nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒10‒16
fourteen papers chosen by
Stan Miles, Thompson Rivers University

  1. Default Forecasting and Credit Valuation Adjustment By Lee, David
  2. Measuring the link between cyclical systemic risk and capital adequacy for Ukrainian banking sector By Alona Shmygel
  3. Consumption Partial Insurance in the Presence of Tail Income Risk By Ghosh, Anisha; Theloudis, Alexandros
  4. Probability of Default modelling with L\'evy-driven Ornstein-Uhlenbeck processes and applications in credit risk under the IFRS 9 By Kyriakos Georgiou; Athanasios N. Yannacopoulos
  5. Time consistency of dynamic risk measures and dynamic performance measures generated by distortion functions By Tomasz R. Bielecki; Igor Cialenco; Hao Liu
  6. Growth at Risk and Uncertainty: Evidence from Mexico By Salgado Alfredo; Trujillo Alejandro
  7. The market for sharing interest rate risk: quantities behind prices By Khetan, Umang; Neamțu, Ioana; Sen, Ishita
  8. Default Process Modeling and Credit Valuation Adjustment By David Xiao
  9. Real-time VaR Calculations for Crypto Derivatives in kdb+/q By Yutong Chen; Paul Bilokon; Conan Hales; Laura Kerr
  10. The European significant risk transfer securitisation market By González, Fernando; Triandafil, Cristina Morar
  11. Are risk preferences optimal? By Skjold, Benjamin; Steinkamp, Simon Richard; Hulme, Oliver J; Peters, Ole; Connaughton, Colm
  12. Macroprudential stress‑test models: a survey By Aikman, David; Beale, Daniel; Brinley-Codd, Adam; Covi, Giovanni; Hüser, Anne‑Caroline; Lepore, Caterina
  13. Margins, debt capacity, and systemic risk By Sirio Aramonte; Andreas Schrimpf; Hyun Song Shin
  14. Tattle-tails: Gauging downside risks using option prices By Greg Adams; Maksym Tupis

  1. By: Lee, David
    Abstract: Credit valuation adjustment has acquired a great deal of attention from both theoreticians and practitioners in recent years. This paper presents a model for default forecasting and credit valuation adjustment. The model links distance-to-default, default probability, survival probability, default correlation, and risky valuation together. It captures default risk, credit migration, and wrong way risk simultaneously and naturally. The numerical study shows that the model implied credit spreads and default correlations are very close to the market observed ones, indicating that the model performs quite well. The results may be of interest to regulators, academics, and practitioners.
    Keywords: credit value adjustment (CVA), credit risk modeling, distance to default, default probability, survival probability, asset pricing involving credit risk.
    JEL: C15 C53 E37 G12 G13 G17 G24
    Date: 2023–09–12
  2. By: Alona Shmygel (National Bank of Ukraine)
    Abstract: In this paper we investigate the impact of cyclical systemic risk on future bank profitability for a large representative panel of Ukrainian banks between 2001 and 2023. Our framework relies on two general methods. The first method is based on linear local projections which allows us to study the estimated negative impact of cyclical systemic risk on bank profitability. The second method is based on the original IMF's Growth-at-Risk approach, utilizing quantile local projections to assess the impact of cyclical systemic risk on the tails of the future bank-level profitability distribution. Additionally, we enhance the macroprudential toolkit with a novel approach to calibrating the countercyclical capital buffer (CCyB). Furthermore, we develop the "Bank Capital-at-Risk" and "Share of vulnerable banks" indicators. These indicators are valuable tools for monitoring the build-up of systemic risk in the banking sector.
    Keywords: Systemic risk; Linear projections; Quantile regressions; Bank capital; Macroprudential policy
    JEL: E58 G21 G32
    Date: 2023–09–28
  3. By: Ghosh, Anisha; Theloudis, Alexandros (Tilburg University, Center For Economic Research)
    Keywords: Income risk; skewness; kurtosis; comsumption; PSID
    Date: 2023
  4. By: Kyriakos Georgiou; Athanasios N. Yannacopoulos
    Abstract: In this paper we develop a framework for estimating Probability of Default (PD) based on stochastic models governing an appropriate asset value processes. In particular, we build upon a L\'evy-driven Ornstein-Uhlenbeck process and consider a generalized model that incorporates multiple latent variables affecting the evolution of the process. We obtain an Integral Equation (IE) formulation for the corresponding PD as a function of the initial position of the asset value process and the time until maturity, from which we then prove that the PD function satisfies an appropriate Partial Integro-Differential Equation (PIDE). These representations allow us to show that appropriate weak (viscosity) as well as strong solutions exist, and develop subsequent numerical schemes for the estimation of the PD function. Such a framework is necessary under the newly introduced International Financial Reporting Standards (IFRS) 9 regulation, which has imposed further requirements on the sophistication and rigor underlying credit modelling methodologies. We consider special cases of the generalized model that can be used for applications to credit risk modelling and provide examples specific to provisioning under IFRS 9, and more.
    Date: 2023–09
  5. By: Tomasz R. Bielecki; Igor Cialenco; Hao Liu
    Abstract: The aim of this work is to study risk measures generated by distortion functions in a dynamic discrete time setup, and to investigate the corresponding dynamic coherent acceptability indices (DCAIs) generated by families of such risk measures. First we show that conditional version of Choquet integrals indeed are dynamic coherent risk measures (DCRMs), and also introduce the class of dynamic weighted value at risk measures. We prove that these two classes of risk measures coincides. In the spirit of robust representations theorem for DCAIs, we establish some relevant properties of families of DCRMs generated by distortion functions, and then define and study the corresponding DCAIs. Second, we study the time consistency of DCRMs and DCAIs generated by distortion functions. In particular, we prove that such DCRMs are sub-martingale time consistent, but they are not super-martingale time consistent. We also show that DCRMs generated by distortion functions are not weakly acceptance time consistent. We also present several widely used classes of distortion functions and derive some new representations of these distortions.
    Date: 2023–09
  6. By: Salgado Alfredo; Trujillo Alejandro
    Abstract: We analyze the relationship between uncertainty and economic growth expectations in Mexico through the Growth at Risk methodology. Our analysis consists of two stages: first, we estimate a quantile regression of annual output growth conditional on lagged values of a measure of macroeconomic uncertainty and other drivers. Second, based on the fitted values of the quantile regression, we estimate the parameters of a t-skewed distribution of expected economic growth. Our results show that an increase in macroeconomic uncertainty has a negative and statistically significant impact on the left tail of the growth distribution, leading to an increased probability of observing lower growth rates. These results remain robust to alternative measures of financial conditions, of economic policy uncertainty, and of risk exposure, as well as to alternative measurements of economic activity.
    Keywords: Macroeconomic Uncertainty;Financial Conditions;Growth at Risk
    JEL: C53 E23 E27 E32 O40
    Date: 2023–09
  7. By: Khetan, Umang (University of Iowa); Neamțu, Ioana (Bank of England); Sen, Ishita (Harvard Business School)
    Abstract: We study the extent of interest rate risk sharing across the financial system. We use granular positions and transactions data in interest rate swaps, covering over 60% of overall swap activity in the world. We show that pension and insurance (PF&I) sector emerges as a natural counterparty to banks and corporations: overall, and in response to decline in rates, PF&I buy duration, whereas banks and corporations sell duration. This cross-sector netting reduces the aggregate net demand that is supplied by dealers. However, two factors impede cross-sector netting and add to dealer imbalances across maturities. (i) PF&I, bank and corporate demand is segmented across maturities. (ii) Large volumes are traded by hedge funds, who behave like banks in the short end and like PF&I in the long end. This worsens segmentation, exposing dealers to a steepening or flattening of the yield curve in addition to residual duration risk. Consistent with this, we find that demand pressure, in particular hedge funds’ trades, impact swap spreads across maturities. We also document that long-tenor pension fund trades are less likely to be centrally cleared, adding counterparty credit risk to demand imbalances.
    Keywords: Interest rate risk; OTC derivatives; hedge funds; pension funds; insurance companies; banks; non-financial corporations; demand elasticities; counterparty credit risk
    JEL: G11 G12 G15 G21 G22 G23 G24 G32
    Date: 2023–07–21
  8. By: David Xiao
    Abstract: This paper presents a convenient framework for modeling default process and pricing derivative securities involving credit risk. The framework provides an integrated view of credit valuation adjustment by linking distance-to-default, default probability, survival probability, and default correlation together. We show that risky valuation is Martingale in our model. The framework reduces the technical issues of performing risky valuation to the same issues faced when performing the ordinary valuation. The numerical results show that the model prediction is consistent with the historical observations.
    Date: 2023–09
  9. By: Yutong Chen; Paul Bilokon; Conan Hales; Laura Kerr
    Abstract: Cryptocurrency market is known for exhibiting significantly higher volatility than traditional asset classes. Efficient and adequate risk calculation is vital for managing risk exposures in such market environments where extreme price fluctuations occur in short timeframes. The objective of this thesis is to build a real-time computation workflow that provides VaR estimates for non-linear portfolios of cryptocurrency derivatives. Many researchers have examined the predictive capabilities of time-series models within the context of cryptocurrencies. In this work, we applied three commonly used models - EMWA, GARCH and HAR - to capture and forecast volatility dynamics, in conjunction with delta-gamma-theta approach and Cornish-Fisher expansion to crypto derivatives, examining their performance from the perspectives of calculation efficiency and accuracy. We present a calculation workflow which harnesses the information embedded in high-frequency market data and the computation simplicity inherent in analytical estimation procedures. This workflow yields reasonably robust VaR estimates with calculation latencies on the order of milliseconds.
    Date: 2023–09
  10. By: González, Fernando; Triandafil, Cristina Morar
    Abstract: The European significant risk transfer (SRT) securitisation market is increasingly being used by major EU banks to manage risk and capital, but is not well known. SRT can provide an extra source of capital, flexibly and at a reasonable cost. Despite the bespoke nature of transactions, the SRT market has expanded significantly in the recent past to the point where it has now become a dependable way for banks to release capital, manage their balance sheets and improve their capital ratios. Banking supervisors assess SRT transactions to evaluate the degree of risk transfer from banks to investors, allowing institutions to achieve capital relief when this is considered sufficient. The market has become a permanent feature in European banks’ capital management toolkit, alongside other standard but better-known instruments. Drawing on the ECB’s unique and comprehensive database of SRT securitisations issued by large European banks supervised by the Single Supervisory Mechanism (SSM), we provide an overview of the main features of the European SRT market, a typology of the structures currently in use and an account of the market’s evolution over the past five years. In so doing, we attempt to shed light on the main conceptual features of SRT securitisations in relation to non-SRT securitisation structures, as well as the regulatory processes behind capital relief that have been instrumental in supporting their increased use by European banks. JEL Classification: G21, G28, G29
    Keywords: asset quality, capital requirements, government policy and regulation, guarantees, lending conditions, Securitisations, significant risk transfer
    Date: 2023–10
  11. By: Skjold, Benjamin; Steinkamp, Simon Richard; Hulme, Oliver J; Peters, Ole; Connaughton, Colm
    Abstract: Decision theories commonly assume that risk preferences are idiosyncratic but stable over time. A recent model from ergodicity economics reveals that optimising the growth rate of wealth requires individuals to adjust their risk preferences to wealth dynamics. Here we ask whether humans are capable of such adjustments. In a randomised control trial, participants will make risky decisions under additive and multiplicative dynamics. We will estimate risk preferences separately in the two conditions for each participant by fitting isoelastic utility functions via hierarchical Bayesian models and standard regression techniques. Growth optimal adjustments to risk preferences would confirm our main hypothesis, whereas risk preferences that are stable across conditions would disconfirm it. Pilot data from 11 participants revealed strong evidence supporting the main hypothesis. We will replicate this pilot in a pre-registered experiment with up to 150 participants.
    Date: 2023–09–07
  12. By: Aikman, David (King’s College, London); Beale, Daniel (Bank of England); Brinley-Codd, Adam (Bank of England); Covi, Giovanni (Bank of England); Hüser, Anne‑Caroline (Bank of England); Lepore, Caterina (International Monetary Fund)
    Abstract: We survey the rapidly developing literature on macroprudential stress‑testing models. In scope are models of contagion between banks, models of contagion within the wider financial system including non‑bank financial institutions such as investment funds, and models that emphasise the two-way interaction between the financial sector and the real economy. Our aim is twofold: first, to provide a reference guide of the state of the art for those developing such models; second, to distil insights from this endeavour for policymakers using these models. In our view, the modelling frontier faces three main challenges: (a) our understanding of the potential for amplification in sectors of the non-bank financial system during periods of stress, (b) multi-sectoral models of the non-bank financial system to analyse the behaviour of the overall demand and supply of liquidity under stress and (c) stress‑testing models that incorporate comprehensive two-way interactions between the financial system and the real economy. Emerging lessons for policymakers are that, for a given-sized shock hitting the system, its eventual impact will depend on (a) the size of financial institutions’ capital and liquidity buffers, (b) the liquidation strategies financial institutions adopt when they need to raise cash and (c) the topology of the financial network.
    Keywords: Stress testing; system-wide models; contagion; systemic risk; market-based finance; real-financial linkages; sectoral interlinkages; macroprudential policy
    JEL: G21 G22 G23 G32
    Date: 2023–08–11
  13. By: Sirio Aramonte; Andreas Schrimpf; Hyun Song Shin
    Abstract: Debt capacity depends on margins. When set in a financial system context with collateralized borrowing, two additional features emerge. The first is the recursive property of leverage whereby higher leverage by one player begets higher leverage overall, reflecting the nature of debt as collateral for others. The second feature is that the "dash for cash" is the mirror image of deleveraging. In any setting where market participants engage in margin budgeting, a generalized increase in margins entails a shift of the overall portfolio away from riskier to safer assets. These findings have important implications for the design of non-bank financial intermediary (NBFI) regulations and of central bank backstops.
    Keywords: financial intermediation, non-banks, market-based finance, market liquidity, systemic risk
    JEL: G22 G23 G28
    Date: 2023–09
  14. By: Greg Adams; Maksym Tupis
    Abstract: Options markets offer unique insights into the changing risks different assets face, which helps us better understand the broader risks to the Canadian economy. We show how option prices help reveal that investors did not anticipate large downside risks to either major Canadian banks or economic growth during the March 2023 financial sector system stress, a period when policy-makers and investors were unsure of what the future held for Canada’s economy.
    Keywords: Financial markets; Monetary policy and uncertainty; Recent economic and financial developments
    JEL: E4 E44 E5 E52
    Date: 2023–09

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