scholarly journals Market and Accounting Measures of Risk: The Case of the Frankfurt Stock Exchange

Risks ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 14
Author(s):  
Anna Rutkowska-Ziarko
Keyword(s):  
Stock Exchange ◽  
Risk Measures ◽  
Risk Measure ◽  
Statistical Significance ◽  
Correlation Coefficients ◽  
Downside Risk ◽  
Average Value ◽  
Market Rate ◽  
Measures Of Risk ◽  
The Relationship

The main purpose of this study was to explore the relationship between market and accounting measures of risk and the profitability of companies listed on the Frankfurt Stock Exchange. An important aspect of the study was to employ accounting beta coefficients as a systematic risk measure. The research considered classical and downside risk measures. The profitability of a company was expressed as ROA and ROE. When determining the downside risk, two approaches were employed: the approach by Bawa and Lindenberg and the approach by Harlow and Rao. In all the analyzed companies, there is a positive and statistically significant correlation between the average value of profitability ratios and the market rate of return on investment in their stocks. Additionally, correlation coefficients are higher for the companies included in the DAX index compared with those from the MDAX or SDAX indices. A positive and in each case a statistically significant correlation was observed for all DAX-indexed companies between all types of market betas and corresponding accounting betas. Likewise, for the MDAX-indexed companies, these correlations were positive but statistical significance emerged only for accounting betas calculated on ROA. As regards the DAX index, not every correlation was positive and significant.

Weighted Scoring Rules and Convex Risk Measures

2022 ◽  
Author(s):  
Zachary J. Smith ◽  
J. Eric Bickel
Keyword(s):  
Risk Measures ◽  
Risk Measure ◽  
Mathematical Finance ◽  
Scoring Rules ◽  
Convex Risk Measures ◽  
University Of Texas ◽  
Probabilistic Forecasts ◽  
Expected Utility Maximization ◽  
The University ◽  
The Relationship

In Weighted Scoring Rules and Convex Risk Measures, Dr. Zachary J. Smith and Prof. J. Eric Bickel (both at the University of Texas at Austin) present a general connection between weighted proper scoring rules and investment decisions involving the minimization of a convex risk measure. Weighted scoring rules are quantitative tools for evaluating the accuracy of probabilistic forecasts relative to a baseline distribution. In their paper, the authors demonstrate that the relationship between convex risk measures and weighted scoring rules relates closely with previous economic characterizations of weighted scores based on expected utility maximization. As illustrative examples, the authors study two families of weighted scoring rules based on phi-divergences (generalizations of the Weighted Power and Weighted Pseudospherical Scoring rules) along with their corresponding risk measures. The paper will be of particular interest to the decision analysis and mathematical finance communities as well as those interested in the elicitation and evaluation of subjective probabilistic forecasts.

Adapting Altman's model to predict the performance of the Palestinian industrial sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bahaa Awwad ◽  
Bahaa Razia
Keyword(s):  
Stock Exchange ◽  
Statistical Significance ◽  
Multiple Linear Regression Model ◽  
Industrial Sector ◽  
Main Hypothesis ◽  
Content Type ◽  
Independent Variables ◽  
Industrial Companies ◽  
And Performance ◽  
The Relationship

PurposeThis study aims to adopt the Altman model in order to predict the performance of industrial companies listed on the Palestinian Stock Exchange during the period of time between 2013 and 2017.Design/methodology/approachThe study sample consisted of 12 industrial companies listed on the Palestine Stock Exchange, and their financial disclosure period extended for 5 years. Multiple linear regression model was used in the analysis to determine the relationship between the independent variables and the dependent variable where the independent variables were (X1, X2, X3). This study is based on one basic assumption, which is that the Altman's model cannot predict the performance of the Palestinian industrial sector.FindingsThe results of the analysis proved the negation of the zero main hypothesis. This means that Altman's model can predict the performance of the Palestinian industrial sector at the level of statistical significance (a = 0.05), as well as the existence of a statistically significant relationship between each of the independent variables (X2, X4, X5) and the dependent variable (Log (Z-score)). Hence, the relationship of X1 and X3 with the dependent variable was not statistically significant.Social implicationsThis paper highlights different challenges that face the adaption of Atman's model and performance prediction in the Palestinian industrial sector. The findings of the analysis have the potential to help future researchers in examining and dealing with new challenges.Originality/valueThis paper presents a vital review of adopting Altman's model in the Palestinian industrial sector. A number of recommendations have been made, the most important of which is that most of the companies are located in the red zone. The Altman's model must be adapted in order to fit the Palestinian environment according to the results of statistical analysis and according to a proposed model, which is Log (Z) = −0.653 + 0.72X2 + 0.18X4 + 0.585X5.

SET-VALUED DYNAMIC RISK MEASURES FOR BOUNDED DISCRETE-TIME PROCESSES

2020 ◽  
Vol 23 (03) ◽  
pp. 2050017
Author(s):  
YANHONG CHEN ◽  
YIJUN HU
Keyword(s):  
Discrete Time ◽  
Value At Risk ◽  
Risk Measures ◽  
Risk Measure ◽  
Dynamic Risk Measures ◽  
Time Value Of Money ◽  
Average Value ◽  
Dynamic Risk ◽  
Entropic Risk Measure ◽  
Average Value At Risk

In this paper, we study how to evaluate the risk of a financial portfolio, whose components may be dependent and come from different markets or involve more than one kind of currencies, while we also take into consideration the uncertainty about the time value of money. Namely, we introduce a new class of risk measures, named set-valued dynamic risk measures for bounded discrete-time processes that are adapted to a given filtration. The time horizon can be finite or infinite. We investigate the representation results for them by making full use of Legendre–Fenchel conjugation theory for set-valued functions. Finally, some examples such as the set-valued dynamic average value at risk and the entropic risk measure for bounded discrete-time processes are also given.

scholarly journals Relationships of total COVID-19 cases and deaths with ten demographic, economic and social indicators

2020 ◽  
Author(s):  
Dimitar Valev
Keyword(s):  
Population Density ◽  
Statistical Significance ◽  
Social Indicators ◽  
Composite Index ◽  
Correlation Coefficients ◽  
Statistical Relationships ◽  
Student’S T ◽  
Relationship Of ◽  
The Relationship ◽  
Economic And Social Indicators

AbstractThe statistical relationships of total COVID-19 Cases and Deaths per million populations in 45 countries, where 85.8% of the world’s population lives with 10 demographic, economic and social indicators were studied. Data for 28 May 2020 were used in the main calculations. The relationship of Deaths per million population and total Cases per million population is very close and reaches correlation coefficient R = 0.926. It is interesting that the close correlations were found of Cases and Deaths per 1 million with a purely economic index like GDP PPP per capita, where R = 0.687 and R = 0.660, respectively. Even more close correlations were found of Cases and Deaths per 1 million with a composite index HDI, where the correlation coefficients reach 0.724 and 0.680, respectively. The main reason for these paradoxical results is the underestimation of pandemic restrictions in the form of masks, social distance and disinfection in most of these countries. Other indicators (excluding Gini index and Population Density) also show statistically significant correlations with Cases and Deaths per 1 million with correlation coefficients from 0.432 to 0.634. The statistical significance of the found correlations determined using Student’s t-test was p <0.0001. Surprisingly, there was no statistically significant correlation between Cases and Deaths with Population Density. To check whether there is a change in the correlations with the development of the pandemic, a statistical analysis was made for four different dates – 9 April, 28 May, 7 August and 30 November 2020. It was found that the correlation coefficients of COVID-19 cases and Deaths with the rest indicators decrease during the pandemic.

scholarly journals The Relationship Between of Cash Flows (Financing, Investment and Operating) and Stock Prices, Size of the Firms

2020 ◽  
Vol 11 (5) ◽  
pp. 424
Author(s):  
Tamer Bahjat Sabri ◽  
Khalid Mohammad Hasan Sweis ◽  
Issam Naim Mahammad Ayyash ◽  
Yasmeen Faheem Asaad Qalalwi ◽  
Israa Sami Abbas Abdullah
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Null Hypothesis ◽  
Stock Exchange ◽  
Statistical Significance ◽  
Nonparametric Test ◽  
Cash Flows ◽  
The Other ◽  
Significant Difference ◽  
The Relationship

This study sought to test the relationship between cash flows from operating activities, investment activities and financial activities and on one hand and stock returns and the volume of assets on the companies listed in Palestine Stock Exchange on the other hand. The study incorporated 24 companies in 2018 and the required data were obtained through the financial statements. To test the hypotheses of the study, the Mann-Whitny U Test was used, a nonparametric test. Also the Kolmogorov-Smirnov was done. The findings demonstrated that the value of the Whitny U Test was (-3.291) Z with a statistical significance at 1%. Based on this, the null hypothesis was rejected and the alternative one, stating that there is a statistically significant difference between the operating flows of companies with low assets and those companies with high assets, was accepted. However, the other null hypothesis was accepted. The study recommended that companies and investors should take into consideration cash flows when taking an investment decision in Palestine Stock Exchange.

scholarly journals A Bi-Objective Portfolio Optimization with Conditional Value-at-Risk

2010 ◽  
Vol 4 (2) ◽  
pp. 47-69 ◽  
Author(s):  
Bartosz Sawik
Keyword(s):  
Value At Risk ◽  
Stock Exchange ◽  
Risk Measure ◽  
Performance Measure ◽  
Conditional Value At Risk ◽  
Programming Approach ◽  
Expected Return ◽  
Worst Case ◽  
Warsaw Stock Exchange ◽  
The Relationship

This paper presents a bi-objective portfolio model with the expected return as a performance measure and the expected worst-case return as a risk measure. The problems are formulated as a bi-objective linear program. Numerical examples based on 1000, 3500 and 4020 historical daily input data from the Warsaw Stock Exchange are presented and selected computational results are provided. The computational experiments prove that the proposed linear programming approach provides the decision maker with a simple tool for evaluating the relationship between the expected and the worst-case portfolio return.

scholarly journals Downside CAPM: The case of South Africa

2017 ◽  
Vol 9 (2) ◽  
pp. 578-608
Author(s):  
Kwasi Okyere-Boakye ◽  
Brandon O’Malley
Keyword(s):  
Asset Pricing ◽  
Risk Measures ◽  
Downside Risk ◽  
Capital Asset Pricing Model ◽  
Capital Asset Pricing ◽  
Pricing Model ◽  
Capital Asset ◽  
Asset Pricing Model ◽  
Risk Framework ◽  
Measures Of Risk

Beta and the capital asset pricing model have traditionally been the preferred measures of risk. However, there is growing literature against the use of the capital asset pricing model to determine the cost of equity in markets, such as emerging markets, where investors display mean-semivariance behaviour and, where share returns are non-normal and asymmetric. Downside risk measures such as semideviation, downside beta and the downside capital asset pricing model have been found to be plausible alternate measures of risk. This study investigates empirically the relationship between risk and return in a downside risk framework and a regular risk framework using returns on companies listed on the JSE Securities Exchange. The empirical evidence from this study indicates that while downside beta and semideviation significantly explain the variation in returns, they do not support them as being more appropriate measures of risk over beta and standard deviation.

scholarly journals Distribution-Invariant Risk Measures, Entropy, and Large Deviations

2007 ◽  
Vol 44 (1) ◽  
pp. 16-40 ◽  
Author(s):  
Stefan Weber
Keyword(s):  
Large Deviations ◽  
Value At Risk ◽  
Empirical Distribution ◽  
Risk Measures ◽  
Risk Measure ◽  
Rate Function ◽  
Average Value ◽  
Simulated Distribution ◽  
Average Value At Risk ◽  
Risk Measurements

The simulation of distributions of financial assets is an important issue for financial institutions. If risk measures are evaluated for a simulated distribution instead of the model-implied distribution, the errors in the risk measurements need to be analyzed. For distribution-invariant risk measures which are continuous on compacts, we employ the theory of large deviations to study the probability of large errors. If the approximate risk measurements are based on the empirical distribution of independent samples, then the rate function equals the minimal relative entropy under a risk measure constraint. We solve this minimization problem explicitly for shortfall risk and average value at risk.

DESIRABLE PROPERTIES OF AN IDEAL RISK MEASURE IN PORTFOLIO THEORY

2008 ◽  
Vol 11 (01) ◽  
pp. 19-54 ◽  
Author(s):  
SVETLOZAR RACHEV ◽  
SERGIO ORTOBELLI ◽  
STOYAN STOYANOV ◽  
FRANK J. FABOZZI ◽  
ALMIRA BIGLOVA
Keyword(s):  
Risk Measures ◽  
Risk Measure ◽  
Approximation Problem ◽  
Performance Ratio ◽  
Probability Metrics ◽  
Time Aggregation ◽  
Computational Advantage ◽  
The Impact ◽  
The Relationship ◽  
Multidimensional Concept

This paper examines the properties that a risk measure should satisfy in order to characterize an investor's preferences. In particular, we propose some intuitive and realistic examples that describe several desirable features of an ideal risk measure. This analysis is the first step in understanding how to classify an investor's risk. Risk is an asymmetric, relative, heteroskedastic, multidimensional concept that has to take into account asymptotic behavior of returns, inter-temporal dependence, risk-time aggregation, and the impact of several economic phenomena that could influence an investor's preferences. In order to consider the financial impact of the several aspects of risk, we propose and analyze the relationship between distributional modeling and risk measures. Similar to the notion of ideal probability metric to a given approximation problem, we are in the search for an ideal risk measure or ideal performance ratio for a portfolio selection problem. We then emphasize the parallels between risk measures and probability metrics, underlying the computational advantage and disadvantage of different approaches.

scholarly journals Non-Cash Risk Measure on Nonconvex Sets

Mathematics ◽  
2018 ◽  
Vol 6 (10) ◽  
pp. 186 ◽  
Author(s):  
Chang Cong ◽  
Peibiao Zhao
Keyword(s):  
Optimization Problem ◽  
Risk Measures ◽  
Risk Measure ◽  
Financial Position ◽  
Nonconvex Sets ◽  
The Relationship

Monetary risk measures are interpreted as the smallest amount of external cash that must be added to a financial position to make the position acceptable. In this paper, A new concept: non-cash risk measure is proposed and this measure provides an approach to transform the unacceptable positions into the acceptable positions in a nonconvex set. Non-cash risk measure uses not only cash but also other kinds of assets to adjust the position. This risk measure is nonconvex due to the use of optimization problem in L 1 norm. A convex extension of the nonconvex risk measure is derived and the relationship between the convex extension and the non-cash risk measure is detailed.

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