{"title":"Resilience in the Phase of Massive Global Financial Catastrophe (A Study with Special Reference to S&P BSE SENSEX - An Industry-Wise Analysis)","authors":"V. V","doi":"10.2139/ssrn.3169119","DOIUrl":"https://doi.org/10.2139/ssrn.3169119","url":null,"abstract":"This Paper scrutinizes the meltdown recovery and fall of Indian securities with special reference to BSE SENSEX. The data consists of Monthly closing prices of BSE 30 Companies. The study period is divided into three sub-periods based on Pre-crisis (2004-2007), During Crisis (2008-2010) and finally Post Crisis (2011-2015). The study period is for 12 years from 1 April 2004 to 31 March 2015. The tools are used to attempt the objectives like Measure of dispersion namely Standard deviation and Coefficient of Variance to measure a risk of the individual stocks and Return. The study found that Indian stock market is affected by the financial crisis that reflected on individual industries.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122670527","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":"Ostensible Financial Stability Caused by Wealth Inequality","authors":"Youngna Choi","doi":"10.2139/ssrn.3147465","DOIUrl":"https://doi.org/10.2139/ssrn.3147465","url":null,"abstract":"This article investigates ostensible financial stability of an economic sector caused by wealth inequality. When a sector is decomposed into two subsectors that possess a severe wealth inequality, the sector in entirety can look financially stable while the two subsectors have opposite extreme financially instability, one from excessive equity the other from lack thereof. The unstable subsector can result in further financial distress and even trigger a financial crisis. The market instability indicator, an early warning system derived from dynamical systems is used to analyze the subsectoral financial instability of the system. An extreme case analysis is provided to explain what financial instabilities can arise amid seemingly stable economy and positive outcomes.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131274132","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":"The Impact of Managerial Style on Bank Credit Risk Responses to Systemic Crises: Examining Syndicated Bank Loan Portfolios","authors":"Y. Shan","doi":"10.2139/ssrn.3101920","DOIUrl":"https://doi.org/10.2139/ssrn.3101920","url":null,"abstract":"When banks are confronted with systemic crises, some banks reduce the credit risk in their loan portfolios, whereas others exploit potential government bailouts and increase their internal credit risk in their loan portfolios. Using a connectedness sample method identifying managerial styles based on both asset and liability side positions, I find that asset innovators most aggressively reduce within-bank credit risk during financial crises, whereas liability innovators respond by increasing internal bank credit risk. In contrast, during non-crisis periods, the bank’s credit risk is positively related to its systemic risk exposure, indicating a baseline risk-taking proclivity. Results are robust to within-loan, GMM, and lead-lag analysis.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"874 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133701266","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":"Are Key Market Players in Currency Derivatives Markets Affected by Financial Conditions?","authors":"Ikhlaas Gurrib","doi":"10.2139/ssrn.3143957","DOIUrl":"https://doi.org/10.2139/ssrn.3143957","url":null,"abstract":"This study investigates if the biggest players in major foreign currencies futures markets are affected by current and previous financial conditions. Using root mean squared errors (RMSE), normalized RMSE, and Nash-Sutcliffe efficiency, this study compares the impact of current, 1 and 2 week lags of financial conditions onto foreign currency futures players’ net positions. The financial conditions indices used are UFCI, STLFSI, NFCI and ANFCI with weekly data set from January 2007 till December 2018. The US dollar index futures is included as a benchmark, since the financial conditions are based on US data and the most actively traded foreign currencies are paired against the USD. While RMSE and NRMSE gave mixed results into how current, 1 week and 2 weeks lagged Financial Conditions Indices (FCIs) values are related to speculators and hedgers’ net positions, lagged NFCI captured the highest correlation with both players’ net positions in Japanese Yen. 95% prediction levels encompassed the actual net positions held, including the financial crisis of 2008-2009. Forecasts were lower (higher) for hedgers (speculators) than actual net positions held during the same period. Comparatively, in the period 2016-2017, hedgers (speculators) net positions forecasts were higher (lower) than actual positions. The latter could be explained by FCIs not being affected during this period’s event, compared to net positions. While net positions data were stationary, excess kurtosis was present pointing to non-normal and autocorrelated series. This suggests the need to look into other components like non-reportable long or short positions in future analysis.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127251393","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":"Matching Frictions, Credit Reallocation and Macroeconomic Activity: How Harmful are Financial Crises?","authors":"Emanuele Ciola, E. Gaffeo, M. Gallegati","doi":"10.2139/ssrn.3126289","DOIUrl":"https://doi.org/10.2139/ssrn.3126289","url":null,"abstract":"This paper develops a macroeconomic model of real-financial market interactions in which the credit and the business cycles reinforce each other according to a bidirectional causal relationship. We do so in the context of a computational agent-based framework, where the channelling of funds from savers to investors occurring through intermediaries is a ected by information frictions. Since banks compete in both the deposit and the loan markets, the whole dynamics is driven by endogenous uctuations in the size of the intermediaries balance sheet. We use the model to show that nancial crisis are particularly harmful when hitting in phase with a real recession, and that when this occurs the loss in real output is permanent.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127950320","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}
Duc Thi Luu, M. Napoletano, P. Barucca, S. Battiston
{"title":"Collateral Unchained: Rehypothecation Networks, Concentration and Systemic Effects","authors":"Duc Thi Luu, M. Napoletano, P. Barucca, S. Battiston","doi":"10.2139/ssrn.3123226","DOIUrl":"https://doi.org/10.2139/ssrn.3123226","url":null,"abstract":"We study how network structure affects the dynamics of collateral in presence of rehypothecation. We build a simple model wherein banks interact via chains of repo contracts and use their proprietary collateral or re-use the collateral obtained by other banks via reverse repos. In this framework, we show that total collateral volume and its velocity are affected by characteristics of the network like the length of rehypothecation chains, the presence or not of chains having a cyclic structure, the direction of collateral flows, the density of the network. In addition, we show that structures where collateral flows are concentrated among few nodes (like in core-periphery networks) allow large increases in collateral volumes already with small network density. Furthermore, we introduce in the model collateral hoarding rates determined according to a Value-at-Risk (VaR) criterion, and we then study the emergence of collateral hoarding cascades in different networks. Our results highlight that network structures with highly concentrated collateral flows are also more exposed to large collateral hoarding cascades following local shocks. These networks are therefore characterized by a trade-off between liquidity and systemic risk.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128507186","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":"Are Lenders Using Risk-Based Pricing in the Consumer Loan Market? The Effects of the 2008 Crisis","authors":"Silvia Magri","doi":"10.2139/ssrn.3127554","DOIUrl":"https://doi.org/10.2139/ssrn.3127554","url":null,"abstract":"This paper analyzes whether in Italy the price of consumer loans is based on borrower specific risk. Mispricing could threat financial stability through negative effects on lenders' profitability; risk-based pricing also leads to a more efficient allocation of credit through lower prices for low-risk borrowers, with positive effects on economic growth and financial stability. The evidence available from data collected since 2006 through the Survey on Household Income and Wealth shows that consumer loan pricing has been more risk-based after the 2008 financial crisis. Households’ economic and financial conditions (net wealth, number of income earners and education of the household head) became significant and economically important in influencing the interest rates in 2010-12. These are also the most important drivers of the probability of delinquency on consumer loans; lenders also focus on these variables in selecting borrowers. As a consequence of the 2008 crisis, lenders have therefore paid more attention to borrowers' credit risk not only during the selection process, but also in deciding the price of the loan.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121071160","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":"Internal Capital Markets in Italian Business Groups: Evidence from the Financial Crisis","authors":"R. Santioni, I. Supino","doi":"10.2139/ssrn.3128206","DOIUrl":"https://doi.org/10.2139/ssrn.3128206","url":null,"abstract":"Using unique detailed data, we describe the role of internal capital markets in Italian business groups before and after the financial crisis, an exogenous event which provides an ideal setting to assess whether the working of internal capital markets helps group-affiliated firms to mitigate external financial constraints. Our findings support the hypothesis that internal capital markets are typically activated by firms standing at the top of the control chain given their easier access to external borrowing. Larger and more profitable firms serve as internal suppliers of capital and support financially constrained group members that struggle to stay viable. We also show that firms affiliated to larger and diversified groups benefit from the existence of internal mechanisms of resource reallocation that can substitute external finance when it becomes more expensive and hard to access. During the crisis, group-affiliated firms were more likely to survive than unaffiliated firms.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128438079","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":"Three Major Financial Crises: What Have We Learned","authors":"Ross P. Buckley, E. Avgouleas, D. Arner","doi":"10.2139/ssrn.3247455","DOIUrl":"https://doi.org/10.2139/ssrn.3247455","url":null,"abstract":"Few experts predicted the Asian Financial Crisis of 1997-1998, or the Global Financial Crisis of 2008 and its close companion the Eurozone Debt Crisis of 2010, and we certainly do not pretend to be able to predict the next one. Yet history teaches there will be another crisis and probably sooner rather than later, and, of course, in the decade since the start of the Global Financial Crisis, the Eurozone crisis has been ongoing in many of its dimensions. Fragility that periodically erupts into a full blown financial crisis appears to be an integral feature of market-based financial systems in spite of the advent of sophisticated risk management tools and regulatory systems. If anything the increased frequency of modern crises since the collapse of the Bretton Woods international monetary system and the period of financial internationalization and globalization which has followed, underscores how difficult it is to prevent and deal with systemic risk. We thus seek to compare and contrast these three major crises both to distill the lessons to be learned, and to identify what more can be done to strengthen our financial systems. The following sections will provide an overview of each crisis in turn, considering in particular (i) its causes; (ii) the effectiveness of policy responses; and (iii) the lessons. In the conclusion we seek to draw some common themes from these experiences going forward.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117256246","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":"An Historical Perspective on Financial Stability and Monetary Policy Regimes: A Case for Caution in Central Banks Current Obsession with Financial Stability","authors":"Michael D. Bordo","doi":"10.2139/ssrn.3160020","DOIUrl":"https://doi.org/10.2139/ssrn.3160020","url":null,"abstract":"This paper surveys the co-evolution of monetary policy and financial stability for a number of countries across four exchange rate regimes from 1880 to the present. Historical evidence is presented on the incidence, costs and determinants of financial crises along with some empirical evidence on the relationship between credit booms, asset price booms and serious financial crises. The results suggests that financial crises have many causes, including credit driven asset price booms, which have become more prevalent in recent decades, but that in general financial crises are very heterogeneous and hard to categorize. Two key historical examples stand out in the record of serious financial crises which were linked to credit driven asset price booms and busts: the 1920s and 30s and the Global Financial Crisis of 2007-2008. The question that arises is whether these two 'perfect storms' should be grounds for permanent changes in the monetary and financial environment.","PeriodicalId":283702,"journal":{"name":"ERN: Financial Crises (Monetary) (Topic)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124999320","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}