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Abstract - Review of the Causes of 1907 Panic and Aftermath
Review of the Causes of 1907 Panic and Aftermath - Pages 18-22Maria Hamideh Ramjerdi
Published: 29 January 2020 |
Abstract: The Panic of 1907 is often known as the Panic that initiated the development of the Federal Reserve System (Bordo, 1985). The Panic of 1907 was “The beginning of the end of unregulated capital markets and banking system without the lender of the last resort in the United States.” (Fohlin, Gehrig and Haas, 2015, page 2). Numerous causes lead to the Panic of 1907 including: shadow banking, the San Francisco earthquake and fire, stock price manipulation, seasonal agriculture fluctuations, an outflow of gold, and higher interest rates. This paper reviews the primary literature on these causes, and how they led to the Panic of 1907 and the subsequent regulations culminating in the Federal Reserve Bank. Keywords: 1907 Panic, Shadow Banks, NY Clearing House, 1906 San Francisco Earthquake and Fire "Silent Crush". |
Abstract - Transformation of the Forecast Assessment of Expected Credit Losses in Monitoring and Assessment of Credit Risk in Commercial Banks
Transformation of the Forecast Assessment of Expected Credit Losses in Monitoring and Assessment of Credit Risk in Commercial Banks - Pages 23-29Elena V. Travkina, Yuliya N. Solnyshkova, Oksana A. Kazankina, Elena G. Azmanova and Yuliya V. Morozova
Published: 29 January 2020 |
Abstract: The article presents the results of the systematization of issues arising in connection with the transformation of the banks forecast assessment of expected credit losses during the monitoring and evaluation of credit risk in commercial banks. Based on the data obtained on the introduction of IFRS 9 "Financial instruments" into the banking sector, it is concluded that in banking practice there is uncertainty regarding the long-term impact of credit risk, and there are significant difficulties with the use of a large amount of additional information, which creates certain difficulties in calculating future credit losses of banks. It is noted that the current use of the model of predictive assessment of expected credit losses of customers in the monitoring and evaluation of credit risk in the bank should take into account the selected collective or individual basis of assessment. The article presents a comprehensive approach to the use of the impairment model of expected losses in banking as a basic tool for modeling expected credit losses in order to form provisions for impairment with the allocation. The modification of this model will depend on the specifics of the bank's credit activities and portfolio, the types of its financial instruments, the sources of available information, as well as the IT systems used. Validation of this model will reduce the expected credit losses, reduce the amount of estimated reserves, as well as improve the efficiency of the Bank as a whole. Keywords: Assessment of expected credit losses, credit risk, default, bank borrower, financial instruments. |
Abstract - Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment
Predicting Aggregate and State-Level US House Price Volatility: The Role of Sentiment - Pages 30-46Rangan Gupta, Chi Keung Marco Lau and Wendy Nyakabawo
Published: 29 January 2020 |
Abstract: This paper examines the predictive ability of housing-related sentiment on housing market volatility for 50 states, District of Columbia, and the aggregate US economy, based on quarterly data covering 1975:3 and 2017:3. Given that existing studies have already shown housing sentiment to predict movements in aggregate and state-level housing returns, we use a k-th order causality-in-quantiles test for our purpose, since this methodology allows us to test for predictability for both housing returns and volatility simultaneously. In addition, this test being a data-driven approach accommodates the existing nonlinearity (as detected by formal tests) between volatility and sentiment, besides providing causality over the entire conditional distribution of (returns and) volatility. Our results show that barring 5 states (Connecticut, Georgia, Indiana, Iowa, and Nebraska), housing sentiment is observed to predict volatility barring the extreme ends of the conditional distribution. As far as returns are concerned, except for California, predictability is observed for all of the remaining 51 cases. Keywords: Housing sentiment, housing market returns and volatility, higher-order nonparametric causality-in-quantiles test, overall and regional US economy. |
Abstract - An Empirical Investigation of the Portuguese Housing Prices (2004-18)
An Empirical Investigation of the Portuguese Housing Prices (2004-18) - Pages 47-67Jianmin Luo, Renato Pereira and Álvaro Dias
Published: 29 January 2020 |
Abstract: This article presents an integrated macro view of the Portuguese housing market with macroeconomic indicators. Firstly, it compares the housing market and several macroeconomic indicators from 2004 to 2018. Then, the dynamic analysis of the housing prices by different regions in Portugal and its typology included. Also, the article is complemented with the regression analysis to identify the relationship between the house prices and macroeconomic indicators. Keywords: Housing Prices, Housing market, Real estate, Portugal. |