|
on Risk Management |
| By: | Fantazzini, Dean |
| Abstract: | This paper investigates the estimation of the Value-at-Risk (VaR) across various probability levels for the log-returns of a comprehensive dataset comprising four thousand crypto-assets. Employing four recently introduced Adaptive Conformal Inference (ACI) algorithms, we aim to provide robust uncertainty estimates crucial for effective risk management in financial markets. We contrast the performance of these ACI algorithms with that of traditional benchmark models, including GARCH models and daily range models. Despite the substantial volatility observed in the majority of crypto-assets, our findings indicate that ACI algorithms exhibit notable efficacy. In contrast, daily range models, and to a lesser extent, GARCH models, encounter challenges related to numerical convergence issues and structural breaks. Among the ACI algorithms, the Fully Adaptive Conformal Inference (FACI) and the Scale-Free Online Gradient Descent (SF-OGD) stand out for their ability to provide precise VaR estimates across all quantiles examined. Conversely, the Aggregated Adaptive Conformal Inference (AgACI) and the Strongly Adaptive Online Conformal Prediction (SAOCP) demonstrate proficiency in estimating VaR for extreme quantiles but tend to be overly conservative for higher probability levels. These conclusions withstand robustness checks encompassing the market capitalization of crypto-assets, time series size, and different forecasting methods for asset log-returns. This study underscores the promise of ACI algorithms in enhancing risk assessment practices in the context of volatile and dynamic crypto-asset markets. |
| Keywords: | Value at Risk (VaR); Adaptive Conformal Inference (ACI); Aggregated Adaptive Conformal Inference (AgACI); Fully Adaptive Conformal Inference (FACI); Scale-Free Online Gradient Descent (SF-OGD); Strongly Adaptive Online Conformal Prediction (SAOCP), GARCH; Daily Range; Risk Management |
| JEL: | C14 C51 C53 C58 G17 G32 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121214 |
| By: | Afees A. Salisu (Centre for Econometrics & Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Ahamuefula E. Ogbonna (Centre for Econometrics & Applied Research, Ibadan, Nigeria); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa) |
| Abstract: | In this study, we use the GARCH–MIDAS (Generalized Autoregressive Conditional Heteroskedasticity variant of Mixed Data Sampling) model to explore the relationship between geopolitical risks and oil return volatility. We analyze the daily crude oil returns (West Texas Intermediate (WTI and Brent) and five different monthly measures of geopolitical risks – geopolitical oil price risk (GOPRX), its augmented variant (GOPRX_Augmented), and the conventional geopolitical risks (GPR), geopolitical risks-threats (GPRT), and geopolitical risks-attacks (GPRA). Our results show that higher levels of geopolitical risk are linked to lower oil return volatility, which is due to reduced trading during periods of high geopolitical risks. This finding is consistent across the different GPR indices, with evidence of even out-of-sample predictability. We also discuss the practical implications of our findings for practitioners and policymakers. |
| Keywords: | Geopolitical risks, Oil price volatility, GARCH-MIDAS, Forecast evaluation |
| JEL: | C53 Q41 Q47 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:pre:wpaper:202429 |
| By: | H\'el\`ene Cossette; Etienne Marceau; Alessandro Mutti; Patrizia Semeraro |
| Abstract: | Building on the one-to-one relationship between generalized FGM copulas and multivariate Bernoulli distributions, we prove that the class of multivariate distributions with generalized FGM copulas is a convex polytope. Therefore, we find sharp bounds in this class for many aggregate risk measures, such as value-at-risk, expected shortfall, and entropic risk measure, by enumerating their values on the extremal points of the convex polytope. This is infeasible in high dimensions. We overcome this limitation by considering the aggregation of identically distributed risks with generalized FGM copula specified by a common parameter $p$. In this case, the analogy with the geometrical structure of the class of Bernoulli distribution allows us to provide sharp analytical bounds for convex risk measures. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.10648 |
| By: | Marcelo Righi |
| Abstract: | We expose a theoretical hedging optimization framework with variational preferences under convex risk measures. We explore a general dual representation for the composition between risk measures and utilities. We study the properties of the optimization problem as a convex and monotone map per se. We also derive results for optimality and indifference pricing conditions. We also explore particular examples inside our setup. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.03431 |
| By: | Franco Da Silveira, Rodrigo Lanna; Davoli Alvarenga, Mayara; Luna, Ivette; Coltri, Priscila Pereira; Gonçalves, Renata Ribeiro Do Valle; Torres, Guilherme Almussa Leite |
| Keywords: | Agricultural Finance, Farm Management, Financial Economics |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343570 |
| By: | Turner, Dylan; Tsiboe, Francis; Baldwin, Katherine L.; Dong, Fengxia |
| Keywords: | Agricultural And Food Policy, Risk And Uncertainty, Farm Management |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343841 |
| By: | Thomas Cook; Patrick Flaherty |
| Abstract: | Experimentation involves risk. The investigator expends time and money in the pursuit of data that supports a hypothesis. In the end, the investigator may find that all of these costs were for naught and the data fail to reject the null. Furthermore, the investigator may not be able to test other hypotheses with the same data set in order to avoid false positives due to p-hacking. Therefore, there is a need for a mechanism for investigators to hedge the risk of financial and statistical bankruptcy in the business of experimentation. In this work, we build on the game-theoretic statistics framework to enable an investigator to hedge their bets against the null hypothesis and thus avoid ruin. First, we describe a method by which the investigator's test martingale wealth process can be capitalized by solving for the risk-neutral price. Then, we show that a portfolio that comprises the risky test martingale and a risk-free process is still a test martingale which enables the investigator to select a particular risk-return position using Markowitz portfolio theory. Finally, we show that a function that is derivative of the test martingale process can be constructed and used as a hedging instrument by the investigator or as a speculative instrument by a risk-seeking investor who wants to participate in the potential returns of the uncertain experiment wealth process. Together, these instruments enable an investigator to hedge the risk of ruin and they enable a investigator to efficiently hedge experimental risk. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.15867 |
| By: | Afees A. Salisu (Centre for Econometrics & Applied Research, Ibadan, Nigeria; Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Ahamuefula E. Ogbonna (Centre for Econometrics & Applied Research, Ibadan, Nigeria); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Sisa Shiba (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa) |
| Abstract: | In this study, we use the GARCH-MIDAS model to evaluate how predictable oil and energy market uncertainties are in relation to gold return volatility. We examine daily gold returns and monthly energy uncertainty measurements such as Oil Market Uncertainty (OMU) and Oil Price Uncertainty (OPU), as well as measurements of energy market uncertainties such as the Global Equally-Weighted Energy Uncertainty Index (GEUI-EQ), GDP-Weighted Global Energy Uncertainty Index (GEUI-GDP), and country-specific energy uncertainty indexes for twenty-eight countries. We calculate the total connectedness index (TCI) for the country-specific indexes as a measure of the composite energy uncertainty index. We find that higher uncertainties in the oil and energy markets lead to increased gold volatilities, suggesting that gold can serve as a reliable hedge against oil and energy market uncertainties. Enhanced trading in the gold market raises its volatility as oil and energy market uncertainties increase. Our analysis, both within the sample and out-of-sample, supports this conclusion, and our findings remain valid even when alternative measures of oil and energy market uncertainties are considered. We provide valuable insights into the practical implications of our findings for both practitioners and policymakers. |
| Keywords: | Energy Market Uncertainties, Gold Return Volatility, GARCH-MIDAS, Forecast Evaluation |
| JEL: | C53 N50 Q43 |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:pre:wpaper:202431 |
| By: | Xia Han; Peng Liu |
| Abstract: | In this paper, we investigate the robust models for $\Lambda$-quantiles with partial information regarding the loss distribution, where $\Lambda$-quantiles extend the classical quantiles by replacing the fixed probability level with a probability/loss function $\Lambda$. We find that, under some assumptions, the robust $\Lambda$-quantiles equal the $\Lambda$-quantiles of the extreme probabilities. This finding allows us to obtain the robust $\Lambda$-quantiles by applying the results of robust quantiles in the literature. Our results are applied to uncertainty sets characterized by three different constraints respectively: moment constraints, probability distance constraints via Wasserstein metric, and marginal constraints in risk aggregation. We obtain some explicit expressions for robust $\Lambda$-quantiles by deriving the extreme probabilities for each uncertainty set. Those results are applied to optimal portfolio selection under model uncertainty. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.13539 |
| By: | Keyu Wu; Ernst Fehr; Sean Hofland; Martin Schonger |
| Abstract: | Ambiguous prospects are ubiquitous in social and economic life, but the psychological foundations of behavior under ambiguity are still not well understood. One of the most robust empirical regularities is the strong correlation between attitudes towards ambiguity and compound risk which suggests that compound risk aversion may provide a psychological foundation for ambiguity aversion. However, compound risk aversion and ambiguity aversion may also be independent psychological phenomena, but what would then explain their strong correlation? We tackle these questions by training a treatment group’s ability to reduce compound to simple risks, and analyzing how this affects their compound risk and ambiguity attitudes in comparison to a control group who is taught something unrelated to reducing compound risk. We find that aversion to compound risk disappears almost entirely in the treatment group, while the aversion towards both artificial and natural sources of ambiguity remain high and are basically unaffected by the teaching of how to reduce compound lotteries. Moreover, similar to previous studies, we observe a strong correlation between compound risk aversion and ambiguity aversion, but this correlation only exists in the control group while in the treatment group it is rather low and insignificant. These findings suggest that ambiguity attitudes are not a psychological relative, and derived from, attitudes towards compound risk, i.e., compound risk aversion and ambiguity aversion do not share the same psychological foundations. While compound risk aversion is primarily driven by a form of bounded rationality – the inability to reduce compound lotteries – ambiguity aversion is unrelated to this inability, suggesting that ambiguity aversion may be a genuine preference in its own right. |
| Keywords: | ambiguity aversion, compound risk aversion, bounded rationality, reduction of compound lotteries |
| JEL: | C91 D01 D91 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11150 |
| By: | Zachary Feinstein; Grzegorz Halaj; Andreas Sojmark |
| Abstract: | We build a balance sheet-based model to capture run risk, i.e., a reduced potential to raise capital from liquidity buffers under stress, driven by depositor scrutiny and further fueled by fire sales in response to withdrawals. The setup is inspired by the Silicon Valley Bank (SVB) meltdown in March 2023 and our model may serve as a supervisory analysis tool to monitor build-up of balance sheet vulnerabilities. Specifically, we analyze which characteristics of the balance sheet are critical in order for banking system regulators to adequately assess run risk and resilience. By bringing a time series of SVB's balance sheet data to our model, we are able to demonstrate how changes in the funding and respective asset composition made SVB prone to run risk, as they were increasingly relying on held-to-maturity, aka hidden-to-maturity, accounting standards, masking revaluation losses in securities portfolios. Finally, we formulate a tractable optimisation problem to address the designation of held-to-maturity assets and quantify banks' ability to hold these assets without resorting to remarking. By calibrating this to SVB's balance sheet data, we shed light on the bank's funding risk and implied risk tolerance in the years 2020--22 leading up to its collapse. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.03285 |
| By: | H. Peter Boswijk (Amsterdam School of Economics, University of Amsterdam); Jun Yu (Department of Finance and Business Economics, Faculty of Business Administration, University of Macau); Yang Zu (Department of Economics, University of Macau) |
| Abstract: | Based on a continuous-time stochastic volatility model with a linear drift, we develop a test for explosive behavior in financial asset prices at a low frequency when prices are sampled at a higher frequency. The test exploits the volatility information in the high-frequency data. The method consists of devolatizing log-asset price increments with realized volatility measures and performing a supremumtype recursive Dickey-Fuller test on the devolatized sample. The proposed test has a nuisance-parameter-free asymptotic distribution and is easy to implement. We study the size and power properties of the test in Monte Carlo simulations. A realtime date-stamping strategy based on the devolatized sample is proposed for the origination and conclusion dates of the explosive regime. Conditions under which the real-time date-stamping strategy is consistent are established. The test and the date-stamping strategy are applied to study explosive behavior in cryptocurrency and stock markets. |
| Keywords: | Stochastic volatility model; Unit root test; Double asymptotics; Explosiveness; Asset price bubbles |
| JEL: | C12 C22 G01 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:boa:wpaper:202402 |
| By: | Philipp Wirth; Francesca Medda; Thomas Schr\"oder |
| Abstract: | In this paper, we introduce the Dynamic Modularity-Spectral Algorithm (DynMSA), a novel approach to identify clusters of stocks with high intra-cluster correlations and low inter-cluster correlations by combining Random Matrix Theory with modularity optimisation and spectral clustering. The primary objective is to uncover hidden market structures and find diversifiers based on return correlations, thereby achieving a more effective risk-reducing portfolio allocation. We applied DynMSA to constituents of the S&P 500 and compared the results to sector- and market-based benchmarks. Besides the conception of this algorithm, our contributions further include implementing a sector-based calibration for modularity optimisation and a correlation-based distance function for spectral clustering. Testing revealed that DynMSA outperforms baseline models in intra- and inter-cluster correlation differences, particularly over medium-term correlation look-backs. It also identifies stable clusters and detects regime changes due to exogenous shocks, such as the COVID-19 pandemic. Portfolios constructed using our clusters showed higher Sortino and Sharpe ratios, lower downside volatility, reduced maximum drawdown and higher annualised returns compared to an equally weighted market benchmark. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.04500 |
| By: | Sokolov, Yuri I. |
| Abstract: | While the banking sector has long been at the forefront of risk management practices, other service industries often lag behind. This disparity is particularly evident in sectors where value-oriented management is crucial for maintaining competitiveness. This article focuses on the development and application of the Factor Endogenous Behaviour Aggregation (FEBA) approach in service industries such as healthcare and health resorts. In these sectors, risk management is typically handled on an ad hoc basis due to the absence of stringent regulatory requirements. Understanding and managing customer loyalty is crucial for sustained profitability and growth. In this context, the SOL (Satisfaction Outcome Loyalty) Solution, proposed by Sokolov (2015), emerges as a pivotal tool for quantifying various risks within the Service Profit Chain. The SOL Solution provides a structured approach to quantify risks associated with employee performance, customer satisfaction, and loyalty. By assigning numerical values to these risks, companies can better understand their impact on profitability. This quantification allows businesses to prioritize actions that will have the most significant positive impact on customer loyalty and profitability. The tool also enables predictive analysis, helping businesses foresee potential risks and opportunities by analyzing trends and patterns. *The approach was set up in “Interaction between market and credit risk: Focus on the endogeneity of aggregate risk” and mentioned in Roubini Global Economic Digest as “Advance in Credit Risk Management”. |
| Keywords: | SOL Solution, Service Profit Chain, FEBA approach, competitiveness, healthcare, health resorts, satisfaction, loyalty, risk management |
| JEL: | G32 I11 L80 M31 |
| Date: | 2024–06–13 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:121188 |
| By: | Oriol Zamora Font |
| Abstract: | We derive a semi-analytical pricing formula for European VIX call options under the Heston-Hawkes stochastic volatility model introduced in arXiv:2210.15343. This arbitrage-free model incorporates the volatility clustering feature by adding an independent compound Hawkes process to the Heston volatility. Using the Markov property of the exponential Hawkes an explicit expression of $\text{VIX}^2$ is derived as a linear combination of the variance and the Hawkes intensity. We apply qualitative ODE theory to study the existence of some generalized Riccati ODEs. Thereafter, we compute the joint characteristic function of the variance and the Hawkes intensity exploiting the exponential affine structure of the model. Finally, the pricing formula is obtained by applying standard Fourier techniques. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.13508 |
| By: | Sabrina Khurshid; Mohammed Shahid Abdulla; Gourab Ghatak |
| Abstract: | Sharpe Ratio (SR) is a critical parameter in characterizing financial time series as it jointly considers the reward and the volatility of any stock/portfolio through its variance. Deriving online algorithms for optimizing the SR is particularly challenging since even offline policies experience constant regret with respect to the best expert Even-Dar et al (2006). Thus, instead of optimizing the usual definition of SR, we optimize regularized square SR (RSSR). We consider two settings for the RSSR, Regret Minimization (RM) and Best Arm Identification (BAI). In this regard, we propose a novel multi-armed bandit (MAB) algorithm for RM called UCB-RSSR for RSSR maximization. We derive a path-dependent concentration bound for the estimate of the RSSR. Based on that, we derive the regret guarantees of UCB-RSSR and show that it evolves as O(log n) for the two-armed bandit case played for a horizon n. We also consider a fixed budget setting for well-known BAI algorithms, i.e., sequential halving and successive rejects, and propose SHVV, SHSR, and SuRSR algorithms. We derive the upper bound for the error probability of all proposed BAI algorithms. We demonstrate that UCB-RSSR outperforms the only other known SR optimizing bandit algorithm, U-UCB Cassel et al (2023). We also establish its efficacy with respect to other benchmarks derived from the GRA-UCB and MVTS algorithms. We further demonstrate the performance of proposed BAI algorithms for multiple different setups. Our research highlights that our proposed algorithms will find extensive applications in risk-aware portfolio management problems. Consequently, our research highlights that our proposed algorithms will find extensive applications in risk-aware portfolio management problems. |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.06552 |
| By: | Wahdat, Ahmad Z.; Bryant, Elijah H.; Hubbell, Caitlinn B.; Balagtas, Joseph V. |
| Keywords: | Food Consumption/Nutrition/Food Safety, Demand And Price Analysis, Risk And Uncertainty |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343899 |
| By: | Navarini, Lorenzo; Verhaest, Dieter |
| Abstract: | When individuals risk being overeducated for their jobs, returns to education might be lower and heterogeneous. To investigate this, we develop a novel framework that decomposes returns using an expected value conditional on overeducation risks and penalties. We estimate these components using Belgian data and a dynamic model of endogenous educational choices, overeducation, and wages. Our findings reveal that overeducated individuals experience a persistent wage penalty. However, as both medium and higher levels of education are associated with an overeducation risk, this risk usually plays a limited role in explaining average returns. Moreover, consistent with job polarization, this role is even positive for Bachelor's degrees as these degrees rather reduce the overeducation risks and the associated penalties. Finally, we find that overeducation generates heterogeneous realized returns among Master's graduates. |
| Keywords: | Skill Mismatch, Overeducation, Dynamic Discrete Choice Model, Heterogeneous Returns to Education, Educational Expansion |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1456 |
| By: | Boyer, Christopher N.; DeLong, Karen L.; Griffith, Andrew P.; Martinez, Charles |
| Keywords: | Farm Management, Livestock Production/Industries, Agricultural Finance |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343568 |
| By: | Liran Einav; Amy Finkelstein; Pietro Tebaldi |
| Abstract: | Health insurance is increasingly provided through managed competition, in which subsidies for consumers and risk adjustment for insurers are key market design instruments. We illustrate that subsidies offer two advantages over risk adjustment in markets with adverse selection. They provide greater flexibility in tailoring premiums to heterogeneous buyers, and they produce equilibria with lower markups and greater enrollment. We assess these effects using demand and cost estimates from the California Affordable Care Act marketplace. Holding government spending fixed, we estimate that subsidies can increase enrollment by 16 percentage points (76%) over risk adjustment, while all consumers are weakly better off. |
| JEL: | G22 G28 H51 I13 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32586 |
| By: | Rao, Xudong; Wang, Xingguo; Turvey, Calum G.; Zhang, Yuehua |
| Keywords: | Livestock Production/Industries, Risk And Uncertainty, Farm Management |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea22:343709 |
| By: | Will Hicks |
| Abstract: | In this article we look at stochastic processes with uncertain parameters, and consider different ways in which information is obtained when carrying out observations. For example we focus on the case of a the random evolution of a traded financial asset price with uncertain volatility. The quantum approach presented, allows us to encode different volatility levels in a state acting on a Hilbert space. We consider different means of defining projective measurements in order to track the evolution of a traded market price, and discuss the results of different Monte-Carlo simulations. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.04520 |
| By: | Söhnke M. Bartram; Gregory W. Brown; René M. Stulz |
| Abstract: | Average idiosyncratic volatility and firm idiosyncratic volatility increase with the number of listed firms. Average industry idiosyncratic volatility increases with the number of listed firms in the industry. We ex-plain the relation between idiosyncratic volatility and the number of listed firms through Schumpeterian creative destruction. We show that Schumpeterian creative destruction increases as the number of listed firms increases. However, there is no consistent evidence of an incremental effect of the number of non-listed firms on idiosyncratic volatility either in the aggregate or at the industry level, suggesting that listed firms play a unique role in the dynamism of the economy. |
| JEL: | G10 G11 G12 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:32568 |
| By: | Scander Mustapha |
| Abstract: | We study a two-dimensional McKean-Vlasov stochastic differential equation, whose volatility coefficient depends on the conditional distribution of the second component with respect to the first component. We prove the strong existence and uniqueness of the solution, establishing the well-posedness of a two-factor local stochastic volatility (LSV) model calibrated to the market prices of European call options. In the spirit of [Jourdain and Zhou, 2020, Existence of a calibrated regime switching local volatility model.], we assume that the factor driving the volatility of the log-price takes finitely many values. Additionally, the propagation of chaos of the particle system is established, giving theoretical justification for the algorithm [Julien Guyon and Henry-Labord\`ere, 2012, Being particular about calibration.]. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.14074 |
| By: | R\"udiger Frey; Theresa Traxler |
| Abstract: | We study the impact of regulatory capital constraints on fire sales and financial stability in a large banking system using a mean field game model. In our model banks adjust their holdings of a risky asset via trading strategies with finite trading rate in order to maximize expected profits. Moreover, a bank is liquidated if it violates a stylized regulatory capital constraint. We assume that the drift of the asset value is affected by the average change in the position of the banks in the system. This creates strategic interaction between the trading behavior of banks and thus leads to a game. The equilibria of this game are characterized by a system of coupled PDEs. We solve this system explicitly for a test case without regulatory constraints and numerically for the regulated case. We find that capital constraints can lead to a systemic crisis where a substantial proportion of the banking system defaults simultaneously. Moreover, we discuss proposals from the literature on macroprudential regulation. In particular, we show that in our setup a systemic crisis does not arise if the banking system is sufficiently well capitalized or if improved mechanisms for the resolution of banks violating the risk capital constraints are in place. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.17528 |
| By: | Fernando Acebes; M Pereda; David Poza; Javier Pajares; Jose M Galan |
| Abstract: | The aim of this paper is to describe a new an integrated methodology for project control under uncertainty. This proposal is based on Earned Value Methodology and risk analysis and presents several refinements to previous methodologies. More specifically, the approach uses extensive Monte Carlo simulation to obtain information about the expected behavior of the project. This dataset is exploited in several ways using different statistical learning methodologies in a structured fashion. Initially, simulations are used to detect if project deviations are a consequence of the expected variability using Anomaly Detection algorithms. If the project follows this expected variability, probabilities of success in cost and time and expected cost and total duration of the project can be estimated using classification and regression approaches. |
| Date: | 2024–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.02589 |
| By: | Emily Quiroga; Michael Tanner |
| Abstract: | The study on risk preferences and its potential changes amid natural catastrophes has been subject of recent study, producing contradictory findings. An often proposed explanation specifically distinguishes between the opposite effect of realized and unrealized losses on risk preferences. Moreover, higher-order risk preferences and its relation to post-disaster behaviors remain unexplored, despite potential theoretical implications. We address these gaps in the literature by conducting experiments with 600 individuals post Turkeys 2023 catastrophic earthquake, specifically heavily affected individuals who are displaced, those who are not and a control group. Results indicate higher risk-taking in heavily affected individuals when compared to unaffected individuals. Our results are specifically driven by affected females. We find no pre existing differences in risk preferences between earthquake and control areas using 2012 data. Within the heavily affected group of individuals, higher house damage, our proxy for realized losses, increases risk aversion. Regarding higher-order risk preferences for individuals heavily affected by the earthquake, we find that prudence is positively associated with selfprotective behaviors after the earthquake, specifically internal migration and/or displacement. While precautionary savings shows initially no correlation to prudence, a positive association emerges when considering that prudence is also related to occupational choices, with individuals with stable incomes and who save being more prudent. Our results contribute insights into how disasters influence risk preferences, specifically aiming to address contradictory findings in the literature, while presenting novel evidence on the relationship between prudence and post-natural disaster behaviors. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.15905 |
| By: | Ndwiga, David |
| Abstract: | Using a Panel VAR model and annual bank level data for the period 2008-2022, this study investigated banks risk taking behaviour amid monetary policy tightening considering the role of banks' non-interest-bearing deposits and equity levels. Estimation results found monetary policy tightening and equity levels reduces the bank risk taking behavior thus evidence of monetary policy risk-taking transmission channel. However, the contrary was reported with regard to bank liability: - non - interest bearing deposit "pseudo assets". However, interaction between policy rate, equity and "pseudo assets" was found to increase bank risk appetite significantly. This study is important since under the risk-taking channel view, a change in the policy rate is immediately transmitted to money-market instruments of different maturity and to other short-term rates, such as interbank deposits and this quickly affects the interest rates that banks charge their customers for variable-rate loans, including overdrafts. |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:kbawps:297987 |
| By: | Guillaume Roussellet |
| Abstract: | Since the late 1990s, the U.S. Treasury has issued debt in two main forms: nominal bonds, which provide fixed-cash scheduled payments, and Treasury Inflation Protected Securities—or TIPS—which provide the holder with inflation-protected payments that rise with U.S. inflation. At the heart of their relative valuation lie market participants’ expectations of future inflation, an object of interest for academics, policymakers, and investors alike. After briefly reviewing the theoretical and empirical links between TIPS and Treasury yields, this post, based on a recent research paper, explores whether market perceptions of U.S. sovereign credit risk can help explain the relative valuation of these financial instruments. |
| Keywords: | Treasury; Treasury Inflation-Protected Securities (TIPS); breakeven inflation; default risk; loss given default; loss-given default (LGD) |
| JEL: | E4 E6 G12 |
| Date: | 2024–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:98470 |
| By: | Nicola F. Zaugg; Lech A. Grzelak |
| Abstract: | The pricing of derivatives tied to baskets of assets demands a sophisticated framework that aligns with the available market information to capture the intricate non-linear dependency structure among the assets. We describe the dynamics of the multivariate process of constituents with a copula model and propose an efficient method to extract the dependency structure from the market. The proposed method generates coherent sets of samples of the constituents process through systematic sampling rearrangement. These samples are then utilized to calibrate a local volatility model (LVM) of the basket process, which is used to price basket derivatives. We show that the method is capable of efficiently pricing basket options based on a large number of basket constituents, accomplishing the calibration process within a matter of seconds, and achieving near-perfect calibration to the index options of the market. |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2407.02901 |
| By: | William G. Morrison; Bradley J. Ruffle |
| Abstract: | We report on a laboratory experiment to investigate whether the price paid for insurance explains dishonesty in reporting an insurance claim. In the experiment, participants earn money in a realeffort task, but risk losing some of this income through one of four randomly assigned and privately observed loss amounts. Prior to observing and reporting their loss, participants indicate their reservation price for an insurance policy that pays an indemnity equal to their stated loss. Participants are insured if their randomly assigned premium is less than or equal to their stated reservation price. This mechanism provides data on each participant’s consumer surplus from the purchase of insurance. After receiving their cash earnings minus their assigned loss amount in private, participants report their loss. Our results indicate that the propensity to dishonestly report an inflated loss neither increases in the amount paid for insurance nor decreases in the consumer surplus associated with an insurance purchase. |
| Keywords: | experimental economics; insurance; dishonesty; claim buildup; known reporting distribution |
| JEL: | C91 D82 G22 |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:mcm:deptwp:2024-05 |
| By: | Zuzanna Kostecka; Robert \'Slepaczuk |
| Abstract: | The scope for the accurate calculation of the Loss Given Default (LGD) parameter is comprehensive in terms of financial data. In this research, we aim to explore methods for improving the approximation of realized LGD in conditions of limited access to the cash-flow data. We enhance the performance of the method which relies on the differences between exposure values (delta outstanding approach) by employing machine learning (ML) techniques. The research utilizes the data from the mortgage portfolio of one of the European countries and assumes a close resemblance to similar economic contexts. It incorporates non-financial variables and macroeconomic data related to the housing market, improving the accuracy of loss severity approximation. The proposed methodology attempts to mitigate the country-specific (related to the local legal) or portfolio-specific factors in aim to show the general advantage of applying ML techniques, rather than case-specific relation. We developed an XGBoost model that does not rely on cash-flow data yet enhances the accuracy of realized LGD estimation compared to results obtained with the delta outstanding approach. A novel aspect of our work is the detailed exploration of the delta outstanding approach and the methodology for addressing conditions of limited access to cash-flow data through machine learning models. |
| Date: | 2024–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2406.17308 |
| By: | Holloway, Samuel |
| Abstract: | This qualitative study explores the pivotal role of supply chain collaboration (SCC) in enhancing marketing effectiveness within organizations. By integrating supply chain management (SCM) practices with marketing strategies, companies can optimize operational efficiencies, anticipate consumer demands, and deliver personalized customer experiences. The study emphasizes technological integration, such as IoT, big data analytics, and blockchain, which enables real-time data sharing, predictive analytics, and enhanced visibility across the supply chain. Strategic alignment between SCM and marketing functions ensures efficient resource allocation and strategic deployment of marketing investments, fostering synergistic outcomes and maximizing market impact. Collaborative innovation within supply chains drives continuous improvement and product innovation, strengthening brand reputation and customer loyalty. Additionally, supply chain resilience, achieved through robust risk management and agile strategies, enables businesses to maintain operational stability and mitigate disruptions, safeguarding customer relationships and brand integrity. This research underscores the strategic imperative for organizations to embrace SCC as a driver of sustainable growth and competitive advantage in dynamic market environments. By leveraging SCC to integrate SCM and marketing functions, companies can navigate complexities, capitalize on market opportunities, and sustain long-term success. The findings provide valuable insights for business leaders seeking to enhance marketing effectiveness through effective SCC strategies. |
| Date: | 2024–06–28 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:zp7fw |
| By: | Timothy Riffe (Max Planck Institute for Demographic Research, Rostock, Germany); Iñaki Permanyer; Rustam Tursun-Zade (Max Planck Institute for Demographic Research, Rostock, Germany); Magdalena Muszynska-Spielauer |
| Keywords: | Italy |
| JEL: | J1 Z0 |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:dem:wpaper:wp-2024-013 |