nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒11‒26
twelve papers chosen by

  1. Regulations of Banks? Capital and Liquidity according to Basel III: Problems and Experience from Eastern Europe Countries By Natalia Konovalova
  2. A new multivariate nonlinear time series model for portfolio risk measurement: the threshold copula-based TAR approach By Wong, Shiu Fung; Tong, Howell; Siu, Tak Kuen; Lu, Zudi
  3. A Dual Early Warning Model of Bank Distress By Nikolaos I. Papanikolaou
  4. The multiplex dependency structure of financial markets By Musmeci, Nicoló; Nicosia, Vincenzo; Aste, Tomaso; Di Matteo, Tiziana; Latora, Vito
  5. Generalized Disappointment Aversion, Learning, and Asset Prices By Mykola Babiak
  6. Asset volatility By Correia, Maria; Kang, Johnny; Richardson, Scott
  7. A tale of two indexes: predicting equity market downturns in China By Lleo, Sebastien; Ziemba, William T.
  8. Term Structure of Risk on Macrofinance Models By Irina Zviadadze
  9. Lenders' Competition and Macro-prudential Regulation: A Model of the UK Mortgage Supermarket By Matteo Benetton
  10. "Bitcoin als alternative Anlagemöglichkeit - unter besonderer Berücksichtigung der Volatilität" By Schmidt, Tim
  11. Financial Weather Derivatives for Corn Production in Northeastern China: Modelling the underlying Weather Index By Baojing Sun
  12. International expansion and riskiness of Banks By Faia, Ester; Ottaviano, Gianmarco I. P.; Sanchez Arjona, Irene

  1. By: Natalia Konovalova (RISEBA University)
    Abstract: Abstract Transition towards regulation of banking activity based on Basel III requirements was caused by consequences of global financial and economic crisis 2007 ? 2009 that endangered the financial system stability in many countries. The banks were forced to form a large volume of accumulations to cover bad debts and could not deal with absorption of losses. It means that the system of banking regulation and supervision existing at that time did not fully reflect the banking sector risks during the periods of economic and financial shocks. The purpose of the study is to identify the influence of Basel III nonmonetary regulation methods on the banking system stability and economic growth. The study has been carried out based on financial accounting of banks in countries of East Europe. The article gives an assessment of banking activity regulation based on the implementation of Basel III requirements, which have become a response of supervisory bodies to the prevention of crisis events. It was reflected in the toughening of requirements for the capital and liquidity, which in turn required the revision of banking activity management methods. Results of the research. Bank regulation based on Basel III requirements may have both positive and adverse aspects and consequences. Positive: Growing requirements for the capital and liquidity will increase the borrowing power and solvency of banks and, therewith, the sustainability of the entire banking sector. Banking system and economy in general will be more resistant to financial shocks. Regulation based on Basel III will also contribute to reduction in systemic risk and prevention of systemic crises in future. Negative: Increase in the capital of banks as well as improvement of its structure and quality will lead to growing expenditures of banks, which in turn can entail growth in credit rates and reduction of banking activity. As a result, economic growth will slow. Reduction of banking activity will have adverse impact on profitability of banking business.
    Keywords: Key words: Capital adequacy, Bank?s liquidity, Capital safety margin, Financial leverage, Economic growth, Economic stability
    JEL: G21
    Date: 2017–10
  2. By: Wong, Shiu Fung; Tong, Howell; Siu, Tak Kuen; Lu, Zudi
    Abstract: We propose a threshold copula-based nonlinear time series model for evaluating quantitative risk measures for financial portfolios with a flexible structure to incorporate nonlinearities in both univariate (component) time series and their dependent structure. We incorporate different dependent structures of asset returns over different market regimes, which are manifested in their price levels. We estimate the model parameters by a two-stage maximum likelihood method. Real financial data and appropriate statistical tests are used to illustrate the efficacy of the proposed model. Simulated results for sampling distribution of parameters estimates are given. Empirical results suggest that the proposed model leads to significant improvement of the accuracy of value-at-risk forecasts at the portfolio lev
    Keywords: quantitative risk measures; copulas; multivariate nonlinear time series; threshold principle
    JEL: C10 C32 C51 G32
    Date: 2017–03
  3. By: Nikolaos I. Papanikolaou (Bournemouth University)
    Abstract: We contribute to the better understanding of the key factors related to the operation of the banking system that led to the global financial crisis through the development of a dual earning warning model that explores the joint determination of the probability of a distressed bank to face a licence withdrawal or to be bailed out. The underlying patterns of distress are analysed based upon a wide spectrum of bank-specific and environmental factors. We obtain precise parameter estimates and superior in- and out-of-sample forecasts. Our results show that the determinants of failures and those of bailouts differ to a considerable extent, revealing that authorities treat a distressed bank differently in their decision to let it fail or to bail it out. Overall, we provide a reliable mechanism for preventing welfare losses due to bank distress.
    Keywords: financial crisis; bank distress; early warning model; forecasting power
    JEL: C24 C53 G01 G21 G28
    Date: 2017–11
  4. By: Musmeci, Nicoló; Nicosia, Vincenzo; Aste, Tomaso; Di Matteo, Tiziana; Latora, Vito
    Abstract: We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex datasets. In particular, we consider multiplex networks made of four layers corresponding, respectively, to linear, nonlinear, tail, and partial correlations among a set of financial time series. We construct the sparse graph on each layer using a standard network filtering procedure, and we then analyse the structural properties of the obtained multiplex networks. The study of the time evolution of the multiplex constructed from financial data uncovers important changes in intrinsically multiplex properties of the network, and such changes are associated with periods of financial stress. We observe that some features are unique to the multiplex structure and would not be visible otherwise by the separate analysis of the single-layer networks corresponding to each dependency measure.
    JEL: F3 G3
    Date: 2017–09–20
  5. By: Mykola Babiak
    Abstract: This paper provides a generalized disappointment aversion (GDA) interpretation of the variance and skew risk premia in equity returns and the volatility skew in equity index options. The key ingredients are Bayesian learning about a hidden con- sumption growth rate and the investor's tail aversion induced by GDA preferences which amplify the impact of consumption shocks. This model with disappointment risk reproduces salient properties of the variance and skew risk premia and generates a realistic volatility skew implied by index options, while simultaneously matching the mean and volatility of risk-free rate and equity returns, and the level of the price-dividend ratio. Additionally, the time-varying probability of disappointment events generates a wide range of dynamic asset pricing phenomena.
    Keywords: equity premium; variance and skew risk premia; volatility skew; generalized disappointment aversion; learning; Markov switching
    JEL: D81 E32 E44 G12
    Date: 2017–10
  6. By: Correia, Maria; Kang, Johnny; Richardson, Scott
    Abstract: We examine whether fundamental measures of volatility are incremental to market based measures of volatility in (i) predicting bankruptcies (out of sample), (ii) explaining crosssectional variation in credit spreads, and (iii) explaining future credit excess returns. Our fundamental measures of volatility include (i) historical volatility in profitability, margins, turnover, operating income growth, and sales growth, (ii) dispersion in analyst forecasts of future earnings, and (iii) quantile regression forecasts of the interquartile range of the distribution of profitability. We find robust evidence that these fundamental measures of volatility improve out of sample forecasts of bankruptcy and are useful in explaining crosssectional variation in credit spreads. This suggests that an analysis of credit risk can be enhanced with a detailed analysis of fundamental information. As a test case of the benefit of volatility forecasting, we document an improved ability to forecast future credit excess returns, particularly when using fundamental measures of volatility.
    JEL: M40 F3 G3
    Date: 2017–07–21
  7. By: Lleo, Sebastien; Ziemba, William T.
    Abstract: Predicting stock market crashes is a focus of interest for both researchers and practitioners. Several prediction models have been developed, mostly for use on mature financial markets. In this paper, we investigate whether traditional crash predictors, the price-to-earnings ratio, the Cyclically Adjusted Price-to-Earnings ratio and the Bond-Stock Earnings Yield Differential model, predicts crashes for the Shanghai Stock Exchange Composite Index and the Shenzhen Stock Exchange Composite Index
    Keywords: equity markets; crashes; China; BSEYD; CAPE
    JEL: G10 G12 G14 G15
    Date: 2017–08–01
  8. By: Irina Zviadadze (Stockholm School of Economics)
    Abstract: I propose a model-based approach to characterize the term structures of risk in cash flows and asset prices. I relax cross-equation restrictions in structural models and estimate the implied dynamics of macro fundamentals and asset prices. I use shock elasticities to characterize how risk propagates in asset prices. To account for time variation in the risk premium, I extend the theory of dynamic value decomposition (Hansen, 2012) to nonnormal shocks. I find that the leading models of time-varying risk premium fall short to account for the shape and level of the term structure of risk in equity returns and cash flows.
    Date: 2017
  9. By: Matteo Benetton (London School of Economics)
    Abstract: This paper develops and estimates an empirical model of the UK mortgage market and studies the effect of macro-prudential regulation on lending activity. We estimate a discrete-continuous choice demand model of mortgages with a new administrative dataset of the universe of residential mortgage originations. Borrowers decide jointly the lender, the rate type and the leverage, facing a non-linear price schedule and affordability constraints on their choice sets. We find: 1) 10 basis points increase in the interest rate decreases the market share of a product by 6% on average; 2) a 1% increase in the interest rate decreases loan demand by about 4%; 3) both elasticities are heterogeneous across leverage levels, borrower types and lenders. We derive a pricing equation that takes into account default and refinancing risk and we characterise the Nash-Bertrand equilibrium, subject to risk-adjusted capital constraints. We use the estimated parameters to study the pass-through of capital requirements in two different counterfactual regimes.
    Date: 2017
  10. By: Schmidt, Tim
    Abstract: Die vorliegende Arbeit setzt sich mit dem Thema der Bitcoin als Kapitalanlage auseinander. Damit der Leser ein erforderliches Verständnis für die komplexe Thematik der Kryptowährung aufbaut, wird zunächst auf die Grundkonzeption der Bitcoin eingegangen. Hierbei erfolgt insbesondere eine Beschreibung des speziellen Peer-to-Peer- Netzwerk und die grundlegende Technologie der Blockchain. Die Analyse der Bitcoin als Anlageklasse beginnt mit der Preisentwicklung sowie der Untersuchung zugehöriger Einflussfaktoren auf Angebot und Nachfrage. Mittels einer Korrelationsanalyse werden die Bitcoin-Renditen anschließend ins Verhältnis zu traditionellen Anlageklassen gesetzt. Hinsichtlich der Fähigkeit, als krisenfestes Investment für Aktienkursrückgänge zu dienen, erfolgt eine historische Gegenüberstellung der Digitalwährung mit der Anlage in Gold. Hierfür werden die entsprechenden Kursentwicklungen während ausgewählter makroökonomischer und politischer Ereignisse der jüngeren Vergangenheit beobachtet. Die Untersuchung ergibt, dass die Anlageklassen Aktien und Gold eine überwiegend konträre Entwicklung aufweisen, was mit der negativen Korrelation erklärt werden kann. Unter zusätzlicher Zuhilfenahme einer Regressionsanalyse von S&P500 und Bitcoin-Preis-Index wird der kaum vorhandene Zusammenhang zwischen beiden Anlagen ersichtlich. Die ermittelten niedrigen Korrelationen zu den Vergleichsobjekten zeigen daher auf, dass die Bitcoin eine alternative und separate Anlageklasse darstellt. Unter Einbezug verschiedener deskriptiver Kennzahlen lässt sich zudem ableiten, dass die Bitcoin über ein hohes Risikopotenzial verfügt und primär als spekulative Anlage einzuordnen ist. Zur Quantifizierung dieses Risikos wird die Standardabweichung der Bitcoin-Renditen vom Erwartungswert gemessen. Die Untersuchungsergebnisse bestätigen dabei das enorme Risiko. Zur Bestimmung des tatsächlichen Verlustrisikos wird weiterhin auf das Risikomaß des Value-at-risk zurückgegriffen.
    Keywords: Bitcoin,Kapitalanlage,Kryptowährung,Peer-to-Peer-Netzwerk,Blockchain,Renditekorrelation,Volatilität,Anlageklassen,krisenfestes Investment,Risikofaktoren
    Date: 2017
  11. By: Baojing Sun
    Keywords: Pricing weather options; weather-based derivatives; stochastic process and econometric modeling; growing degree days; agricultural finance
    JEL: Q14 G11 G12 G32
    Date: 2017–09
  12. By: Faia, Ester; Ottaviano, Gianmarco I. P.; Sanchez Arjona, Irene
    Abstract: We exploit an original dataset on European G-SIBs to assess how expansion in foreign markets affects their riskiness. We find a robust negative correlation between foreign expansion and bank risk (proxied by various individual and systemic risk metrics). Given individual bank riskiness, banks’expansion reduces the average riskiness of the banks’ pool (between effect). Moreover, foreign expansion of any given bank reduces its own risk (within effect). Diversification, competition and regulation channels are all important. Expansion in destination countries with different business cycle co-movement, stricter regulations and higher competition than the origin country decreases a bank’s riskiness.
    Keywords: banks' risk; systemic risk; global expansion; competition; diversification; regulation
    JEL: G32 F3 G3
    Date: 2017–04

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