nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒04‒15
twenty-one papers chosen by
Stan Miles
Thompson Rivers University

  1. Risk Measures Based on Benchmark Loss Distributions By Valeria Bignozzi; Matteo Burzoni; Cosimo Munari
  2. Hedge or Rebalance: Optimal Risk Management with Transaction Costs By Florent Gallien; Serge Kassibrakis; Semyon Malamud
  3. CHANGING THE GAME; NEW FRAMEWORK OF CAPITAL ADEQUACY RATIO By Abdelbary, Amr
  4. Model-Free Reinforcement Learning for Financial Portfolios: A Brief Survey By Yoshiharu Sato
  5. Analyzing gold returns: Indian perspective By Moradia, Abha; Mehta, Ashish C.
  6. Strategic Interaction between Hedge Funds and Prime Brokers By Nataliya Gerasimova; Eric Jondeau
  7. Optimal excess-of-loss reinsurance for stochastic factor risk models By Matteo Brachetta; Claudia Ceci
  8. Absolute momentum, sustainable withdrawal rates and glidepath investing in US retirement portfolios from 1925 By Andrew Clare; James Seaton; Peter N. Smith; Stephen Thomas
  9. NEAREST COMOMENT ESTIMATION WITH UNOBSERVED FACTORS By Kris Boudt; Dries Cornilly; Tim Verdonck
  10. Term Structure Modeling under Volatility Uncertainty: A Forward Rate Model driven by G-Brownian Motion By Julian H\"olzermann; Qian Lin
  11. From (Martingale) Schrodinger bridges to a new class of Stochastic Volatility Models By Pierre Henry-Labordere
  12. Risks and strategic opportunities of a new technology cluster: Distributed digital ledgers By Marc Lassagne; Laurent Dehouck
  13. Individual and social preferences under risk: laboratory evidence on the group size effect By Morone, Andrea; Caferra, Rocco
  14. Willingness to Pay for Mortality Risk Reduction from Air Quality Improvement: Evidence from Urban Bangladesh By Minhaj Mahmud; Yasuyuki Sawada; Eiji Yamada
  15. Five Facts About Beliefs and Portfolios By Giglio, Stefano W; Maggiori, Matteo; Ströbel, Johannes; Utkus, Stephen
  16. RISK MANAGEMENT FOR CONNECT PROJECT (FACTORY OF THE FUTURE) By Virginie Borsa
  17. Risk management in monetary policymaking: remarks to the National Association of Corporate Directors, New England Chapter, Boston, Massachusetts, March 5, 2019 By Rosengren, Eric S.
  18. Model Risk and Disappointment Aversion By Hasan Fallahgoul; Loriano Mancini; Stoyan V. Stoyanov
  19. Risk Preferences of Children and Adolescents in Relation to Gender, Cognitive Skills, Soft Skills, and Executive Functions By James Andreoni; Amalia Di Girolamo; John A. List; Claire Mackevicius; Anya Samek
  20. The Impact of Uncertainty Shocks on the Volatility of Commodity Prices. By Dimitrios Bakas; Athanasios Triantafyllou
  21. Exchange Rate Volatility and Cryptocurrencies: a panel discussion at the 2018 BOJ-IMES Conference, Central Banking in a Changing World, Tokyo, Japan By Bullard, James B.

  1. By: Valeria Bignozzi (Università di Milano Bicocca - Dipartimento di Statistica e Metodi Quantitativi); Matteo Burzoni (ETH Zurich); Cosimo Munari (University of Zurich - Department of Banking and Finance; Swiss Finance Institute)
    Abstract: We introduce a class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associates to each potential loss a maximal acceptable probability of occurrence. The corresponding risk measure, called Loss VaR (LVaR), determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the BLD boils down to first-order stochastic dominance. We provide a comprehensive study of the main finance theoretical and statistical properties of LVaR with a focus on their comparison with VaR and ES. Merits and drawbacks are discussed and applications to capital adequacy, portfolio risk management and catastrophic risk are presented.
    Keywords: risk measures, loss distributions, tail risk, capital adequacy, portfolio management, catastrophic risk, robustness, backtestability
    JEL: D81 G32
    Date: 2018–01
    URL: http://d.repec.org/n?u=RePEc:chf:rpseri:rp1848&r=all
  2. By: Florent Gallien (Swissquote Bank); Serge Kassibrakis (Swissquote Bank); Semyon Malamud (Ecole Polytechnique Federale de Lausanne; Centre for Economic Policy Research (CEPR); Swiss Finance Institute)
    Abstract: We solve the problem of optimal risk management for an investor holding an illiquid, alpha generating fund and hedging his position with a liquid futures contract. When the investor is subject to a drawdown constraint, he is forced to reduce the total risk of his portfolio after a drawdown. In this case, he faces a tradeoff of either paying the transaction costs and deleveraging, or keeping his current position in the illiquid instrument and hedging away some of the risk while keeping the residual, unhedgeable risk on his balance sheet. We explicitly characterize this tradeoff and study its dependence on asset characteristics. In particular, we show that higher alpha and lower beta typically widen the no-trading zone, while the impact of volatility is ambiguous.
    Keywords: Optimal Portfolio Choice, Transaction Costs, Hedging, Drawdown Constraints
    JEL: G11 C61
    Date: 2018–08
    URL: http://d.repec.org/n?u=RePEc:chf:rpseri:rp1860&r=all
  3. By: Abdelbary, Amr
    Abstract: The supervisory committees governed the banking supervision on all over the world which becomes a core activity Since the financial crisis of 2008. Capital adequacy ratio (CAR) is one of the measures which ensure the financial soundness of banks in absorbing a reasonable amount of loss. The objective of this paper is to develop a framework for measuring the capital adequacy by assessing the bank’s risks according to the basics of Basel’s norms in respect of the component of tire 1&2 of capital adequacy. The model used the relationships between equity, deposits, loans and assets to determine the risk ratio, which is calculated in regard of retention ratio. As liquidity risk is usually regulated from a micro prudential perspective, a better knowledge of these interactions among banks may have very important consequences on the design of macro prudential policy.
    Keywords: Capital adequacy ratio (CAR), Liquidity, Credit Risk, Loan to Deposits (LTD), Equity to Assets (ETA), Retained Earnings (RE).
    JEL: G21
    Date: 2019–03–05
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:93072&r=all
  4. By: Yoshiharu Sato
    Abstract: Financial portfolio management is one of the problems that are most frequently encountered in the investment industry. Nevertheless, it is not widely recognized that both Kelly Criterion and Risk Parity collapse into Mean Variance under some conditions, which implies that a universal solution to the portfolio optimization problem could potentially exist. In fact, the process of sequential computation of optimal component weights that maximize the portfolio's expected return subject to a certain risk budget can be reformulated as a discrete-time Markov Decision Process (MDP) and hence as a stochastic optimal control, where the system being controlled is a portfolio consisting of multiple investment components, and the control is its component weights. Consequently, the problem could be solved using model-free Reinforcement Learning (RL) without knowing specific component dynamics. By examining existing methods of both value-based and policy-based model-free RL for the portfolio optimization problem, we identify some of the key unresolved questions and difficulties facing today's portfolio managers of applying model-free RL to their investment portfolios.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1904.04973&r=all
  5. By: Moradia, Abha; Mehta, Ashish C.
    Abstract: Investors are forever in need of an asset that adds value to the portfolio. Therefore, along with fixed income investments, stocks, gold and other assets are inevitable parts of a balanced portfolio. For Indian investors, gold is not only an investment asset but a commodity with a major importance in the social customs that makes it all the more interesting to study. As an investment asset, it is considered a diversifier asset and a hedging asset. Not only that, it is called a ‘safe-haven’ asset for times of economic distress, meaning that it retains its value when the stock market is giving low or negative returns. In this paper, we analyze the risk-return parameters of both the gold and Sensex for a period from 1992 to 2017 and find out how they perform along with each other. We also do detailed subperiod analysis in terms of Pearson’s correlation coefficient and see how it changes in pre-recession and post-recession period. We analyze whether gold is a diversifier asset, a hedge, a safe haven or all three for Indian investors. It is interesting to note how the exchange rate variability has a great impact on gold’s rate of return.
    Keywords: gold, stock market, risk-return, correlation coefficient, hedge, safe-haven asset
    JEL: G10 G11
    Date: 2018–08–02
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:92989&r=all
  6. By: Nataliya Gerasimova (Norwegian School of Economics (NHH) - Department of Finance); Eric Jondeau (UUniversity of Lausanne - Faculty of Business and Economics (HEC Lausanne); Swiss Finance Institute)
    Abstract: We develop a framework for the strategic interaction between a hedge fund and a prime broker. The hedge fund optimally determines its cash holdings and the fraction of shorted securities. The prime broker optimally determines its cash holdings, the margin rates, and the rehypothecation rate. The hedge fund and the prime broker make optimal decisions to maximize their expected return on equity. We describe how the evolution of market returns affects the equity of the hedge fund and may force it to delever or even default. Because an eventual default of the hedge fund would severely affect the prime broker’s performance, the prime broker determines the lending rate to cover its expected loss in case of a default. We then explore the strategic interaction between hedge fund and prime broker decisions by calibrating and solving our model for realistic parametrizations. We find that this interaction may give rise to some undesirable implications, such as an increase in overall risk and leverage, when the regulator controls only the prime broker’s balance sheet.
    Keywords: Hedge fund, Prime broker, Leverage, Balance sheet, Financing decisions
    JEL: G2 G23 G24
    Date: 2018–08
    URL: http://d.repec.org/n?u=RePEc:chf:rpseri:rp1854&r=all
  7. By: Matteo Brachetta; Claudia Ceci
    Abstract: We study the optimal excess-of-loss reinsurance problem when both the intensity of the claims arrival process and the claim size distribution are influenced by an exogenous stochastic factor. We assume that the insurer's surplus is governed by a marked point process with dual-predictable projection affected by an environmental factor and that the insurance company can borrow and invest money at a constant real-valued risk-free interest rate $r$. Our model allows for stochastic risk premia, which take into account risk fluctuations. Using stochastic control theory based on the Hamilton-Jacobi-Bellman equation, we analyze the optimal reinsurance strategy under the criterion of maximizing the expected exponential utility of the terminal wealth. A verification theorem for the value function in terms of classical solutions of a backward partial differential equation is provided. Finally, some numerical results are discussed.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1904.05422&r=all
  8. By: Andrew Clare; James Seaton; Peter N. Smith; Stephen Thomas
    Abstract: A significant part of the development in pension provision in many countries is the emergence of ‘Target Date Funds’ or TDFs. In this paper we examine the proposition of de-risking through life and the guidance offered by TDFs in the decumulation phase following retirement. We investigate the withdrawal experience associated with Glidepath Investing in the US since 1925 for conventional bond-equity portfolios. We find one very powerful conclusion: that smoothing the returns on individual assets by simple absolute momentum or trend following techniques is a potent tool to enhance withdrawal rates, often by as much as 50% per annum! And, perhaps of even greater social relevance is that it removes the ‘left-tail’ of unfortunate withdrawal rate experiences, i.e. the bad luck of a poor sequence of returns early in decumulation. We show that diversifying assets over time by switching between an asset and cash in a systematic way is potentially more important for the retirement income experience than diversifying one’s portfolio across asset classes. We also show that Glidepath investing is only sensible within a few years of the target date. This finding provides succour to enthusiasts for target date investing in the face of the growing hostility in the literature.
    Keywords: Sequence Risk, Perfect Withdrawal Rate, Decumulation, Absolute Momentum, Trend Following
    JEL: G10 G11 G22
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:een:camaaa:2019-31&r=all
  9. By: Kris Boudt; Dries Cornilly; Tim Verdonck (-)
    Abstract: We propose a minimum distance estimator for the higher-order comoments of a multivariate distribution exhibiting a lower dimensional latent factor structure. We derive the in uence function of the proposed estimator and prove its consistency and asymptotic normality. The simulation study confirms the large gains in accuracy compared to the traditional sample comoments. The empirical usefulness of the novel framework is shown in applications to portfolio allocation under non-Gaussian objective functions and to the extraction of factor loadings in a dataset with mental ability scores.
    Keywords: Higher-order multivariate moments; latent factor model; minimum distance estimation; risk assessment; structural equation modelling.
    JEL: C10 C13 C51
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:rug:rugwps:19/970&r=all
  10. By: Julian H\"olzermann; Qian Lin
    Abstract: We show how to set up a forward rate model in the presence of volatility uncertainty by using the theory of G-Brownian motion. In order to formulate the model, we extend the G-framework to integration with respect to two integrators and prove a version of Fubini's theorem for stochastic integrals. The evolution of the forward rate in the model is described by a diffusion process, which is driven by a G-Brownian motion. Within this framework, we derive a sufficient condition for the absence of arbitrage, known as the drift condition. In contrast to the traditional model, the drift condition consists of two equations and two market prices of risk, respectively, uncertainty. Furthermore, we examine the connection to short rate models and discuss some examples.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1904.02930&r=all
  11. By: Pierre Henry-Labordere (SOCIETE GENERALE)
    Abstract: Following closely the construction of the Schrodinger bridge, we build a new class of Stochastic Volatility Models exactly calibrated to market instruments such as for example Vanillas, options on realized variance or VIX options. These models differ strongly from the well-known local stochastic volatility models, in particular the instantaneous volatility-of-volatility of the associated naked SVMs is not modified, once calibrated to market instruments. They can be interpreted as a martingale version of the Schrodinger bridge. The numerical calibration is performed using a dynamic-like version of the Sinkhorn algorithm. We finally highlight a striking relation with Dyson non-colliding Brownian motions.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1904.04554&r=all
  12. By: Marc Lassagne (Arts et Métiers ParisTech - ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique); Laurent Dehouck (ENS Rennes - École normale supérieure - Rennes)
    Abstract: his article examines the risks and opportunities associated with distributed ledgers technologies. A novel methodology is developed and presented in order to diagnose and manage their impacts using a strategic risk management perspective. Possible responses to the identified challenges are suggested.
    Abstract: Cet article porte sur les enjeux stratégiques, les risques et les opportunités de la grappe technologique des registres numériques distribués. Il propose une nouvelle méthodologie dans une perspective de gestion stratégique des risques pour en apprécier l'impact et bâtir des réponses adaptées.
    Date: 2018–10–16
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02074330&r=all
  13. By: Morone, Andrea; Caferra, Rocco
    Abstract: In this paper we investigated group size impact on social risk aversion when a majority rule is applied. We used the well-known Holt and Laury's (2002) mechanism to elicit individuals and social risk attitudes. We observed a risk shift in small group and a vanishing of such effect as group size increase.
    Keywords: Preferences; Group; Risk Attitude; Majority Rule; Laboratory
    JEL: C9
    Date: 2019–03–19
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:92856&r=all
  14. By: Minhaj Mahmud; Yasuyuki Sawada; Eiji Yamada
    Abstract: This paper reports on the first attempt to measure the value of statistical life (VSL) in the context of mortality risk from air pollution in urban Bangladesh, using the contingent valuation (CV) method. The CV survey was conducted in 2013 in Dhaka and Chittagong, the two most densely populated cities in the country. We asked individuals willingness to pay (WTP) for mortality risk reduction from air quality improvement program and found that willingness to pay is correlated with the socio-economic characteristics, health status, and risk perception of the respondents, consistently with existing studies. The bootstrapped mean of VSL is ranged from 17,480-22,463 USD in purchasing power parity terms, which is equivalent to 9.78-12.57 times of GDP per capita of Bangladesh. Considering our study setting, the results we obtained may be regarded as a lower bound of VSL estimates in the context of environmental risk reductions in Bangladesh.
    Keywords: value of statistical life, willingness to pay, contingent valuation, air pollution, Bangladesh
    Date: 2019–03
    URL: http://d.repec.org/n?u=RePEc:jic:wpaper:190&r=all
  15. By: Giglio, Stefano W; Maggiori, Matteo; Ströbel, Johannes; Utkus, Stephen
    Abstract: We administer a newly-designed survey to a large panel of retail investors who have substantial wealth invested in financial markets. The survey elicits beliefs that are crucial for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition and their trading activity. We establish five facts in this data: (1) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (2) It is hard to predict when investors trade, but conditional on trading, belief changes affect both the direction and the magnitude of trades. (3) Beliefs are mostly characterized by large and persistent individual heterogeneity; demographic characteristics explain only a small part of why some individuals are optimistic and some are pessimistic. (4) Investors who expect higher cash flow growth also expect higher returns and lower long-term price-dividend ratios. (5) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts challenge the rational expectation framework for macro-finance, and provide important guidance for the design of behavioral models.
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:13657&r=all
  16. By: Virginie Borsa (Air Liquide)
    Abstract: Summary CONNECT project is a project of modernization of Air Liquide Large Industries French operations through integration of digital technologies within plants, automation of plant operations, implementation of a remote control / optimization center. Work in risk management took place at the global level of the project and at the local level (by plant). Major changes of this project are the importance given to information technology risks, a more reinforced monitoring of non-technological risks and the digitalization of topics on safety / risk management. The lessons learned are mainly related to the innovative aspect of the subject.
    Abstract: Le projet CONNECT est un projet de transformation numérique de la branche grande industrie (production primaire) d'Air Liquide en France qui inclut la création d'un centre d'opération et d'optimisation à distance. Le projet d'usine du futur d'Air Liquide introduit également les dernières technologies digitales au quotidien sur les sites. Le travail de maîtrise des risques s'est déroulé au niveau global du projet et au niveau local (par site). Les nouveautés majeures de ce projet sont l'importance accordée aux risques liés aux technologies de l'information, un suivi plus renforcé des risques non technologiques et la digitalisation de sujets sécurité / maîtrise des risques. Les enseignements à tirer sont principalement liés à l'aspect innovant du sujet.
    Date: 2018–10–16
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-02072700&r=all
  17. By: Rosengren, Eric S. (Federal Reserve Bank of Boston)
    Abstract: Eric Rosengren, the Boston Fed president, offered up a “relatively strong forecast” for the economy in 2019: growth somewhat above 2 percent, inflation close to the Fed’s 2 percent target, and a labor market that continues to tighten. However, “risks to that outlook have increased recently,” he said, in a talk focused on assessing and managing those risks.
    Keywords: monetary policy; interest rates; financial stability; fiscal policy; markets; economic outlook
    Date: 2019–03–05
    URL: http://d.repec.org/n?u=RePEc:fip:fedbsp:141&r=all
  18. By: Hasan Fallahgoul (Monash University); Loriano Mancini (USI Lugano - Institute of Finance; Swiss Finance Institute); Stoyan V. Stoyanov (Stony Brook University)
    Abstract: Extensions of utility functions sensitive to the tail behavior of the portfolio return distribution may not be approximated reliably through higher-order moment expansions and require specifying a complete distribution. This, however, implies that an optimal allocation can be adversely influenced by an incorrect distribution specification. We develop a novel approach for model risk assessment based on a projection method which is applied to portfolio construction. In an out-of-sample empirical study, we find that the marginal utility gains of the optimal portfolio of a generalized disappointment aversion investor are remarkably robust to misspecifications in the marginal distributions but are very sensitive to the structural assumption of stock returns implemented through a factor model.
    Keywords: Model risk, utility function, disappointment aversion
    JEL: C5 G12
    Date: 2018–07
    URL: http://d.repec.org/n?u=RePEc:chf:rpseri:rp1865&r=all
  19. By: James Andreoni; Amalia Di Girolamo; John A. List; Claire Mackevicius; Anya Samek
    Abstract: We conduct experiments eliciting risk preferences with over 1,400 children and adolescents aged 3-15 years old. We complement our data with an assessment of cognitive and executive function skills. First, we find that adolescent girls display significantly greater risk aversion than adolescent boys. This pattern is not observed among young children, suggesting that the gender gap in risk preferences emerges in early adolescence. Second, we find that at all ages in our study, cognitive skills (specifically math ability) are positively associated with risk taking. Executive functions among children, and soft skills among adolescents, are negatively associated with risk taking. Third, we find that greater risk-tolerance is associated with higher likelihood of disciplinary referrals, which provides evidence that our task is equipped to measure a relevant behavioral outcome. For academics, our research provides a deeper understanding of the developmental origins of risk preferences and highlights the important role of cognitive and executive function skills to better understand the association between risk preferences and cognitive abilities over the studied age range.
    JEL: C72 C91 C93
    Date: 2019–04
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:25723&r=all
  20. By: Dimitrios Bakas; Athanasios Triantafyllou
    Abstract: In this paper, we empirically examine the impact of uncertainty shocks on the volatility of commodity prices. Using alternative measures of economic uncertainty for the U.S. we estimate their effects on commodity price volatility by employing both VAR and OLS regression models. We find that the unobservable economic uncertainty measures of Jurado et al. (2015) have a significant and long-lasting positive impact on the volatility of commodity prices.Our results indicate that a positive shock in both macroeconomic and financial uncertainty leads to a persistent increase in the volatility of the broad commodity market index and of the individual commodity prices, with the macroeconomic effect being more significant. The impact is stronger in energy commodities compared to the agricultural and metals markets. In addition, our findings show that the measure of unpredictability of the macroeconomic environment has the most significant impact on the commodity price volatility when compared to the observable measures of economic uncertainty that have a rather small and transitory effect. Finally, we show that uncertainty in the macroeconomy is significantly reduced after the occurrence of large commodity market volatility episodes.
    Keywords: Economic Uncertainty, Commodity Prices, Volatility.
    JEL: C22 E32 G13 O13 Q02
    Date: 2018–01
    URL: http://d.repec.org/n?u=RePEc:nbs:wpaper:2018/02&r=all
  21. By: Bullard, James B. (Federal Reserve Bank of St. Louis)
    Date: 2018–05–31
    URL: http://d.repec.org/n?u=RePEc:fip:fedlps:311&r=all

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