pages, 384 KiB

Open AccessArticle

Firm, Industry and Macroeconomics Dynamics of Stock Returns: A Case of Pakistan Non-Financial Sector

by Mirza Muhammad Naseer, Muhammad Asif Khan, József Popp and Judit Oláh

J. Risk Financial Manag. 2021, 14(5), 190; https://doi.org/10.3390/jrfm14050190 - 22 Apr 2021

Cited by 6 | Viewed by 5110

Abstract

The available research literature on stock performance has primarily stressed the importance of asset price theories, macroeconomic and microeconomic, and institutional differences. However, there is still an open question: Are there any other factors those influence stock performance? This research aims to answer [...] Read more.

The available research literature on stock performance has primarily stressed the importance of asset price theories, macroeconomic and microeconomic, and institutional differences. However, there is still an open question: Are there any other factors those influence stock performance? This research aims to answer this question by providing new insights into industry factors along with country-level and firm-specific factors in conjunction with the stock performance of the non-financial sector firms listed at the Pakistan Stock Exchange. The study provides new insights into the prevailing research literature by considering an emerging economy, Pakistan. We find that non-financial sector firms are heterogeneous, suggesting applying a fixed effect approach for reliable estimation. To investigate the issue, data from 80 companies spanning 17 years (2004–2020) were analyzed with a fixed-effect model. Our study results revealed that firm tangibility, munificence, gross domestic product, inflation and money supply have negative, while size, growth, dynamism, Herfindahl–Hirschman index, exchange rate and oil prices have a positive relationship with financial performance. The results are robust under alternative estimation approaches and offer useful policy implications. Full article

(This article belongs to the Special Issue Economic Forecasting)

Review

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24 pages, 474 KiB

Open AccessReview

Economic Trends in the Transition into a Circular Bioeconomy

by Manfred Kircher

J. Risk Financial Manag. 2022, 15(2), 44; https://doi.org/10.3390/jrfm15020044 - 19 Jan 2022

Cited by 11 | Viewed by 4550

Abstract

The shift away from fossil fuels needed to reduce CO₂ emissions requires the use of renewable carbon and energy sources, including biomass in the bioeconomy. Already today, the bioeconomy has a significant share in the EU economy with traditionally bio-based sectors. For [...] Read more.

The shift away from fossil fuels needed to reduce CO₂ emissions requires the use of renewable carbon and energy sources, including biomass in the bioeconomy. Already today, the bioeconomy has a significant share in the EU economy with traditionally bio-based sectors. For the future, the energy, mobility and chemical sectors have additional high expectations of the bioeconomy, especially for agriculture and forestry to produce biomass as an industrial feedstock. Numerous studies have been published on the availability of feedstocks, but these often only look at individual applications. Looking at the total demand and considering the sustainability limits of biomass production leads to the conclusion that the expected demand for all industries that could process biomass exceeds the sustainably available capacity. To mitigate this conflict between feedstock demand and availability, it is proposed that the organic chemical sector be fully integrated into the bioeconomy and the energy sector be only partially integrated. In addition, recycling of wastes and residues including CO₂ should lead to a circular bioeconomy. The purpose of this manuscript is to help fill the research gap of quantitatively assessing the demand and supply of biomass, to derive economic trends for the current transition phase, and to further develop the theoretical concept of the bioeconomy towards circularity. Full article

(This article belongs to the Special Issue Economic Forecasting)

28 pages, 671 KiB

Open AccessReview

Measurement of Economic Forecast Accuracy: A Systematic Overview of the Empirical Literature

by Goran Buturac

J. Risk Financial Manag. 2022, 15(1), 1; https://doi.org/10.3390/jrfm15010001 - 21 Dec 2021

Cited by 6 | Viewed by 7501

Abstract

The primary purpose of the paper is to enable deeper insight into the measurement of economic forecast accuracy. The paper employs the systematic literature review as its research methodology. It is also the first systematic review of the measures of economic forecast accuracy [...] Read more.

The primary purpose of the paper is to enable deeper insight into the measurement of economic forecast accuracy. The paper employs the systematic literature review as its research methodology. It is also the first systematic review of the measures of economic forecast accuracy conducted in scientific research. The citation-based analysis confirms the growing interest of researchers in the topic. Research on economic forecast accuracy is continuously developing and improving with the adoption of new methodological approaches. An overview of the limits and advantages of the methods used to assess forecast accuracy not only facilitate the selection and application of appropriate measures in future analytical works but also contribute to a better interpretation of the results. In addition to the presented advantages and disadvantages, the chronological presentation of methodological development (measures, tests, and strategies) provides an insight into the possibilities of further upgrading and improving the methodological framework. The review of empirical findings, in addition to insight into existing results, indicates insufficiently researched topics. All in all, the results presented in this paper can be a good basis and inspiration for creating new scientific contributions in future works. Full article

(This article belongs to the Special Issue Economic Forecasting)

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