DecisionSciRN: Institutional Financial Decision-Making (Sub-Topic)最新文献

{"title":"IFRS 9 Expected Loss: A Model Proposal for Estimating the Probability of Default for Non-Rated Companies","authors":"David Delgado-Vaquero, José Morales-Díaz, Constancio Zamora-Ramírez","doi":"10.2139/ssrn.3364451","DOIUrl":"https://doi.org/10.2139/ssrn.3364451","url":null,"abstract":"Bajo el modelo de provisiones por riesgo de crédito de la NIIF 9, las empresas deben estimar una Probabilidad de Default o quiebra (PD) para todos los activos financieros (y otros elementos) no valorados a valor razonable con cambios en la cuenta de resultados. Existen varias metodologías para estimar dicha PD utilizando información histórica o de mercado. No obstante, en algunos casos las empresas no disponen de información histórica o de mercado acerca de una contraparte. Para estos casos proponemos un modelo denominado Financial Ratios Scoring (FRS), a través del cual la entidad puede obtener un rating interno de la contraparte como primer paso para estimar la PD. El modelo se diferencia de otros modelos recientes en varios aspectos como, por ejemplo, el tamaño de la base de datos o el hecho de que se enfoca en empresas sin rating. Se basa en dar una puntuación a la contraparte en función de sus ratios financieros clave. La puntuación sitúa a la empresa en un percentil dentro de una distribución del sector previamente construida utilizando empresas con rating oficial u ofrecido por vendors. Hemos analizado la fiabilidad del modelo calculando el rating interno para empresas con rating oficial y hemos comparado el rating interno con el oficial, obteniendo resultados positivos.\u0000 Under the IFRS 9 impairment model, entities must estimate the PD (Probability of Default) for all financial assets (and other elements) not measured at fair value through profit or loss. There are several methodologies for estimating this PD from market or historical information. However, in some cases entities do not possess market or historical information concerning a counterparty. For such cases, we propose a model called Financial Ratios Scoring (FRS), by means of which an entity can obtain a “shadow rating” for a counterparty as a first step in estimating the PD. The model differentiates from other recent models in several aspects, such as the size of the database and the fact that it is focused on non-rated companies, for example. It is based on scoring the counterparty according to its key financial ratios. The score will place the counterparty on a percentile within a previously constructed sector distribution using companies with a credit rating published by rating agencies or financial vendors. We have tested the model reliability by calculating the internal credit rating of several companies (which have an official/quoted credit rating), and by comparing the rating obtained with the official one, and obtained positive results.","PeriodicalId":192282,"journal":{"name":"DecisionSciRN: Institutional Financial Decision-Making (Sub-Topic)","volume":"502 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134388496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Financial Crisis Prediction Capability of Financial Ratios","authors":"M. Islam","doi":"10.2139/ssrn.3622574","DOIUrl":"https://doi.org/10.2139/ssrn.3622574","url":null,"abstract":"Bankruptcy of a business firm is an event which results substantial losses to creditors and stockholders. A model which is capable of predicting an upcoming business failure will serve as a very useful tool to reduce such losses by providing warning to the interested parties. This was the main motivation for Beaver (1966) and Altman (1968) to construct bankruptcy prediction models based on the financial data (Deakin 1972).\u2028This research study also initiated with a great interest on this subject to investigate the predictive capability of financial ratios for forecasting of corporate distress and bankruptcy events. <br><br>The current global financial climate demands even the best international companies to constantly monitor their financial situation and their related companies with which they cooperate. Globalization process has delivered a complex network of relationships in the business environment. Due to increase in complexity of related business environment, forecasting the financial health of companies nowadays became increasingly important and worthwhile to analyse (Korol 2013). Bankruptcy is a continuous process, which can be distinguished into several stages, starting from the emergence of the first signs of financial crisis, through blindness and ignorance towards the financial and nonfinancial symptoms of crisis in a firm, to inappropriate activities that lead to the final phase of the crisis, which is bankruptcy. The Bankruptcy process cycle may take up to 5–6 years which is not a sudden phenomenon and impossible to predict, however the earlier warning signals can be detected and corrective measures may avoid the ultimate bankruptcy event depending on the preparation and reactions of the management to tackle the bankruptcy (Korol 2013). Due to the recent worldwide corporate financial crisis the need to reform the existing financial architecture has been intensified. Objective of business crisis prediction is to build models that can read the risk factors from the past observations and evaluate business crisis risk of companies with a much broader scope (Lin et al. 2011). <br><br>Ozkan cited in Lin et al. 2011 mentioned that financial indicators has been reviewed by number of researchers as a major basis for predicting financial distress and some common methodologies including peer group analysis, comprehensive risk assessment systems, and statistical and econometric analysis. Premachandra (2009) argued that bankruptcy prediction is important because corporate failure imposes significant direct and indirect costs on stakeholders. Warner cited in Premachandra (2009), evidence suggests that direct bankruptcy costs (such as court costs, lawyers and accountants fees) may be as low as 5%, or (Altman cited in Premachandra 2009) can shoot up to 28% when both direct and indirect costs (such as lost sales, lost profits, higher cost of credit, inability to issue new securities and lost investment opportunities) are considered. Therefore the ear","PeriodicalId":192282,"journal":{"name":"DecisionSciRN: Institutional Financial Decision-Making (Sub-Topic)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126217675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"6 Forecasting Financial Statements","authors":"Ignacio Vélez-Pareja","doi":"10.2139/SSRN.882872","DOIUrl":"https://doi.org/10.2139/SSRN.882872","url":null,"abstract":"This is a course material from the book Investment Decision Making. For Firm and Project Valuation. The book is originally in Spanish and is untitled as Decisiones de inversion. Para la valoracion financiera de proyectos y empresas.Chapter 6 studies the proper construction of financial statements. We present the Income Statement, the Cash Budget and the Balance Sheet. In this chapter we show how to proceed step by step in order to have consistent financial statements for the future.","PeriodicalId":192282,"journal":{"name":"DecisionSciRN: Institutional Financial Decision-Making (Sub-Topic)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114513485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Multidisciplinary Perspective on the Evolution of Corporate Investment Decision Making","authors":"M. Dempsey","doi":"10.2139/ssrn.458964","DOIUrl":"https://doi.org/10.2139/ssrn.458964","url":null,"abstract":"This paper offers a multidisciplinary perspective on the evolution of corporate investment decision-making theory and practice since the middle of the 20th century. To this end, perspectives from across the Finance, Management Accounting and Strategic Management disciplines are provided. Additionally, the paper considers the current potential for integration across our understandings from these disciplines. Accordingly, the article should be of interest to students and educators who wish to reconcile their understanding of corporate investment decision-making across financial, accounting, management and strategic perspectives.","PeriodicalId":192282,"journal":{"name":"DecisionSciRN: Institutional Financial Decision-Making (Sub-Topic)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114669765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}