Earnings forecasts and idiosyncratic volatilities

Kryzanowski, Lawrence; Mohsni, Sana

doi:10.1016/j.irfa.2015.06.001

Cited by 6 publications

(3 citation statements)

References 79 publications

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“…Similarly, we controlled for the financial solvency ratio as a firm's long‐term debt/equity ratio (Zarb, 2018). Return on equity (ROE) was also included in the analysis as a factor influencing investors' decisions and stock market volatility (Kryzanowski & Mohsni, 2015). We included a dummy variable to control for the organizational structure of firms in the sample (Ezzamel & Watson, 1993); it was coded one for holding companies and zero if the firm is an operating firm.…”

Section: Methodsmentioning

confidence: 99%

Forecasting volatility by integrating financial risk with environmental, social, and governance risk

Capelli¹,

Ielasi

Russo

2021

Corp Soc Responsibility Env

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The study aims to verify whether the consideration of a risk measure based on environmental, social, and governance (ESG) factors can reduce the difference between the ex‐ante financial risk and ex‐post volatility of financial assets. The statistical models are run on 17,996 firm‐year observations (3332 active firms from 55 countries and 10 industries, listed on the ECPI Global Ethical Equity index) in 2007–2015. According to our main results, the forecasting effectiveness of traditional financial risk measures can be improved by integrating financial risk with an ESG risk measure that considers the ESG entropy. We found that the dispersion of ESG scores within a country, sector and year is a risk factor that would be helpful in predicting the volatility of financial assets. Other similar long‐run risk measures, such as issuers' credit ratings, do not reveal the same forecasting power. By reducing unexpected volatility, especially in the medium term, the ESG risk measure provides investors and fund managers with a useful metric for decision making.

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Section: Methodsmentioning

confidence: 99%

Forecasting volatility by integrating financial risk with environmental, social, and governance risk

Capelli¹,

Ielasi

Russo

2021

Corp Soc Responsibility Env

View full text Add to dashboard Cite

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“…Pyramid decomposition is an instrument utilised for advanced analysis, and many authors applied this method (e.g., Borodin et al, 2021;Dluhošová, 2004Dluhošová, , 2021Jencova et al, 2018;Jeppson, 2021;Jin and Yan, 2017;Kryzanowski and Mohsni, 2015;Szymańska, 2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic and Static Decomposition Analysis of the Czech Automotive Production Sector

Dluhosova,

Lisztwanova,

Poncik

et al. 2022

ERSJ

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Purpose:The objective of the paper is to analyse financial performance through the economic value added (EVA) measure of the Czech automotive production sector, NACE 29, in the years 2015-2019, using dynamic and static decomposition methods. Design/Methodology/Approach: The applied methods are as follows: literature review, economic value-added measure formulation, pyramid decomposition, static decomposition deviation analysis, and dynamic decomposition deviation analysis due to variance analysis. Findings: The static analysis results showed the non-stability of the crucial influential factors in both absolute and relative EVA measures. Dynamic decomposition analysis can reveal fundamental ratios influencing the EVA measure dynamically in state span. It was verified that the functional decomposition method is suitable for static analysis modelling positive and negative ratio deviations. The dynamic decomposition analysis based on the variance analysis method is appropriate for problem modelling. It was found that the Czech automotive sector is declining in relative EVA measures. Practical Implications: Knowing the ranking and volume of influential financial factors of financial performance allows one to manage operational and strategic objectives successfully. Declining relative EVA measures, even if positive, reveal the necessity to correct and improve the management, financial and business model. Originality/Value: The study contributes to the analysis of crucial sectors of the Czech economy, and the dynamic aspect is investigated as well. The findings can provide a better understanding of the development of the automotive production sector. Furthermore, crucial financial ratios are defined for managerial decision-making.

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“…Three authors [4][5][6][7] have, for instance, applied EVA performance measures. A financial performance measure can be decomposed by the pyramid (DuPont) method in several financial ratios and simulated as their function with correlations, obtaining a more robust prediction (see [8][9][10][11][12][13]). (b) A crucial problem in financial decision making is achieving good financial forecasting, and researchers have verified various methods (see [14][15][16][17][18][19]).…”

Section: Introductionmentioning

confidence: 99%

Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy

et al. 2023

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The paper is focused on predicting the financial performance of a small open economy with an automotive industry with an above-standard share. The paper aims to predict the probability distribution of the decomposed relative economic value-added measure of the automotive production sector NACE 29 in the Czech economy. An advanced Monte Carlo simulation prediction model is applied using the exact pyramid decomposition function. The problem is modelled using advanced stochastic process instruments such as Levy-driven mean-reversion, skew t-regression, normal inverse Gaussian distribution, and t-copula interdependencies. The proposed method procedure was found to fit the investigated financial ratios sufficiently, and the estimation was valid. The decomposed approach allows the reflection of the ratios’ complex relationships and improves the prediction results. The decomposed results are compared with the direct prediction. Precision distribution tests confirmed the superiority of the decomposed approach for particular data. Moreover, the Czech automotive sector tends to decrease the mean value and median of financial performance in the future with negative asymmetry and high volatility hidden in financial ratios decomposition. Scholars can generally use forecasting methods to investigate economic system development, and practitioners can obtain quality and valuable information for decision making.

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Earnings forecasts and idiosyncratic volatilities

Cited by 6 publications

References 79 publications

Forecasting volatility by integrating financial risk with environmental, social, and governance risk

Forecasting volatility by integrating financial risk with environmental, social, and governance risk

Dynamic and Static Decomposition Analysis of the Czech Automotive Production Sector

Distribution Prediction of Decomposed Relative EVA Measure with Levy-Driven Mean-Reversion Processes: The Case of an Automotive Sector of a Small Open Economy

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