nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒09‒18
eleven papers chosen by
Stan Miles, Thompson Rivers University

  1. Measuring systemic financial stress and its risks for growth By Chavleishvili, Sulkhan; Kremer, Manfred
  2. How do Financial Crises Redistribute Risk? By Kris James Mitchener; Angela Vossmeyer
  3. Risk Management and Derivatives Losses By Vicente García Averell; Calixto López Castañon; Gabriel Levin-Konigsberg; Hillary Stein
  4. The Financial Origins of Non-Fundamental Risk By Sushant Acharya; Keshav Dogra; Sanjay R. Singh
  5. The Price of Macroeconomic Uncertainty: Evidence from Daily Options By Juan M. Londono; Mehrdad Samadi
  6. Loan portfolio management and Liquidity Risk: The impact of limited liability and haircut By Deb Narayan Barik; Siddhartha P. Chakrabarty
  7. Predicting Financial Crises: The Role of Asset Prices By Tristan Hennig; Mr. Plamen K Iossifov; Mr. Richard Varghese
  8. Managing new technology: the combination of model risk and enterprise risk management By Eleanor Toye Scott; Philip Stiles; Pradeep Debata
  9. Contagion Effects of the Silicon Valley Bank Run By Dong Beom Choi; Paul Goldsmith-Pinkham; Tanju Yorulmazer
  10. The volatility of economic policy uncertainty By Tacye Hong; Paul Kattuman
  11. Demand Volatility and Firm Export Margins: Evidence from Egypt By Yasmine Kamal

  1. By: Chavleishvili, Sulkhan; Kremer, Manfred
    Abstract: This paper proposes a general statistical framework for systemic financial stress indices which measure the severity of financial crises on a continuous scale. Several index designs from the financial stress and systemic risk literature can be represented as special cases. We introduce an enhanced daily variant of the CISS (composite indicator of systemic stress) for the euro area and the US. The CISS aggregates a representative set of stress indicators using their time-varying cross-correlations as systemic risk weights, computationally similar to how portfolio risk is computed from the risk characteristics of individual assets. A boot-strap algorithm provides test statistics. Single-equation and system quantile growth-at-risk regressions show that the CISS has stronger effects in the lower tails of the growth distribu-tion. Simulations based on a quantile VAR suggest that systemic stress is a major driver of the Great Recession, while its contribution to the COVID-19 crisis appears to be small. JEL Classification: C14, C31, C43, C53, E44, G01
    Keywords: Financial crisis, Financial stress index, Macro-financial linkages, Quantile VAR, Systemic risk
    Date: 2023–08
  2. By: Kris James Mitchener; Angela Vossmeyer
    Abstract: We examine how financial crises redistribute risk, employing novel empirical methods and micro data from the largest financial crisis of the 20th century – the Great Depression. Using balance-sheet and systemic risk measures at the bank level, we build an econometric model with incidental truncation that jointly considers bank survival, the type of bank closure (consolidations, absorption, and failures), and changes to bank risk. Despite roughly 9, 000 bank closures, risk did not leave the financial system; instead, it increased. We show that risk was redistributed to banks that were healthier prior to the financial crisis. A key mechanism driving the redistribution of risk was bank acquisition. Each acquisition increases the balance-sheet and systemic risk of the acquiring bank by 25%. Our findings suggest that financial crises do not quickly purge risk from the system, and that merger policies commonly used to deal with troubled financial institutions during crises have important implications for systemic risk.
    JEL: C3 E44 G21 N12
    Date: 2023–08
  3. By: Vicente García Averell; Calixto López Castañon; Gabriel Levin-Konigsberg; Hillary Stein
    Abstract: Even though financial risk management has the ability to generate value, the use of financial derivatives among nonfinancial corporations remains limited. We identify a channel that contributes to this limited use: the decoupling of derivatives losses and operational gains. Specifically, firms ex post consider their operational profits separately from their derivatives profits. We explore this phenomenon among firms in Mexico. We use the universe of US dollar Mexican peso currency derivatives transactions in Mexico along with customs data to construct a unique data set on operational exchange rate exposure and financial hedging. We find that contrary to a rational and frictionless benchmark, performance in previous derivatives transactions predicts future derivatives use. Using a regression kink design to measure the impact of decoupling on risk management, we find that when losses from previous transactions increase 1 percentage point, firms become 4.24 percentage points less likely to take out a new derivatives position within 90 days. We provide further evidence that is consistent with decoupling and supports rejecting a net worth channel.
    Keywords: risk management; exchange rates; financial hedging; narrow framing; loss aversion
    JEL: G32 F31
    Date: 2023–07–01
  4. By: Sushant Acharya; Keshav Dogra; Sanjay R. Singh
    Abstract: We formalize the idea that the financial sector can be a source of non-fundamental risk. Households' desire to hedge against price volatility can generate price volatility in equilibrium, even absent fundamental risk. Fearing that asset prices may fall, risk-averse households demand safe assets from leveraged intermediaries, whose issuance of safe assets exposes the economy to self-fulfilling fire sales. Policy can eliminate nonfundamental risk by (i) increasing the supply of publicly backed safe assets, through issuing government debt or bailing out intermediaries, or (ii) reducing the demand for safe assets, through social insurance or by acting as a market maker of last resort.
    Keywords: safe assets; market crashes; liquidity; fire sales
    JEL: D52 D84 E62 G10 G12
    Date: 2023–05–01
  5. By: Juan M. Londono; Mehrdad Samadi
    Abstract: Using recently available daily S&P 500 index option expirations, we examine the ex ante pricing of uncertainty surrounding key economic releases and the determinants of risk premia associated with these releases. The cost of insurance against price, variance, and downside risk is higher for options that span U.S. CPI, FOMC, Nonfarm Payroll, and GDP releases compared to neighboring expirations. We calculate release-driven forward equity and variance risk premia and find that premia vary considerably across economic releases and increase with risk aversion as well as with monetary policy and real economic uncertainty. The empirical framework presented in this paper can be used to examine the ex ante pricing of a wide variety of events.
    Keywords: variance risk; uncertainty; risk premium; macroeconomic releases; Federal Open Market Committee (FOMC); inflation; tail risk
    JEL: E44 G1 G12
    Date: 2023–06
  6. By: Deb Narayan Barik; Siddhartha P. Chakrabarty
    Abstract: In this article, we consider the problem of a bank's loan portfolio in the context of liquidity risk, while allowing for the limited liability protection enjoyed by the bank. Accordingly, we construct a novel loan portfolio model with limited liability, while maintaining a threshold level of haircut in the portfolio. For the constructed three-time step loan portfolio, at the initial time, the bank raises capital via debt and equity, investing the same in several classes of loans, while at the final time, the bank either meets its liabilities or becomes insolvent. At the intermediate time step, a fraction of the deposits are withdrawn, resulting in liquidation of some of the bank's assets. The liquidated portfolio is designed with the goal of minimizing the liquidation cost. Our theoretical results show that model with the haircut constraint leads to lesser liquidity risk, as compared to the scenario of no haircut constraint being imposed. Finally, we present numerical results to illustrate the theoretical results which were obtained.
    Date: 2023–08
  7. By: Tristan Hennig; Mr. Plamen K Iossifov; Mr. Richard Varghese
    Abstract: We explore the early warning properties of a composite indicator which summarizes signals from a range of asset price growth and asset price volatility indicators to capture mispricing of risk in asset markets. Using a quarterly panel of 108 advanced and emerging economies over 1995-2017, we show that the combination of rapid asset price growth and low asset price volatility is a good predictor of future financial crises. Elevated levels of our indicator significantly increase the probability of entering a crisis within the next three years relative to normal times when the indicator is not elevated. The indicator outperforms credit-based early warning metrics, a result robust to prediction horizons, methodological choices, and income groups. Our results are consistent with the idea that measures based on asset prices can offer critical information about systemic risk levels to policymakers.
    Keywords: Early Warning Indicator; ROC; Financial Crises
    Date: 2023–08–04
  8. By: Eleanor Toye Scott; Philip Stiles; Pradeep Debata (Cambridge Judge Business School, University of Cambridge)
    Abstract: Artificial intelligence (AI) and machine learning (ML) offer organisations expanding opportunities for greater control and efficiency and more timely and accurate results, but at the same time bring escalating emergent risks. Two significant and complementary approaches to the organisational challenges posed by AI and ML are model risk management (MRM) and enterprise risk management (ERM). In this review we identify the key literature on technology risk and organisations and use it to consider how effectively MRM policies nested within an ERM approach can resolve the risk conundrum created by the growing complexity of algorithmic technologies. We develop here a framework of the elements of MRM and ERM and the links between them. We first look at MRM and highlight four areas of model development (data, design, implementation and performance) and their associated risks. We then consider ERM and how digital technology implementation affects the entire organisation. We highlight the need to move away from a measurement and compliance approach to risk towards a broader and more proactive approach, aimed at organising technology risk, to which our MRM/ERM framework contributes. We argue that careful attention to the roles, aspirations and incentives of human operators and other stakeholders will be critical in making this transition successfully. Our review has implications for future research in several areas, including the design of human-machine hybrid systems, development of organisational best practice in managing risks arising from algorithmic bias, the design of effective government regulation for artificial intelligence and machine learning, and the role of algorithms in regulatory regimes.
    Date: 2022–01
  9. By: Dong Beom Choi (Seoul National University); Paul Goldsmith-Pinkham (Yale University and NBER); Tanju Yorulmazer (Koç University)
    Abstract: This paper analyzes the contagion effects associated with the failure of Silicon Valley Bank (SVB) and identifies bank-specific vulnerabilities contributing to the subsequent declines in banks’ stock returns. We find that uninsured deposits, unrealized losses in held-to-maturity securities, bank size, and cash holdings had a significant impact, while better-quality assets or holdings of liquid securities did not help mitigate the negative spillovers. Interestingly, banks whose stocks performed worse post SVB also had lower returns in the previous year following Federal Reserve interest rate hikes. The stock market partially anticipated risks associated with uninsured deposit reliance, but did not price in unrealized losses due to interest rate hikes nor risks linked to bank size. While mid-sized banks experienced particular stress immediately after the SVB failure, over time negative spillovers became widespread except for the largest banks.
    Keywords: Contagion, Banking crisis, Bank run, Systemic risk, Interest rate risk, Hidden losses, Held-to-maturity.
    JEL: G01 G21 G14 G28 E58 E43
    Date: 2023–09
  10. By: Tacye Hong; Paul Kattuman (Cambridge Judge Business School, University of Cambridge)
    Abstract: Theory as well as empirics suggest that both the level and the volatility of uncertainty impact important economic variables. There is a need to extend models of uncertainty to the volatility of uncertainty. We analyse the dynamics of the Economic Policy Uncertainty index developed by (Baker et al., 2016) and show that for four major economies in Europe – France, Germany, Italy and the UK – between 1997 and 2019, considerable portions of both the level and the volatility of economic policy uncertainty were generated by spillovers. Spillovers in the volatility of economic policy uncertainty was higher than spillovers in levels during major crises. These findings are relevant to the appraisal of economic policy uncertainty episodes in major trading partners.
    Date: 2021–10
  11. By: Yasmine Kamal (Cairo University)
    Abstract: This study explains the export behavior of Egyptian firms under demand volatility in destination countries using detailed customs data and high-dimensional fixed effects. It finds that demand volatility negatively affects both intensive and extensive export margins. The effects are particularly evident for large firms that reduce their export sales (especially over time) to more volatile destinations/products and are therefore more likely to exit from exporting more volatile products and less (more) likely to enter (exit) more volatile destinations. These findings corroborate recent literature that emphasizes the greater elasticity of large firms to foreign demand shocks. They are also in line with risk aversion models in which the average risk premium increases with firm size. Given the disproportionate adverse impacts on large exporters, we find that higher demand volatility leads to lower aggregate exports, especially to geographically close countries with low trade costs. Accordingly, uncertainty in demand lessens the positive effect of lower trade barriers on exports.
    Date: 2023–03–20

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