nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒01‒01
six papers chosen by
Stan Miles
Thompson Rivers University

  1. Is CAViaR model really so good in Value at Risk forecasting? Evidence from evaluation of a quality of Value-at-Risk forecasts obtained based on the: GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(1,1), CAViaR and the historical simulation models depending on the stability of financial markets By Mateusz Buczyński; Marcin Chlebus
  2. Modelling Crypto-Currencies Financial Time-Series By Leopoldo Catania; Stefano Grassi
  3. Entropy-based implied moments By Xiao Xiao; Chen Zhou
  4. Risk Apportionment: The Dual Story By Louis R. Eeckhoudt; Roger J. A. Laeven; Harris Schlesinger
  5. Spain; Financial Sector Assessment Program-Technical Note-Interconnectedness and Spillover Analysis in Spain’s Financial System By International Monetary Fund
  6. Pricing double barrier options on homogeneous diffusions: a Neumann series of Bessel functions representation By Igor V. Kravchenko; Vladislav V. Kravchenko; Sergii M. Torba; Jos\'e Carlos Dias

  1. By: Mateusz Buczyński (Faculty of Economic Sciences, University of Warsaw); Marcin Chlebus (Faculty of Economic Sciences, University of Warsaw)
    Abstract: In the literature, there is no consensus which Value-at-Risk forecasting model is the best for measuring a market risk in banks. In the study an analysis of Value-at-Risk forecasting models quality over varying economic stability periods for main indices from stock exchanges was conducted. The VaR forecasts from GARCH(1,1), GARCH-t(1,1), GARCH-st(1,1), QML-GARCH(1,1), CAViaR and historical simulation models in periods with contrasting volatility trends (increasing, constantly high and decreasing) for countries economically developed (the USA – S&P 500, Germany - DAX and Japan – Nikkei 225) and economically developing (China – SSE COMP, Poland – WIG20 and Turkey – XU100) were compared. The data samples used in the analysis were selected from period 01.01.1999 – 24.03.2017. To assess the VaR forecasts quality: excess ratio, Basel traffic light test, coverage tests (Kupiec test, Christoffersen test), Dynamic Quantile test, cost functions and Diebold-Marino test were used. Obtained results shows that the quality of Value-at-Risk forecasts for the models varies depending on a volatility trend. However, GARCH-st (1,1) and QML-GARCH(1,1) were found as the most robust models to the different volatility periods. The results shows, as well that the CAViaR model forecasts were less appropriate in the increasing volatility period. Moreover, no significant differences for the VaR forecasts quality were found for the developed and developing countries.
    Keywords: risk management, value at risk, GARCH, CAViaR, historical simulation, quality of model assessment
    JEL: G32 C52 C53 C58
    Date: 2017
  2. By: Leopoldo Catania (DEF, University of Rome "Tor Vergata"); Stefano Grassi (DEF, University of Rome "Tor Vergata")
    Abstract: This paper studies the behaviour of crypto{currencies financial time{series of which Bitcoin is the most prominent example. The dynamic of those series is quite complex displaying extreme observations, asymmetries and several nonlinear characteristics which are difficult to model. We develop a new dynamic model able to account for long{memory and asymmetries in the volatility process as well as for the presence of time{varying skewness and kurtosis. The empirical application, carried out on a large set of crypto{currencies, shows evidence of long memory and leverage effect that has a substantial contribution in the volatility dynamic. Going forward, as this new and unexplored market will develop, our results will be important for investment and risk management purposes.
    Keywords: Crypto-currency; Bitcoin, Score{Driven model; Leverage effect; Long memory; Higher Order Moments
    JEL: C01 C22 C51 C58
    Date: 2017–12–11
  3. By: Xiao Xiao; Chen Zhou
    Abstract: This paper investigates the maximum entropy method for estimating the option implied volatility, skewness and kurtosis.The maximum entropy method allows for non-parametric estimation of the risk neutral distribution and construction of confidence intervals around the implied volatility. Numerical study shows that the maximum entropy method outperforms the existing methods such as the Black-Scholes model and model-free method when the underlying risk neutral distribution exhibits heavy tail and skewness. By applying this method to the S&P 500 index options, we find that the entropy-based implied volatility outperforms the Black-Scholes implied volatility and model-free implied volatility, in terms of in-sample fit and out-of-sample predictive power. The differences between entropy based and model-free implied moments can be explained by the level of the higher-order implied moments of the underlying distribution.
    Keywords: Option pricing; risk neutral distribution; higher order moments
    JEL: C14 G13 G17
    Date: 2017–12
  4. By: Louis R. Eeckhoudt; Roger J. A. Laeven; Harris Schlesinger
    Abstract: By specifying model free preferences towards simple nested classes of lottery pairs, we develop the dual story to stand on equal footing with that of (primal) risk apportionment. The dual story provides an intuitive interpretation, and full characterization, of dual counterparts of such concepts as prudence and temperance. The direction of preference between these nested classes of lottery pairs is equivalent to signing the successive derivatives of the probability weighting function within Yaari's (1987) dual theory. We explore implications of our results for optimal portfolio choice and show that the sign of the third derivative of the probability weighting function may be naturally linked to a self-protection problem.
    Date: 2017–12
  5. By: International Monetary Fund
    Abstract: The significant international presence of Spanish banks provides welcome diversification effects but may also have significant implications for inward and outward spillovers. The share of financial assets abroad has grown continuously for the Spanish banking sector, with the largest international exposures by financial assets concentrated in the United Kingdom, the United States, Brazil, Mexico, Turkey and Chile. Spanish subsidiaries are systemically important for the banking system in several host countries. To some extent, spillovers could be mitigated by the Spanish subsidiary model characterized by a large share of local funding in local currency and a relatively high degree of autonomy of risk management practices.
    Date: 2017–11–13
  6. By: Igor V. Kravchenko; Vladislav V. Kravchenko; Sergii M. Torba; Jos\'e Carlos Dias
    Abstract: This paper develops a novel analytically tractable Neumann series of Bessel functions representation for pricing (and hedging) European-style double barrier knock-out options, which can be applied to the whole class of one-dimensional time-homogeneous diffusions even for the cases where the corresponding transition density is not known. The proposed numerical method is shown to be efficient and simple to implement. To illustrate the flexibility and computational power of the algorithm, we develop an extended jump to default model that is able to capture several empirical regularities commonly observed in the literature.
    Date: 2017–12

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