
on Risk Management 
Issue of 2013‒12‒20
seven papers chosen by 
By:  di Iasio, Giovanni; Battiston, Stefano; Infante, Luigi; Pierobon, Federico 
Abstract:  We implement a novel method to detect systemically important financial institutions in a network. The method consists in a simple model of distress and losses redistribution derived from the interaction of banks' balancesheets through bilateral exposures. The algorithm goes beyond the traditional defaultcascade mechanism, according to which contagion propagates only through banks that actually default. We argue that even in the absence of other defaults, distressedbutnondefaulting institutions transmit the contagion through channels other than solvency: weakness in their balance sheet reduces the value of their liabilities, thereby negatively affecting their interbank lenders even before a credit event occurs. In this paper, we apply the methodology to a unique dataset covering bilateral exposures among all Italian banks in the period 20082012. We find that the systemic impact of individual banks has decreased over time since 2008. The result can be traced back to decreasing volumes in the interbank market and to an intense recapitalization process. We show that the marginal effect of a bank's capital on its contribution to systemic risk in the network is considerably larger when interconnectedness is high (good times): this finding supports the regulatory work on countercyclical (macroprudential) capital buffers. 
Keywords:  Systemic risk; interbank market; contagion; network; feedback centrality. 
JEL:  C45 D85 G01 G21 
Date:  2013–12 
URL:  http://d.repec.org/n?u=RePEc:pra:mprapa:52141&r=rmg 
By:  Ray, David 
Keywords:  risk management, production risk, crop insurance, Agribusiness, Farm Management, Risk and Uncertainty, 
Date:  2013–05–01 
URL:  http://d.repec.org/n?u=RePEc:ags:ncissr:160464&r=rmg 
By:  : Andrea Gamba; : Alexander J. Triantis 
Date:  2013 
URL:  http://d.repec.org/n?u=RePEc:wbs:wpaper:wpn1307&r=rmg 
By:  Safarian, Mher 
Abstract:  [Statement of the problem] The present work considers the problem of investment portfolio risk estimation, including dynamic adjustment for each new transaction. Any Bank portfolio has a complex structure. It consists of stocks, bonds and a set of derivative securities. A portion of bonds and loans is riskless. For some of these assets, the methods offered cannot be applied without additional consideration of the term structure of interest rates and credit risks features. The risk estimation of this part of the portfolio containing some peculiar financial tools represents a separate issue, solving which exceeds the limits of the present research. We use as an estimation of a portfolio risk the amount of probable losses that can be sustained in case of a complete asset sale, related to current market value of these assets. The investment portfolio includes a number of shares, sale of which can significantly affect the market for a brief period of time, making the calculated estimation of risk insolvent. Thus it is necessary to estimate the quantity of shares that can be sold without having a material influence on the prices dynamics. Knowing this size, it is easy to calculate a time interval during which this portfolio can be sold. Definition of the stability of the concrete market is directly concerned with its specificity. This represents a separate practical problem, which is not considered in the submitted paper. Consequently, for a portfolio risk calculation, it is necessary to estimate dynamics of price behaviour for the time period during which controllable realization of portfolio assets is possible. Such an approach is described in many papers where estimation of risk is based on studying prices dynamics of stocks included in a portfolio (VaR  'RiskMetrics', RiskManagement+). However, forecasting such processes represents a complicated problem itself. For example, on NASDAQ the prices of the most liquid stocks have large volatility. Deviation from average value of a stock price can run up to several percent even on ordinary days. To circumvent this problem, a new approach, which is not considered earlier, is offered in the given research.  
Date:  2013 
URL:  http://d.repec.org/n?u=RePEc:zbw:kitwps:52&r=rmg 
By:  Claudia Ceci; Katia Colaneri; Alessandra Cretarola 
Abstract:  In this paper we investigate the local riskminimization approach for a financial market where there are restrictions on the available information to agents who can observe at least the asset prices. We characterize the optimal strategy in terms of the predictable covariation of the optimal value process and the stock price with respect to a given filtration representing the information level, even in presence of jumps. Finally, we discuss some practical examples in a Markovian framework and show that the computation of the optimal strategy leads to solve filtering problems under the realworld probability measure and under the minimal martingale measure. 
Date:  2013–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1312.4385&r=rmg 
By:  Collins, Keith; Bulut, Harun 
Keywords:  crop insurance, risk management, risk management agency, farmers, production agriculture, agriculture, Agribusiness, Agricultural and Food Policy, Agricultural Finance, Crop Production/Industries, Risk and Uncertainty, 
Date:  2013–05 
URL:  http://d.repec.org/n?u=RePEc:ags:ncissr:160463&r=rmg 
By:  Tommaso Paletta; Arturo Leccadito; Radu Tunaru 
Abstract:  Theoretical models applied to option pricing should take into account the empirical characteristics of the underlying financial time series. In this paper, we show how to price basket options when assets follow a shifted lognormal process with jumps capable of accommodating negative skewness. Our technique is based on the Hermite polynomial expansion that can match exactly the first m moments of the model impliedprobability distribution. This method is shown to provide superior results for basket options not only with respect to pricing but also for hedging. 
Date:  2013–12 
URL:  http://d.repec.org/n?u=RePEc:arx:papers:1312.4443&r=rmg 