nep-rmg New Economics Papers
on Risk Management
Issue of 2020‒12‒14
twenty-six papers chosen by
Stan Miles
Thompson Rivers University

  1. Systemic Impact of the Risk Based Fund Classification and Implications for Fund Management By Martin Ewen; Marc Oliver Rieger
  2. Continuous-Time Risk Contribution and Budgeting for Terminal Variance By Mengjin Zhao; Guangyan Jia
  3. Risk-taking behaviour of family firms: evidence from Tunisia By Dorra Ellouze; Khadija Mnasri
  4. A Risk Based approach for the Solvency Capital requirement for Health Plans By Fabio Baione; Davide Biancalana; Paolo De Angelis
  5. Solving path dependent PDEs with LSTM networks and path signatures By Marc Sabate-Vidales; David \v{S}i\v{s}ka; Lukasz Szpruch
  6. The Impact of Policy Interventions on Systemic Risk across Banks By Simona Nistor; Steven Ongena
  7. State Space Vasicek Model of a Longevity Bond By Georgina Onuma Kalu; Chinemerem Dennis Ikpe; Benjamin Ifeanyichukwu Oruh; Samuel Asante Gyamerah
  8. Would Ambiguity Averse Investors Hedge Risk in Equity Markets? By Gertsman, Gleb; Frehen, Rik; Werker, Bas
  9. From risk sharing to pure premium for a large number of heterogeneous losses By DENUIT, M.; ROBERT, C.Y.
  10. Credit Risk and the Transmission of Interest Rate Shocks By Berardino Palazzo; Ram Yamarthy
  11. The adaptive value of probability distortion and risk-seeking in macaques' decision-making By Aurélien Nioche; Nicolas P. Rougier; Marc Deffains; Sacha Bourgeois-Gironde; Sébastien Ballesta; Thomas Boraud
  12. Nonparametric Estimation of Truncated Conditional Expectation Functions By Tomasz Olma
  13. Safety First, Loss Probability, and the Cross Section of Expected Stock Returns By Ji Cao; Marc Oliver Rieger; Lei Zhao
  14. Applications of liquidity risk discovery using financial market infrastructures transaction archives By Heuver, Richard
  15. Credit Risk in Commercial Real Estate Bank Loans : The Role of Idiosyncratic versus Macro-Economic Factors By Nijskens, Rob; Mokas, Dimitris
  16. Ultimate behavior of conditional mean risk sharing for independent compound Panjer-Katz sums with gamma and Pareto severities By DENUIT, M.; ROBERT, C.Y.
  17. Economic uncertainty before and during the COVID-19 pandemic By Dave Altig; Scott Baker; Jose Maria Barrero; Nick Bloom; Phil Bunn; Scarlet Chen; Steven J Davis; Julia Leather; Brent Meyer; Emil Mihaylov; Paul Mizen; Nick Parker; Thomas Renault; Pawel Smietanka; Grey Thwaites
  18. Unified Extreme Value Estimation for Heterogeneous Data By Einmahl, John; He, Y.
  19. Empirical Tail Copulas for Functional Data By Einmahl, John; Segers, Johan
  20. Heterogeneous Default Effects on Retirement Saving : Sledgehammers or Precision Instruments By de Bresser, Jochem; Knoef, M.G.
  21. Static Hedging of Weather and Price Risks in Electricity Markets By Javier Pantoja Robayo; Juan C. Vera
  22. On Simultaneous Long-Short Stock Trading Controllers with Cross-Coupling By Atul Deshpande; John A Gubner; B. Ross Barmish
  23. Federal Unemployment Reinsurance and Local Labor-Market Policies By Ignaszak, Marek; Jung, Philip; Kuester, Keith
  24. Financial Performance Analysis Of Distressed Banks: Exploration Of Financial Ratios And The Z-score By Matey, Juabin
  25. Fat tails arise endogenously in asset prices from supply/demand, with or without jump processes By Gunduz Caginalp
  26. Forecasting mortality rates and life expectancy in the year of Covid-19 By Francesca Di Iorio; Stefano Fachin

  1. By: Martin Ewen; Marc Oliver Rieger
    Abstract: This paper examines the impact of European legislation regarding risk classification of mutual funds. We conduct analyses on a set of worldwide equity indices and find that a strategy based on the long term volatility as it is imposed by the Synthetic Risk Reward Indicator (SRRI) would lead to substantial variations in exposures ranging from short phases of very high leverage to long periods of under-investments that would be required to keep the risk classes. In some cases funds will be forced to migrate to higher risk classes due to limited means to reduce volatilities after crises events. In other cases they might have to migrate to lower risk classes or increase their leverage to ridiculous amounts. Overall we find if the SRRI creates a binding mechanism for fund managers, it will have substantial negative impact on portfolio management.
    Keywords: portfolio risk, volatility, SRRI, regulation
    JEL: G11 G23 G32
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:trr:qfrawp:201901&r=all
  2. By: Mengjin Zhao; Guangyan Jia
    Abstract: Seeking robustness of risk among different assets, risk-budgeting portfolio selections have become popular in the last decade. Aiming at generalizing risk budgeting method from single-period case to the continuous-time, we characterize the risk contributions and marginal risk contributions on different assets as measurable processes, when terminal variance of wealth is recognized as the risk measure. Meanwhile this specified risk contribution has a aggregation property, namely that total risk can be represented as the aggregation of risk contributions among assets and $(t,\omega)$. Subsequently, risk budgeting problem that how to obtain the policy with given risk budget in continuous-time case, is also explored which actually is a stochastic convex optimization problem parametrized by given risk budget. Moreover single-period risk budgeting policy is related to the projected risk budget in continuous-time case. Based on neural networks, numerical methods are given in order to get the policy with a specified budget process.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.10747&r=all
  3. By: Dorra Ellouze; Khadija Mnasri (CEREFIGE - Centre Européen de Recherche en Economie Financière et Gestion des Entreprises - UL - Université de Lorraine)
    Abstract: Using a unique database of 87 Tunisian non-financial firms over the period 1998-2014, we analyse risk-taking behaviour of family firms. We find evidence that family ownership is positively related to corporate risk-taking. But family firms undertake less risky projects when the manager is not a member of the family or when the founder is no longer active in the firm. Our results show also that in these cases, family ownership becomes negatively associated to risk-taking. Finally, we find that family firms take more risk only when they belong to diversified groups, especially those operating in several industries.
    Keywords: family ownership,corporate governance,group affiliation,risk-taking
    Date: 2019–12–30
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02999642&r=all
  4. By: Fabio Baione; Davide Biancalana; Paolo De Angelis
    Abstract: The study deals with the assessment of risk measures for Health Plans in order to assess the Solvency Capital Requirement. For the estimation of the individual health care expenditure for several episode types, we suggest an original approach based on a three-part regression model. We propose three Generalized Linear Models (GLM) to assess claim counts, the allocation of each claim to a specific episode and the severity average expenditures respectively. One of the main practical advantages of our proposal is the reduction of the regression models compared to a traditional approach, where several two-part models for each episode types are requested. As most health plans require co-payments or co-insurance, considering at this stage the non-linearity condition of the reimbursement function, we adopt a Montecarlo simulation to assess the health plan costs. The simulation approach provides the probability distribution of the Net Asset Value of the Health Plan and the estimate of several risk measures.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.09254&r=all
  5. By: Marc Sabate-Vidales; David \v{S}i\v{s}ka; Lukasz Szpruch
    Abstract: Using a combination of recurrent neural networks and signature methods from the rough paths theory we design efficient algorithms for solving parametric families of path dependent partial differential equations (PPDEs) that arise in pricing and hedging of path-dependent derivatives or from use of non-Markovian model, such as rough volatility models in Jacquier and Oumgari, 2019. The solutions of PPDEs are functions of time, a continuous path (the asset price history) and model parameters. As the domain of the solution is infinite dimensional many recently developed deep learning techniques for solving PDEs do not apply. Similarly as in Vidales et al. 2018, we identify the objective function used to learn the PPDE by using martingale representation theorem. As a result we can de-bias and provide confidence intervals for then neural network-based algorithm. We validate our algorithm using classical models for pricing lookback and auto-callable options and report errors for approximating both prices and hedging strategies.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.10630&r=all
  6. By: Simona Nistor (Babes-Bolyai University - Department of Finance); Steven Ongena (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; KU Leuven; Centre for Economic Policy Research (CEPR))
    Abstract: What is the impact of policy interventions on the systemic risk of banks? To answer this question, we analyze a comprehensive sample that combines bank-specific bailout events with balance sheets of key affected and non-affected European banks between 2008 and 2014. We find that guarantees reduce the systemic risk contribution made by small banks in the short run and by small or less liquid banks in the long run. Recapitalizations immediately decrease banks’ systemic importance, but the effect is also short-lived. Liquidity injections may even significantly increase systemic risk especially when administered to the less capitalized or highly profitable banks.
    Keywords: systemic risk, policy interventions, risk profile, Conditional Value at Risk, G-SIBs
    JEL: E58 G01 G21 G28 H81
    Date: 2020–12
    URL: http://d.repec.org/n?u=RePEc:chf:rpseri:rp20101&r=all
  7. By: Georgina Onuma Kalu; Chinemerem Dennis Ikpe; Benjamin Ifeanyichukwu Oruh; Samuel Asante Gyamerah
    Abstract: Life expectancy have been increasing over the past years due to better health care, feeding and conducive environment. To manage future uncertainty related to life expectancy, various insurance institutions have resolved to come up with financial instruments that are indexed-linked to the longevity of the population. These new instrument is known as longevity bonds. In this article, we present a novel classical Vasicek one factor affine model in modelling zero coupon longevity bond price (ZCLBP) with financial and mortality risk. The interest rate r(t) and the stochastic mortality of the constructed model are dependent but with uncorrelated driving noises. The model is presented in a linear state-space representation of the contiuous-time infinite horizon and used Kalman filter for its estimation. The appropriate state equation and measurement equation derived from our model is used as a method of pricing a longevity bond in a financial market. The empirical analysis results show that the unobserved instantaneous interest rate shows a mean reverting behaviour in the U.S. term structure. The zero-coupon bonds yields are used as inputs for the estimation process. The results of the analysis are gotten from the monthly observations of U.S. Treasury zero coupon bonds from December, 1992 to January, 1993. The empirical evidence indicates that to model properly the historical mortality trends at different ages, both the survival rate and the yield data are needed to achieve a satisfactory empirical fit over the zero coupon longevity bond term structure. The dynamics of the resulting model allowed us to perform simulation on the survival rates, which enables us to model longevity risk.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.12753&r=all
  8. By: Gertsman, Gleb (Tilburg University, School of Economics and Management); Frehen, Rik (Tilburg University, School of Economics and Management); Werker, Bas (Tilburg University, School of Economics and Management)
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:bd3eb3e5-517e-40d4-aab9-ee57a02fa76e&r=all
  9. By: DENUIT, M.; ROBERT, C.Y.
    Date: 2020–01–01
    URL: http://d.repec.org/n?u=RePEc:aiz:louvad:2020015&r=all
  10. By: Berardino Palazzo (Board of Governors of the Federal Reserve System); Ram Yamarthy (Office of Financial Research)
    Abstract: Using daily credit default swap (CDS) data going back to the early 2000s, we find a positive and significant relation between corporate credit risk and unexpected interest rate shocks around FOMC announcement days. Positive interest rate movements increase the expected loss component of CDS spreads as well as a risk premium component that captures compensation for default risk. Not all firms respond in the same manner. Consistent with recent evidence, we find that firm-level credit risk (as proxied by the CDS spread) is an important driver of the response to monetary policy shocks - both in credit and equity markets - and plays a more prominent role in determining monetary policy sensitivity than other common proxies of firm-level risk such as leverage and market size. A stylized corporate model of monetary policy, firm investment, and financing decisions rationalizes our findings.
    Keywords: credit risk, CDS, monetary policy, shock transmission, equity returns
    Date: 2020–12–03
    URL: http://d.repec.org/n?u=RePEc:ofr:wpaper:20-05&r=all
  11. By: Aurélien Nioche (Department of Communications and Networking [Aalto] - Aalto University); Nicolas P. Rougier (Mnemosyne - Mnemonic Synergy - LaBRI - Laboratoire Bordelais de Recherche en Informatique - CNRS - Centre National de la Recherche Scientifique - École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB) - Université Sciences et Technologies - Bordeaux 1 - Université Bordeaux Segalen - Bordeaux 2 - Inria Bordeaux - Sud-Ouest - Inria - Institut National de Recherche en Informatique et en Automatique - IMN - Institut des Maladies Neurodégénératives [Bordeaux] - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Marc Deffains (IMN - Institut des Maladies Neurodégénératives [Bordeaux] - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique); Sacha Bourgeois-Gironde (LEMMA - Laboratoire d'économie mathématique et de microéconomie appliquée - UP2 - Université Panthéon-Assas - Sorbonne Université, IJN - Institut Jean-Nicod - DEC - Département d'Etudes Cognitives - ENS Paris - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - Département de Philosophie - ENS Paris - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres); Sébastien Ballesta (UNISTRA - Université de Strasbourg); Thomas Boraud (IMN - Institut des Maladies Neurodégénératives [Bordeaux] - UB - Université de Bordeaux - CNRS - Centre National de la Recherche Scientifique)
    Abstract: In humans, the attitude toward risk is not neutral and is dissimilar between bets involving gains and bets involving losses. The existence and prevalence of these decision features in non-human primates are unclear. In addition, only a few studies have tried to simulate the evolution of agents based on their attitude toward risk. Therefore, we still ignore to which extent Prospect theory's claims are evolutionary rooted. To shed light on this issue, we collected data in 9 macaques that performed bets involving gains or losses. We confirmed that their overall behaviour is coherent with Prospect theory's claims. In parallel, we used a genetic algorithm to simulate the evolution of a population of agents across several generations. We showed that the algorithm selects progressively agents that exhibit risk-seeking and an inverted S-shape distorted perception of probability. We compared these two results and found that monkeys' attitude toward risk when facing losses only is congruent with the simulation. This result is consistent with the idea that gambling in the loss domain is analogous to deciding in a context of life-threatening challenges where a certain level of risk-seeking behaviours and probability distortions may be adaptive.
    Keywords: Genetic algorithm,Cognitive biases,Monkey,Autonomous Cognitive Testing,Experimental economics
    Date: 2021–01–21
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-03005035&r=all
  12. By: Tomasz Olma
    Abstract: Truncated conditional expectation functions are objects of interest in a wide range of economic applications, including income inequality measurement, financial risk man- agement, and impact evaluation. They typically involve truncating the outcome variable above or below certain quantiles of its conditional distribution. In this paper, based on local linear methods, I propose a novel, two-stage, nonparametric estimator of such functions. In this estimation problem, the conditional quantile function is a nuisance pa- rameter, which has to be estimated in the first stage. I immunize my estimator against the first-stage estimation error by exploiting a Neyman-orthogonal moment in the second stage. This construction ensures that the proposed estimator has favorable bias proper- ties and that inference methods developed for the standard nonparametric regression can be readily adapted to conduct inference on truncated conditional expectation functions. As an extension, I consider estimation with an estimated truncation quantile level. I ap- ply my estimator in three empirical settings: (i) sharp regression discontinuity designs with a manipulated running variable, (ii) program evaluation under sample selection, and (iii) conditional expected shortfall estimation.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2020_244&r=all
  13. By: Ji Cao; Marc Oliver Rieger; Lei Zhao
    Abstract: Recent studies show that loss probability (LP) is a decisive factor when peopleevaluate risk of assets in laboratory experiments, suggesting a positive relationshipbetween LP and expected stock returns. This corresponds to the classical “Safety-First” principle. We find strong empirical support for this prediction in the U.S.stock market. During our sample period, average risk-adjusted return differencesbetween stocks in the two extreme LP deciles exceed 0.75% per month. The posi-tive LP effect, characterized by the intention of some investors to pay low prices forhigh LP stocks, remains significant after controlling for traditional downside riskmeasures.
    Keywords: Loss Probability, Stock Returns, Mental Accounting, Safety-First, RiskAttitudes
    JEL: G11 G12 G14
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:trr:qfrawp:201902&r=all
  14. By: Heuver, Richard (Tilburg University, School of Economics and Management)
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:c33f9db1-8b3f-43ab-bddd-3f340e82f82f&r=all
  15. By: Nijskens, Rob (Tilburg University, School of Economics and Management); Mokas, Dimitris
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:ea4f2f0e-dc50-4987-91d3-67686ea75a66&r=all
  16. By: DENUIT, M.; ROBERT, C.Y.
    Date: 2020–01–01
    URL: http://d.repec.org/n?u=RePEc:aiz:louvad:2020014&r=all
  17. By: Dave Altig; Scott Baker; Jose Maria Barrero; Nick Bloom; Phil Bunn; Scarlet Chen; Steven J Davis; Julia Leather; Brent Meyer; Emil Mihaylov; Paul Mizen; Nick Parker; Thomas Renault; Pawel Smietanka; Grey Thwaites
    Abstract: We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based policy uncertainty, twitter chatter about economic uncertainty, subjective uncertainty about business growth, forecaster disagreement about future GDP growth, and a model-based measure of macro uncertainty. Four results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatly – from a 35% rise for the model-based measure of US economic uncertainty (relative to January 2020) to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: Implied volatility rose rapidly from late February, peaked in mid-March, and fell back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting differences between Wall Street and Main Street uncertainty measures. Fourth, in Cholesky-identified VAR models fit to monthly U.S. data, a COVID-size uncertainty shock foreshadows peak drops in industrial production of 12-19%.
    Keywords: forward-looking uncertainty measures, volatility, COVID-19, coronavirus
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:not:notcfc:2020/07&r=all
  18. By: Einmahl, John (Tilburg University, School of Economics and Management); He, Y. (Tilburg University, School of Economics and Management)
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:dfe6c38c-823b-4394-b4fd-ad1924403551&r=all
  19. By: Einmahl, John (Tilburg University, School of Economics and Management); Segers, Johan
    Date: 2020
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:edc722e6-cc70-4221-87a2-8493156e1ab3&r=all
  20. By: de Bresser, Jochem (Tilburg University, School of Economics and Management); Knoef, M.G. (Tilburg University, School of Economics and Management)
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:tiu:tiutis:c889dcee-39b2-4817-99fc-70d89014ce63&r=all
  21. By: Javier Pantoja Robayo (School of Economics and Finance, Universidad EAFIT. Medellin, Colombia); Juan C. Vera (Tilburg School of Economics and Management, Tilburg University, The Netherlands)
    Abstract: We present the closed-form solution to the problem of hedging price and quantity risks for energy retailers (ER), using financial instruments based on electricity price and weather indexes. Our model considers an ER who is intermediary in a regulated electricity market. ERs buy a fixed quantity of electricity at a variable cost and must serve a variable demand at a fixed cost. Thus ERs are subject to both price and quantity risks. To hedge such risks, an ER could construct a portfolio of financial instruments based on price and weather indexes. We construct the closed form solution for the optimal portfolio for the mean-Var model in the discrete setting. Our model does not make any distributional assumption.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.08620&r=all
  22. By: Atul Deshpande; John A Gubner; B. Ross Barmish
    Abstract: The Simultaneous Long-Short(SLS) controller for trading a single stock is known to guarantee positive expected value of the resulting gain-loss function with respect to a large class of stock price dynamics. In the literature, this is known as the Robust Positive Expectation(RPE)property. An obvious way to extend this theory to the trading of two stocks is to trade each one of them using its own independent SLS controller. Motivated by the fact that such a scheme does not exploit any correlation between the two stocks, we study the case when the relative sign between the drifts of the two stocks is known. The main contributions of this paper are three-fold: First, we put forward a novel architecture in which we cross-couple two SLS controllers for the two-stock case. Second, we derive a closed-form expression for the expected value of the gain-loss function. Third, we use this closed-form expression to prove that the RPE property is guaranteed with respect to a large class of stock-price dynamics. When more information over and above the relative sign is assumed, additional benefits of the new architecture are seen. For example, when bounds or precise values for the means and covariances of the stock returns are included in the model, numerical simulations suggest that our new controller can achieve lower trading risk than a pair of decoupled SLS controllers for the same level of expected trading gain.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.09109&r=all
  23. By: Ignaszak, Marek (Goethe University Frankfurt); Jung, Philip (TU Dortmund); Kuester, Keith (University of Bonn)
    Abstract: Consider a union of atomistic member states, each faced with idiosyncratic business-cycle shocks. Private cross-border risk-sharing is limited, giving a role to a federal unemployment-based transfer scheme. Member states control local labor-market policies, giving rise to a trade-off between moral hazard and insurance. Calibrating the economy to a stylized European Monetary Union, we find notable welfare gains if the federal scheme's payouts take the member states' past unemployment level as a reference point. Member states' control over policies other than unemployment benefits can limit generosity during the transition phase.
    Keywords: unemployment reinsurance, labor-market policy, fiscal federalism, search and matching
    JEL: E32 E24 E62
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp13886&r=all
  24. By: Matey, Juabin
    Abstract: A robust bank industry is a major player in the stability of an economy, and therefore the macroeconomic decisions of most countries revolve around the bank-based financial sector. The Ghana financial industry witnessed a cleanup exercise in 2017 due to the impaired conditions under which it operated in the past. This study used financial ratios aided by the Z-score to analyse the financial performance of UT Bank prior to the 2017 bank industry health check in Ghana. Annual financials over a ten-year period (2007-2016) were used. It was realised that debt management practices of UT Bank were quite unsatisfactory and unimpressive. This was observed in the poor leverage and risk management variable ratios. Considering the results, UT Bank clearly had difficulty obliging to customers’ maturing debts. The average mean values of debt-to-equity and debt-to asset of 7.6 and 0.90 respectively pointed to a case of distress. The entire bank sector stands to benefit if credit management practices of banks, especially UT Bank and all other banks that suffered the same fate, are improved on. As a policy recommendation, the regulator of the bank industry should tighten up its supervisory and monitoring powers to help in detecting early signs of non-performing banks. The study further recommends that statutory lending limits of banks be re-enforced to uphold the threshold of 10 percent for unsecured loans and 25 percent for secured loans of net owned funds of banks.
    Keywords: Debt, Distress, Performance, Credit Management Practice, Z-score
    JEL: G2 G21 G28 G3 G32 G33 G34 G38
    Date: 2019–11–12
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:104499&r=all
  25. By: Gunduz Caginalp
    Abstract: Fat tails arise endogenously from modeling of price change based on a quotient of arbitrarily correlated demand and supply (i.e., excess demand) whether or not jump discontinuities are present. The assumption is that supply and demand are described by drift terms, Brownian (i.e., Gaussians or normals) and compound Poisson jump processes. If $P^{-1}dP/dt$ (the relative price change in an interval $dt$) is given by a suitable function of excess demand, $\mathcal{D}/\mathcal{S}-1$ (where $\mathcal{D}$ and $\mathcal{S}$ are demand and supply), then the distribution has tail behavior $F\left( x\right) \sim x^{-\zeta}$ for a power $\zeta$ that depends on the function $G$ in $P^{-1}dP/dt=G\left( \mathcal{D}/\mathcal{S}\right) $. For $G\left( x\right) \sim\left\vert x\right\vert ^{1/q}$ one has $\zeta=q.$ The value, $q\in\left[ 3,5\right] $ is in agreement with empirical data. While many theoretical explanations have been offered for the paradox of fat tails, we show that this issue never arises if one models price dynamics using basic economics methodology, rather than the usual starting point for classical finance which assumes a normal distribution of price changes. The function, $G,$ can be calibrated in the absence of rare events. The results establish a simple link between the decay exponent of the density function and the price adjustment function, a feature that can improve methodology for risk assessment.
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2011.08275&r=all
  26. By: Francesca Di Iorio (University of Naples Federico II); Stefano Fachin ("Sapienza" University of Rome)
    Abstract: Forecasting mortality rates and life expectancy is an issue of critical importance made arguably more dicult by the e ects of current Covid-19 pandemic. In this paper we compare the performances of a simple random walk model (benchmark), three variants of the standard Lee-Carter model (Lee-Carter, Lee-Miller, Booth-Maindonald-Smith), the Hyndman-Ullah functional data analysys model, and a general factor model. We use both symmetric and asymmetric loss functions, as the latter are arguably more suitable to capture preferences of forecast users such as insurance companies and pension and health system planners. In a counterfactual study, designed exploiting the particular features of Italian data, we reproduce the likely impact of Covid-19 on forecasts using 2020 as a jump-off year. To put the results in perspective, we also carry out out a general assessment on 1950-2016 data for three countries with very diverse demographic profiles, France, Italy and USA. While the results with these latter datasets suggest that in normal conditions the Lee-Miller and Hyndman-Ullah models are somehow superior,from the counterfactual study the best option appears to be the Booth-Maindonald- Smith model.
    Keywords: Mortality forecasting, life expectancy forecasting, Lee-Carter, factor model, Covid-19.
    JEL: C12 C33 C55
    Date: 2020–11
    URL: http://d.repec.org/n?u=RePEc:sas:wpaper:20201&r=all

This nep-rmg issue is ©2020 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.