Risk Management
http://lists.repec.orgmailman/listinfo/nep-rmg
Risk Management
2016-09-25
Hedging Interest Rate Risk Using a Structural Model of Credit Risk
http://d.repec.org/n?u=RePEc:ecl:ohidic:2016-04&r=rmg
Recent evidence has shown that structural models fail to capture interest rate sensitivities of corporate debt. We consider a structural model that incorporates a three-factor dynamic term structure model (DTSM) into the Merton (1974) model. We show that the proposed model largely captures the interest rate exposure of corporate bonds. We also find that for investment-grade bonds, hedging effectiveness substantially improves under the proposed model. Our results indicate that to better capture and hedge the interest rate exposure of corporate bonds, we need to incorporate a more realistic DTSM in the existing structural models.
Huang, Jing-Zhi
Shi, Zhan
2016-02
Multistate survival analysis in Stata
http://d.repec.org/n?u=RePEc:boc:usug16:02&r=rmg
Multistate models are increasingly being used to model complex disease profiles. By modeling transitions between disease states, accounting for competing events at each transition, we can gain a much richer understanding of patient trajectories and how risk factors impact over the entire disease pathway. In this talk, we will introduce some new Stata commands for the analysis of multistate survival data. This includes msset, a data preparation tool that converts a dataset from wide (one observation per subject, multiple time and status variables) to long (one observation for each transition for which a subject is at risk for). We develop a new estimation command, stms, that allows the user to fit different parametric distributions for different transitions, simultaneously, while allowing for sharing of covariate effects across transitions. Finally, predictms calculates transition probabilities, and many other useful measures of absolute risk, following the fit of any model using streg, stms, or stcox, using either a simulation approach or the Aalen–Johansen estimator. We illustrate the software using a dataset of patients with primary breast cancer.
Michael Crowther
Paul Lambert
2016-09-16
Replica Analysis for the Duality of the Portfolio Optimization Problem
http://d.repec.org/n?u=RePEc:arx:papers:1609.05475&r=rmg
In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics, and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.
Takashi Shinzato
2016-09
Systemic Default and Return Predictability in the Stock and Bond Markets
http://d.repec.org/n?u=RePEc:ecl:ohidic:2016-2&r=rmg
Using a structural model of default, we construct a measure of systemic default defined as the probability that many firms default at the same time. Our estimation accounts for correlations in defaults between firms through common exposures to shocks. The systemic default measure spikes during recession periods and is strongly correlated with traditional credit-related macroeconomic measures such as the default spread and VIX. Furthermore, our measure predicts future equity and corporate bond index returns, particularly at the one-year horizon, and even after controlling for many traditional return predictors such as the dividend yield, default spread, inflation, and tail risk. These predictability results are robust to out-of-sample tests.
Bao, Jack
Hou, Kewei
Zhang, Shaojun A.
2016-01
"Predatory" margins and the regulation and supervision of central counterparty clearing houses (CCPs)
http://d.repec.org/n?u=RePEc:zbw:safewh:41&r=rmg
This note discusses the basic economics of central clearing for derivatives and the need for a proper regulation, supervision and resolution of central counterparty clearing houses (CCPs). New regulation in the U.S. and in Europe renders the involvement of a central counterparty mandatory for standardized OTC derivatives' trading and sets higher capital and collateral requirements for non-centrally cleared derivatives. From a macrofinance perspective, CCPs provide a trade-off between reduced contagion risk in the financial industry and the creation of a significant systemic risk. However, so far, regulation and supervision of CCPs is very fragmented, limited and ignores two important aspects: the risk of consolidation of CCPs on the one side and the competition among CCPs on the other side. i) As the economies of scale of CCP operations in risk and cost reduction can be large, they provide an argument in favor of consolidation, leading at the extreme to a monopoly CCP that poses the ultimate default risk - a systemic risk for the entire financial sector. As a systemic risk event requires a government bailout, there is a public policy issue here. ii) As long as no monopoly CCP exists, there is competition for market share among existing CCPs. Such competition may undermine the stability of the entire financial system because it induces "predatory margining": a reduction of margin requirements to increase market share. The policy lesson from our consideration emphasizes the importance of a single authority supervising all competing CCPs as well as of a specific regulation and resolution framework for CCPs. Our general recommendations can be applied to the current situation in Europe, and the proposed merger between Deutsche Börse and London Stock Exchange.
Krahnen, Jan Pieter
Pelizzon, Loriana
central counterparties,CCP,derivatives,financial market regulation,financial market supervision
2016
More Accurate Measurement for Enhanced Controls: VaR vs ES?
http://d.repec.org/n?u=RePEc:hal:journl:halshs-01281940&r=rmg
This paper analyses how risks are measured in financial institutions, for instance Market, Credit, Operational, etc with respect to the choice of the risk measures, the choice of the distributions used to model them and the level of confidence selected. We discuss and illustrate the characteristics, the paradoxes and the issues observed comparing the Value-at-Risk and the Expected Shortfall in practice. This paper is built as a differential diagnosis and aims at discussing the reliability of the risk measures as long as making some recommendations.
Dominique Guegan
Bertrand Hassani
Risk measures,Marginal distributions,Level of confidence,Capital requirement
2016-02
Empirical Hedging Performance on Long-dDted Crude Oil Derivatives
http://d.repec.org/n?u=RePEc:uts:rpaper:376&r=rmg
This paper presents an empirical study on hedging long-dated crude oil futures options with forward price models incorporating stochastic interest rates and stochastic volatility. Several hedging schemes are considered including delta, gamma, vega and interest rate hedge. Factor hedging is applied to the proposed multi-dimensional models and the corresponding hedge ratios are estimated by using historical crude oil futures prices, crude oil option prices and Treasury yields. Hedge ratios from stochastic interest rate models consistently improve hedging performance over hedge ratios from deterministic interest rate models, an improvement that becomes more pronounced over periods with high interest rate volatility, such as during the GFC. An interest rate hedge consistently improves hedging beyond delta, gamma and vega hedging, especially when shorter maturity contracts are used to roll the hedge forward. Furthermore, when the market experiences high interest rate volatility and the hedge is subject to high basis risk, adding interest rate hedge to delta hedge provides an improvement, while adding gamma and/or vega to the delta hedge worsens performance.
Benjamin Cheng
Christina Nikitopoulos-Sklibosios
Erik Schlogl
Stochastic interest rates; Delta hedge; Interest rate hedge; Long-dated crude oil options
2016-09-01
Hedging Futures Options with Stochastic Interest Rates
http://d.repec.org/n?u=RePEc:uts:rpaper:375&r=rmg
This paper presents a simulation study of hedging long-dated futures options, in the Rabinovitch (1989) model which assumes correlated dynamics between spot asset prices and interest rates. Under this model and when the maturity of the hedging instruments match the maturity of the option, forward contracts and futures contracts can hedge both the market risk and the interest rate risk of the options positions. When the hedge is rolled forward with shorter maturity hedging instruments, then bond contracts are additionally required to hedge the interest rate risk. This requirement becomes more pronounced for longer maturity contracts and amplifies as the interest rate volatility increases. Factor hedging ratios are also considered, which are suited for multi-dimensional models, and their numerical efficiency is validated.
Benjamin Cheng
Christina Nikitopoulos-Sklibosios
Erik Schlogl
Futures options; Stochastic interest rates; Delta hedging; Interest rate hedging
2016-09-01
How Management Risk Affects Corporate Debt
http://d.repec.org/n?u=RePEc:ecl:ohidic:2016-06&r=rmg
Management risk, which reflects uncertainty about the management's value added, is an important yet unexplored determinant of a firm's default risk and debt pricing. CDS spreads, loan spreads and bond yield spreads all increase at the time of management turnover, when management risk is highest, and decline over the first three years of CEO and CFO tenure, regardless of the reason for the turnover. These effects all vary with the ex ante uncertainty about the new management. Understanding the effects of management risk on corporate liabilities has a number of implications for the pricing of liabilities and corporate financial management.
Pan, Yihui
Wang, Tracy Yue
Weisbach, Michael S.
2016-05
Forecasting Financial Stress Indices in Korea: A Factor Model Approach
http://d.repec.org/n?u=RePEc:abn:wpaper:auwp2016-10&r=rmg
We propose factor-based out-of-sample forecast models for Korea's financial stress index and its 4 sub-indices that are developed by the Bank of Korea. We extract latent common factors by employing the method of the principal components for a panel of 198 monthly frequency macroeconomic data after differencing them. We augment an autoregressive-type model of the financial stress index with estimated common factors to formulate out-of-sample forecasts of the index. Our models overall outperform both the stationary and the nonstationary benchmark models in forecasting the financial stress indices for up to 12-month forecast horizons. The first common factor that represents not only financial market but also real activity variables seems to play a dominantly important role in predicting the vulnerability in the financial markets in Korea.
Hyeongwoo Kim
Wen Shi
Hyun Hak Kim
Financial Stress Index; Principal Component Analysis; PANIC; In-Sample Fit; Out-of-Sample Forecast; Diebold-Mariano-West Statistic
2016-09
Tree-based censored regression with applications in insurance
http://d.repec.org/n?u=RePEc:hal:journl:hal-01364437&r=rmg
We propose a regression tree procedure to estimate the conditional distribution of a variable which is not directly observed due to censoring. The model that we consider is motivated by applications in insurance , including the analysis of guarantees that involve durations, and claim reserving. We derive consistency results for our procedure, and for the selection of an optimal subtree using a pruning strategy. These theoretical results are supported by a simulation study, and two applications involving insurance datasets. The first concerns income protection insurance, while the second deals with reserving in third-party liability insurance.
Olivier Lopez
Xavier Milhaud
Pierre-Emmanuel Thérond
Survival analysis,censoring,regression tree,model selection,insurance,CART
2016-09-12
Institutional Investments in Pure Play Stocks and Implications for Hedging Decisions
http://d.repec.org/n?u=RePEc:ecl:ohidic:2016-3&r=rmg
We show that institutions invest in stocks within an industry that maintain exposure to their underlying industry risk factor. These "pure play" stocks have greater numbers of institutional investors and institutions systematically overweight them in their portfolios while underweighting low industry-exposure stocks of firms in the same nominal industry. Pure play stocks also have greater liquidity measured by stock turnover and price impact. An implication of these results is that catering to these preferences could be an important variable in firms' risk management decisions, potentially offsetting incentives to reduce volatility via hedging. We further characterize institutions' investments for pure play stocks across institution type, industries, and over time.
Minton, Bernadette A.
Schrand, Catherine M.
2016-01
Stress Testing in Wartime and in Peacetime
http://d.repec.org/n?u=RePEc:ecl:upafin:16-01&r=rmg
Stress testing served us well as a crisis management tool, and we see it applied increasingly to peacetime oversight of banks and banking systems. Stress testing is rapidly become the dominant supervisory tool on both sides of the Atlantic. Yet the objectives and certainly the conditions are quite different, and to date we see a range of practices across jurisdictions. Stress testing has proved to be enormously useful, not just for the supervisors but also for the banks. Using a simple taxonomy of stress testing--scenario design, models and projections, and disclosure--I analyze some of those different approaches with a view to examining how wartime stress testing can be adapted to peacetime concerns.
Schuermann, Til
2016-03
Risk management for mathematical optimization under uncertainty
http://d.repec.org/n?u=RePEc:ehu:biltok:18875&r=rmg
We present a general multistage stochastic mixed 0-1 problem where the uncertainty appears everywhere in the objective function, constraints matrix and right-hand-side. The uncertainty is represented by a scenario tree that can be a symmetric or a nonsymmetric one. The stochastic model is converted in a mixed 0-1 Deterministic Equivalent Model in compact representation. Due to the difficulty of the problem, the solution offered by the stochastic model has been traditionally obtained by optimizing the objective function expected value (i.e., mean) over the scenarios, usually, along a time horizon. This approach (so named risk neutral) has the inconvenience of providing a solution that ignores the variance of the objective value of the scenarios and, so, the occurrence of scenarios with an objective value below the expected one. Alternatively, we present several approaches for risk averse management, namely, a scenario immunization strategy, the optimization of the well known Value-at-Risk (VaR) and several variants of the Conditional Value-at-Risk strategies, the optimization of the expected mean minus the weighted probability of having a "bad" scenario to occur for the given solution provided by the model, the optimization of the objective function expected value subject to stochastic dominance constraints (SDC) for a set of profiles given by the pairs of threshold objective values and either bounds on the probability of not reaching the thresholds or the expected shortfall over them, and the optimization of a mixture of the VaR and SDC strategies.
Escudero Bueno, Laureano F.
Garín Martín, María Araceli
Aranburu Laka, Larraitz
Merino Maestre, María
Pérez Sainz de Rozas, Gloria
scenario analysis, mixed 0-1 Deterministic Equivalent Model, risk aversion measures, scenario immunization, VaR, CVAR, mean-risk, stochastic dominance constraints, multistage stochastic mixed 0-1 optimization
2016
Predicting US banks bankruptcy: logit versus Canonical Discriminant analysis
http://d.repec.org/n?u=RePEc:hal:journl:halshs-01281948&r=rmg
Using a large panel of US banks over the period 2008-2013, this paper proposes an early-warning framework to identify bank leading to bankruptcy. We conduct a comparative analysis based on both Canonical Discriminant Analysis and Logit models to examine and to determine the most accurate of these models. Moreover, we analyze and improve suitability of models by comparing different optimal cut-off score (ROC curve vs theoretical value). The main conclusions are: i) Results vary with cut-off value of score, ii) the logistic regression using 0.5 as critical cut-off value outperforms DA model with an average of correct classification equal to 96.22%. However, it produces the highest error type 1 rate 42.67%, iii) ROC curve validation improves the quality of the model by minimizing the error of misclassification of bankrupt banks: only 4.42% in average and exhibiting 0% in both 2012 and 2013. Also, it emphasizes better prediction of failure of banks because it delivers in mean the highest error type II 8.43%.
Zeineb Affes
Rania Hentati-Kaffel
Bankruptcy prediction,Canonical Discriminant Analysis,Logistic regression,CAMELS,ROC curve,Early-warning system
2016-02
Investigating gender differences under time pressure in financial risk taking
http://d.repec.org/n?u=RePEc:qut:qubewp:wp045&r=rmg
We investigate the nature of gender differences in financial risk taking under time pressure. Motivated by the large gender imbalance on financial trading floor we investigate gender differences under pressure and whether testosterone plays a role in gender differences in risk attitude under pressure. We find that testosterone exposure affects both outcome and probability sensitivity in men. We also find that testosterone exposure makes men relatively more risk seeking and optimistic when having to make risky decision under time pressure.
Zhixin Xie
Lionel Page
Ben Hardy
2016-09-23
The Elephant in the Room: The Impact of Labor Obligations on Credit Risk
http://d.repec.org/n?u=RePEc:ecl:ohidic:2015-17&r=rmg
We study the impact of labor market frictions on credit risk. Our central finding is that labor market variables are the first-order effect in driving both of the aggregate time series and the cross sectional variations of credit risk. Recent studies have highlighted a link between credit risk and macroeconomic/firm-level variables such as investment growth, financial leverage, volatility, etc. We show that labor market variables (wage growth or labor share) can forecast the aggregate credit spread as well as or better than alternative predictors. Furthermore, firm-level labor expense growth rates and labor share can predict Moody-KMV expected default frequency (EDF) in the cross-section across a wide range of countries. A model with wage rigidity and endogenous long-term defaultable debt can explain these links as well as produce large credit spreads despite realistically low default probabilities (credit spread puzzle). This is because pre-committed payments to labor make other committed payments (such as debt) riskier; for this reason variables related to pre-committed labor payments have explanatory power for credit risk.
Favilukis, Jack
Lin, Xiaoji
Zhao, Xiaofei
2014-12
Differences of Opinion and Stock Market Volatility: Evidence from a Nonparametric Causality-in-Quantiles Approach
http://d.repec.org/n?u=RePEc:pre:wpaper:201668&r=rmg
This paper examines whether the differences of opinion across active money managers relates to stock market volatility via the recently proposed nonparametric causality-in-quantiles test. Using the dispersion in equity market exposures of active managers as a proxy for differences in opinion, we analyze the predictability of (realized) volatility of the S&P500 for the period July, 2006-August, 2016. Unlike the result of no predictability obtained under the misspecified linear set-up, our nonparametric causality-in-quantiles test indicates that dispersion in active managers’ risk exposures to the stock market can predict volatility over the range of quantiles that correspond to moderately high levels of market volatility. Our findings are in line with the previous literature that relates divergent beliefs across investors to subsequent stock returns and suggest that the effect on subsequent returns is likely to be transmitted via the volatility channel. Our results highlight the importance of detecting and modeling nonlinearity when analyzing the information content of divergent beliefs across market participants.
Mehmet Balcilar
Riza Demirer
Rangan Gupta
Mark E. Wohar
Realized Volatility; Differences of opinion, Quantile Causality
2016-09
Prices and Volatilities in the Corporate Bond Market
http://d.repec.org/n?u=RePEc:ecl:ohidic:2015-18&r=rmg
We document a strong positive cross-sectional relation between corporate bond yield spreads and bond return volatilities. As corporate bond prices are generally attributable to both credit risk and illiquidity as discussed in Huang and Huang (2012), we apply a decomposition methodology to quantify the relative contributions of credit and illiquidity. Overall, our credit and illiquidity proxies can explain almost three quarters of the yield spread-bond volatility relation with credit and illiquidity contributing in a 70:30 ratio. Furthermore, we find that the credit portion of the yield spread-bond volatility relation is important even after controlling for equity volatility. The relation between yield spreads and volatilities is robust to different sample periods, including the financial crisis. We also find the ratio to be smaller for the investment-grade sub-sample, consistent with credit risk being relatively more important for understanding the yield spread-volatility relation in speculative-grade bonds.
Bao, Jack
Chen, Jia
Hou, Kewei
Lu, Lei
2015-08
Realized Matrix-Exponential Stochastic Volatility with Asymmetry, Long Memory and Spillovers
http://d.repec.org/n?u=RePEc:ucm:doicae:1615&r=rmg
The paper develops a novel realized matrix-exponential stochastic volatility model of multivariate returns and realized covariances that incorporates asymmetry and long memory (hereafter the RMESV-ALM model). The matrix exponential transformation guarantees the positivedefiniteness of the dynamic covariance matrix. The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 1988, 39(1-2), 69–104), especially for developing tests for leverage and spillover effects in the covariance dynamics. Efficient importance sampling is used to maximize the likelihood function of RMESV-ALM, and the finite sample properties of the quasi-maximum likelihood estimator of the parameters are analysed. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The forecasting performance of the new model is compared with a novel dynamic realized matrix-exponential conditional covariance model. The volatility and co-volatility spillovers are examined via the news impact curves and the impulse response functions from returns to volatility and co-volatility.
Manabu Asai
Chia-Lin Chang
Michael McAleer
Matrix-exponential transformation, Realized stochastic covariances, Realized conditional covariances, Asymmetry, Long memory, Spillovers, Dynamic covariance matrix, Finite sample properties, Forecasting performance.
2016-09
Why Does Idiosyncratic Risk Increase with Market Risk?
http://d.repec.org/n?u=RePEc:ecl:ohidic:2016-13&r=rmg
From 1963 through 2015, idiosyncratic risk (IR) is high when market risk (MR) is high. We show that the positive relation between IR and MR is highly stable through time and is robust across exchanges, firm size, liquidity, and market-to-book groupings. Though stock liquidity affects the strength of the relation, the relation is strong for the most liquid stocks. The relation has roots in fundamentals as higher market risk predicts greater idiosyncratic earnings volatility and as firm characteristics related to the ability of firms to adjust to higher uncertainty help explain the strength of the relation. Consistent with the view that growth options provide a hedge against macroeconomic uncertainty, we find evidence that the relation is weaker for firms with more growth options.
Bartram, Sohnke M.
Brown, Gregory W.
Stulz, Rene M.
2016-07