nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒06‒24
24 papers chosen by
Stan Miles
Thompson Rivers University

  1. Historical Evolution of Monthly Anomalies in International Stock Markets By Alex Plastun; Xolani Sibande; Rangan Gupta; Mark E. Wohar
  2. Regime-Switching And Levy Jump Dynamics In Option-Adjusted Spreads By Shaw, Charles
  3. Superkurtosis By Degiannakis, Stavros; Filis, George; Siourounis, Grigorios; Trapani, Lorenzo
  4. Basel III in Africa: Making It Work By Ozili, Peterson K
  5. From Basel I to Basel III: Sequencing Implementation in Developing Economies By Caio Ferreira; Nigel Jenkinson; Christopher Wilson
  6. Credit Default Swap Regulation in Experimental Bond Markets By Matthias Weber; John Duffy; Arthur Schram
  7. Bank Capital Requirements, Loan Guarantees and Firm Performance By Sergio Mayordomo; Antonio Moreno; Steven Ongena; Maria Rodriguez-Moreno
  8. Stress testing the German mortgage market By Barasinska, Nataliya; Haenle, Philipp; Koban, Anne; Schmidt, Alexander
  9. Consumer Protection and the Design of the Default Option of a Pan-European Pension Product By Andrea Berardi; Claudio Tebaldi; Fabio Trojani
  10. On the Nature of Jump Risk Premia By Piotr Orłowski; Paul Schneider; Fabio Trojani
  11. Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting By Gerlach, Richard; Naimoli, Antonio; Storti, Giuseppe
  12. Incremental Risk Charge Methodology By Xiao, Tim
  13. How do Housing Returns in Emerging Countries Respond to Oil Shocks? A MIDAS Touch By Afees A. Salisu; Rangan Gupta
  14. A Flexible Regime Switching Model for Asset Returns By Marc S. Paolella; Pawel Polak; Patrick S. Walker
  15. Insurance: Models, Digitalization, and Data Science By Hansjoerg Albrecher; Antoine Bommier; Damir Filipović; Pablo Koch-Medina; Stéphane Loisel; Hato Schmeiser
  16. Heterogeneous effects of the implementation of macroprudential policies on bank risk By Ely, Regis Augusto; Tabak, Benjamin Miranda; Teixeira, Anderson Mutter
  17. Arbitrage Free Dispersion By Piotr Orłowski; Andras Sali; Fabio Trojani
  18. Sentiment-Driven Stochastic Volatility Model: A High-Frequency Textual Tool for Economists By Jozef Barunik; Cathy Yi-Hsuan Chen; Jan Vecer
  19. Decomposition formula for rough Volterra stochastic volatility models By Raul Merino; Jan Posp\'i\v{s}il; Tom\'a\v{s} Sobotka; Tommi Sottinen; Josep Vives
  20. A Theory of Scenario Generation By Paul Schneider
  21. A Clark-Ocone type formula via Ito calculus and its application to finance By Takuji Arai; Ryoichi Suzuki
  22. Model Risk in Credit Risk By Roberto Fontana; Elisa Luciano; Patrizia Semeraro
  23. Trade Uncertainties and the Hedging Abilities of Bitcoin By Elie Bouri; Konstantinos Gkillas; Rangan Gupta
  24. ESG Investing: From Sin Stocks to Smart Beta By Fabio Alessandrini; Eric Jondeau

  1. By: Alex Plastun (Faculty of Economics and Management, Sumy State University, Sumy, Ukraine); Xolani Sibande (Department of Economics, University of Pretoria, Pretoria, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Mark E. Wohar (College of Business Administration, University of Nebraska; USA and School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)
    Abstract: This paper is a comprehensive investigation of the evolution of various monthly anomalies (January effect, December effect, and the Mark Twain effect) in the US stock market for its entire history. This is done using various statistical techniques (average analysis, Student’s t-test, ANOVA, the Mann-Whitney test) and a trading simulation approach). To confirm our results we extended the analysis to the UK, Japan, Canada, France, Switzerland, Germany and Italy stock markets. The results indicate that the January effect was most prevalent in the US and that the December effect and the Mark Twain effect were never prevalent in the US. This result was confirmed in other markets as well. The January effect was most prevalent in the middle of the 20th century but has since disappeared. Furthermore, the January effect provided exploitable profit opportunities. Our results are consistent and add to the existing literature through the use of a complete history of the US market. Overall, the US stock market is consistent with the Adaptive Market Hypothesis.
    Keywords: Calendar Anomalies, Month of the Year Effect, Stock Market, Efficient Market Hypothesis, January Effect, December Effect, Mark Twain Effect
    JEL: G12 C63
    Date: 2019–06
  2. By: Shaw, Charles
    Abstract: A regime-switching Levy framework, where all parameter values depend on the value of a continuous time Markov chain as per Chevallier and Goutte (2017), is employed to study US Corporate Option-Adjusted Spreads (OASs). For modelling purposes we assume a Normal Inverse Gaussian distribution, allowing heavier tails and skewness. After the Expectation-Maximization algorithm is applied to this general class of regime switching models, we compare the obtained results with time series models without jumps, including one with regime switching and one without. We find that a regime-switching Levy model clearly defines two regimes for A-, AA-, and AAA-rated OASs. We find further evidence of regime-switching effects, with data showing relatively pronounced jump intensity around the time of major crisis periods, thereby confirming the presence and importance of volatility regimes. Results indicate that ignoring the complex and dynamic dependence structure in favour of certain model assumptions may lead to a significant underestimation of risk.
    Keywords: time-series, regime-switching, Levy model, OAS
    JEL: C3
    Date: 2018–12–28
  3. By: Degiannakis, Stavros; Filis, George; Siourounis, Grigorios; Trapani, Lorenzo
    Abstract: Very little is known on how traditional risk metrics behave in ultra high frequency trading (UHFT). We fi�ll this void �firstly by examining the existence of the intraday returns moments, and secondly by assessing the impact of their (non)existence in a risk management framework. We show that in the case of UHFT, the returns' third and fourth moments do not exist, which entails that traditional risk metrics are unable to judge capital adequacy adequately. Hence, the use of risk management techniques, such as VaR, by market participants who engage with UHFT impose serious threats to the stability of fi�nancial markets, given that capital ratios may be severely underestimated.
    Keywords: Ultra high frequency trading, risk management, fi�nite moments, superkurtosis.
    JEL: C12 C54 F30 F31 G10 G15 G17
    Date: 2019–01–14
  4. By: Ozili, Peterson K
    Abstract: Basel III is a framework to protect the global banking system. This article provides a policy discussion on Basel III in Africa. The significance of Basel III is discussed, and some ideas to consider when implementing Basel III to make it work in Africa, are provided. Under Basel III, the African banking industry should expect better capital quality, higher capital levels, minimum liquidity requirement for banks, reduced systemic risk, and differences in Basel III transitional arrangements. This article also emphasizes that (i) there should be enough time for the transition to Basel III in Africa, (ii) a combination of micro and macro-prudential regulations is needed; and (iii) the need to repair the balance sheets of banks, in preparation for Basel III. The discussions in this article will benefit policymakers, academics and other stakeholders interested in financial regulation in Africa such as the World bank and the International Monetary Fund (IMF).
    Keywords: Basel III, Bank business models, Bank performance, Financial stability, Capital regulation, Bank regulation, Africa
    JEL: G21 G23 G28 G32
    Date: 2019
  5. By: Caio Ferreira; Nigel Jenkinson; Christopher Wilson
    Abstract: Developing economies can strengthen their financial systems by implementing the main elements of global regulatory reform. But to build an effective prudential framework, they may need to adapt international standards taking into account the sophistication and size of their financial institutions, the relevance of different financial operations in their market, the granularity of information available and the capacity of their supervisors. Under a proportionate application of the Basel standards, smaller institutions with less complex business models would be subject to a simpler regulatory framework that enhances the resilience of the financial sector without generating disproportionate compliance costs. This paper provides guidance on how non-Basel Committee member countries could incorporate banks’ capital and liquidity standards into their framework. It builds on the experience gained by the authors in the course of their work in providing technical assistance on—and assessing compliance with—international standards in banking supervision.
    Date: 2019–06–14
  6. By: Matthias Weber (University of St. Gallen); John Duffy (UC Irvine); Arthur Schram (University of Amsterdam)
    Abstract: Credit default swaps (CDS) played an important role in the financial crisis of 2008. While CDS can be used to hedge risks, they can also be used for speculative purposes (as occurred during the financial crisis) and regulations have been proposed to limit such speculative use. Here, we provide the first controlled experiment analyzing the pricing of credit default swaps in a bond market subject to default risk. We further use the laboratory as a testbed to analyze CDS regulation. Our results show that the regulation achieves the goal of increasing the use of CDS for hedging purposes while reducing the use of CDS for speculation. This success does not come at the expense of lower bond IPO revenues and does not negatively affect CDS prices or bond prices in the secondary market.
    Keywords: Experimental finance, asset market experiment, CDS, financial regulation, behavioral finance
    JEL: D53 C92
    Date: 2019–06–10
  7. By: Sergio Mayordomo (Banco de España); Antonio Moreno (School of Economics and Business, University of Navarra); Steven Ongena (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; KU Leuven; Centre for Economic Policy Research (CEPR)); Maria Rodriguez-Moreno (Banco de España)
    Abstract: This paper studies the effects of the bank capital requirements imposed by the European authorities in October 2011 on loan collateral and personal guarantees usage to enhance capital ratios. We use detailed information on the loan contracts granted by a representative Spanish bank and several subsidiaries to nonfinancial corporations around that date. We document that personal guarantees usage increases more than that of collateral, especially at subsidiaries with lower capital ratios. However, although the former type of guarantees demonstrably disciplined firms in their risk-taking before 2011, their subsequent overuse may have blunted their impact and may have even undermined firm performance and investment.
    Keywords: Banks, Asymmetric Information, Real Guarantees, Personal Guarantees, Risk Taking, Capital Requirements
    JEL: D43 E32 G21 G32
    Date: 2019–06
  8. By: Barasinska, Nataliya; Haenle, Philipp; Koban, Anne; Schmidt, Alexander
    Abstract: This paper presents a framework for estimating losses in the residential real estate mortgage portfolios of German banks. We develop an EL model where LGD estimates are based on current collateral values and PD dynamics are estimated using a structural PVAR approach. We confirm empirically that foreclosure rates are rising with the unemployment rate and are inversely related to house price inflation. Being consistent with our expectation that strategic defaults do not play a central role given the full personal liability of German households, the results give broad support for the double-trigger hypothesis of mortgage defaults. In order to analyse the possible credit losses stemming from residential mortgage lending we then use the model to run a top-down stress test and simulate losses on the individual bank level for the years from 2018 to 2020 for the whole German banking sector. Our results show that loss rates in the residential mortgage portfolios of German banks do increase significantly in an adverse economic environment. The estimated expected losses are widely distributed in the banking system leading, on average, to a 0.4 percentage points reduction in the CET1 ratio over the simulation period.
    Keywords: residential real estate,mortgages,credit risk,stress testing,German banks
    JEL: G01 G17 G21 G28
    Date: 2019
  9. By: Andrea Berardi (Ca Foscari University of Venice - Dipartimento di Economia); Claudio Tebaldi (Bocconi University - CAREFIN - Centre for Applied Research in Finance; Bocconi University - Department of Finance; Bocconi University - IGIER - Innocenzo Gasparini Institute for Economic Research); Fabio Trojani (Swiss Finance Institute; University of Geneva)
    Abstract: We address potential strengths and weaknesses of alternative protection schemes, which can be adopted as a ‘default option’ in a private, third pillar, pension product. In light of the observed behavior of savers adopting the ‘default option’ at international level, we perform a comparative analysis aimed at quantifying the costs and the benefits of two different risk mitigation techniques and market-standard investment products available to European consumers. We make the case for eligibility of life-cycle target-date funds as default option for the pan-European pension products.
    Keywords: Life-Cycle Saving, Household Finance, Guaranteed Strategies
    JEL: G11 D14 D91
    Date: 2019–03
  10. By: Piotr Orłowski (HEC Montreal); Paul Schneider (University of Lugano - Institute of Finance; Swiss Finance Institute); Fabio Trojani (Swiss Finance Institute; University of Geneva)
    Abstract: We shed light on the nature of jump risk compensation by studying the profits from a trading strategy that bets on the high-frequency jump skew of S&P 500 returns. Earlier evidence suggests the jump risk premium is large and positive. We find it to be concentrated in periods when the index option market is closed, and investors cannot trade options. Whenever jump skew can be traded continuously, the premium vanishes. We conclude the jump skew premium in index options is not compensation for the risk of occasional, large returns, but for the investors’ inability to adjust their nonlinear risk exposure.
    Keywords: rare events, jump risk premium, options, high-frequency data
    JEL: G10 G12 C58
    Date: 2019–06
  11. By: Gerlach, Richard; Naimoli, Antonio; Storti, Giuseppe
    Abstract: This paper proposes generalisations of the Realized GARCH model by Hansen et al. (2012), in three different directions. First, heteroskedasticity in the noise term in the measurement equation is allowed, since this is generally assumed to be time-varying as a function of an estimator of the Integrated Quarticity for intra-daily returns. Second, in order to account for attenuation bias effects, the volatility dynamics are allowed to depend on the accuracy of the realized measure. This is achieved by letting the response coefficient of the lagged realized measure depend on the time-varying variance of the volatility measurement error, thus giving more weight to lagged volatilities when they are more accurately measured. Finally, a further extension is proposed by introducing an additional explanatory variable into the measurement equation, aiming to quantify the bias due to effect of jumps and measurement errors.
    Keywords: Realized Volatility, Realized GARCH, Measurement Error, Realized Quarticity
    JEL: C22 C53 C58
    Date: 2018–01–08
  12. By: Xiao, Tim
    Abstract: The incremental risk charge (IRC) is a new regulatory requirement from the Basel Committee in response to the recent financial crisis. Notably few models for IRC have been developed in the literature. This paper proposes a methodology consisting of two Monte Carlo simulations. The first Monte Carlo simulation simulates default, migration, and concentration in an integrated way. Combining with full re-valuation, the loss distribution at the first liquidity horizon for a subportfolio can be generated. The second Monte Carlo simulation is the random draws based on the constant level of risk assumption. It convolutes the copies of the single loss distribution to produce one year loss distribution. The aggregation of different subportfolios with different liquidity horizons is addressed. Moreover, the methodology for equity is also included, even though it is optional in IRC.
    Keywords: Incremental risk charge (IRC), constant level of risk, liquidity horizon, constant loss distribution, Merton-type model, concentration.
    JEL: C51 C58 G12 G15 G17
    Date: 2019–05–08
  13. By: Afees A. Salisu (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam and Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: In this study, we utilize the recent oil shock data of Baumeister and Hamilton (2019) to analyze how housing returns in China, India and Russia respond to different oil shocks. Given the available data for the relevant variables, the MIDAS approach which helps circumvent aggregation problem in the estimation process is employed. We also extend the MIDAS framework to account for nonlinearities in the model. Expectedly, the housing returns of the countries considered respond differently to the variants of oil shocks. More specifically, we find that the housing returns of India and China which are net oil-importing countries do not seem to possess oil risk hedging characteristics albeit with the converse for Russia which is a major net oil-exporter. We also find that modeling with the MIDAS framework offers better predictability than other variants with uniform frequency.
    Keywords: Housing return, Oil shock, MIDAS regression, Nonlinearities, Forecasting
    JEL: C12 C22 Q41 Q47 R12 R31
    Date: 2019–06
  14. By: Marc S. Paolella (University of Zurich - Department of Banking and Finance; Swiss Finance Institute); Pawel Polak (University of Zurich; Ecole Polytechnique Fédérale de Lausanne - Ecole Polytechnique Fédérale de Lausanne); Patrick S. Walker (University of Zurich, Department of Banking and Finance)
    Abstract: A non-Gaussian multivariate regime switching dynamic correlation model for fi nancial asset returns is proposed. It incorporates the multivariate generalized hyperbolic law for the conditional distribution of returns. All model parameters are estimated consistently using a new two-stage expectation-maximization algorithm that also allows for incorporation of shrinkage estimation via quasi-Bayesian priors. It is shown that use of Markov switching correlation dynamics not only leads to highly accurate risk forecasts, but also potentially reduces the regulatory capital requirements during periods of distress. In terms of portfolio performance, the new regime switching model delivers consistently higher Sharpe ratios and smaller losses than the equally weighted portfolio and all competing models. Finally, the regime forecasts are employed in a dynamic risk control strategy that avoids most losses during the fi nancial crisis and vastly improves risk-adjusted returns.
    Keywords: sGARCH; Markov Switching; Multivariate Generalized Hyperbolic Distribution; Portfolio Optimization; Value-at-Risk
    JEL: C32 C51 C53 G11 G17 G32
    Date: 2019–05
  15. By: Hansjoerg Albrecher (University of Lausanne; Swiss Finance Institute); Antoine Bommier (ETH Zürich - CER-ETH - Center of Economic Research at ETH Zurich); Damir Filipović (Ecole Polytechnique Fédérale de Lausanne; Swiss Finance Institute); Pablo Koch-Medina (University of Zurich - Department of Banking and Finance; Swiss Finance Institute); Stéphane Loisel (University of Lyon 1 - Institute of Finance and Insurance Science (ISFA)); Hato Schmeiser (University of Muenster - Faculty of Economics; University of St. Gallen - I.VW-HSG)
    Abstract: This article summarizes the main topics and findings from the Swiss Risk and Insurance Forum 2018. That event gathered experts from academia, insurance industry, regulatory bodies, and consulting companies to discuss the challenges arising from the impact of data science and, more generally, of digitalization to the insurance sector.
    Keywords: venture
    Date: 2019–05
  16. By: Ely, Regis Augusto; Tabak, Benjamin Miranda; Teixeira, Anderson Mutter
    Abstract: In this article, we analyze the effect of a set of 12 macroprudential policies on the risk-taking of banks using a large number of countries and banks. Our empirical results show that, although on average these policies reduce risk-taking, the effects are quite heterogeneous and vary considerably depending on the instrument implemented, market concentration, size of banks, liquidity, leverage and different levels of risk. Structural policies, such as limits on asset concentration and interbank exposures, are the most effective in terms of financial stability. Borrower based policies, such as loan-to-value and debt-to-income ratios, also have a positive effect on stability. Concentration limits tend to be more effective for larger and more leveraged banks, while loan-to-value and debt-to-income ratios are more effective in concentrated markets. We also show that there seems to be a greater effect through the leverage channel for policies that are most effective in reducing risk-taking.
    Keywords: financial stability, macroprudential policies, bank regulation
    JEL: G21 G28 L10
    Date: 2019–06–17
  17. By: Piotr Orłowski (HEC Montreal); Andras Sali (Alphacruncher); Fabio Trojani (Swiss Finance Institute; University of Geneva)
    Abstract: We develop a theory of arbitrage-free dispersion (AFD) that characterizes the testable restrictions of asset pricing models. AFD measures Jensen’s gap in the cumulant generating function of pricing kernels and returns. It implies a wide family of model-free dispersion constraints, which extend dispersion and co-dispersion bounds in the literature and are applicable with a unifying approach in multivariate and multiperiod settings. Empirically, the dispersion of stationary and martingale pricing kernel components in the benchmark long-run risk model yields a counterfactual dependence of short- vs. long-maturity bond returns and is insufficient for pricing optimal portfolios of market equity and short-term bonds.
    Keywords: Arbitrage-Free Dispersion, Cumulant Generating Function, Convexity, Convex Inequalities, Jensen’s Gap, Pricing Kernel Bounds, Entropy, Long-Run Risk Models, Tests of Asset Pricing Models
    JEL: G12 G15 C14 C52 C58
    Date: 2019–01
  18. By: Jozef Barunik; Cathy Yi-Hsuan Chen; Jan Vecer
    Abstract: We propose how to quantify high-frequency market sentiment using high-frequency news from NASDAQ news platform and support vector machine classifiers. News arrive at markets randomly and the resulting news sentiment behaves like a stochastic process. To characterize the joint evolution of sentiment, price, and volatility, we introduce a unified continuous-time sentiment-driven stochastic volatility model. We provide closed-form formulas for moments of the volatility and news sentiment processes and study the news impact. Further, we implement a simulation-based method to calibrate the parameters. Empirically, we document that news sentiment raises the threshold of volatility reversion, sustaining high market volatility.
    Date: 2019–05
  19. By: Raul Merino; Jan Posp\'i\v{s}il; Tom\'a\v{s} Sobotka; Tommi Sottinen; Josep Vives
    Abstract: The research presented in this article provides an alternative option pricing approach for a class of rough fractional stochastic volatility models. These models are increasingly popular between academics and practitioners due to their surprising consistency with financial markets. However, they bring several challenges alongside. Most noticeably, even simple non-linear financial derivatives as vanilla European options are typically priced by means of Monte-Carlo (MC) simulations which are more computationally demanding than similar MC schemes for standard stochastic volatility models. In this paper, we provide a proof of the prediction law for general Gaussian Volterra processes. The prediction law is then utilized to obtain an adapted projection of the future squared volatility -- a cornerstone of the proposed pricing approximation. Firstly, a decomposition formula for European option prices under general Volterra volatility models is introduced. Then we focus on particular models with rough fractional volatility and we derive an explicit semi-closed approximation formula. Numerical properties of the approximation for a popular model -- the rBergomi model -- are studied and we propose a hybrid calibration scheme which combines the approximation formula alongside MC simulations. This scheme can significantly speed up the calibration to financial markets as illustrated on a set of AAPL options.
    Date: 2019–06
  20. By: Paul Schneider (University of Lugano - Institute of Finance; Swiss Finance Institute)
    Abstract: We show how distributions can be reduced to low-dimensional scenario trees. Applied to intertemporal distributions, the scenarios and their probabilities become time-varying factors. From S&P 500 options, two or three time-varying scenarios suffice to forecast returns, implied variance or skewness on par, or better, than extant multivariate stochastic volatility jump-diffusion models, while reducing the computational effort to fractions of a second.
    Keywords: scenario generation, moment problem, quadrature, prediction, options
    JEL: G13 G02 G17 C02 C14 C46 C52 C53
    Date: 2019–03
  21. By: Takuji Arai; Ryoichi Suzuki
    Abstract: An explicit martingale representation for random variables described as a functional of a Levy process will be given. The Clark-Ocone theorem shows that integrands appeared in a martingale representation are given by conditional expectations of Malliavin derivatives. Our goal is to extend it to random variables which are not Malliavin differentiable. To this end, we make use of Ito's formula, instead of Malliavin calculus. As an application to mathematical finance, we shall give an explicit representation of locally risk-minimizing strategy of digital options for exponential Levy models. Since the payoff of digital options is described by an indicator function, we also discuss the Malliavin differentiability of indicator functions with respect to Levy processes.
    Date: 2019–06
  22. By: Roberto Fontana; Elisa Luciano; Patrizia Semeraro
    Abstract: The issue of model risk in default modeling has been known since inception of the Academic literature in the field. However, a rigorous treatment requires a description of all the possible models, and a measure of the distance between a single model and the alternatives, consistent with the applications. This is the purpose of the current paper. We first analytically describe all possible joint models for default, in the class of finite sequences of exchangeable Bernoulli random variables. We then measure how the model risk of choosing or calibrating one of them affects the portfolio loss from default, using two popular and economically sensible metrics, Value-at-Risk (VaR) and Expected Shortfall (ES).
    Date: 2019–06
  23. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Konstantinos Gkillas (Department of Business Administration, University of Patras − University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: In this paper, we use daily data from October 2011 to May 2019 to estimate the monthly realized correlation between stock returns of the United States (US) and Bitcoin returns. Then, we relate the realized correlation with a news-based measure of the growth of trade uncertainty for the US. Our results show that the realized correlation is negatively impacted by increases in trade uncertainty, suggesting that Bitcoin can act as a hedge relative to the US stock market in the wake of heightened trade policy-related uncertainties, and can provide diversification benefits for investors.
    Keywords: US stock market, Bitcoin, realized correlation, trade uncertainty
    JEL: C22 G10
    Date: 2019–06
  24. By: Fabio Alessandrini (University of Lausanne; Banque Cantonale Vaudoise); Eric Jondeau (University of Lausanne - Faculty of Business and Economics (HEC Lausanne); Swiss Finance Institute)
    Abstract: Research on socially responsible investment in equity markets initially focused on sin stocks. Since then, the availability of data has been extended substantially and now covers environmental, social, and governance (ESG) criteria. Using ESG scores of firms belonging to the MSCI World universe, we measure the impact of score-based exclusion on both passive investment and smart beta strategies. We find that exclusion leads to improved scores of otherwise standard portfolios without deterioration of their risk-adjusted performance. Smart beta strategies exhibit a similar pattern, often in a more pronounced way. Moreover, our results demonstrate that exclusion also implies regional and sectoral tilts as well as (possibly undesirable) risk exposures of the portfolios.
    Date: 2019–03

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