nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒06‒25
twelve papers chosen by
Stan Miles
Thompson Rivers University

  1. Dynamic balance sheet model with liquidity risk By Hałaj, Grzegorz
  2. Regulation and Bankers' Incentives By Fabiana Gómez; Jorge Ponce
  3. Banks' Credit-Portfolio Choices and Risk-Based Capital Regulation By Nielsen, Caren Yinxia
  4. Time-varying correlation between oil and stock market volatilities: Evidence from oil-importing and oil-exporting countries By Boldanov, Rustam; Degiannakis, Stavros; Filis, George
  5. Additional Market Risk Shocks: Prepayment Uncertainty and Option-Adjusted Spreads By Alexander N. Bogin; Nataliya Polkovnichenko
  6. Multi-Period Portfolio Optimization: Translation of Autocorrelation Risk to Excess Variance By Byung-Geun Choi; Napat Rujeerapaiboon; Ruiwei Jiang
  7. Stock Market Volatility Spillovers: Evidence for Latin America By Santiago Gamba-Santamaria; Jose Eduardo Gomez-Gonzalez; Luis Fernando Melo-Velandia; Jorge Luis Hurtado-Guarin
  8. The multiplex dependency structure of financial markets By Nicol\'o Musmeci; Vincenzo Nicosia; Tomaso Aste; Tiziana Di Matteo; Vito Latora
  9. Forecasting implied volatility indices worldwide: A new approach By Degiannakis, Stavros; Filis, George; Hassani, Hossein
  10. Generating Historically-Based Stress Scenarios Using Parsimonious Factorization By Alexander N. Bogin; William M. Doerner
  11. Unravelling the Asymmetric Volatility Puzzle: A Novel Explanation of Volatility Through Anchoring By Mihaly Ormos; Dusan Timotity
  12. Vibrato and automatic differentiation for high order derivatives and sensitivities of financial options By Gilles Pag\`es; Olivier Pironneau; Guillaume Sall

  1. By: Hałaj, Grzegorz
    Abstract: Theoretically optimal responses of banks to various liquidity and solvency shocks are modelled. The proposed framework is based on a risk-adjusted return portfolio choice in multiple periods subject to the default risk related either to liquidity or solvency problems. Performance of the model and sensitivity of optimal balance sheet structures to some key parameters of the model are illustrated in a specific calibrated setup. The results of the simulations shed light on the effectiveness of the liquidity and solvency regulation. The flexible implementation of the model and its semi-analytical solvability allows for various easy applications of the framework for the macro-prudential policy analysis. JEL Classification: G11, G21, C61
    Keywords: asset structure, banking, optimal portfolio
    Date: 2016–04
  2. By: Fabiana Gómez (University of Bristol); Jorge Ponce (Banco Central del Uruguay)
    Abstract: We formally compare the effects of minimum capital requirements, capital buffers, liquidity requirements and loan loss provisions on the incentives of bankers to exert effort and take excessive risk. We find that these regulations impact differently the behavior of bankers. In the case of investment banks, the application of capital buffers and liquidity requirements makes it more difficult to achieve the first best solution. In the case of commercial banks, capital buffers, reserve requirements and traditional loan loss provisions for expected losses provide adequate incentives to bank managers, although the capital buffer is the most powerful instrument. Counter-cyclical (so-called dynamic) loan loss provisions may provide bank managers with incentives to gamble. The results inform policy makers in the ongoing debate about the harmonization of banking regulation and the implementation of Basel III.
    Keywords: Banking regulation, minimum capital requirement, capital buffer, liquidity requirement, (countercyclical) loan loss provision, commercial banks, investment banks, bankers' incentives, effort, risk; Regulación bancaria, requerimiento mínimo de capital, colchones de capital, requerimientos de liquidez, provisiones (contracíclicas), bancos comerciales, bancos de inversión, incentivos del banquero, esfuerzo, riesgo
    JEL: G21 G28
    Date: 2015
  3. By: Nielsen, Caren Yinxia (Department of Economics, Lund University)
    Abstract: To address banks’ risk taking during the recent financial crisis, we develop a model of credit-portfolio optimization and study the impact of risk-based capital regulation (Basel Accords) on banks’ asset allocations. The model shows that, when a bank’s capital is constrained by regulation, regulatory cost (risk weightings in the Basel Accords) alters the risk and value calculations for the bank’s assets. The model predicts that the effect of a tightening of the capital requirements – for banks for which these requirements are (will become) binding – will be to skew the risky portfolio towards high-risk, high-earning assets (low-risk, low-earning assets), provided that the asset valuation – i.e., reward-to-regulatory-cost ratio – of the high-risk asset is higher than that of the low-risk asset. Empirical examination of U.S. banks supports the predictions applicable to the dataset. In addition, our tests show the characteristics of banks with different levels of risk taking. In particular, the core banks that use the internal ratings-based approach under Basel II invest more in high-risk assets.
    Keywords: Banks; asset risk; credit risk; portfolio choice; risk-based capital regulation
    JEL: G11 G18 G21 G28
    Date: 2016–06–13
  4. By: Boldanov, Rustam; Degiannakis, Stavros; Filis, George
    Abstract: This paper investigates the time-varying conditional correlation between oil price and stock market volatility for six major oil-importing and oil-exporting countries. The period of the study runs from January 2000 until December 2014 and a Diag-BEKK model is employed. Our findings report the following regularities. (i) The correlation between the oil and stock market volatilities changes over time fluctuating at both positive and negative values. (ii). Heterogeneous patterns in the time-varying correlations are evident between the oil-importing and oil-exporting countries. (iii) Correlations are responsive to major economic and geopolitical events, such as the early-2000 recession, the 9/11 terrorist attacks and the global financial crisis of 2007-2009. These findings are important for risk management practices, derivative pricing and portfolio rebalancing.
    Keywords: Conditional volatility, realized volatility, time-varying correlation, Diag-BEKK, GARCH, oil-importing countries, oil-exporting countries
    JEL: C32 C51 G15 Q40
    Date: 2015–10–01
  5. By: Alexander N. Bogin (Federal Housing Finance Agency); Nataliya Polkovnichenko (Federal Housing Finance Agency)
    Abstract: Assessments of market risk for economic or regulatory capital typically involve calculating a portfolio’s sensitivity to key risk factor movements. Historically, practitioners have focused on two classical sources of risk, adverse changes in interest rates and volatility. As stress testing has evolved, additional risk factors have been identified, including several specific to fixed-income securities with embedded optionality. These include changes in prepayment rates or any of several other market risk factors, which affect option-adjusted spreads (OAS). We describe an empirical framework for generating shocks to prepayment rates and mortgage security OAS, which are consistent with simultaneous movements in other key risk factors, including the term structure of interest rates and implied volatility. Our prepayment rate shocks capture model misspecification and are calculated using historical performance data from multiple vendor prepayment models. These shocks are well defined, but capture only a portion of prepayment model error. Mortgage security OAS serves as a broader measure of model error, which encompasses both, model misspecification and forecasting errors as well as credit and liquidity risk. Our OAS shocks are calculated using historical six-month changes in spreads derived from multiple vendor quotes.
    Date: 2015–07
  6. By: Byung-Geun Choi; Napat Rujeerapaiboon; Ruiwei Jiang
    Abstract: Growth-optimal portfolios are guaranteed to accumulate higher wealth than any other investment strategy in the long run. However, they tend to be risky in the short term. For serially uncorrelated markets, similar portfolios with more robust guarantees have been recently proposed. This paper extends these robust portfolios by accommodating non-zero autocorrelations that may reflect investors' beliefs about market movements. Moreover, we prove that the risk incurred by such autocorrelations can be absorbed by modifying the covariance matrix of asset returns.
    Date: 2016–06
  7. By: Santiago Gamba-Santamaria; Jose Eduardo Gomez-Gonzalez (Banco de la República de Colombia); Luis Fernando Melo-Velandia (Banco de la República de Colombia); Jorge Luis Hurtado-Guarin (Banco de la República de Colombia)
    Abstract: We extend the framework of Diebold and Yilmaz [2009] and Diebold and Yilmaz [2012] and construct volatility spillover indexes using a DCC-GARCH framework to model the multivariate relationships of volatility among assets. We compute spillover indexes directly from the series of asset returns and recognize the time-variant nature of the covariance matrix. Our approach allows for a better understanding of the movements of financial returns within a framework of volatility spillovers. We apply our method to stock market indexes of the United States and four Latin American countries. Our results show that Brazil is a net volatility transmitter for most of the sample period, while Chile, Colombia and Mexico are net receivers. The total spillover index is substantially higher between 2008Q3 and 2012Q2, and shock transmission from the United States to Latin America substantially increased around the Lehman Brothers’ episode. Classification JEL: G01, G15, C32
    Keywords: Volatility spillovers, DCC-GARCH model, Stock market linkages, financial crisis
    Date: 2016–05
  8. By: Nicol\'o Musmeci; Vincenzo Nicosia; Tomaso Aste; Tiziana Di Matteo; Vito Latora
    Abstract: We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex data sets. In particular, we consider multiplex networks made of four layers corresponding respectively to linear, non-linear, 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.
    Date: 2016–06
  9. By: Degiannakis, Stavros; Filis, George; Hassani, Hossein
    Abstract: This study provides a new approach for implied volatility indices forecasting. We assess whether non-parametric techniques provide better predictions of implied volatility compared to standard forecasting models, such as AFRIMA and HAR. A combination of Singular Spectrum Analysis (SSA) and Holt-Winters (HW) model is applied on eight implied volatility indices for the period from February, 2001 to July, 2013. The findings confirm that the SSA-HW provides statistically superior one trading day and ten trading days ahead implied volatility forecasts world widely. Model-averaged forecasts suggest that the forecasting accuracy is further enhanced, for the ten-days ahead, when the SSA-HW is combined with an ARI(1,1) model. Additionally, the trading game reveals that the SSA-HW and the ARI-SSA-HW are able to generate significant average positive net daily returns in the out-of-sample period. The results are important for option pricing, portfolio management, value-at-risk and economic policy.
    Keywords: Implied Volatility, Volatility Forecasting, Singular Spectrum Analysis, ARFIMA, HAR, Holt-Winters, Model Confidence Set, Combined Forecasts.
    JEL: C14 C22 C52 C53 G15
    Date: 2015–09–01
  10. By: Alexander N. Bogin (Federal Housing Finance Agency); William M. Doerner (Federal Housing Finance Agency)
    Abstract: This paper describes an empirical approach to generate plausible, historically-based interest rate shocks, which can be applied to any market environment and can readily link to movements in other key risk factors. The approach is based upon yield curve parameterization and requires a parsimonious yet flexible factorization model.
    Keywords: factorization, implied volatility, interest rates, market risk
    JEL: G21 G28 G32
    Date: 2013–10
  11. By: Mihaly Ormos; Dusan Timotity
    Abstract: This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors focusing on recent price changes and price levels, which two lead to a belief in continuing trend and mean-reversion respectively. The empirical results support our theoretical explanation through an analysis of large price fluctuations in the S&P 500 and the resulting effects on implied and realized volatility. These results indicate that asymmetry (a negative relationship) between shocks and volatility in the subsequent period indeed exists. Moreover, contrary to previous research, our empirical tests also suggest that implied volatility is not simply an upward biased predictor of future deviation compensating for the variance of the volatility but rather, due to investors systematic anchoring to losses and gains in their volatility forecasts, it is a co-integrated yet asymmetric over/under estimated financial instrument. We also provide results indicating that the medium-term implied volatility (measured by the VIX Index) is an unbiased though inefficient estimation of realized volatility, while in contrast, the short-term volatility (measured by the recently introduced VXST Index representing the 9-day implied volatility) is also unbiased and yet efficient.
    Date: 2016–06
  12. By: Gilles Pag\`es (UPMC); Olivier Pironneau (LJLL); Guillaume Sall (LJLL)
    Abstract: This paper deals with the computation of second or higher order greeks of financial securities. It combines two methods, Vibrato and automatic differentiation and compares with other methods. We show that this combined technique is faster than standard finite difference, more stable than automatic differentiation of second order derivatives and more general than Malliavin Calculus. We present a generic framework to compute any greeks and present several applications on different types of financial contracts: European and American options, multidimensional Basket Call and stochastic volatility models such as Heston's model. We give also an algorithm to compute derivatives for the Longstaff-Schwartz Monte Carlo method for American options. We also extend automatic differentiation for second order derivatives of options with non-twice differentiable payoff. 1. Introduction. Due to BASEL III regulations, banks are requested to evaluate the sensitivities of their portfolios every day (risk assessment). Some of these portfolios are huge and sensitivities are time consuming to compute accurately. Faced with the problem of building a software for this task and distrusting automatic differentiation for non-differentiable functions, we turned to an idea developed by Mike Giles called Vibrato. Vibrato at core is a differentiation of a combination of likelihood ratio method and pathwise evaluation. In Giles [12], [13], it is shown that the computing time, stability and precision are enhanced compared with numerical differentiation of the full Monte Carlo path. In many cases, double sensitivities, i.e. second derivatives with respect to parameters, are needed (e.g. gamma hedging). Finite difference approximation of sensitivities is a very simple method but its precision is hard to control because it relies on the appropriate choice of the increment. Automatic differentiation of computer programs bypass the difficulty and its computing cost is similar to finite difference, if not cheaper. But in finance the payoff is never twice differentiable and so generalized derivatives have to be used requiring approximations of Dirac functions of which the precision is also doubtful. The purpose of this paper is to investigate the feasibility of Vibrato for second and higher derivatives. We will first compare Vibrato applied twice with the analytic differentiation of Vibrato and show that it is equivalent, as the second is easier we propose the best compromise for second derivatives: Automatic Differentiation of Vibrato. In [8], Capriotti has recently investigated the coupling of different mathematical methods -- namely pathwise and likelihood ratio methods -- with an Automatic differ
    Date: 2016–06

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