nep-rmg New Economics Papers
on Risk Management
Issue of 2010‒10‒09
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Modeling a Distribution of Mortgage Credit Losses By Petr Gapko; Martin Šmíd
  2. Macro-prudential Approach to Regulation - Scope and Issues By Shyamala Gopinath
  3. Building Loss Models By Burnecki, Krzysztof; Janczura, Joanna; Weron, Rafal
  4. Capital allocation for credit portfolios under normal and stressed market conditions By Norbert Jobst; Dirk Tasche
  5. The Role of the State in Managing and Forestalling Systemic Financial Crises: Some Issues and Perspectives By Charles Adams
  6. An econometric model to quantify benchmark downturn LGD on residential mortgages By Morone, Marco; Cornaglia, Anna
  7. Perceived Vulnerability to Downside Risk By Felix Povel
  8. Towards a volatility index for the Italian stock market By Silvia Muzzioli
  9. Jump Tails, Extreme Dependencies, and the Distribution of Stock Returns By Tim Bollerslev; Viktor Todorov

  1. By: Petr Gapko (Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic; Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic); Martin Šmíd (Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic)
    Abstract: One of the biggest risks arising from financial operations is the risk of counterparty default, commonly known as a “credit risk”. Leaving unmanaged, the credit risk would, with a high probability, result in a crash of a bank. In our paper, we will focus on the credit risk quantification methodology. We will demonstrate that the current regulatory standards for credit risk management are at least not perfect, despite the fact that the regulatory framework for credit risk measurement is more developed than systems for measuring other risks, e.g. market risks or operational risk. Generalizing the well known KMV model, standing behind Basel II, we build a model of a loan portfolio involving a dynamics of the common factor, influencing the borrowers’ assets, which we allow to be non-normal. We show how the parameters of our model may be estimated by means of past mortgage deliquency rates. We give a statistical evidence that the non-normal model is much more suitable than the one assuming the normal distribution of the risk factors. We point out how the assumption that risk factors follow a normal distribution can be dangerous. Especially during volatile periods comparable to the current crisis, the normal distribution based methodology can underestimate the impact of change in tail losses caused by underlying risk factors.
    Keywords: Credit Risk, Mortgage, Delinquency Rate, Generalized Hyperbolic Distribution, Normal Distribution
    JEL: G21
    Date: 2010–09
  2. By: Shyamala Gopinath
    Abstract: It is being acknowledged that a macro prudential perspective is critical in designing and pursuing micro prudential regulation of institutions and markets. Two distinct but highly inter-related constructs have come to epitomize this post-crisis framework: macro prudential regulation and systemic risk management. Both these concepts are philosophically appealing and conceptually sound, but operationally quite challenging. Understanding the nuanced interplay between these would be crucial in designing an efficient operative framework for financial stability. [Paper presented at the ADBI-BNM Conference on “Macroeconomic and Financial Stability in Asian Emerging Marketsâ€, Kuala Lumpur].
    Keywords: asian, emerging, markets, macro prudential, micro, crisis, philosophically, framework, financial stability, institutions, markets, risk management, economic, procyclical, bank, capital,
    Date: 2010
  3. By: Burnecki, Krzysztof; Janczura, Joanna; Weron, Rafal
    Abstract: This paper is intended as a guide to building insurance risk (loss) models. A typical model for insurance risk, the so-called collective risk model, treats the aggregate loss as having a compound distribution with two main components: one characterizing the arrival of claims and another describing the severity (or size) of loss resulting from the occurrence of a claim. In this paper we first present efficient simulation algorithms for several classes of claim arrival processes. Then we review a collection of loss distributions and present methods that can be used to assess the goodness-of-fit of the claim size distribution. The collective risk model is often used in health insurance and in general insurance, whenever the main risk components are the number of insurance claims and the amount of the claims. It can also be used for modeling other non-insurance product risks, such as credit and operational risk.
    Keywords: Insurance risk model; Loss distribution; Claim arrival process; Poisson process; Renewal process; Random variable generation; Goodness-of-fit testing
    JEL: G22 C63 C46 C15 G32
    Date: 2010–09
  4. By: Norbert Jobst; Dirk Tasche
    Abstract: If the probability of default parameters (PDs) fed as input into a credit portfolio model are estimated as through-the-cycle (TTC) PDs stressed market conditions have little impact on the results of the capital calculations conducted with the model. At first glance, this is totally different if the PDs are estimated as point-in-time (PIT) PDs. However, it can be argued that the reflection of stressed market conditions in input PDs should correspond to the use of reduced correlation parameters or even the removal of correlations in the model. Additionally, the confidence levels applied for the capital calculations might be made reflective of the changing market conditions. We investigate the interplay of PIT PDs, correlations, and confidence levels in a credit portfolio model in more detail and analyse possible designs of capital-levelling policies. Our findings may of interest to banks that want to combine their approaches to capital measurement and allocation with active portfolio management that, by its nature, needs to be reflective of current market conditions.
    Date: 2010–09
  5. By: Charles Adams
    Abstract: This paper reviews recent state interventions in financial crises and draws lessons for crisis management. A number of areas are identified where crisis management could be strengthened, including with regard to the tools and instruments used to involve the private sector in crisis resolution (with a view to reducing the recent enhanced role of official bailouts and the associated moral hazard), to allow for the orderly resolution of systemically important financial firms (to make these firms “safe to failâ€), and with regard to achieving better integration with ex ante macroprudential surveillance. The paper proposes the establishment of high level systemic risk councils (SRCs) in each country with responsibility for overseeing systemic risk in both tranquil times and crisis periods and coordinating the activities of key government ministries, agencies, and the central bank. [ADBI Working Paper 242]
    Keywords: state, financial crises, crisis management, instruments, financial, government ministries, agencies, central bank
    Date: 2010
  6. By: Morone, Marco; Cornaglia, Anna
    Abstract: The paper describes a theoretical approach to determine the downturn LGD for residential mortgages, which is compliant with the regulatory requirement and thus suited to be used for validation, at least as it can give benchmark results. The link between default rates and recovery rates is in fact acknowledged by the regulatory framework as the driver of the downturn LGD, but data constraints do not usually allow for direct estimation of such a dependency. Both default rates and LGD parameters can anyway be related to macroeconomic variables: in the case of mortgages, real estate prices are the common driver. Household default rates are modelled inside a Vector Autoregressive Model incorporating a few other macroeconomic variables, which is estimated on Italian data. Assuming that LGD historical data series are not available, real estate prices influence on recovery rates is described through a theoretical Bayesian approach: possession probability conditional to Loan to Value can thus be quantified, which determines the magnitude of the effect of a price increase on LGD. Macroeconomic variables are then simulated on a five years path in order to determine the loss distribution (default rates times LGD per unit of EAD), both in the case of stochastic price dependent LGD and of deterministic LGD (but still variable default rates). The ratio between the two measures of loss, calculated at the 99.9th percentile for consistency with the regulatory formulas, corresponds to the downturn effect on LGD. In fact, the numerator of the ratio takes into account correlations between DR and LGD. Some results are presented for different combinations of average LGD and unconditional possession probability, which are specific for each bank.
    Keywords: downturn LGD; default and recovery rates correlation; mortgage; Loan to Value; real estate price; possession probability; Bayesian approach; stress testing; Vector Autoregression;
    JEL: C32 C15 G32 C01 C11 G21
    Date: 2010–05–28
  7. By: Felix Povel (Georg-August-University Göttingen)
    Abstract: In this paper we propose an approach to vulnerability called perceived vulnerability to downside risk. We argue that the other concepts of vulnerability, though partially adhering to the focus axiom, do not exclusively consider downside risks in their measures. The reason for this is that most of them use a pre-determined threshold such as the poverty line as their benchmark for analysis. Instead, we opt for the current level of wellbeing of a household as reference point. Also, we propose to use subjective risk perception as the source of information for quantifying vulnerability since it overcomes some of the shortcomings connected to the reliance on information about the past. Finally, we apply the measure of perceived vulnerability to downside risk to risk perception data from Thailand and Vietnam and find that households in the latter country tend to be more vulnerable than households in the former. Moreover, determinants of perceived vulnerability to downside risk differ significantly between the two countries.
    Keywords: Vulnerability; Risk; Risk Perception; Subjective Wellbeing
    JEL: D81 I31 I32 O12
    Date: 2010–09–28
  8. By: Silvia Muzzioli
    Abstract: The aim of this paper is to analyse and empirically test how to unlock volatility information from option prices. The information content of three option based forecasts of volatility: Black-Scholes implied volatility, model-free implied volatility and corridor implied volatility is addressed, with the ultimate plan of proposing a new volatility index for the Italian stock market. As for model-free implied volatility, two different extrapolation techniques are implemented. As for corridor implied volatility, five different corridors are compared. Our results, which point to a better performance of corridor implied volatilities with respect to both Black-Scholes implied volatility and model-free implied volatility, are in favour of narrow corridors. The volatility index proposed is obtained with an overall 50% cut of the risk neutral distribution. The properties of the volatility index are explored by analysing both the contemporaneous relationship between implied volatility changes and market returns and the usefulness of the proposed index in forecasting future market returns.
    Keywords: volatility index; Black-Scholes implied volatility; model-free implied volatility; corridor implied volatility; implied binomial trees
    JEL: G13 G14
    Date: 2010–09
  9. By: Tim Bollerslev (Department of Economics, Duke University, and NBER and CREATES); Viktor Todorov (Department of Finance, Kellogg School of Management, Northwestern University)
    Abstract: We provide a new framework for estimating the systematic and idiosyncratic jump tail risks in financial asset prices. The theory underlying our estimates are based on in-fill asymptotic arguments for directly identifying the systematic and idiosyncratic jumps, together with conventional long-span asymptotics and Extreme Value Theory (EVT) approximations for consistently estimating the tail decay parameters and asymptotic tail dependencies. On implementing the new estimation procedures with a panel of highfrequency intraday prices for a large cross-section of individual stocks and the aggregate S&P 500 market portfolio, we find that the distributions of the systematic and idiosyncratic jumps are both generally heavy-tailed and not necessarily symmetric. Our estimates also point to the existence of strong dependencies between the market-wide jumps and the corresponding systematic jump tails for all of the stocks in the sample. We also show how the jump tail dependencies deduced from the high-frequency data together with the day-to-day temporal variation in the volatility are able to explain the “extreme” dependencies vis-a-vis the market portfolio.
    Keywords: Extreme events, jumps, high-frequency data, jump tails, non-parametric estimation, stochastic volatility, systematic risks, tail dependence.
    JEL: C13 C14 G10 G12
    Date: 2010–09–10

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