Search results for: GARCH models

Authors: Kamel Malik Bensafta, Gervasio Semedo

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Niya Chen, Jennifer Chan

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In the financial market, risk management helps to minimize potential loss and maximize profit. There are two ways to assess risks; the first way is to calculate the risk directly based on the volatility. The most common risk measurements are Value at Risk (VaR), sharp ratio, and beta. Alternatively, we could look at the quantile of the return to assess the risk. Popular return models such as GARCH and stochastic volatility (SV) focus on modeling the mean of the return distribution via capturing the volatility dynamics; however, the quantile/expectile method will give us an idea of the distribution with the extreme return value. It will allow us to forecast VaR using return which is direct information. The advantage of using these non-parametric methods is that it is not bounded by the distribution assumptions from the parametric method. But the difference between them is that expectile uses a second-order loss function while quantile regression uses a first-order loss function. We consider several quantile functions, different volatility measures, and estimates from some volatility models. To estimate the expectile of the model, we use Realized Conditional Autoregressive Expectile (CARE) model with the bayesian method to achieve this. We would like to see if our proposed models outperform existing models in cryptocurrency, and we will test it by using Bitcoin mainly as well as Ethereum.

Keywords: expectile, CARE Model, CARR Model, quantile, cryptocurrency, Value at Risk

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Authors: Usoro Anthony E., Udoh Emediong

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Diagonal Vector Autoregressive Models are special classes of the general vector autoregressive models identified under certain conditions, where parameters are restricted to the diagonal elements in the coefficient matrices. Variance, autocovariance, and autocorrelation properties of the upper and lower diagonal VAR models are derived. The new set of VAR models is verified with empirical data and is found to perform favourably with the general VAR models. The advantage of the diagonal models over the existing models is that the new models are parsimonious, given the reduction in the interactive coefficients of the general VAR models.

Keywords: VAR models, diagonal VAR models, variance, autocovariance, autocorrelations

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Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

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In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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Authors: Y. Bhatt, N. Ghosh, N. Tiwari

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Acreage response function are modeled taking account of expected harvest prices, weather related variables and other non-price variables allowing for partial adjustment possibility. At the outset, based on the literature on price expectation formation, we explored suitable formulations for estimating the farmer’s expected prices. Assuming that farmers form expectations rationally, the prices of food and biofuel crops are modeled using time-series methods for possible ARCH/GARCH effects to account for volatility. The prices projected on the basis of the models are then inserted to proxy for the expected prices in the acreage response functions. Food crop acreages in different growing states are found sensitive to their prices relative to those of one or more of the biofuel crops considered. The required percentage improvement in food crop yields is worked to offset the acreage loss.

Keywords: acreage response function, biofuel, food security, sustainable development

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Authors: Sayed Kifayat Shah, Tang Zhongjun, Arfa Tanveer

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This study explores the significant heatwave effect on stock return and volatility. Using an ARCH/GARCH approach, it examines the relationship between the heatwave of Karachi, Islamabad, and Lahore on the KSE-100 index. It also explores the impact of heatwave on returns of the pharmaceutical and electronics industries. The empirical results confirm that that stock return is positively related to the heat waves of Karachi, negatively related to that of Islamabad, and is not affected by the heatwave of Lahore. Similarly, pharmaceutical and electronics indices are also positively related to heatwaves. These differences in results can be ascribed to the change in the behavior of the residents of that city. The outcomes are useful for understanding an investor's behavior reacting to weather and fluxes in stock price related to heatwave severity levels. The results can support investors in fixing biases in behavior.

Keywords: ARCH/GARCH model, heat wave, KSE-100 index, stock market return

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Imen Dhaou

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This study examines conditional Value at Risk by applying the GJR-EVT-Copula model, and finds the optimal portfolio for eight Dow Jones Islamic-conventional pairs. Our methodology consists of modeling the data by a bivariate GJR-GARCH model in which we extract the filtered residuals and then apply the Peak over threshold model (POT) to fit the residual tails in order to model marginal distributions. After that, we use pair-copula to find the optimal portfolio risk dependence structure. Finally, with Monte Carlo simulations, we estimate the Value at Risk (VaR) and the conditional Value at Risk (CVaR). The empirical results show the VaR and CVaR values for an equally weighted portfolio of Dow Jones Islamic-conventional pairs. In sum, we found that the optimal investment focuses on Islamic-conventional US Market index pairs because of high investment proportion; however, all other index pairs have low investment proportion. These results deliver some real repercussions for portfolio managers and policymakers concerning to optimal asset allocations, portfolio risk management and the diversification advantages of these markets.

Keywords: CVaR, Dow Jones Islamic index, GJR-GARCH-EVT-pair copula, portfolio optimization

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Authors: Yanqi Yang, Chongshan Liao, Cheuk Hin Ho, Susan Bridges

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Aim: To investigate student’s perceptions of using e-models in an inquiry-based curriculum. Approach: 52 second-year dental students completed a pre- and post-test questionnaire relating to their perceptions of e-models and their use in inquiry-based learning. The pre-test occurred prior to any learning with e-models. The follow-up survey was conducted after one year's experience of using e-models. Results: There was no significant difference between the two sets of questionnaires regarding student’s perceptions of the usefulness of e-models and their willingness to use e-models in future inquiry-based learning. Most of the students preferred using both plaster models and e-models in tandem. Conclusion: Students did not change their attitude towards e-models and most of them agreed or were neutral that e-models are useful in inquiry-based learning. Whilst recognizing the utility of 3D models for learning, student's preference for combining these with solid models has implications for the development of haptic sensibility in an operative discipline.

Keywords: e-models, inquiry-based curriculum, education, questionnaire

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Authors: Marco Barassi, Nicola Spagnolo

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This paper uses a DCC-GARCH model framework to examine mean and volatility spillovers (i.e. causality in mean and variance) dynamics between financial centers and the stock market indexes of the BRICS countries. In addition, tests for changes in the transmission mechanism are carried out by first testing for structural breaks and then setting a dummy variable to control for the 2008 financial crises. We use weekly data for nine countries, four financial centers (Germany, Japan, UK and USA) and the five BRICS countries (Brazil, Russia, India, China and South Africa). Furthermore, we control for monetary policy using domestic interest rates (90-day Treasury Bill interest rate) over the period 03/1/1990 - 04/2/2014, for a total of 1204 observations. Results show that the 2008 financial crises changed the causality dynamics for most of the countries considered. The same pattern can also be observed in conditional correlation showing a shift upward following the turbulence associated to the 2008 crises. The magnitude of these effects suggests a leading role played by the financial centers in effecting Brazil and South Africa, whereas Russia, India and China show a higher degree of resilience.

Keywords: financial crises, DCC-GARCH model, volatility spillovers, economics

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Authors: Edson Vengesai

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Derivative products have become essential instruments in portfolio diversification, price discovery, and, most importantly, risk hedging. Derivatives are complex instruments; their valuation, volatility implications, and real impact on the underlying assets' behaviour are not well understood. Little is documented empirically, with conflicting conclusions on how these instruments affect firm risk exposures. Given the growing interest in using derivatives in risk management and portfolio engineering, this study examines the practical impact of derivative usage on the underlying stock price exposure and systematic risk. The paper uses data from South African listed firms. The study employs GARCH models to understand the effect of derivative uses on conditional stock volatility. The GMM models are used to estimate the effect of derivatives use on stocks' systematic risk as measured by Beta and on the total risk of stocks as measured by the standard deviation of returns. The results provide evidence on whether derivatives use is instrumental in reducing stock returns' systematic and total risk. The results are subjected to numerous controls for robustness, including financial leverage, firm size, growth opportunities, and macroeconomic effects.

Keywords: derivatives use, hedging, volatility, stock price exposure

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Authors: Kwabena Asare, Ezekiel N. N. Nortey, Felix O. Mettle

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Modelling of extreme events has always been of interest in fields such as hydrology and meteorology. However, after the recent global financial crises, appropriate models for modelling of such rare events leading to these crises have become quite essential in the finance and risk management fields. This paper models the extreme values of the Ghana Stock Exchange All-Shares indices (2000-2010) by applying the Extreme Value Theory to fit a model to the tails of the daily stock returns data. A conditional approach of the EVT was preferred and hence an ARMA-GARCH model was fitted to the data to correct for the effects of autocorrelation and conditional heteroscedastic terms present in the returns series, before EVT method was applied. The Peak Over Threshold (POT) approach of the EVT, which fits a Generalized Pareto Distribution (GPD) model to excesses above a certain selected threshold, was employed. Maximum likelihood estimates of the model parameters were obtained and the model’s goodness of fit was assessed graphically using Q-Q, P-P and density plots. The findings indicate that the GPD provides an adequate fit to the data of excesses. The size of the extreme daily Ghanaian stock market movements were then computed using the Value at Risk (VaR) and Expected Shortfall (ES) risk measures at some high quantiles, based on the fitted GPD model.

Keywords: extreme value theory, expected shortfall, generalized pareto distribution, peak over threshold, value at risk

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Authors: Shahbaz G. Hassan

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Water quality models are very important to predict the changes in surface water quality for environmental management. The aim of this paper is to give an overview of the water qualities, and to provide directions for selecting models in specific situation. Water quality models include one kind of model based on a mechanistic approach, while other models simulate water quality without considering a mechanism. Mechanistic models can be widely applied and have capabilities for long-time simulation, with highly complexity. Therefore, more spaces are provided to explain the principle and application experience of mechanistic models. Mechanism models have certain assumptions on rivers, lakes and estuaries, which limits the application range of the model, this paper introduces the principles and applications of water quality model based on the above three scenarios. On the other hand, mechanistic models are more easily to compute, and with no limit to the geographical conditions, but they cannot be used with confidence to simulate long term changes. This paper divides the empirical models into two broad categories according to the difference of mathematical algorithm, models based on artificial intelligence and models based on statistical methods.

Keywords: empirical models, mathematical, statistical, water quality

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Authors: Clive L. Morley

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Gravity models and panel data modelling of tourism flows are receiving renewed attention, after decades of general neglect. Such models have quite different underpinnings from conventional demand models derived from micro-economic theory. They operate at a different level of data and with different theoretical bases. These differences have important consequences for the interpretation of the results and their policy and managerial implications. This review compares and contrasts the two model forms, clarifying the distinguishing features and the estimation requirements of each. In general, gravity models are not recommended for use to address specific management and marketing purposes.

Keywords: gravity models, micro-economics, demand models, marketing

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Abdelmounaim Lahrech, Hajar Bousfiha

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This paper examines equity market integration between Morocco and France and its consequent implications on international portfolio diversification. In the absence of stock market linkages, Morocco can act as a diversification destination to European investors, allowing higher returns at a comparable level of risk in developed markets. In contrast, this attractiveness is limited if both financial markets show significant linkage. The research empirically measures financial market’s integration in by capturing the conditional correlation between the two markets using the Generalized Autoregressive Conditionally Heteroscedastic (GARCH) model. Then, the research uses the Dynamic Conditional Correlation (DCC) model of Engle (2002) to track the correlations. The research findings show that there is no important increase over the years in the correlation between the Moroccan and the French equity markets, even though France is considered Morocco’s first trading partner. Failing to prove evidence of the stock index linkage between the two countries, the volatility series of each market were assumed to change over time separately. Yet, the study reveals that despite the important historical and economic linkages between Morocco and France, there is no evidence that equity markets follow. The small correlations and their stationarity over time show that over the 10 years studied, correlations were fluctuating around a stable mean with no significant change at their level. Different explanations can be attributed to the absence of market linkage between the two equity markets.

Keywords: equity market linkage, DCC GARCH, international portfolio diversification, Morocco, France

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Authors: Kachout Mnaouer, Bel Hadj Tahar Jamel, Choubani Fethi

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In this paper, three electric equivalent models to evaluate crosstalk between three-conductor transmission lines are proposed. First, electric equivalent models for three-conductor transmission lines are presented. Secondly, rigorous equations to calculate the per-unit length inductive and capacitive parameters are developed. These models allow us to calculate crosstalk between conductors. Finally, to validate the presented models, we compare the theoretical results with simulation data. Obtained results show that proposed models can be used to predict crosstalk performance.

Keywords: near-end crosstalk, inductive parameter, L, Π, T models

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Authors: Emily Fortune Super, Ameerah Khadaroo, Aurore Bardey

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Fashion models are often assumed to have a glamorous job with limited consideration for their well-being. This study aims to assess the well-being of models through semi-structured interviews with six professional fashion models and six industry professionals. Thematic analysis revealed that although models experienced improved self-confidence, they also reported heightened anxiety levels, body image issues, and the negative influence of modelling on their self-esteem. By contrast, industry professionals reported no or minimum concerns about anxious behaviours or the general well-being of fashion models. Being resilient as a model was perceived as an essential attribute to have by both models and industry professionals as they face recurrent rejection in this industry. These results demonstrate a significant gap in the current understanding of the well-being of fashion models between industry professionals and the models themselves. Findings imply that there is an inherent need for change in the modelling industry to promote and enhance their well-being.

Keywords: body image, fashion industry, modelling, well-being

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Authors: Tariq Aziz, Suresh Kumar, Vikesh Kumar, Sheraz Mustafa, Jhanzeb Marwat

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The paper provides an updated version of volatility spillover among the equity markets of South Asian countries, including Pakistan, India, Srilanka, and Bangladesh. The analysis uses both symmetric and asymmetric Generalized Autoregressive Conditional Heteroscedasticity models to investigate volatility persistence and leverage effect. The bivariate EGARCH model is used to test for volatility transmission between two equity markets. Weekly data for the period February 2013 to August 2019 is used for empirical analysis. The findings indicate that the leverage effect exists in the equity markets of all the countries except Bangladesh. The volatility spillover from the equity market of Bangladesh to all other countries is negative and significant whereas the volatility of the equity market of Sri-Lanka does influence the volatility of any other country’s equity market. Indian equity market influence only the volatility of the Sri-Lankan equity market; and there is bidirectional volatility spillover between the equity markets of Pakistan and Bangladesh. The findings are important for policy-makers and international investors.

Keywords: volatility spillover, volatility persistence, garch, egarch

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Authors: Y. Tiamaz, N. Souissi

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The purpose of this paper is to present a classification of Lean models which aims to capture all the concepts related to this approach and thus facilitate its implementation. This classification allows the identification of the most relevant models according to several dimensions. From this perspective, we present a review and an analysis of Lean models literature and we propose dimensions for the classification of the current proposals while respecting among others the axes of the Lean approach, the maturity of the models as well as their application domains. This classification allowed us to conclude that researchers essentially consider the Lean approach as a toolbox also they design their models to solve problems related to a specific environment. Since Lean approach is no longer intended only for the automotive sector where it was invented, but to all fields (IT, Hospital, ...), we consider that this approach requires a generic model that is capable of being implemented in all areas.

Keywords: lean approach, lean models, classification, dimensions, holistic view

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Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

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The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

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Authors: Allen A. Espinosa, Arlyne C. Marasigan, Janir T. Datukan

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The study explored how students visualize the states and classifications of matter using scientific models. It also identified misconceptions of students in using scientific models. In general, high percentage of students was able to use scientific models correctly and only a little misconception was identified. From the result of the study, a teaching framework was formulated wherein scientific models should be employed in classroom instruction to visualize abstract concepts in chemistry and for better conceptual understanding.

Keywords: visual conception, scientific models, mental models, states of matter, classification of matter

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Authors: Noha Nagy, Hoda Mokhtar, Mohamed El Sherkawi

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The popularity of workflow delegation models and the increasing number of workflow provenance-aware systems motivate the need for finding more strict delegation models. Such models combine different approaches for enhanced security and respecting workflow privacy. Although modern enterprises seek conformance to workflow constraints to ensure correctness of their work, these constraints pose a threat to security, because these constraints can be good seeds for attacking privacy even in secure models. This paper introduces a comprehensive Workflow Delegation Model (WFDM) that utilizes provenance and workflow constraints to prevent malicious delegate from attacking workflow privacy as well as extending the delegation functionalities. In addition, we argue the need for exploiting workflow constraints to improve workflow security models.

Keywords: workflow delegation models, secure workflow, workflow privacy, workflow provenance

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Authors: Mohamed Arbi Khlifi, Badr M. Alshammari

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This paper discusses the general methods to saturation in the steady-state, two axis (d & q) frame models of synchronous machines. In particular, the important role of the magnetic coupling between the d-q axes (cross-magnetizing phenomenon), is demonstrated. For that purpose, distinct methods of saturation modeling of dumper synchronous machine with cross-saturation are identified, and detailed models synthesis in d-q axes. A number of models are given in the final developed form. The procedure and the novel models are verified by a critical application to prove the validity of the method and the equivalence between all developed models is reported. Advantages of some of the models over the existing ones and their applicability are discussed.

Keywords: cross-magnetizing, models synthesis, synchronous machine, saturated modeling, state-space vectors

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Authors: John Allard, Alex Rich, Iris Aguilar, Zachary Dodds

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With this paper we present several experiences deploying novel, low-cost resources for computing with 3D spatial models. Certainly, computing with 3D models undergirds some of our field’s most important contributions to the human experience. Most often, those are contrived artifacts. This work extends that tradition by focusing on novel resources that deliver uncontrived models of a system’s current surroundings. Atop this new capability, we present several projects investigating the student-accessibility of the computational tools for reasoning about the 3D space around us. We conclude that, with current scaffolding, real-world 3D models are now an accessible and viable foundation for creative computational work.

Keywords: 3D vision, matterport model, real-world 3D models, mathematical and computational methods

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Authors: Gadah Alkeniah

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Leadership is acknowledged internationally as fundamental to school efficiency and school enhancement nevertheless there are various understandings of what leadership is and how it is realised in practice. There are a number of educational leadership models that are considered important. However, the present study uses a systematic review method to examine and compare five models of the most well-known contemporary models of leadership as well as introduces the dimension of each model. Our results reveal that recently the distributed leadership has grown in popularity within the field of education. The study concludes by suggesting future directions in leadership development and education research.

Keywords: distributed leadership, instructional leadership, leadership models, moral leadership, strategic leadership, transformational leadership

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Authors: Serkan Aras, Emrah Gulay

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Combining various forecasting models is an important tool for researchers to attain more accurate forecasts. A great number of papers have shown that selecting single models as dissimilar models, or methods based on different information as possible leads to better forecasting performances. However, there is not a certain rule regarding the number of single models to be used in any combining methods. This study focuses on determining the optimal or near optimal number for single models with the help of statistical tests. An extensive experiment is carried out by utilizing some well-known time series data sets from diverse fields. Furthermore, many rival forecasting methods and some of the commonly used combining methods are employed. The obtained results indicate that some statistically significant performance differences can be found regarding the number of the single models in the combining methods under investigation.

Keywords: combined forecast, forecasting, M-competition, time series

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Authors: Sheena K. J., Jyoti Badge, Sayed Mohammed Zeeshan

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A Comparative Study of Exponential and Logistic Population Growth Models in India India is the second most populous city in the world, just behind China, and is going to be in the first place by next year. The Indian population has remarkably at higher rate than the other countries from the past 20 years. There were many scientists and demographers who has formulated various models of population growth in order to study and predict the future population. Some of the models are Fibonacci population growth model, Exponential growth model, Logistic growth model, Lotka-Volterra model, etc. These models have been effective in the past to an extent in predicting the population. However, it is essential to have a detailed comparative study between the population models to come out with a more accurate one. Having said that, this research study helps to analyze and compare the two population models under consideration - exponential and logistic growth models, thereby identifying the most effective one. Using the census data of 2011, the approximate population for 2016 to 2031 are calculated for 20 Indian states using both the models, compared and recorded the data with the actual population. On comparing the results of both models, it is found that logistic population model is more accurate than the exponential model, and using this model, we can predict the future population in a more effective way. This will give an insight to the researchers about the effective models of population and how effective these population models are in predicting the future population.

Keywords: population growth, population models, exponential model, logistic model, fibonacci model, lotka-volterra model, future population prediction, demographers

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Authors: Mohammad Mahdi Mousavi

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Bankruptcy prediction models have been implemented for continuous evaluation and monitoring of firms. With the huge number of bankruptcy models, an extensive number of studies have focused on answering the question that which of these models are superior in performance. In practice, one of the drawbacks of existing comparative studies is that the relative assessment of alternative bankruptcy models remains an exercise that is mono-criterion in nature. Further, a very restricted number of criteria and measure have been applied to compare the performance of competing bankruptcy prediction models. In this research, we overcome these methodological gaps through implementing an extensive range of criteria and measures for comparison between dynamic and static bankruptcy models, and through proposing a multi-criteria framework to compare the relative performance of bankruptcy models in forecasting firm distress for UK firms.

Keywords: bankruptcy prediction, data envelopment analysis, performance criteria, performance measures

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Authors: Emma M. Iglesias

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We have analyzed extreme movements of the main stocks traded in the Eurozone in the 2000-2012 period. Our results can help future very-risk-averse investors to choose their portfolios in the Eurozone for risk management purposes. We find two main results. First, we can clearly classify firms by economic sector according to their different estimated VaR values in five of the seven countries we analyze. In special, we find sectors in general where companies have very high (telecommunications and banking) and very low (petroleum, utilities, energy and consumption) estimated VaR values. Second, we only find differences according to the geographical situation of where the stocks are traded in two countries: (1) all firms in the Irish stock market (the only financially rescued country we analyze) have very high estimated VaR values in all sectors; while (2) in Spain all firms have very low estimated VaR values including in the banking and the telecommunications sectors. All our results are supported when we study also the expected shortfall of the firms.

Keywords: risk management, firms, pareto tail thickness parameter, GARCH-type models, value-at-risk, extreme value theory, heavy tails, stock indexes, eurozone

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