Risk Management
http://lists.repec.org/mailman/listinfo/nep-rmg
Risk Management2014-12-13Stan MilesClimate Risk Management Strategies in Agriculture – The Case of Flood Risk
http://d.repec.org/n?u=RePEc:ags:aaea14:172679&r=rmg
Sauer, Johannes, Finger, Robert2014Production Economics, Risk and Uncertainty,Volatility vs. downside risk: optimally protecting against drawdowns and maintaining portfolio performance
http://d.repec.org/n?u=RePEc:ven:wpaper:2014:18&r=rmg
As a consequence of recent market conditions an increasing number of investors are realizing the importance of controlling tail risk to reduce drawdowns thus increasing possibilities of achieving long-term objectives. Recently, so called volatility control strategies and volatility target approaches to investment have gained a lot of interest as strategies able to mitigate tail risk and produce better risk-adjusted returns. Essentially these are rule-based backward looking strategies in which no optimization is considered. In this contribution we focus on the role of volatility in downside risk reduction and, in particular, in tail risk reduction. The first contribution of our paper is to provide a viable way to integrate a target volatility approach, into a multiperiod portfolio optimization model, through the introduction of a local volatility control approach. Our optimized volatility control is contrasted with existing rule-based target volatility strategies, in an out-of sample simulation on real data, to assess the improvement that can be obtained from the optimization process. A second contribution of this work is to study the interaction between volatility control and downside risk control. We show that combining the two tools we can enhance the possibility of achieving the desired performance objectives and, simultaneously, we reduce the cost of hedging. The multiperiod portfolio optimization problem is formulated in a stochastic programming framework that provides the necessary flexibility for dealing with different constraints and multiple sources of risk.Diana Barro, Elio Canestrelli, Fabio LanzaVolatility, tail risk, stochastic programming, risk management.Methodological thoughts on expected loss estimates for IFRS 9 Impairment: hidden reserves, cyclical loss predictions and LGD backtesting
http://d.repec.org/n?u=RePEc:arx:papers:1411.4265&r=rmg
After the release of the final accounting standards for impairment in July 2014 by the IASB, banks will face another significant methodological challenge after Basel 2. The presented work shares some first methodological thoughts and proposes ways how to approach underlying questions. It starts with a detailed discussion of the structural conservatism in the final standard. The exposure value outlined in the first exposure draft 2009 will be interpreted as a fair under amortized cost accounting and consequently provides a valid benchmark. Therefore the ED 2009 is used to quantify conservatism or hidden reserves in the actual implementation of the final standard and to separate operational side-effects from real risk impacts. The second part continues with a quantification of expected credit losses based on Impact of Risk instead of traditional cost of risk. An objective framework is suggested which allows for improved testing of forward looking credit risk estimates during credit cycles. This framework will prove useful to mitigate overly pro-cyclical provisioning and earnings volatility. Finally, an LGD monitoring and backtesting approach applicable for regulatory requirements and accounting standards is proposed. On basis of the NPL Backtest, which is part of the Impact of Risk concept, specific key risk indicators are introduced that allow for a detailed assessment of collections performance versus LGD in bucket 3.Wolfgang Reitgruber2014-11Assessing systemic fragility: A probabilistic perspective
http://d.repec.org/n?u=RePEc:zbw:safewp:70&r=rmg
We outline a procedure for consistent estimation of marginal and joint default risk in the euro area financial system. We interpret the latter risk as the intrinsic financial system fragility and derive several systemic fragility indicators for euro area banks and sovereigns, based on CDS prices. Our analysis documents that although the fragility of the euro area banking system had started to deteriorate before Lehman Brothers' file for bankruptcy, investors did not expect the crisis to affect euro area sovereigns' solvency until September 2008. Since then, and especially after November 2009, joint sovereign default risk has outpaced the rise of systemic risk within the banking system.Radev, Deyan2014Banking Stability,Financial Distress,Tail Risk,ContagionReconsidering Bank Capital Regulation: A New Combination of Rules, Regulators, and Market Discipline
http://d.repec.org/n?u=RePEc:imf:imfwpa:14/169&r=rmg
Despite revisions to bank capital standards, fundamental shortcomings remain: the rules for setting capital requirements need to be simpler, and resolution should be an essential part of the capital requirement framework.We propose a new system of capital regulation that addresses these needs by making changes to all three pillars of bank regulation: only common equity should be recognized as capital for regulatory purposes, and risk weighting of assets should be abandoned; capital requirements should be assigned on an institution-by-institution basis according to a regulatory (s,S) approach developed in the paper; a standard for prompt, corrective action is incorporated into the (s,S) approach.Connel Fullenkamp, Céline Rochon2014-09-15Bank capital;Capital regulation;Capital requirements;Bank regulations;Bank supervision;Banking systems;Regulation, Bank Capital.Multi-curve HJM modelling for risk management
http://d.repec.org/n?u=RePEc:arx:papers:1411.3977&r=rmg
We present a HJM approach to the projection of multiple yield curves developed to capture the volatility content of historical term structures for risk management purposes. Since we observe the empirical data at daily frequency and only for a finite number of time to maturity buckets, we propose a modelling framework which is inherently discrete. In particular, we show how to approximate the HJM continuous time description of the multi-curve dynamics by a Vector Autoregressive process of order one. The resulting dynamics lends itself to a feasible estimation of the model volatility-correlation structure. Then, resorting to the Principal Component Analysis we further simplify the dynamics reducing the number of covariance components. Applying the constant volatility version of our model on a sample of curves from the Euro area, we demonstrate its forecasting ability through an out-of-sample test.Chiara Sabelli, Michele Pioppi, Luca Sitzia, Giacomo Bormetti2014-11Hedging Crude Oil and Corn Futures: An Application in International Trade
http://d.repec.org/n?u=RePEc:ags:aaea14:170174&r=rmg
Corn and crude oil futures contracts are analyzed for their effectiveness in reducing uncertainty for international corn traders after China's accession to the World Trade Organization. A theoretical model is developed for a trader exposed to several types of risk. The naive hedge strategy is compared to the OLS hedge ratio estimation and the VECM-DCC-Multivariate-GARCH method. Explicit modeling of the time-varying in hedge ratios using all derivatives, and taking into account dependencies between different, yet related markets, resulting in reduction in risk during the 2008 financial crisis period. In general, hedging effectiveness is increasing in hedging horizon.Li, Xin2014-07corn and oil futures, multiple risks, optimal hedge ratio, Demand and Price Analysis, International Relations/Trade, Q17, G01, C32,Tail Dependence is to be Expected Among Crop Yields
http://d.repec.org/n?u=RePEc:ags:aaea14:174315&r=rmg
Rate setting methods for crop yield and revenue contracts employ methods that presume that correlations are state invariant. Whether this is true matters. If yield-yield correlations strengthen when crops are subject to widespread stress then diversification opportunities for private insurers weaken when most needed. For the government’s book of business, such tail dependence will increase the transactions and political costs of inter-agency reallocation of funds. In this paper we propose a simple model of yields according to interactions between the weather outcome and land limitations as in the United States Soil Conservation Service’s land capability classification. Our model shows that yield-yield tail dependence is to be expected and, furthermore, should take a particular form. Yield correlations should be stronger in the left and right tails than in the center, i.e., U shaped state-conditional correlation is hypothesized. Using Risk Management Agency unit level data and a variety of statistics, we find strong evidence in favor of the U shaped tail dependence hypothesis. But the goodness-of-fit test fails to reject the standard Gaussian Copula model, which can be due to power of the tests, sampling error, and/or relatively weak tail dependence over the sample years. We conclude that existing RMA rate-setting methods are deficient.Du, Xiaodong, Hennessy, David, Feng, Hongli2014actuarial fairness, crop insurance, Gaussian copula, reinsurance, systemic risk, Crop Production/Industries, Risk and Uncertainty, G12, H2, Q18.,Systemic Risk in Wheat Yields
http://d.repec.org/n?u=RePEc:ags:aaea14:169376&r=rmg
In 2011 and 2012 severe droughts caused extensive damage in crops throughout the Midwest. These conditions combined with concerns for climate change have led to a growing focus on risk management in agriculture. The increasing emphasis on risk management is reflected in the 2014 Farm Bill, which replaces direct payments with shallow loss programs. For this paper we turn our attention to winter wheat production in Kansas and explore the ratings of the crop insurance policies as well as predicted payouts from the new Agricultural Risk Coverage program established under the 2014 Farm Bill. Using spatial models we simulate yields of non-irrigated winter wheat and irrigated winter wheat to estimate crop insurance premium rates as well as payouts from the Agricultural Risk Coverage program.Hungerford, Ashley2014-05-21Spatial, Crop Insurance, Farm Bill, Crop Production/Industries, Production Economics, Risk and Uncertainty, Q1,Forecasting the Volatility of the Dow Jones Islamic Stock Market Index: Long Memory vs. Regime Switching
http://d.repec.org/n?u=RePEc:zbw:fmpwps:2&r=rmg
The financial crisis has fueled interest in alternatives to traditional asset classes that might be less a ected by large market gyrations and, thus, provide for a less volatile development of a portfolio. One attempt at selecting stocks that are less prone to extreme risks, is obeyance of Islamic Sharia rules. In this light, we investigate the statistical properties of the Dow Jones Islamic Stock Market Index (DJIM) and explore its volatility dynamics using a number of up-to-date statistical models allowing for long memory and regime-switching dynamics. We find that the DJIM shares all stylized facts of traditional asset classes, and estimation results and forecasting performance for various volatility models are also in line with prevalent findings in the literature. Overall, the relatively new Markov-switching multifractal model performs best under the majority of time horizons and loss criteria. Long memory GARCH-type models always improve upon the short-memory GARCH specification and additionally allowing for regime changes can further improve their performance.Ben Nasr, Adnen, Lux, Thomas, Ajmi, Ahdi Noomen, Gupta, Rangan2014Islamic finance,volatility dynamics,long memory,multifractalsHolding Period Information in Options Hedging
http://d.repec.org/n?u=RePEc:arx:papers:1411.3947&r=rmg
We examine the possibility of incorporating information or views of market movements during the holding period of a portfolio, in the hedging of European options with respect to the underlying. Given a holding period interval that is bounded below, we explore whether it is possible to adjust the number of shares needed to effectively hedge our position to account for views on market dynamics from present until liquidation, to account for the time-dependence of the options' sensitivity to the underlying. We derive a preliminary analytical expression for the number of shares needed by adjusting the standard Black-Scholes-Merton $\Delta$ quantity and present numerical results.Antoine E. Zambelli2014-11Substitutes versus Complements among Canadian Business Risk Management Programs
http://d.repec.org/n?u=RePEc:ags:aaea14:174942&r=rmg
Business risk management (BRM) continues to be the central objective of agricultural policy in many countries, including Canada and the US. The unprecedented volatility that has characterized the farming sector in recent years is only expected to rise. Thus, governments continue to implement comprehensive suites of BRM programs to assist farmers in coping with these gyrations. This paper aims to examine 1) the relationships between the main Canadian BRM programs (AgriInsurance, AgriStability, and AgriInvest), and 2) if and how those relationships differ across different farms. Understanding the interlinkages between government BRM programs is central for policy makers in order to achieve the desired objectives. The analysis uses data from the Ontario Farm Income Database (OFID), which is a longitudinal farm-level dataset compiled from Ontario farm tax-file records from 2003 to 2011. The dataset contains detailed financial, production and program payment (except for Production Insurance/AgriInsurance payments) data for all Ontario tax-filling farm operations. Additional operator-level Production Insurance/AgriInsurance payment data is linked to farm-level OFID records to complement the program payment data. The paper uses a two-stage approach to examine the relationships between AgriInsurance, AgriStability, and AgriInvest. First, a multinomial probit model is estimated in which the dependent variables are dummies for all eight possible combinations of participation in the three programs and the independent variables include program participation in previous year, operating profit margin, operating expense ratio, leverage, diversification index, size, and sector. In the second stage, the predicted probabilities of the eight participation states from the first stage multinomial function is used as regressors against percentage falls in gross margin (operating revenue minus operating expense), controlled for size and sector. We find that participation in the previous year has a strong and positive effect on participation in the current year, and the three programs are generally treated as compliments. We also find that in general, farms that participate in some combination programs have smaller drops in gross margin compared to those that participate in no programs. Despite this effect, operators continue to drop out of BRM programs.Uzea, Florentina, Poon, Kenneth, Sparling, David, Weersink, Alfons2014Program Participation, BRM, risk management., Agricultural and Food Policy, Agricultural Finance,Long Term Risk: A Martingale Approach
http://d.repec.org/n?u=RePEc:arx:papers:1411.3078&r=rmg
This paper extends the long-term factorization of the pricing kernel due to Alvarez and Jermann (2005) in discrete time ergodic environments and Hansen and Scheinkman (2009) in continuous ergodic Markovian environments to general semimartingale environments, without assuming the Markov property. An explicit and easy to verify sufficient condition is given that guarantees convergence in Emery's semimartingale topology of the trading strategies that invest in T-maturity zero-coupon bonds to the long bond and convergence in total variation of T-maturity forward measures to the long forward measure. As applications, we explicitly construct long-term factorizations in generally non-Markovian Heath-Jarrow-Morton (1992) models evolving the forward curve in a suitable Hilbert space and in the non-Markovian model of social discount of rates of Brody and Hughston (2013). As a further application, we extend Hansen and Jagannathan (1991), Alvarez and Jermann (2005) and Bakshi and Chabi-Yo (2012) bounds to general semimartingale environments. When Markovian and ergodicity assumptions are added to our framework, we recover the long-term factorization of Hansen and Scheinkman (2009) and explicitly identify their distorted probability measure with the long forward measure. Finally, we give an economic interpretation of the recovery theorem of Ross (2013) in non-Markovian economies as a structural restriction on the pricing kernel leading to the growth optimality of the long bond and identification of the physical measure with the long forward measure. This latter result extends the interpretation of Ross' recovery by Borovicka et al. (2014) from Markovian to general semimartingale environments.Likuan Qin, Vadim Linetsky2014-11