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on Risk Management |
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Issue of 2024‒04‒22
nineteen papers chosen by |
| By: | Matteo Bonato (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France.); Oguzhan Cepni (Department of Economics, Copenhagen Business School, Denmark; Ostim Technical University, Ankara, Turkiye); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany) |
| Abstract: | We compare the contribution of various popular economic policy uncertainty (EPU) measures with that of widely-studied realized moments (realized leverage, realized skewness, realized kurtosis, realized good and bad volatilities, realized jumps, and realized up and down tail risks) to the performance of out-of-sample forecasts of stock market volatility of the United States (US) over the sample period from 2011 to 2023. To this end, we construct optimal forecasting models by combining the popular heterogeneous autoregressive realized volatility (HAR-RV) model with optimal stepwise predictor selection algorithms and shrinkage estimators (lasso, elastic net, and ridge regression), where we control for macroeconomic factors and sentiment as well. We find that realized moments improve out-of-sample forecasting performance relative to the baseline HAR-RV model. EPU measures do not add to forecasting performance beyond realized moments, and even deteriorate forecasting performance as the length of the forecast horizon increases. The punchline is that realized moments rather than EPU measures matter for forecasting stock market volatility. |
| Keywords: | Stock market, Volatility, Forecasting, Moments, Economic policy uncertainty |
| JEL: | C22 C53 G10 G17 D80 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:202408&r=rmg |
| By: | Oguzhan Cepni (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark; Ostim Technical University, Ankara, Turkiye); Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany) |
| Abstract: | This paper extends the literature on the nexus between political geography and financial markets to the stock market volatility context by examining the interrelation between political geography and the predictive relation between the state- and aggregate-level stock market volatility via recently constructed measures of political alignment. Using monthly data for the period from February 1994 to March 2023 and a machine learning technique called random forests, we show that the importance of the state-level realized stock market volatilities as a driver of aggregate stock market volatility displays considerable cross- sectional dispersion as well as substantial variation over time, with the state of New York playing a prominent role. Further analysis shows that stronger political alignment of a state with the ruling party is associated with a lower contribution of the state's realized volatility to aggregate stock market volatility, highlighting the role of risk effects associated with the political geography of firms. Finally, we show that the negative link between the political alignment of a state and the importance of that state's realized volatility over aggregate stock market volatility is statistically significant during high-sentiment periods, but weak and statistically insignificant during low-sentiment periods, underscoring the role of investor sentiment for the nexus between political geography and financial markets. Our findings presents new insight to the risk-based arguments that associate political geography with stock market dynamics. |
| Keywords: | Stock market volatility, Random forests, Political alignment, Investor sentiment |
| JEL: | C22 C23 C51 C53 G10 D81 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:202414&r=rmg |
| By: | Afees A. Salisu (Centre for Econometrics and Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Ahamuefula E.Oghonna (Centre for Econometrics and Applied Research, Ibadan, Nigeria); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Oguzhan Cepni (Copenhagen Business School, Department of Economics, Porcelaenshaven 16A, Frederiksberg DK-2000, Denmark; Ostim Technical University, Ankara, Turkiye) |
| Abstract: | In this paper, we employ the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework to forecast the daily volatility of state-level stock returns in the United States (US) based on monthly metrics of oil price uncertainty (OPU), and relatively broader energy market-related uncertainty index (EUI). We find that over the daily period of (February) 1994 to (September) 2022 and various forecast horizons, in 37 out of the 50 states, the GARCH-MIDAS model with EUI can outperform the benchmark, i.e., the GARCH-MIDAS-realized volatility (RV), which in turn, holds for at most 18 cases under OPU. The statistical evidence is further strengthened when we are able to detect higher utlilty gains delivered for 42 states by the GARCH-MIDAS-EUI in comparison to the GARCH-MIDAS-RV. Our findings have important implications for investors and policymakers. |
| Keywords: | Monthly Oil Price and Energy Market Uncertainties, Daily State-Level Stock Returns Volatility, GARCH-MIDAS, Forecasting |
| JEL: | C32 C53 G10 Q02 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:pre:wpaper:202409&r=rmg |
| By: | Dalderop, J.; Linton, O. B. |
| Abstract: | Option-implied risk-neutral densities are widely used for constructing forward-looking risk measures. Meanwhile, investor risk aversion introduces a multiplicative pricing kernel between the risk-neutral and true conditional densities of the underlying asset’s return. This paper proposes a simple local estimator of the pricing kernel based on inverse density weighting, and characterizes its asymptotic bias and variance. The estimator can be used to correct biased density forecasts, and performs well in a simulation study. A local exponential linear variant of the estimator is proposed to include conditioning variables. In an application, we estimate a demand-based model for S&P 500 index options using net positions data, and attribute the U-shaped pricing kernel to heterogeneous beliefs about conditional volatility. |
| Keywords: | Density Forecasting, Nonparametric Estimation, Option Pricing, Trade Data |
| JEL: | C14 G13 |
| Date: | 2024–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camjip:2405&r=rmg |
| By: | Cavallaro, Eleonora (University of Rome, Sapienza, Department of Economics and Law); Villani, Ilaria (Banking Supervision, European Central Bank) |
| Abstract: | This paper proposes an index to benchmark EU financial systems against their potential to enhance resilient growth and international risk sharing. It finds that the risk sharing mechanism is more effective in more stable financial environments, whereas a larger fraction of shocks remains unsmoothed in the lower financial clusters, especially in the aftermath of the global financial crisis, when the credit channel is significantly downsized. |
| Keywords: | financial structure, financial heterogeneity, growth, volatility, risk sharing |
| JEL: | F15 F36 O16 E44 G1 |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:bda:wpsmep:wp2024/21&r=rmg |
| By: | Corentin Roussel |
| Abstract: | Differentiated treatment of green credit risk in banks’ capital requirements to favor green transition generates lot of debates among European prudential regulators. The aim of this paper is to examine whether the key Basel 3 finalization instrument - the Output Floor - should be applied to green credit risk in order to ensure stability of banking system and promote green finance. To do so, we assess macrofinancial and environmental benefits of such green policy for the Euro Area through the lens of a general equilibrium model. We get three main results. First, when banks get transitory ’environmental awareness’, an Output Floor (OF) applied to brown credits only (i.e. a brown OF) faces a trade-off between limiting environmental aftermaths and reaching OF objectives (i.e reducing volatility of banks’ capital adequacy ratio). Second, to mitigate the prudential cost of this trade-off, brown OF should be joined with additional green financial policies such as green Quantitative Easing. Third, pollutant emissions tax erodes brown OF efficiency along financial and economic cycles but limits the welfare cost implied by pollution in the long run. |
| Keywords: | Output Floor, Credit Risk, Green Finance, Climate Change, DSGE. |
| JEL: | Q54 G21 E44 E51 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-07&r=rmg |
| By: | Andrew Caplin (New York University); Victoria Gregory (FRB St. Louis); Eungik Lee (New York University); Soeren Leth-Petersen (University of Copenhagen); Johan Saeverud (University of Copenhagen) |
| 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: | 2023–03–09 |
| URL: | http://d.repec.org/n?u=RePEc:kud:kucebi:2301&r=rmg |
| By: | Ostry, D. A. |
| Abstract: | I build a model in which speculators unwind carry trades and hedgers fly to relatively liquid U.S. Treasuries during global financial disasters. The net effect of these flows produces an amplified U.S. dollar appreciation against high-yield currencies in disasters and a dampened depreciation, or even an appreciation, against low-yield ones. I verify this prediction by examining deviations from uncovered interest parity (UIP) within a novel quantile-regression framework. In the tail quantiles, I show that interest differentials predict high-yield currencies to suffer depreciations ten times as large as suggested by UIP, while spikes in Treasury liquidity premia meaningfully appreciate the dollar regardless of the U.S. relative interest rate. A complementary analysis of speculators’ and hedgers’ currency futures positions substantiates my model’s mechanism and highlights that hedging agents imbue the U.S. dollar with its unique safe-haven status. |
| Keywords: | Disaster Risk, Exchange Rates, Liquidity Yields, Quantile regression, U.S. Safety |
| JEL: | C22 F31 G15 |
| Date: | 2023–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camjip:2311&r=rmg |
| By: | Markus Dertwinkel-Kalt; Johannes Kasinger; Dmitrij Schneider |
| Abstract: | We test for skewness preferences in a large set of observational panel data on online poker games (n=4, 450, 585). Each observation refers to a choice between a safe option and a binary risk of winning or losing the game. Our setting offers a real-world choice situation with substantial incentives where probability distributions are simple, transparent, and known to the decision-makers. Individuals reveal a strong and robust preference for skewness, which is inconsistent with expected utility theory. The effect of skewness is most pronounced among experienced and unsuccessful players but remains significant in all subsamples that we investigate, in contrast to the effect of variance. |
| Keywords: | risk preferences, choice under risk, skewness, gambling |
| JEL: | D01 D81 G40 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10977&r=rmg |
| By: | Holz, Raúl; Jacas, Isabel; Robles, Claudia |
| Date: | 2024–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:ecr:col041:69042&r=rmg |
| By: | Aknouche, Abdelhakim; Almohaimeed, Bader; Dimitrakopoulos, Stefanos |
| Abstract: | This paper proposes a noisy GARCH model with two volatility sequences (an unobserved and an observed one) and a stochastic time-varying conditional kurtosis. The unobserved volatility equation, equipped with random coefficients, is a linear function of the past squared observations and of the past observed volatility. The observed volatility is the conditional mean of the unobserved volatility, thus following the standard GARCH specification, where its coefficients are equal to the means of the random coefficients. The means and the variances of the random coefficients as well as the unobserved volatilities are estimated using a three-stage procedure. First, we estimate the means of the random coefficients, using the Gaussian quasi-maximum likelihood estimator (QMLE), then, the variances of the random coefficients, using a weighted least squares estimator (WLSE), and finally the latent volatilities through a filtering process, under the assumption that the random parameters follow an Inverse Gaussian distribution, with the innovation being normally distributed. Hence, the conditional distribution of the model is the Normal Inverse Gaussian (NIG), which entails a closed form expression for the posterior mean of the unobserved volatility. Consistency and asymptotic normality of the QMLE and WLSE are established under quite tractable assumptions. The proposed methodology is illustrated with various simulated and real examples. |
| Keywords: | Noised volatility GARCH, Randon coefficient GARCH, Markov switching GARCH, QMLE, Weighted least squares, filtering volatility, time-varying conditional kurtosis. |
| JEL: | C13 C22 C51 C58 |
| Date: | 2024–03–15 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120456&r=rmg |
| By: | Alexander Lipton |
| Abstract: | An intriguing link between a wide range of problems occurring in physics and financial engineering is presented. These problems include the evolution of small perturbations of linear flows in hydrodynamics, the movements of particles in random fields described by the Kolmogorov and Klein-Kramers equations, the Ornstein-Uhlenbeck and Feller processes, and their generalizations. They are reduced to affine differential and pseudo-differential equations and solved in a unified way by using Kelvin waves and developing a comprehensive math framework for calculating transition probabilities and expectations. Kelvin waves are instrumental for studying the well-known Black-Scholes, Heston, and Stein-Stein models and more complex path-dependent volatility models, as well as the pricing of Asian options, volatility and variance swaps, bonds, and bond options. Kelvin waves help to solve several cutting-edge problems, including hedging the impermanent loss of Automated Market Makers for cryptocurrency trading. This title is also available as Open Access on Cambridge Core. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.09761&r=rmg |
| By: | Marielle BRUNETTE; Stéphane COUTURE; Kene BOUN MY |
| Abstract: | Decisions under uncertainty are an integral part of the daily life of economic agents. However, if uncertainty bears on the probability, on the outcome, or on both, it may not be trivial. In this paper, we study how agents react to these di\u001Berent sources of uncertainty. For that purpose, we implemented a lab experiment with 209 students. We mainly show that the way the decision-makers behave when faced with di\u001Berent sources of uncertainty depends on the level of probability of winning a certain outcome. A majority of subjects thus prefers uncertainty to risk, regardless of the source, when the probability is low. For medium and high probability levels, most of the subjects prefers to face uncertainty on the outcome rather than uncertainty on the probability, whereas the opposite is true for low probability levels. Finally, we show that ambiguity preferences have a signi\u001Ccant e\u001Bect on the individual's behavior under all sources of uncertainty, whereas risk preferences play a role only when double uncertainty is at stake. |
| Keywords: | risk, uncertainty, ambiguity, experiments. |
| JEL: | D8 D9 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-15&r=rmg |
| By: | Lambert, Thomas; Tobe, Christopher |
| Abstract: | This paper examines a looming possible crisis in many Americans’ retirement plans due to the proliferation of annuity products in their retirement investment portfolios. As defined benefit pension plans have almost completely disappeared as a means of retirement savings and have been replaced by defined contribution retirement plans over the last 40 to 50 years, a great number of private and public sector defined contribution retirement plans have become laden with insurance contracts called annuities. Of the remaining solid defined benefit plans many, through a process called Pension Risk Transfer are being converted to high-risk single entity annuities. Such products have been sold to employers and employees as “safe” and “guaranteed’ financial instruments that that are just as good as a defined retirement benefit plan backed by Federal PBGC (Pension Benefit Guarantee Corporation) insurance. The results of the analysis in this paper calls this into question, and with so many of these annuities having ties to investments and loans related to risky assets, the authors find that many annuity products are exposed to systemic risk that could lead to a bust in the pensions of many retirees and soon-to-be retirees. The “Emperor has no Clothes” as the life insurance industry has poured billions of dollars into advertising, lobbying, commissions & trade articles with misinformation on annuities with everyone afraid to call out the obvious fiduciary problems. To invest in annuities one must look the other way at one of most basic investment principals -diversification, i.e., “do not put your eggs in one basket.” Excessive monopolistic profits through secret spread fees have remained hidden with no US Federal regulation or oversight. This paper shows the drawbacks, weaknesses, and pitfalls of annuities as investments for retirement plans as well as the injustices of such plans toward lower income workers. |
| Keywords: | annuities, financialization, monopoly capital, pensions, retirement, risky assets, systemic risk. |
| JEL: | B51 B52 G18 G22 |
| Date: | 2024–03–18 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120482&r=rmg |
| By: | Gianluca Pallante (Institute of Economics and l'EmbeDS, Scuola Superiore Sant'Anna, Pisa, Italy); Mattia Guerini (Universita di Brescia; Fondazione ENI Enrico Mattei; Université Côte d'Azur, CNRS, GREDEG, France; Sant'Anna School of Advanced Studies); Mauro Napoletano (Université Côte d'Azur, CNRS, GREDEG, France; Sciences Po, OFCE, France; Sant'Anna School of Advanced Studies); Andrea Roventini (Institute of Economics and EMbeDS, Scuola Superiore Sant'Anna; Sciences Po, OFCE) |
| Abstract: | We extend the Schumpeter meeting Keynes (K+S; see Dosi et al., 2010, 2013, 2015) to model the emergence and the dynamics of an interbank network in the money market. The extended model allows banks to directly exchange funds, while evaluating their interbank positions using a network-based clearing mechanism (NEVA, see Barucca et al., 2020). These novel adds on, allow us to better measure financial contagion and systemic risk events in the model and to study the possible interactions between micro-prudential and macro-prudential policies. We find that the model can replicate new stylized facts concerning the topology of the interbank network, as well as the dynamics of individual banks' balance sheets. Policy results suggest that the economic system at large can benefit from the introduction of a micro-prudential regulation that takes into account the interbank network relationships. Such a policy decreases the incidence of systemic risk events and the bankruptcies of financial institutions. Moreover, a trade-off between financial stability and macroeconomic performance does not emerge in a two-pillar regulatory framework grounded on i) a Basel III macro-prudential regulation and ii) a NEVA-based micro-prudential policy. Indeed, the NEVA allows the economic system to achieve financial stability without overly stringent capital requirements. |
| Keywords: | Financial contagion, Systemic risk, Micro-prudential policy, Macro-prudential policy, Macroeconomic stability, Agent-based computational economics |
| JEL: | C63 E32 E42 E58 G18 |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:gre:wpaper:2024-10&r=rmg |
| By: | Lee, David |
| Abstract: | This paper presents a model to calculate daily returns and corresponding value changes of hedge funds. In the past, the values of hedge funds were typically available on a monthly basis. The model link daily hedge fund performance with the returns on indices selected to provide a comprehensive spectrum of possible market exposures. The model gives an estimate of the daily returns of hedge funds based on the daily values of a list of market indices. The daily return of each hedge fund is estimated as a linear combination of daily market index returns. The coefficients of this linear combination are obtained through linear regression of monthly index returns against monthly hedge fund returns. |
| Keywords: | hedge fund performance, daily return, cash flow, market index, linear regression. |
| JEL: | C1 C13 C51 G11 G12 |
| Date: | 2024–03–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:120350&r=rmg |
| By: | Kristoffer Balle Hvidberg (CEBI, University of Copenhagen) |
| Abstract: | This paper documents how extensive economic education can reduce the risk of getting into financial trouble by comparing people who enter business and economics programs with people who enter other higher education programs. To identify the causal effect, I exploit GPA admission thresholds that quasi-randomize applicants near the thresholds into different higher education programs. I find that admission to an economics program reduces the probability of loan default and delinquency by one half. This large reduction is associated with changes in financial behavior, but it is not associated with differences in the level or stability of people' income. |
| Keywords: | Financial Problems, Education, Regression Discontinuity, Financial Literacy |
| JEL: | G51 G53 I23 |
| Date: | 2023–05–11 |
| URL: | http://d.repec.org/n?u=RePEc:kud:kucebi:2112&r=rmg |
| By: | Ngai, L. Rachel; Sheedy, Kevin D. |
| Abstract: | This article documents the role of inflows (new listings) and outflows (sales) in explaining the volatility and comovement of housing-market variables. An “ins versus outs” decomposition shows that both flows are quantitatively important for housing-market volatility. The correlations between sales, prices, new listings, and time-to-sell are stable over time, whereas the signs of their correlations with houses for sale are found to be time-varying. A calibrated search-and-matching model with endogenous inflows and outflows and shocks to housing demand matches many of the stable correlations and predicts that the correlations with houses for sale depend on the source and persistence of shocks. |
| Keywords: | housing-market cyclicality; inflows and outflows; search frictions; match quality; Rachel Ngai acknowledges support from the British Academy Mid-Career Fellowship; Wiley deal |
| JEL: | R31 E32 R21 E22 |
| Date: | 2024–03–05 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:121451&r=rmg |
| By: | Yunyun Wang; Tatsushi Oka; Dan Zhu |
| Abstract: | Macro variables frequently display time-varying distributions, driven by the dynamic and evolving characteristics of economic, social, and environmental factors that consistently reshape the fundamental patterns and relationships governing these variables. To better understand the distributional dynamics beyond the central tendency, this paper introduces a novel semi-parametric approach for constructing time-varying conditional distributions, relying on the recent advances in distributional regression. We present an efficient precision-based Markov Chain Monte Carlo algorithm that simultaneously estimates all model parameters while explicitly enforcing the monotonicity condition on the conditional distribution function. Our model is applied to construct the forecasting distribution of inflation for the U.S., conditional on a set of macroeconomic and financial indicators. The risks of future inflation deviating excessively high or low from the desired range are carefully evaluated. Moreover, we provide a thorough discussion about the interplay between inflation and unemployment rates during the Global Financial Crisis, COVID, and the third quarter of 2023. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.12456&r=rmg |