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on Risk Management |
| By: | Feng-Hui Yu; Wai-Ki Ching; Jia-Wen Gu; Tak-Kuen Siu |
| Abstract: | In this paper we consider a reduced-form intensity-based credit risk model with a hidden Markov state process. A filtering method is proposed for extracting the underlying state given the observation processes. The method may be applied to a wide range of problems. Based on this model, we derive the joint distribution of multiple default times without imposing stringent assumptions on the form of default intensities. Closed-form formulas for the distribution of default times are obtained which are then applied to solve a number of practical problems such as hedging and pricing credit derivatives. The method and numerical algorithms presented may be applicable to various forms of default intensities. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1603.02902&r=rmg |
| By: | Delis, Manthos D.; Hasan, Iftekhar; Tsionas, Efthymios G. |
| Abstract: | Use of variability of profits and other accounting-based ratios in order to estimate a firm's risk of insolvency is a well-established concept in management and economics. This paper argues that these measures fail to approximate the true level of risk accurately because managers consider other strategic choices and goals when making risky decisions. Instead, we propose an econometric model that incorporates current and past strategic choices to estimate risk from the profit function. Specifically, we extend the well-established multiplicative error model to allow for the endogeneity of the uncertainty component. We demonstrate the power of the model using a large sample of U.S. banks, and show that our estimates predict the accelerated bank risk that led to the subprime crisis in 2007. Our measure of risk also predicts the probability of bank default both in the period of the default, but also well in advance of this default and before conventional measures of bank risk. |
| Keywords: | risk, strategic management, endogenous, profit function |
| Date: | 2015–08–20 |
| URL: | http://d.repec.org/n?u=RePEc:bof:bofrdp:urn:nbn:fi:bof-201508211363&r=rmg |
| By: | Berdin, Elia; Sottocornola, Matteo |
| Abstract: | This paper investigates systemic risk in the insurance industry. We first analyze the systemic contribution of the insurance industry vis-à-vis other industries by applying 3 measures, namely the linear Granger causality test, conditional value at risk and marginal expected shortfall, on 3 groups, namely banks, insurers and non-financial companies listed in Europe over the last 14 years. We then analyze the determinants of the systemic risk contribution within the insurance industry by using balance sheet level data in a broader sample. Our evidence suggests that i) the insurance industry shows a persistent systemic relevance over time and plays a subordinate role in causing systemic risk compared to banks, and that ii) within the industry, those insurers which engage more in non-insurance-related activities tend to pose more systemic risk. In addition, we are among the first to provide empirical evidence on the role of diversification as potential determinant of systemic risk in the insurance industry. Finally, we confirm that size is also a significant driver of systemic risk, whereas price-to-book ratio and leverage display counterintuitive results. |
| Keywords: | systemic risk,insurance activities,systemically important financial institutions |
| JEL: | G01 G22 G28 G32 |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safewp:121&r=rmg |
| By: | Marcin Pitera; Thorsten Schmidt |
| Abstract: | The estimation of risk measured in terms of a risk measure is typically done in two steps: in the first step, the distribution is estimated by statistical methods, either parametric or non-parametric. In the second step, the estimated distribution is considered as true distribution and the targeted risk-measure is computed. In the parametric case this is achieved by using the formula for the risk-measure in the model and inserting the estimated parameters. It is well-known that this procedure is not efficient because the highly nonlinear mapping from model parameters to the risk-measure introduces an additional biases. Statistical experiments show that this bias leads to a systematic underestimation of risk. In this regard we introduce the concept of unbiasedness to the estimation of risk. We show that an appropriate bias correction is available for many well known estimators. In particular, we consider value-at-risk and tail value-at-risk (expected shortfall). In the special case of normal distributions, closed-formed solutions for unbiased estimators are given. For the general case we propose a bootstrapping algorithm and illustrate the outcomes by several data experiments. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1603.02615&r=rmg |
| By: | Beatriz Martínez, Beatriz Martínez; Hipòlit Torró, Hipòlit Torró |
| Abstract: | In many futures markets, trading is concentrated in the front contract and positions are rolled-over until the strategy horizon is attained. In this paper, a pair-wise comparison between the conventional risk premium and the accrued risk premium in rolled-over positions in the front contract is carried out for UK natural gas futures. Several novel results are obtained. Firstly, and most importantly, the accrued risk premium in rollover strategies is significatively larger than conventional risk premiums and increases with the time to delivery. Specifically, for strategy horizons between three and six months, this difference increases from 1% to 10%. Secondly, it is the first time that risk premium in day-ahead futures has been measured in this market. The average value of the day-ahead risk premium is 0.5% per day and it is statistically significant. Thirdly, all risk premiums are significantly larger and more volatile in winter. Finally, risk premium time-variation is analyzed using a regression model. It is shown that reservoirs, weather, liquidity, volatility, skewness, and seasons are able in all cases to explain between 21% and 59% of the risk premium time-variation (depending on the futures maturity and sub-period). |
| Keywords: | Natural Gas Market, Futures Premium, Rollover, Seasonal Risk Premiums, Environmental Economics and Policy, G13, L95, |
| Date: | 2016–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:ags:feemes:232212&r=rmg |
| By: | Hannah Cheng; Juan Zhan; William Rea; Alethea Rea |
| Abstract: | We report the results of fifteen sets of portfolio selection simulations using stocks in the ASX200 index for the period May 2000 to December 2013. We investigated five portfolio selection methods, randomly and from within industrial groups, and three based on neighbor-Net phylogenetic networks. We report that using random, industrial groups, or neighbor-Net phylogenetic networks alone rarely produced statistically significant reduction in risk, though in four out of the five cases in which it did so, the portfolios selected using the phylogenetic networks had the lowest risk. However, we report that when using the neighbor-Net phylogenetic networks in combination with industry group selection that substantial reductions in portfolio return spread were achieved. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1603.02354&r=rmg |
| By: | Gong, Di; Wagner, Wolf |
| Abstract: | Public guarantees extended during systemic crises can affect the relative pricing of risks in the financial system. Studying the market for syndicated loans, we find that banks require lower compensation for aggregate risk than for idiosyncratic risk, consistent with systemic risk-taking due to guarantees. The underpricing of aggregate risk is concentrated among banks that benefit more from exposure to public guarantees and disappears for non-bank lenders not protected by these guarantees. Estimates from loan spread regressions imply a sizeable guarantee that is passed onto borrowers, but also distortions in the economy's capital allocation. |
| Keywords: | loan pricing; public guarantees; systemic risk-taking; too-many-to-fail |
| JEL: | G21 G32 |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:11150&r=rmg |
| By: | Byström, Hans (Department of Economics, Lund University) |
| Abstract: | In this paper (letter) I discuss how blockchains potentially could affect the way credit risk is modeled, and how the improved trust and timing associated with blockchain-enabled real-time accounting could improve default prediction. To demonstrate the (quite substantial) effect the change would have on well-known credit risk measures, a simple case-study compares Z-scores and Merton distances to default computed using typical accounting data of today to the same risk measures computed under a hypothetical future blockchain regime. |
| Keywords: | blockchain; credit risk modeling; real-time accounting |
| JEL: | G33 G39 M41 M42 |
| Date: | 2016–03–02 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lunewp:2016_004&r=rmg |
| By: | Bienz, Carsten; Thorburn, Karin; Walz, Uwe |
| Abstract: | Private equity fund managers are typically required to invest their own money alongside the fund. We examine how this coinvestment affects the acquisition strategy of leveraged buyout funds. In a simple model, where the investment and capital structure decisions are made simultaneously, we show that a higher coinvestment induces managers to chose less risky firms and use more leverage. We test these predictions in a unique sample of private equity investments in Norway, where the fund manager's taxable wealth is publicly available. Consistent with the model, portfolio company risk decreases and leverage ratios increase with the coinvestment fraction of the manager's wealth. Moreover, funds requiring a relatively high coinvestment tend to spread its capital over a larger number of portfolio firms, consistent with a more conservative investment policy. |
| Keywords: | private equity,leveraged buyouts,incentives,coinvestment,risk taking,wealth |
| JEL: | D86 G12 G31 G32 G34 |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:safewp:126&r=rmg |
| By: | Beck, Thorsten; Carletti, Elena; Goldstein, Itay |
| Abstract: | This chapter discusses recent regulatory reforms and relates them to different market failures in banking, based on the recent theoretical and empirical literature with focus on insights from the recent crisis. We also provide a broader discussion of challenges in financial sector regulation, related to the regulatory perimeter and financial innovation as tools financial market participants use to evade tighter regulatory frameworks. We argue for a dynamic view of regulation that takes into account the changing nature of risk-taking activities and regulatory arbitrage efforts. We also stress the need for a balanced approach between complex and simple tools, a strong focus on systemic in addition to idiosyncratic regulation, and a stronger emphasis on the resolution phase of financial regulation. |
| Keywords: | Banking; Basel III; financial stability; regulation |
| JEL: | G21 G28 |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:11147&r=rmg |
| By: | Giulio Bottazzi; Alessandro De Sanctis; Fabio Vanni |
| Abstract: | After the outbreak of the financial crisis in 2007-2008 the level of non-performing loans (NPLs) in the economy has generally increased. However, while in some countries this has been a transitory phenomenon, in others it still represents a major threat for economic recovery and financial stability. The present work investigates the relationship between non-performing loans and systemic risk using a network-based approach. In particular, we analyze how an increase in NPLs at firm level propagates to the financial system through the network of credits and debits. To this end we develop a model with two types of agents, banks and firms, linked one another in a two-layers structure by their reciprocal credits and debits. The model is analyzed via numerical simulations and allows a) to define a synthetic measure of systemic risk and b) to quantify the resilience of the financial system to external shocks, making it particularly useful from a policy point of view. For illustrative purposes, in section 3 we present an application of the model to Italy, Germany, and United Kingdom, using empirically observed data for the three countries. |
| Keywords: | financial crisis, network theory, non-performing loans, resilience, systemic risk |
| Date: | 2016–01–03 |
| URL: | http://d.repec.org/n?u=RePEc:ssa:lemwps:2016/08&r=rmg |
| By: | Eric Helland; Anupam B. Jena; Dan P. Ly; Seth A. Seabury |
| Abstract: | When faced with financial uncertainty, rational agents have incentives to take steps ex ante to reduce the probability (self-protection) or size (self-insurance) of a loss. However, in the case of liability risk, especially physician responses to malpractice risk, most empirical analyses have focused exclusively on measuring self-protection. This paper studies whether physicians invest in self-insurance by exploring how they respond to policies that allow them to lower the financial cost of malpractice liability. Specifically, we test whether physicians exploit provisions of bankruptcy laws and adjust the value of their home purchases to protect assets from liability claims exceeding their malpractice policy limits. We find that in states with unlimited “homestead” exceptions—provisions of state law that protect home equity when individuals file for bankruptcy—physicians invest 13% more in the value of their homes compared to what they would have invested in the absence of an exemption, whereas no such effect is true for other professionals of similar family income, family size, demographics, and city of residence. Additionally, the response of physicians to unlimited homestead exemptions is larger in areas with higher liability risk, where physicians would have greater incentive to insure against financial risks. Our findings suggest that physicians take financially costly decisions to protect themselves from uninsured malpractice risk, implying more generally that individuals self-insure against liability risk when insurance markets are incomplete. |
| JEL: | G22 I1 K13 |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22031&r=rmg |
| By: | Asian Development Bank (ADB); Asian Development Bank (ADB) (Sustainable Development and Climate Change Department, ADB); Asian Development Bank (ADB) (Sustainable Development and Climate Change Department, ADB); Asian Development Bank (ADB) |
| Abstract: | The Asian Development Bank (ADB) has been working closely with the Association of Southeast Asian Nations (ASEAN) and the People’s Republic of China, Japan, and the Republic of Korea—collectively known as ASEAN+3—to foster the development of local currency bond markets and facilitate regional bond market integration under the Asian Bond Markets Initiative (ABMI). ABMI was launched in 2002 to strengthen the resilience of the region’s financial system by developing local currency bond markets as an alternative source to foreign currency denominated short-term bank loans for long-term investment. Bond investors typically have a long position in local currency bond markets. To manage their foreign exchange (FX) risk, they may want to hedge that exposure for a period of time. They also want to be sure they can easily convert the local currency to dollars upon the sale of a bond. This study was undertaken under ABMI and funded by the Government of Japan. It reviews the FX and FX hedging markets in ASEAN+3 as they relate to cross-border investments in local currency bonds, and makes recommendations to facilitate the development of the markets and FX risk management. |
| Keywords: | Regional cooperation, Regional integration, ASEAN+3, Local currency bonds, and Foreign exchange risk management |
| Date: | 2015–08 |
| URL: | http://d.repec.org/n?u=RePEc:asd:wpaper:rpt157560-2&r=rmg |
| By: | Gareth W. Peters; Wilson Y. Chen; Richard H. Gerlach |
| Abstract: | This paper discusses different classes of loss models in non-life insurance settings. It then overviews the class Tukey transform loss models that have not yet been widely considered in non-life insurance modelling, but offer opportunities to produce flexible skewness and kurtosis features often required in loss modelling. In addition, these loss models admit explicit quantile specifications which make them directly relevant for quantile based risk measure calculations. We detail various parameterizations and sub-families of the Tukey transform based models, such as the g-and-h, g-and-k and g-and-j models, including their properties of relevance to loss modelling. One of the challenges with such models is to perform robust estimation for the loss model parameters that will be amenable to practitioners when fitting such models. In this paper we develop a novel, efficient and robust estimation procedure for estimation of model parameters in this family Tukey transform models, based on L-moments. It is shown to be more robust and efficient than current state of the art methods of estimation for such families of loss models and is simple to implement for practical purposes. |
| Date: | 2016–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:1603.01041&r=rmg |