|
on Risk Management |
| By: | Xuehai Zhang (Paderborn University) |
| Abstract: | Risk management has been emphasized by financial institutions and the Basel Com- mittee on Banking Supervision (BCBS). The core issue in risk management is the mea- surement of the risks. Value at Risk (VaR) and Expected Shortfall (ES) are the widely used tools in quantitative risk management. Due to the ineptitude of VaR on tail risk performances, ES is recommended as the financial risk management metrics by BCBS. In this paper, we generate general SemiGARCH class models with a time-varying scale function. GARCH class models, based on the conditional t-distribution, are parametric extensions. Besides, backtesting with the semiparametric approach is also discussed. Fol- lowing Basel III, the trac light tests are applied in the model validation. Finally, we propose the loss functions with the views from regulators and firms, combing a power transformation in the model selection and it is shown that semiparametric models are a necessary option in practical financial risk management. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:pdn:ciepap:126&r=all |
| By: | Yuan Hu; Svetlozar T. Rache; Frank J. Fabozzi |
| Abstract: | Despite being described as a medium of exchange, cryptocurrencies do not have the typical attributes of a medium of exchange. Consequently, cryptocurrencies are more appropriately described as crypto assets. A common investment attribute shared by the more than 2,500 crypto assets is that they are highly volatile. An investor interested in reducing price volatility of a portfolio of crypto assets can do so by constructing an optimal portfolio through standard optimization techniques that minimize tail risk. Because crypto assets are not backed by any real assets, forming a hedge to reduce the risk contribution of a single crypto asset can only be done with another set of similar assets (i.e., a set of other crypto assets). A major finding of this paper is that crypto portfolios constructed via optimizations that minimize variance and Conditional Value at Risk outperform a major stock market index (the S$\&$P 500). As of this writing, options in which the underlying is a crypto asset index are not traded, one of the reasons being that the academic literature has not formulated an acceptable fair pricing model. We offer a fair valuation model for crypto asset options based on a dynamic pricing model for the underlying crypto assets. The model was carefully backtested and therefore offers a reliable model for the underlying crypto assets in the natural world. We then obtain the valuation of crypto options by passing the natural world to the equivalent martingale measure via the Esscher transform. Because of the absence of traded crypto options we could not compare the prices obtained from our valuation model to market prices. Yet, we can claim that if such options on crypto assets are introduced, they should follow closely our theoretical prices after adjusting for market frictions and design feature nuances. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05419&r=all |
| By: | Anna Denkowska; Stanis{\l}aw Wanat |
| Abstract: | This paper is part of the research on the interlinkages between insurers and their contribution to systemic risk on the insurance market. Its main purpose is to present the results of the analysis of linkage dynamics and systemic risk in the European insurance sector which are obtained using correlation networks. These networks are based on dynamic dependence structures modelled using a copula. Then, we determine minimum spanning trees (MST). Finally, the linkage dynamics is described by means of selected topological network measures. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.01142&r=all |
| By: | Xiao,Tim |
| Abstract: | This article presents a comprehensive framework for valuing financial instruments subject to credit risk. In particular, we focus on the impact of default dependence on asset pricing, as correlated default risk is one of the most pervasive threats in financial markets. We analyze how swap rates are affected by bilateral counterparty credit risk, and how CDS spreads depend on the trilateral credit risk of the buyer, seller, and reference entity in a contract. Moreover, we study the effect of collateralization on valuation, since the majority of OTC derivatives are collateralized. The model shows that a fully collateralized swap is risk-free, whereas a fully collateralized CDS is not equivalent to a risk-free one. |
| Keywords: | asset pricing,credit risk modeling,unilateral,bilateral,multilateral credit risk,collateralization,comvariance,comrelation,correlation |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:201542&r=all |
| By: | Arno Botha; Conrad Beyers; Pieter de Villiers |
| Abstract: | A new procedure is presented for the objective comparison and evaluation of default definitions. This allows the lender to find a default threshold at which the financial loss of a loan portfolio is minimised, in accordance with Basel II. Alternative delinquency measures, other than simply measuring payments in arrears, can also be evaluated using this optimisation procedure. Furthermore, a simulation study is performed in testing the procedure from `first principles' across a wide range of credit risk scenarios. Specifically, three probabilistic techniques are used to generate cash flows, while the parameters of each are varied, as part of the simulation study. The results show that loss minima can exist for a select range of credit risk profiles, which suggests that the loss optimisation of default thresholds can become a viable practice. The default decision is therefore framed anew as an optimisation problem in choosing a default threshold that is neither too early nor too late in loan life. These results also challenges current practices wherein default is pragmatically defined as `90 days past due', with little objective evidence for its overall suitability or financial impact, at least beyond flawed roll rate analyses or a regulator's decree. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.12615&r=all |
| By: | Yali Dou; Haiyan Liu; Georgios Aivaliotis |
| Abstract: | This paper explores the dependence modeling of financial assets in a dynamic way and its critical role in measuring risk. Two new methods, called Accelerated Moving Window method and Bottom-up method are proposed to detect the change of copula. The performance of these two methods together with Binary Segmentation \cite{vostrikova1981detection} and Moving Window method \cite{guegan2009forecasting} is compared based on simulated data. The best-performing method is applied to Standard \& Poor 500 and Nasdaq indices. Value-at-Risk and Expected Shortfall are computed from the dynamic and the static model respectively to illustrate the effectiveness of the best method as well as the importance of dynamic dependence modeling through backtesting. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05130&r=all |
| By: | Elisa Alos; Fabio Antonelli; Alessandro Ramponi; Sergio Scarlatti |
| Abstract: | In this work we want to provide a general principle to evaluate the CVA (Credit Value Adjustment) for a vulnerable option, that is an option subject to some default event, concerning the solvability of the issuer. CVA is needed to evaluate correctly the contract and it is particularly important in presence of WWR (Wrong Way Risk), when a credit deterioration determines an increase of the claim's price. In particular, we are interested in evaluating the CVA in stochastic volatility models for the underlying's price (which often fit quite well the market's prices) when admitting correlation with the default event. By cunningly using Ito's calculus, we provide a general representation formula applicable to some popular models such as SABR, Hull \& White and Heston, which explicitly shows the correction in CVA due to the processes correlation. Later, we specialize this formula and construct its approximation for the three selected models. Lastly, we run a numerical study to test the formula's accuracy, comparing our results with Monte Carlo simulations. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.12922&r=all |
| By: | Subhojit Biswas; Diganta Mukherjee |
| Abstract: | This paper proposes swaps on two important new measures of generalized variance, namely the maximum eigen-value and trace of the covariance matrix of the assets involved. We price these generalized variance swaps for financial markets with Markov-modulated volatilities. We consider multiple assets in the portfolio for theoretical purpose and demonstrate our approach with numerical examples taking three stocks in the portfolio. The resultsobtained in this paper have important implications for the commodity sector where such swaps would be useful for hedging risk |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.03899&r=all |
| By: | Timo Dimitriadis; Julie Schnaitmann |
| Abstract: | In this paper, we introduce new forecast encompassing tests for the risk measure Expected Shortfall (ES). Forecasting and forecast evaluation techniques for the ES are rapidly gaining attention through the recently introduced Basel III Accords, which stipulate the use of the ES as primary market risk measure for the international banking regulations. Encompassing tests generally rely on the existence of strictly consistent loss functions for the functionals under consideration, which do not exist for the ES. However, our encompassing tests are based on recently introduced loss functions and an associated regression framework which considers the ES jointly with the corresponding Value at Risk (VaR). This setup facilitates several testing specifications which allow for both, joint tests for the ES and VaR and stand-alone tests for the ES. We present asymptotic theory for our encompassing tests and verify their finite sample properties through various simulation setups. In an empirical application, we utilize the encompassing tests in order to demonstrate the superiority of forecast combination methods for the ES for the IBM stock. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.04569&r=all |
| By: | Hans Fehr; Maurice Hofmann |
| Abstract: | We study the interplay between tenure decisions, stock market investment and the public social security system. Housing equity not only serves a dual purpose as a consumption good and as an asset, but also provides insurance to buffer various risks in retirement. Our life cycle model captures these links in order to explain why homeownership in Germany is so low. Our simulation results indicate that the public long-term care as well as the pension system reduce the homeownership rate in Germany by 10-15 percentage points. |
| Keywords: | homeownership, stock market participation, life-cycle models, long-term care |
| JEL: | C61 G11 H55 |
| Date: | 2019 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_7783&r=all |
| By: | Subhojit Biswas; Diganta Mukherjee |
| Abstract: | We consider an investor, whose portfolio consists of a single risky asset and a risk free asset, who wants to maximize his expected utility of the portfolio subject to the Value at Risk assuming a heavy tail distribution of the stock prices return. We use Markov Decision Process and dynamic programming principle to get the optimal strategies and the value function which maximize the expected utility for parametric as well as non parametric distributions. Due to lack of explicit solution in the non parametric case, we use numerical integration for optimization |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.03907&r=all |
| By: | Wentao Hu |
| Abstract: | To find a trade-off between profitability and prudence, financial practitioners need to choose appropriate risk measures. Two key points are: Firstly, investors' risk attitudes under uncertainty conditions should be an important reference for risk measures. Secondly, risk attitudes are not absolute. For different market performance, investors have different risk attitudes. We proposed a new risk measure named SlideVaR which sufficiently reflects the different subjective attitudes of investors and the impact of market changes on investors' attitudes. We proposed the concept of risk-tail region and risk-tail sub-additivity and proved that SlideVaR satisfies several important mathematical properties. Moreover, SlideVaR has a simple and intuitive form of expression for practical application. Several simulate and empirical computations show that SlideVaR has obvious advantages in markets where the state changes frequently. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.11855&r=all |
| By: | Valery Baskakov; Nikolay Sheparnev; Evgeny Yanenko |
| Abstract: | The paper proposes an original methodology for constructing quantitative statistical models based on multidimensional distribution functions constructed on the basis of the insurance companies' data on inshurance policies (including policies with deductible) and claims incurred. Real data of some Russian insurance companies on non-life insurance contracts illustrate some opportunities of the proposed approach. The point and interval estimates of net premium, claims frequency, claims reserves including IBNR and OCR, are thus obtained. The resulting estimate of claims reserves falls in the range of reasonable estimates calculated on the basis of traditional reserving methods (the chain-ladder method, the frequency-severity method and the Bornhuetter-Ferguson method). The proposed methodology is based on additive estimates of a company's financial indicators, in the sense that they are calculated as a sum of estimates built separately for each element of the sample (claim). This allows using the proposed methodology to model insurance companies' financial flows and, in particular, to solve the problems of reserve redistribution between particular segments of insurance portfolio and/or time intervals; to adjust risk as part of financial reporting under IAS 17 Insurance Contracts; and to deal with many other tasks. The accuracy of insurance companies' financial parameters estimate based on the proposed methods was tested by statistical modeling. IBNR was used as the test parameter. The modeling results showed a satisfactory accuracy of the proposed reserve estimates. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05200&r=all |
| By: | Mohammed Bilal Girach; Shashank Oberoi; Siddhartha P. Chakrabarty |
| Abstract: | The problem of data uncertainty has motivated the incorporation of robust optimization in various arenas, beyond the Markowitz portfolio optimization. This work presents the extension of the robust optimization framework for the minimization of downside risk measures, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR). We perform an empirical study of VaR and CVaR frameworks, with respect to their robust counterparts, namely, Worst-Case VaR and Worst-Case CVaR, using the market data as well as the simulated data. After discussing the practical usefulness of the robust optimization approaches from various standpoints, we infer various takeaways. The robust models in the case of VaR and CVaR minimization exhibit superior performance with respect to their base versions in the cases involving higher number of stocks and simulated setup respectively. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05002&r=all |
| By: | Kyungsub Lee; Byoung Ki Seo |
| Abstract: | The third moment variation of a financial asset return process is defined by the quadratic covariation between the return and square return processes. The skew and fat tail risk of an underlying asset can be hedged using a third moment variation swap under which a predetermined fixed leg and the floating leg of the realized third moment variation are exchanged. The probability density function of the hedged portfolio with the third moment variation swap was examined using a partial differential equation approach. An alternating direction implicit method was used for numerical analysis of the partial differential equation. Under the stochastic volatility and jump diffusion stochastic volatility models, the distributions of the hedged portfolio return are symmetric and have more Gaussian-like thin-tails. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05105&r=all |
| By: | Patrice Gaillardetz; Saeb Hachem |
| Abstract: | In this paper, we consider the pricing of derivative products that involve dynamic hedging strategies and payments within the planning horizon. Equity-indexed annuities (EIAs), Guaranteed investment certificate (GIC), American and Barrier options are typical examples of these products. Our exploration involves evaluation under different assumptions related to the way the risk is tailored by the issuer. The unified constrained discrete stochastic dynamic programming framework presented in this paper makes use of sequential local minimizing strategies related to stochastic transitions. This sequential minimizations takes into account all intermediate requirements and involves several dynamic risk measures modelling. To demonstrate the flexibility of this framework we present numerical examples featuring GICs and point-to-point EIAs. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.02228&r=all |
| By: | Frank Bosserhoff; Mitja Stadje |
| Abstract: | We consider a time-consistent mean-variance portfolio selection problem of an insurer and allow for the incorporation of basis (mortality) risk. The optimal solution is identified with a Nash subgame perfect equilibrium. We characterize an optimal strategy as solution of a system of partial integro-differential equations (PIDEs), a so called extended Hamilton-Jacobi-Bellman (HJB) system. We prove that the equilibrium is necessarily a solution of the extended HJB system. Under certain conditions we obtain an explicit solution to the extended HJB system and provide the optimal trading strategies in closed-form. A simulation shows that the previously found strategies yield payoffs whose expectations and variances are robust regarding the distribution of jump sizes of the stock. The same phenomenon is observed when the variance is correctly estimated, but erroneously ascribed to the diffusion components solely. Further, we show that differences in the insurance horizon and the time to maturity of a longevity asset do not add to the variance of the terminal wealth. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.05534&r=all |
| By: | Distaso, Walter; Mele, Antonio; Vilkov, Grigory |
| Abstract: | Standard asset pricing theories treat return volatility and correlations as two intimately related quantities, which hinders achieving a neat definition of a correlation premium. We introduce a model with a continuum of securities that have returns driven by a string. This model leads to new arbitrage pricing restrictions, according to which, holding any asset requires compensation for the granular exposure of this asset returns to changes in all other asset returns: an average correlation premium. We find that this correlation premium is both statistically and economically significant, and considerably fluctuates, driven by time-varying correlations and global market developments. The model explains the cross-section of expected returns and their counter-cyclicality without making reference to common factors affecting asset returns. It also explains the time-series behavior of the premium for the risk of changes in asset correlations (the correlation-risk premium), including its inverse relation with realized correlations. |
| Keywords: | arbitrage pricing; correlation premium; correlation-risk premium; cross-section of returns; implied correlation; string models |
| JEL: | G11 G12 G13 G17 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13873&r=all |
| By: | T. N. Li; A. Papanicolaou |
| Abstract: | In this paper we construct and analyse a multi-asset model to be used for long-term statistical arbitrage strategies. A key feature of the model is that all assets have \textit{co-integration}, which, if sustained, allows for long-term positive profits with low probability of losses. Optimal portfolios are found by solving a Hamilton-Jacobi-Bellman equation, to which we can introduce portfolio constraints such as market neutral or dollar neutral. Under specific conditions of the parameters, we can prove there is long-term stability for an optimal portfolio with stable growth rate. Historical prices of the S\&P500 constituents can be tested for co-integration and our model calibrated for analysis, from which we find that co-integration strategies require a terminal investment horizon sufficiently far into the future in order for the optimal portfolios to gain from co-integration. The data also demonstrates that statistical arbitrage portfolios will have improved in-sample Sharpe ratios compared to multivariate Merton portfolios, and that statistical arbitrage portfolios are naturally immune to market fluctuations. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.02164&r=all |
| By: | Carey Caginalp; Gunduz Caginalp |
| Abstract: | We analyze the relative price change of assets starting from basic supply/demand considerations. The resulting stochastic differential equation has coefficients that are functions of supply and demand. The variance in the relative price change is then dependent on the supply and demand, and is closely connected to the expected return. An important consequence for risk assessment and options pricing is the implication that variance is highest when the magnitude of price change is greatest, and lowest near market extrema. This differs from the standard equation in mathematical finance in which the expected return and variance are decoupled. The methodology has implications for the basic framework for risk assessment, suggesting that volatility should be measured in the context of regimes of price change. The model we propose shows how investors are often misled by the apparent calm of markets near a market peak. Risk assessment methods utilizing volatility can be improved using this formulation. |
| Date: | 2019–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1908.01103&r=all |
| By: | Shahzad, Muhammad Faisal; Abdulai, Awudu |
| Keywords: | Risk and Uncertainty |
| Date: | 2019–06–25 |
| URL: | http://d.repec.org/n?u=RePEc:ags:aaea19:291283&r=all |
| By: | Mele, Antonio; Obayashi, Yoshiki; Yang, Shihao |
| Abstract: | How valuable would it be to mitigate government debt volatility? This paper introduces a model that accounts for the complex structure of government bond volatility and provides predictions on the fair value of government bond variance swaps and derivatives referenced thereon. Our calibrated model predicts that expected volatilities frequently oscillate between episodes of backwardation and contango, a feature that is in stark contrast with dynamics observed in equity markets. We use the model in risk-management experiments and evaluate scenarios such as the reaction of the U.S. Treasury volatility curve to shocks including unanticipated Fed decisions or global economic imbalances. Unlike equity volatility dynamics, which may be specified exogenously without violating no-arbitrage conditions, government bond volatility must be consistent with the dynamics of the whole yield curve. The paper provides quasi-closed form solutions that can readily be implemented despite the high-dimensional no-arbitrage restrictions that underlie the model dynamics. |
| Keywords: | fixed income volatility; government bond variance swaps; information content of government bond volatility; Treasury markets |
| JEL: | E43 E44 G12 G13 |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:13874&r=all |
| By: | Crane-Droesch, Andrew; Marshall, Elizabeth; Rosch, Stephanie; Riddle, Anne; Cooper, Joseph; Wallander, Steven |
| Abstract: | Programs that help farmers manage risk are a major component of the Federal Government’s support to rural America. Changes to this risk—and thus to the Government’s fiscal exposure— are expected as weather averages and extremes change over the coming decades. This study uses a combination of statistical and economic modeling techniques to explore the mechanisms by which climate change could affect the cost of the Federal Crop Insurance Program (FCIP) to the Federal Government, which accounts for approximately half of Government expenditures on agricultural risk management. Our approach is to compare scenarios of the future that differ only in terms of climate. Using weather scenarios for 2060-99 from general circulation models, we project decreases in corn and soybean yields and mixed changes to winter wheat yields, compared to a baseline scenario in which climate is identical to that of the past three decades. We use an economic model of the U.S. agricultural sector to estimate how projected yield changes may induce farmers to change what and where they plant, and the resulting impacts on production and output prices. These ingredients allow us to explore drivers of change in the cost of the FCIP’s Revenue Protection program, which is used as a heuristic for potential farm safety net programs that could exist in the future. Differences between the scenarios are driven by increasing prices for the three crops studied, caused by relatively lower production in the presence of inelastic demand, as well as by changing volatility in both yields and prices. |
| Keywords: | Environmental Economics and Policy, Farm Management, Risk and Uncertainty |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:ags:uersrr:291962&r=all |
| By: | Anna Stelzer |
| Abstract: | This study conducts a benchmarking study, comparing 23 different statistical and machine learning methods in a credit scoring application. In order to do so, the models' performance is evaluated over four different data sets in combination with five data sampling strategies to tackle existing class imbalances in the data. Six different performance measures are used to cover different aspects of predictive performance. The results indicate a strong superiority of ensemble methods and show that simple sampling strategies deliver better results than more sophisticated ones. |
| Date: | 2019–07 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1907.12996&r=all |