nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒06‒12
27 papers chosen by

  1. Does Private Equity Over-Lever Portfolio Companies? By Sharjil M. Haque
  2. Financial Risk-Taking under Health Risk By Björn Bos; Moritz A. Drupp; Jasper N. Meya; Martin F. Quaas
  3. Does Corporate Hedging of Foreign Exchange Risk Affect Real Economic Activity? By Hyeyoon Jung
  4. Range Volatility Spillover across Sectoral Stock Indices during COVID-19 Pandemic: Evidence from Indian Stock Market By Datta, Susanta; Hatekar, Neeraj
  5. Market Making and Pricing of Financial Derivatives based on Road Travel Times By Ke Wan; Alain Kornhauser
  6. Deep learning of Value at Risk through generative neural network models : the case of the Variational Auto Encoder By Pierre Brugière; Gabriel Turinici
  7. Stressed Banks? Evidence from the Largest-Ever Supervisory Review By Puriya Abbassi; Rajkamal Iyer; José-Luis Peydró; Paul E. Soto
  8. Maximum Implied Variance Slope -- Practical Aspects By Fabien Le Floc'h; Winfried Koller
  9. CRISK: Measuring the Climate Risk Exposure of the Financial System By Hyeyoon Jung
  10. Calibration of Local Volatility Models with Stochastic Interest Rates using Optimal Transport By Gregoire Loeper; Jan Obloj; Benjamin Joseph
  11. Household, Bank, and Insurer Exposure to Miami Hurricanes: a flow-of-risk analysis By Benjamin Dennis
  12. Subjective Earnings Risk By Andrew Caplin; Victoria Gregory; Eungik Lee; Soren Leth-Petersen; Johan Sæverud
  13. Monitoring multicountry macroeconomic risk By Dimitris Korobilis; Maximilian Schröder
  14. Consistent Valuation of a Reduction in Mortality Risk using Values per Life, Life Year, and Quality-Adjusted Life Year By Hammitt, James K.
  15. Understanding Uncertainty Shocks and the Role of Black Swans By Laura Veldkamp
  16. Stress testing with multi-faceted liquidity: the central bank collateral framework as a financial stability tool By Cuzzola, Angelo; Barbieri, Claudio; Bindseil, Ulrich
  17. Construct sparse portfolio with mutual fund's favourite stocks in China A share market By Ke Zhang
  18. How to address monotonicity for model risk management? By Dangxing Chen; Weicheng Ye
  19. Global Commodity Markets and Sovereign Risk across 150 Years By Angélica Domínguez-Cardoza; Adelina Garamow; Josefin Meyer
  20. Population Diversity and Financial Risk-Taking By Manthos D Delis; Evangelos V Dioikitopoulos; Steven Ongena
  21. Does Asset Encumbrance Affect Bank Risk? Evidence from Covered Bonds By Emilia Garcia-Appendini; Stefano Gatti; Giacomo Nocera
  22. Robust Equilibrium Strategy for Mean-Variance Portfolio Selection By Mengge Li; Shuaijie Qian; Chao Zhou
  23. Mitigating the Risk of Runs on Uninsured Deposits: the Minimum Balance at Risk By Richard Berner; Marco Cipriani; Michael Holscher; Antoine Martin; Patrick E. McCabe
  24. FIEGARCH, modulus asymmetric FILog-GARCH and trend-stationary dual long memory time series By Yuanhua Feng; Thomas Gries; Sebastian Letmathe
  25. The optimal reinsurance strategy with price-competition between two reinsurers By Liyuan Lin; Fangda Liu; Jingzhen Liu abd Luyang Yu
  26. Does the SPF Help Predict the Shape of Recessions in Real Time?  By Yunjong Eo; James Morley
  27. One Asset Does Not Fit All: Inflation Hedging by Index and Horizon By Stefania D'Amico; Thomas B. King

  1. By: Sharjil M. Haque
    Abstract: Detractors have warned that Private Equity (PE) funds tend to over-lever their portfolio companies because of an option-like payoff, building up default risk and debt overhang. This paper argues PE-ownership leads to substantially higher levels of optimal (value-maximizing) leverage, by reducing the expected cost of financial distress. Using data from a large sample of PE buyouts, I estimate a dynamic trade-off model where leverage is chosen by the PE investor. The model is able to explain both the level and change in leverage documented empirically following buyouts. The increase in optimal leverage is driven primarily by a reduction in the portfolio company's asset volatility and, to a lesser extent, an increase in asset return. Counterfactual analysis shows significant loss in firmvalue if PE sub-optimally chose lower leverage. Consistent with lower asset volatility, additional tests show PE-backed firms experience lower volatility of sales and receive greater equity injections for distress resolution, compared to non PE-backed firms. Overall, my findings broaden our understanding of factors that drive buyout leverage.
    Keywords: Private Equity; Capital Structure; Default Risk; Trade-off Theory
    JEL: G23 G30 G32 G33
    Date: 2023–02–03
  2. By: Björn Bos; Moritz A. Drupp; Jasper N. Meya; Martin F. Quaas
    Abstract: We study how background health risk affects financial risk-taking. We elicit financial risk-taking behavior of a representative sample of more than 5, 000 Germans in five panel waves during the COVID-19 pandemic. Exploiting variation in local infections across time and space, we find that an increase in infections affecting background health risk translates into higher levels of self-reported fear and decreases financial investments in a risky asset. Once vaccines become available as a self-insurance device, the tempering effect on investments ceases. Our results provide evidence that non-financial background risks affect financial risk-taking, and for the alleviating effect of self-insurance devices.
    JEL: D14 D91 G11 G41 G51
    Date: 2023
  3. By: Hyeyoon Jung
    Abstract: Foreign exchange derivatives (FXD) are a key tool for firms to hedge FX risk and are particularly important for exporting or importing firms in emerging markets. This is because FX volatility can be quite high—up to 120 percent per annum for some emerging market currencies during stress episodes—yet the vast majority of international trades, almost 90 percent, are invoiced in U.S. dollars (USD) or euros (EUR). When such hedging instruments are in short supply, what happens to firms’ real economic activities? In this post, based on my related Staff Report, I use hand-collected FXD contract-level data and exploit a quasi-natural experiment in South Korea to measure the real effects of hedging using FXD.
    Keywords: real effects; macroprudential policy; international finance; derivatives hedging; FX risk management
    JEL: E2 G2 G3 F00
    Date: 2023–04–12
  4. By: Datta, Susanta; Hatekar, Neeraj
    Abstract: The study examines volatility spillover across sectoral stock indices from one Emerging Market Economies, viz. India during COVID-19 pandemic. Our contributions are threefold: (a) incorporation of range volatility during the pandemic, (b) comparative assessment of volatility spillover at the sectoral level, and (c) identify evidence of volatility spillover across different sectoral indices. Using daily historical price data for 11 sectoral stock indices during the first wave of the pandemic; we find that Range GARCH (1, 1) performs better not only during the crisis but also during pandemic periods. The multivariate Range DCC model confirms evidence of volatility spillover across sectoral stock indices.
    Keywords: Forecasting, Volatility, Spillover, Return, Range, NIFTY, COVID 19
    JEL: C22 C58 G17
    Date: 2022–04–04
  5. By: Ke Wan; Alain Kornhauser
    Abstract: Travel time derivatives are introduced as financial derivatives based on road travel times - a non-tradable underlying asset. In the transportation area, it is proposed as a more fundamental approach to value pricing because it conduct road pricing based on not only level but also volatility of travel time; in the financial market, it is propose as an innovative hedging instrument against market risk, especially after the recent stress of crypto market and traditional banking sector. The paper addresses (a) the motivation for introducing such derivatives (that is, the demand for hedging), (b) the potential market, and (c) the product design and pricing schemes. Pricing schemes are designed based on the travel time data captured by real time sensors, which are modeled as Ornstein - Uhlenbeck processes and more generally, continuous time auto regression moving average (CARMA) models. The calibration of such model is conducted via a hidden factor model, which described the dynamics of travel time processes. The risk neutral pricing principle is used to generate the derivative price, with reasonably designed procedures to identify the market value of risk.
    Date: 2023–05
  6. By: Pierre Brugière (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique); Gabriel Turinici (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We present in this paper a method to compute, using generative neural networks, an estimator of the "Value at Risk" for a nancial asset. The method uses a Variational Auto Encoder with a 'energy' (a.k.a. Radon- Sobolev) kernel. The result behaves according to intuition and is in line with more classical methods.
    Date: 2023–04–24
  7. By: Puriya Abbassi; Rajkamal Iyer; José-Luis Peydró; Paul E. Soto
    Abstract: We study short-term and medium-term changes in bank risk-taking as a result of supervision, and the associated real effects. For identification, we exploit the European Central Bank's asset-quality review (AQR) in conjunction with security and credit registers. After the AQR announcement, reviewed banks reduce riskier securities and credit supply, with the greatest effect on riskiest securities. We find negative spillovers on asset prices and firm-level credit availability. Moreover, non-banks with higher exposure to reviewed banks acquire the shed risk. After the AQR compliance, reviewed banks reload riskier securities but not riskier credit, resulting in negative medium-term firm-level real effects. These effects are especially strong for firms with high ex-ante credit risk. Among these non-safe firms, even those with high ex-ante productivity experience negative real effects. Our findings suggest that banks' liquid assets help them to mask risk from supervisors and risk adjustments banks make in response to supervision have persistent corporate real effects.
    Keywords: Corporate real effects from bank credit; Asset quality review; Stress tests; Supervision; Risk-masking; Costs of safe assets
    JEL: E58 G21 G28 H63 L51
    Date: 2023–04–13
  8. By: Fabien Le Floc'h; Winfried Koller
    Abstract: In the Black-Scholes model, the absence of arbitrages imposes necessary constraints on the slope of the implied variance in terms of log-moneyness, asymptotically for large log-moneyness. The constraints are used for example in the SVI implied volatility parameterization to ensure the resulting smile has no arbitrages. This note shows that those no-arbitrage contraints are very mild, and that arbitrage is almost always guaranteed in a large range of slopes where the contraints are enforced.
    Date: 2023–04
  9. By: Hyeyoon Jung
    Abstract: A growing number of climate-related policies have been adopted globally in the past thirty years (see chart below). The risk to economic activity from changes in policies in response to climate risks, such as carbon taxes and green subsidies, is often referred to as transition risk. Transition risk can adversely affect the real economy through the banking sector. For example, a shock to borrowers’ transition risk can impair their ability to repay, which can then lead to an amplified effect on banks’ current and expected future profits, resulting in a systemic undercapitalization of banks. In a recent Staff Report co-authored with Robert Engle and Richard Berner, we examine whether banks are sufficiently capitalized to absorb losses during stressful conditions due to heightened climate (transition) risk.
    Keywords: climate; climate risk; financial stability; stress testing; systemic risk
    JEL: G1 G2
    Date: 2023–04–20
  10. By: Gregoire Loeper; Jan Obloj; Benjamin Joseph
    Abstract: We develop a non-parametric, optimal transport driven, calibration methodology for local volatility models with stochastic interest rate. The method finds a fully calibrated model which is the closest to a given reference model. We establish a general duality result which allows to solve the problem via optimising over solutions to a non-linear HJB equation. We then apply the method to a sequential calibration setup: we assume that an interest rate model is given and is calibrated to the observed term structure in the market. We then seek to calibrate a stock price local volatility model with volatility coefficient depending on time, the underlying and the short rate process, and driven by a Brownian motion which can be correlated with the randomness driving the rates process. The local volatility model is calibrated to a finite number of European options prices via a convex optimisation problem derived from the PDE formulation of semimartingale optimal transport. Our methodology is analogous to Guo, Loeper, and Wang, 2022 and Guo, Loeper, Obloj, et al., 2022a but features a novel element of solving for discounted densities, or sub-probability measures. We present numerical experiments and test the effectiveness of the proposed methodology.
    Date: 2023–04
  11. By: Benjamin Dennis
    Abstract: We analyze possible future financial losses in the event of hurricane damage to Miami residential real estate, where the hurricane's destructiveness reflects climate-change. We focus on three scenarios: (i) a business-as-usual scenario, (ii) a Hurricane-Ian-spillovers scenario, and (iii) a cautious-markets scenario. We quantify bank exposures and loss rates, where exposures are proportional to the size of real estate markets and loss rates depend on post-hurricane devaluations and insurance coverage. This quantitative methodology could complement modeling of local economy impacts, stress on public finances, asset market losses, and other financial developments that will also affect banks.
    Keywords: Climate-related risk; Financial stability; Flow of risk; Real estate loans
    JEL: Q54 R31 G20
    Date: 2023–02–13
  12. By: Andrew Caplin; Victoria Gregory; Eungik Lee; Soren Leth-Petersen; Johan Sæverud
    Abstract: Earnings risk is central to economic analysis. While this risk is essentially subjective, it is typically inferred from administrative data. Following the lead of Dominitz and Manski (1997), we introduce a survey instrument to measure subjective earnings risk. We pay particular attention to the expected impact of job transitions on earnings. A link with administrative data provides multiple credibility checks. It also shows subjective earnings risk to be far lower than its administratively- estimated counterpart. This divergence arises because expected earnings growth is heterogeneous, even within narrow demographic and earnings cells. We calibrate a life-cycle model of search and matching to administrative data and compare the model-implied expectations with our survey instrument. This calibration produces far higher estimates of individual earnings risk than do our subjective expectations, regardless of age, earnings, and whether or not workers switch jobs. This divergence highlights the need for survey-based measures of subjective earnings risk.
    Keywords: earnings risk; job transitions; subjective expectations
    JEL: D31 D84 E24 J31
    Date: 2023–03–03
  13. By: Dimitris Korobilis (University of Glasgow, UK; Rimini Centre for Economic Analysis); Maximilian Schröder (BI Norwegian Business School, Norway; Norges Bank, Norway)
    Abstract: We propose a multicountry quantile factor augmented vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a parsimonious way. We develop two algorithms for posterior inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for the euro area, we establish the good empirical properties of the QFAVAR as a tool for assessing the effects of global shocks on country-level macroeconomic risks. In particular, QFAVAR short-run tail forecasts are more accurate compared to a FAVAR with symmetric Gaussian errors, as well as univariate quantile autoregressions that ignore comovements among quantiles of macroeconomic variables. We also illustrate how quantile impulse response functions and quantile connectedness measures, resulting from the new model, can be used to implement joint risk scenario analysis.
    Keywords: quantile VAR, MCMC, variational Bayes, dynamic factor model
    JEL: C11 C32 E31 E32 E37 E66
    Date: 2023–05
  14. By: Hammitt, James K.
    Abstract: The monetary value of a reduction in mortality risk can be accurately characterized using the alternative concepts of value per statistical life (VSL), value per statistical life year (VSLY), and value per quality-adjusted life year (VQALY). Typically, each of these values depends on the age and other characteristics of the affected individual; at most one of the values can be independent of age. The common practice of valuing a transient or persistent risk reduction using a constant VSL, VSLY, or VQALY yields systematic differences in the calculated monetary value that depend on the age at which the risk reduction begins, its duration, time path, and whether future lives, life years, or quality-adjusted life years are discounted. Mutually consistent, age-dependent VSL, VSLY, and VQALY are derived and the large differences in valuation of illustrative transient and persistent risk reductions that can result from assuming age-independent values of each of the three concepts are illustrated.
    Date: 2023–05–03
  15. By: Laura Veldkamp
    Abstract: Economic uncertainty is a powerful force in the modern economy. Research shows that surges in uncertainty can trigger business cycles, bank runs and asset price fluctuations. But where do sudden surges in uncertainty come from? This paper provides a data-disciplined theory of belief formation that explains large fluctuations in uncertainty. It argues that people do not know the true distribution of macroeconomic outcomes. Like Bayesian econometricians, they estimate a distribution. Our main contribution is to explain why real-time estimation of distributions with non-normal tails results in large uncertainty fluctuations. We use theory and data to show how small changes in estimated skewness whip around probabilities of unobserved tail events (black swans). Our estimates, based on real-time GDP data, reveal that revisions in the estimates of black swan risk explain most of the fluctuations in uncertainty.
    Keywords: forecast bias; rational expectations; model uncertainty; expectations formation; bayesian econometrics
    JEL: D80 D84 C11
    Date: 2022–12
  16. By: Cuzzola, Angelo; Barbieri, Claudio; Bindseil, Ulrich
    Abstract: The paper studies the central bank collateral framework and its impact on banks’ liquidity under an adverse stress test scenario. We construct a stress test model that accounts for a granular and multi-faceted representation of the liquidity of marketable and non-marketable assets. In particular, the model analyses banks’ strategic decisions to mobilise assets through four funding channels: unsecured loans, asset sales, private repurchase agreements, or Central Bank lending. We test three scenarios: the EBA regulatory stress test exercise, a shock to Russia and the Eastern European countries, and a shock to the Southern European countries. Results show that illiquidity can trigger insolvency and that liquidity adjustment can last significantly after the initial shock. We find evidence of a threshold in the benefits of expanding the collateral framework and highlight the heterogeneous effects across different jurisdictions and financial institutions. We find that bank equity losses are reduced in aggregate up to 17% at the tail of the loss distribution and on average by around 5% when financial institutions can rely on the collateral framework channel. JEL Classification: C63, E52, G01, G28
    Keywords: Asset liquidity, Central Bank Collateral Framework, Collateral, Lender-Of-Last Resort, Stress test
    Date: 2023–05
  17. By: Ke Zhang
    Abstract: Unlike developed market, some emerging markets are dominated by retail and unprofessional trading. China A share market is a good and fitting example in last 20 years. Meanwhile, lots of research show professional investor in China A share market continuously generate excess return compare with total market index. Specifically, this excess return mostly come from stock selectivity ability instead of market timing. However for some reason such as fund capacity limit, fund manager change or market regional switch, it is very hard to find a fund could continuously beat market. Therefore, in order to get excess return from mutual fund industry, we use quantitative way to build the sparse portfolio that take advantage of favorite stocks by mutual fund in China A market. Firstly we do the analysis about favourite stocks by mutual fund and compare the different method to construct our portfolio. Then we build a sparse stock portfolio with constraint on both individual stock and industry exposure using portfolio optimizer to closely track the partial equity funds index 930950.CSI with median 0.985 correlation. This problem is much more difficult than tracking full information index or traditional ETF as higher turnover of mutual fund, just first 10 holding of mutual fund available and fund report updated quarterly with 15 days delay. Finally we build another low risk and balanced sparse portfolio that consistently outperform benchmark 930950.CSI.
    Date: 2023–04
  18. By: Dangxing Chen; Weicheng Ye
    Abstract: In this paper, we study the problem of establishing the accountability and fairness of transparent machine learning models through monotonicity. Although there have been numerous studies on individual monotonicity, pairwise monotonicity is often overlooked in the existing literature. This paper studies transparent neural networks in the presence of three types of monotonicity: individual monotonicity, weak pairwise monotonicity, and strong pairwise monotonicity. As a means of achieving monotonicity while maintaining transparency, we propose the monotonic groves of neural additive models. As a result of empirical examples, we demonstrate that monotonicity is often violated in practice and that monotonic groves of neural additive models are transparent, accountable, and fair.
    Date: 2023–04
  19. By: Angélica Domínguez-Cardoza; Adelina Garamow; Josefin Meyer
    Abstract: How do commodity price movements affect sovereign default risk over the long-run? Using a novel dataset covering 41 countries and 42 raw commodities, we take a comprehensive long-run view to shed light on this so far understudied relationship between commodity risk and sovereign risk across 150 years. We create a novel country-specific commodity price index that allows us to take advantage of countries’ variation in their commodity export compositions. Our results are twofold: first, commodity price fluctuations show a persistent association with sovereign borrowing costs for countries that are commodity export dependent across the last one and a half centuries. Second, historically this relationship was driven by agricultural price movements; today it is driven by mineral and energy price movements.
    Keywords: Sovereign Risk, commodity prices
    JEL: E44 F41 F34 H63 G12
    Date: 2022
  20. By: Manthos D Delis (Audencia Business School); Evangelos V Dioikitopoulos (AUEB - Athens University of Economics and Business); Steven Ongena (UZH - Universität Zürich [Zürich] = University of Zurich)
    Keywords: Stock market participation Equity share SIPP Immigrants Individualism Scientific knowledge Financial endowment G41, O16, Z13, Stock market participation, Equity share, SIPP, Immigrants, Individualism, Scientific knowledge, Financial endowment G41
    Date: 2023–04–27
  21. By: Emilia Garcia-Appendini (UZH - Universität Zürich [Zürich] = University of Zurich); Stefano Gatti (Bocconi University [Milan, Italy]); Giacomo Nocera (Audencia Business School)
    Abstract: Theories suggest that asset encumbrance, the ring-fencing of certain assets for protected debtholders, can affect banks' risk-taking and lead to funding instability. We test these hypotheses using a unique, hand-collected dataset on outstanding covered bonds issued by a sample of listed European banks. Our results suggest that the effect of asset encumbrance on risk depends on the proportion of debtholders exerting market discipline and on the bank's liquidity buffers. We deal with concerns regarding omitted variables and reverse causality using several fixed effects estimations and an instrumental variables approach. Our findings can alert policymakers about potential side effects of policy interventions that can induce an increase of asset encumbrance in banks.
    Keywords: Asset encumbrance, Covered bond, Market discipline, Debt priority, Bank risk
    Date: 2022–10–26
  22. By: Mengge Li; Shuaijie Qian; Chao Zhou
    Abstract: The classical mean-variance portfolio selection problem induces time-inconsistent (precommited) strategies (see Zhou and Li (2000)). To overcome this time-inconsistency, Basak and Chabakauri (2010) introduce the game theoretical approach and look for (sub-game perfect Nash) equilibrium strategies, which is solved from the corresponding partial differential equations (PDE) system. In their model, the investor perfectly knows the drift and volatility of the assets. However, in reality investors only have an estimate on them, e.g, a 95% confidence interval. In this case, some literature (e.g., Pham, Wei and Zhou (2022)) derives the optimal precommited strategy under the worst parameters, which is the robust control. The relation between the equilibrium strategy and the PDE system has not been justified when incorporating robust control. In this paper, we consider a general dynamic mean-variance framework and propose a novel definition of the robust equilibrium strategy. Under our definition, a classical solution to the corresponding PDE system implies a robust equilibrium strategy. We then explicitly solve for some special examples.
    Date: 2023–05
  23. By: Richard Berner; Marco Cipriani; Michael Holscher; Antoine Martin; Patrick E. McCabe
    Abstract: The incentives that drive bank runs have been well understood since the seminal work of Nobel laureates Douglas Diamond and Philip Dybvig (1983). When a bank is suspected to be insolvent, early withdrawers can get the full value of their deposits. If and when the bank runs out of funds, however, the bank cannot pay remaining depositors. As a result, all depositors have an incentive to run. The failures of Silicon Valley Bank and Signature Bank remind us that these incentives are still present for uninsured depositors, that is, those whose bank deposits are larger than deposit insurance limits. In this post, we discuss a policy proposal to reduce uninsured depositors’ incentives to run.
    Keywords: bank run; Minimum Balance at Risk; money market funds (MMFs); uninsured deposits
    JEL: F0 G2 G01
    Date: 2023–04–14
  24. By: Yuanhua Feng (Paderborn University); Thomas Gries (Paderborn University); Sebastian Letmathe (Paderborn University)
    Abstract: A novel long memory volatility model MAFILog-GARCH (modulus asymmetric FILog-GARCH) is introduced, which has some advantages compared to the FIEGARCH. A general dual long memory FARIMA with them as error processes is defined. Moreover, a trend-stationary dual long memory model is proposed. The FIEGARCH and MAFILog-GARCH are first applied to returns of eight top US firms. It is found that their practical performances are comparable. Both are superior to the FIGARCH and FILog-GARCH. Further application provides evidence of trend-stationary dual long memory time series in different fields.
    Keywords: Modulus asymmetric FILog-GARCH, FIEGARCH, dual long memory, trend-stationary dual long memory, implementation in R
    Date: 2023–05
  25. By: Liyuan Lin; Fangda Liu; Jingzhen Liu abd Luyang Yu
    Abstract: We study optimal reinsurance in the framework of stochastic game theory, in which there is an insurer and two reinsurers. A Stackelberg model is established to analyze the non-cooperative relationship between the insurer and reinsurers, where the insurer is considered as the follower and the reinsurers are considered as the leaders. The insurer is a price taker who determines reinsurance demand in the reinsurance market, while the reinsurers can price the reinsurance treaties. Our contribution is to use a Nash game to describe the price-competition between two reinsurers. We assume that one of the reinsurers adopts the variance premium principle and the other adopts the expected value premium principle. The insurer and the reinsurers aim to maximize their respective mean-variance cost functions which lead to a time-inconsistency control problem. To overcome the time-inconsistency issue in the game, we formulate the optimization problem of each player as an embedded game and solve it via a corresponding extended Hamilton-Jacobi-Bellman equation. We find that the insurer will sign propositional and excess loss reinsurance strategies with reinsurer 1 and reinsurer 2, respectively. When the claim size follows exponential distribution, there exists a unique equilibrium reinsurance premium strategy. Our numerical analysis verifies the impact of claim size, risk aversion and interest rates of the insurer and reinsurers on equilibrium reinsurance strategy and premium strategy, which can help to understand competition in the reinsurance market
    Date: 2023–04
  26. By: Yunjong Eo; James Morley
    Abstract: We revisit our Markov-switching model of U.S. real GDP that accommodates different shapes of recessions to determine what it suggests about the nature of the COVID-19 recession. As with linear time series models, we find that it is important to account for the extreme outliers during the pandemic when estimating model parameters, but a simple decay function for volatility from 2020Q2 leads to robust inferences compared to our original estimates and clearly suggests that the COVID-19 recession was more U shaped than L shaped. We then consider the extent to which our model can be used to predict the shape of recessions in a real-time setting, rather than just classifying recessions ex post. Considering the last four recessions with real-time data and estimation, we find that feeding SPF data through our model can help accurately predict the nature of recovery at the time of the trough of each recession.
    Keywords: L-shaped recession, U-shaped recession, COVID-19, Markov switching, real-time analysis
    JEL: C22 C51 E32 E37
    Date: 2023–05
  27. By: Stefania D'Amico; Thomas B. King
    Abstract: We examine the inflation-hedging properties of various financial assets and portfolios by estimating simple time-series models of the joint dynamics of each asset-inflation pair, for multiple inflation indices and at horizons from one month to 30 years. There is no one-size-fits-all approach to inflation hedging: the optimal hedge depends on the particular types of prices that an investor is exposed to and at which horizons. For example, food and energy prices are easy to hedge with commodities and certain stock portfolios, while non-housing service prices and wages are not highly correlated with any financial asset. Inflation-protected bonds are good hedges for headline consumer inflation at horizons matching their maturities but can perform quite poorly at shorter horizons and for other price indices. During the inflationary period of 2020-2022, many historical hedging relationships failed, as monetary policy tightening lagged inflation.
    Keywords: Inflation; real assets; Treasury Inflation-Protected Securities (TIPS); Hedging
    Date: 2023–04–14

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