|
on Risk Management |
|
Issue of 2022‒03‒28
twenty-six papers chosen by |
| By: | Giuseppe Genovese; Ashkan Nikeghbali; Nicola Serra; Gabriele Visentin |
| Abstract: | We introduce a new portfolio credit risk model based on Restricted Boltzmann Machines (RBMs), which are stochastic neural networks capable of universal approximation of loss distributions. We test the model on an empirical dataset of default probabilities of 30 investment-grade US companies and we show that it outperforms commonly used parametric factor copula models -- such as the Gaussian or the t factor copula models -- across several credit risk management tasks. In particular, the model leads to better out-of-sample fits for the empirical loss distribution and more accurate risk measure estimations. We introduce an importance sampling procedure which allows risk measures to be estimated at high confidence levels in a computationally efficient way and which is a substantial improvement over the Monte Carlo techniques currently available for copula models. Furthermore, the statistical factors extracted by the model admit an interpretation in terms of the underlying portfolio sector structure and provide practitioners with quantitative tools for the management of concentration risk. Finally, we show how to use the model for stress testing by estimating stressed risk measures (e.g. stressed VaR) for our empirical portfolio under various macroeconomic stress test scenarios, such as those specified by the FRB's Dodd-Frank Act stress test. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.11060&r= |
| By: | Benjamin Bruder; Nazar Kostyuchyk; Thierry Roncalli |
| Abstract: | This article develops a model that takes into account skewness risk in risk parity portfolios. In this framework, asset returns are viewed as stochastic processes with jumps or random variables generated by a Gaussian mixture distribution. This dual representation allows us to show that skewness and jump risks are equivalent. As the mixture representation is simple, we obtain analytical formulas for computing asset risk contributions of a given portfolio. Therefore, we define risk budgeting portfolios and derive existence and uniqueness conditions. We then apply our model to the equity/bond/volatility asset mix policy. When assets exhibit jump risks like the short volatility strategy, we show that skewness-based risk parity portfolios produce better allocation than volatility-based risk parity portfolios. Finally, we illustrate how this model is suitable to manage the skewness risk of long-only equity factor portfolios and to allocate between alternative risk premia. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.10721&r= |
| By: | Elisa Luciano; Jean Charles Rochet |
| Abstract: | The risk appetite of insurance companies fluctuates over time in a quasi cyclical fashion. When their capitalization is high (low), companies choose portfolios with a high (small) share of risky assets. We show that this phenomenon may have the same source as the un derwriting cycle, namely recapitalization costs. We build a simple dynamic model of the insurance sector where financial frictions prevent companies from maintaining a target leverage. Portfolio decisions of insurers fluctuate with their aggregate capitalization. The model rationalizes two apparently disjoint pieces of evidence: long-standing empirical evidence on underwriting cycles and more recent evidence on the fluctuations of insurance companies’ risk appetite |
| Keywords: | endogenous risk appetite, macro finance, insurance cycles, insurance asset allocation |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:cca:wpaper:666&r= |
| By: | Yusuke Uchiyama; Kei Nakagawa |
| Abstract: | The mean-variance portfolio that considers the trade-off between expected return and risk has been widely used in the problem of asset allocation for multi-asset portfolios. However, since it is difficult to estimate the expected return and the out-of-sample performance of the mean-variance portfolio is poor, risk-based portfolio construction methods focusing only on risk have been proposed, and are attracting attention mainly in practice. In terms of risk, asset fluctuations that make up the portfolio are thought to have common factors behind them, and principal component analysis, which is a dimension reduction method, is applied to extract the factors. In this study, we propose the Schr\"{o}dinger risk diversification portfolio as a factor risk diversifying portfolio using Schr\"{o}dinger principal component analysis that applies the Schr\"{o}dinger equation in quantum mechanics. The Schr\"{o}dinger principal component analysis can accurately estimate the factors even if the sample points are unequally spaced or in a small number, thus we can make efficient risk diversification. The proposed method was verified to outperform the conventional risk parity and other risk diversification portfolio constructions. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.09939&r= |
| By: | John Stachurski |
| Abstract: | Eisenberg and Noe (2001) analyze systemic risk for financial institutions linked by a network of liabilities. They show that the solution to their model is unique when the financial system is satisfies a regularity condition involving risk orbits. We show that this condition is not needed: a unique solution always exists. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.11183&r= |
| By: | Supriya Kapoor (Technological University Dublin); Adnan Velic (Technological University Dublin) |
| Abstract: | In the aftermath of the sub-prime mortgage bubble, the Federal Reserve implemented large scale asset purchase (LSAP) programmes that aimed to increase bank liquidity and lending. The excess liquidity created by quantitative easing (QE) in turn may have stimulated bank risk-taking in search of higher profits. Using comprehensive data on balance sheets, risk measures, and daily market returns in the U.S., we investigate the link between QE, bank risk-taking, profitability, and systemic risk. We find that, particularly during the third round of QE, banks that were more exposed to the unconventional monetary policy increased their risk-taking behavior and profitability. However, these banks also reduced their contribution to systemic risk indicating that the implementation of QE had an overall stabilizing effect on the banking sector. These results highlight the different distributional effects of QE. |
| Keywords: | large-scale asset purchases, quantitative easing, bank risk-taking, systemic risk, expected shortfall |
| JEL: | E52 E58 G21 |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:tcd:tcduee:tep0122&r= |
| By: | Victoria Dobrynskaya (National Research University Higher School of Economics); Mikhail Dubrovskiy (National Research University Higher School of Economics) |
| Abstract: | We consider a variety of cryptocurrency and equity risk factors as potential forces that drive cryptocurrency returns and carry risk premiums. In a cross-section of 2,000 biggest cryptocurrencies, only downside market risk, cryptocurrency size and policy uncertainty factors are systematically priced with significant premiums. Momentum premium has vanished in the recent years. Equity market risk, particularly equity downside market risk, appears to be more important than cryptocurrency market risk, suggesting greater linkages between cryptocurrency and equity markets than we used to think. Global and US equity factors are the most relevant for the cryptocurrency market |
| Keywords: | cryptocurrency, asset pricing; risk factors, factor models, alternative investments |
| JEL: | D14 G12 G15 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:hig:wpaper:86/fe/2022&r= |
| By: | Pavel V. Shevchenko (Department of Actuarial Studies and Business Analytics, Macquarie Business School, Macquarie University, Sydney NSW 2109, Australia; Center for Econometrics and Business Analytics, Saint-Petersburg State University, Russia); Jiwook Jang (Department of Actuarial Studies and Business Analytics, Macquarie Business School, Macquarie University, Sydney NSW 2109, Australia); Matteo Malavasi (Department of Actuarial Studies and Business Analytics, Macquarie Business School, Macquarie University, Sydney NSW 2109, Australia); Gareth W. Peters (Department of Statistics and Applied Probability, College of Letters and Science, University of California Santa Barbara, Santa Barbara, California 93106 USA); Georgy Sofronov (School of Mathematical and Physical Sciences, Faculty of Science and Engineering, Macquarie University, Sydney NSW 2109, Australia); Stefan Tr\"uck (Department of Actuarial Studies and Business Analytics, Macquarie Business School, Macquarie University, Sydney NSW 2109, Australia) |
| Abstract: | In this study we examine the nature of losses from cyber related events across different risk categories and business sectors. Using a leading industry dataset of cyber events, we evaluate the relationship between the frequency and severity of individual cyber-related events and the number of affected records. We find that the frequency of reported cyber related events has substantially increased between 2008 and 2016. Furthermore, the frequency and severity of losses depend on the business sector and type of cyber threat: the most significant cyber loss event categories, by number of events, were related to data breaches and the unauthorized disclosure of data, while cyber extortion, phishing, spoofing and other social engineering practices showed substantial growth rates. Interestingly, we do not find a distinct pattern between the frequency of events, the loss severity, and the number of affected records as often alluded to in the literature. We also analyse the severity distribution of cyber related events across all risk categories and business sectors. This analysis reveals that cyber risks are heavy-tailed, i.e., cyber risk events have a higher probability to produce extreme losses than events whose severity follows an exponential distribution. Furthermore, we find that the frequency and severity of cyber related losses exhibits a very dynamic and time varying nature. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.10189&r= |
| By: | Alhonita Yatie (BSE) |
| Abstract: | As the first crisis faced by Crypto-assets, Covid-19 updated the debate about their safehaven properties. Our paper tries to analyze the safe-haven properties of Crypto-assets and Gold for European assets. We find that Gold has not been more efficient than Cryptoassets (Tether, Cardano and Dogecoin) as safe-haven during the market crash due to Covid-19 in March 2020. We also found that during the study period Bitcoin, Ethereum, Litecoin and Ripple were just diversifiers for the European indices. Finally, Tether, Cardano and Dogecoin showed hedging properties like Gold before and after the market crash. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.10760&r= |
| By: | Джусангалиева Камилла // Jussangaliyeva Kamilla (National Bank of Kazakhstan); Миллер Алия // Miller Aliya (National Bank of Kazakhstan); Хакимжанов Сабит // Khakimzhanov Sabit (National Bank of Kazakhstan) |
| Abstract: | В этой статье анализируется казахстанская практика внедрения пруденциальных нормативов ликвидности (LCR и NSFR), рекомендованных Базельским комитетом по банковскому надзору (БКБН). В статье проводится анализ соответствия казахстанских нормативов стандартам Базеля, оценивается эффект альтернативных интерпретаций, обсуждается информативность и эффективность нормативов для отражения рисков фондирования и улучшения рыночных практик управления ликвидностью, их взаимодействие с другими нормативами и обусловленность регуляторной и конкурентной средой. // This paper analyzes Kazakhstan's practice of implementing prudential liquidity standards (LCR and NSFR) recommended by the Basel Committee on Banking Supervision (BCBS). The paper analyzes the compliance of Kazakhstan's standards with Basel standards, evaluates the effect of alternative interpretations, discusses the informativeness and effectiveness of standards to reflect funding risks and improve market liquidity management practices, their interaction with other standards and the conditionality of the regulatory and competitive environment. |
| Keywords: | риски ликвидности и фондирования, Базель III, показатели краткосрочной ликвидности и чистого стабильного финансирования (LCR, NSFR), liquidity and funding risks, Basel III, a liquidity coverage ratio and a net stable funding ratio, LCR, NSFR |
| JEL: | G01 G21 G28 G32 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:aob:wpaper:28&r= |
| By: | Thanasis Stengos (Department of Economics and Finance, University of Guelph, Guelph ON Canada); Theodore Panagiotidis (University of Macedonia); Georgios Papapanagiotou (University of Macedonia) |
| Abstract: | We perform a large-scale analysis to evaluate the performance of traditional and Markov-switching GARCH models for the volatility of 292 cryptocurrencies. For each cryptocurrency, we estimate a total of 27 alternative GARCH specifications. We consider models that allow up to three different regimes. First, the models are compared in terms of goodness-of-fit using the Deviance Information Criterion and the Bayesian Predictive Information Criterion. Next, we evaluate the ability of the models in forecasting one-day ahead conditional volatility and Value-at-Risk. The results indicate that for a wide range of cryptocurrencies, time-varying models outperform traditional ones. |
| Keywords: | Bitcoin, Cryptocurrency, Volatility, GARCH, Markov-switching, Information criteria |
| JEL: | C12 C13 C15 C22 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:gue:guelph:2022-02&r= |
| By: | Xu, Yongdeng (Cardiff Business School) |
| Abstract: | This paper proposes an Exponential HEAVY (EHEAVY) model. The model specifies the dynamics of returns and realized measures of volatility in an exponential form, which guarantees the positivity of volatility without restrictions on parameters and naturally allows the asymmetric effects. It provides a more flexible modelling of the volatility than the HEAVY models. A joint quasi-maximum likelihood estimation and closed form multi-step ahead forecasting is derived. The model is applied to 31 assets extracted from the Oxford-Man Institute's realized library. The empirical results show that the dynamic of return volatility is driven by the realized measure, while the asymmetric effect is captured by the return shock (not by the realized return shock). Hence, both return and realized measure are included in the return volatility equation. Out-of-sample forecast and portfolio exercise further shows the superior forecasting performance of the EHEAVY model, in both statistical and economic sense. |
| Keywords: | HEAVY model, High-frequency data, Asymmetric effects, Realized variance, Portfolio |
| JEL: | C32 C53 G11 G17 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:cdf:wpaper:2022/5&r= |
| By: | George-Marian Aevoae (Alexandru Ioan Cuza University - Faculty of Economics and Business Administration); Alin Marius Andries (Alexandru Ioan Cuza University of Iasi; Romanian Academy - Institute for Economic Forecasting); Steven Ongena (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; KU Leuven; NTNU Business School; Centre for Economic Policy Research (CEPR)); Nicu Sprincean (Alexandru Ioan Cuza University of Iasi) |
| Abstract: | How do changes in Environmental, Social and Governance (ESG) scores influence banks’ systemic risk contribution? We document a beneficial impact of the ESG Combined Score and Governance pillar on banks’ contribution to system-wide distress analysing a panel of 367 publicly listed banks from 47 countries over the period 2007-2020. Stakeholder theory and theory relating social performance to expected returns in which enhanced investments in corporate social responsibility mitigate bank specific risks explain our findings. However, only better corporate governance represents a tool in reducing bank interconnectedness and maintaining financial stability. A similar relationship for banks’ exposure to systemic risk is also found. Our findings stress the importance of integrating banks’ ESG disclosure into regulatory authorities’ supervisory mechanisms as qualitative information. |
| Keywords: | Systemic Risk; Financial Stability, Corporate Social Responsibility (CSR), Environmental, Social and Governance (ESG) Scores |
| JEL: | G01 G21 M14 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:chf:rpseri:rp2225&r= |
| By: | Florian Bourgey; Stefano De Marco; Emmanuel Gobet |
| Abstract: | We provide explicit approximation formulas for VIX futures and options in stochastic forward variance models, with particular emphasis on the family of so-called Bergomi models: the one-factor Bergomi model [Bergomi, Smile dynamics II, Risk, 2005], the rough Bergomi model [Bayer, Friz, and Gatheral, Pricing under rough volatility, Quantitative Finance, 16(6):887-904, 2016], and an enhanced version of the rough model that can generate realistic positive skew for VIX smiles - introduced simultaneously by De Marco [Bachelier World Congress, 2018] and Guyon [Bachelier World Congress, 2018] on the lines of [Bergomi, Smile dynamics III, Risk, 2008], that we refer to as "mixed rough Bergomi model". Following the methodology set up in [Gobet and Miri, Weak approximation of averaged diffusion processes. Stochastic Process. Appl., 124(1):475-504, 2014], we derive weak approximations for the law of the VIX random variable, leading to option price approximations under the form of explicit combinations of Black-Scholes prices and greeks. The new challenge we tackle is to handle the fractional integration kernel appearing in rough models and to deal with non-smooth payoffs. We stress that our approach does not rely on small-time asymptotics nor small-parameter (such as small volatility-of-volatility) asymptotics and can therefore be applied to any option maturity and a wide range of parameter configurations. Our results are illustrated by several numerical experiments and calibration tests to VIX market data. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.10413&r= |
| By: | Verena Monschang; Bernd Wilfling |
| Abstract: | We investigate mean-squared-forecast-error (MSE) accuracy improvements for linear-convex combination forecasts, whose components are pretreated by a procedure called 'Vector Autoregressive Forecast Error Modeling' (VAFEM). Assuming that the fore-cast-error series of the individual forecasts are governed by a stable VAR process under classic conditions, we obtain the following results: (i) VAFEM treatment bias-corrects all individual and linear-convex combination forecasts. (ii) Any VAFEM-treated combination has smaller theoretical MSE than its untreated analogue, if the VAR parameters are known. (iii) In empirical applications, VAFEM gains depend on (1) in-sample sizes, (2) out-of-sample forecast horizons, (3) the biasedness of the untreated forecast combination. We demonstrate the VAFEM capacity for realized-volatility forecasting, using S&P 500 data. |
| Keywords: | Combination forecasts, mean-squared-error loss, VAR forecast-error molding, multivariate least squares estimation |
| JEL: | C10 C32 C51 C53 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:cqe:wpaper:9722&r= |
| By: | German Rodikov; Nino Antulov-Fantulin |
| Abstract: | Volatility prediction for financial assets is one of the essential questions for understanding financial risks and quadratic price variation. However, although many novel deep learning models were recently proposed, they still have a "hard time" surpassing strong econometric volatility models. Why is this the case? The volatility prediction task is of non-trivial complexity due to noise, market microstructure, heteroscedasticity, exogenous and asymmetric effect of news, and the presence of different time scales, among others. In this paper, we analyze the class of long short-term memory (LSTM) recurrent neural networks for the task of volatility prediction and compare it with strong volatility-econometric models. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.11581&r= |
| By: | Christoph Carnehl; Johannes Schneider |
| Abstract: | We study the tradeoff between fundamental risk and time. A time-constrained agent has to solve a problem. She dynamically allocates effort between implementing a risky initial idea and exploring alternatives. Discovering an alternative implies progress that has to be converted to a solution. As time runs out, the chances of converting it in time shrink. We show that the agent may return to the initial idea after having left it in the past to explore alternatives. Our model helps explain so-called false starts. To finish fast, the agent delays exploring alternatives reducing the overall success probability. |
| Keywords: | dynamic problem solving, endogenous bandits, time pressure |
| JEL: | D01 D83 O31 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:bon:boncrc:crctr224_2022_342&r= |
| By: | Dorinel Bastide (UEVE - Université d'Évry-Val-d'Essonne, Université Paris-Saclay, LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - UEVE - Université d'Évry-Val-d'Essonne - ENSIIE - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, BNP-Paribas , Stress Testing Methodologies & Models - BNP-Paribas); Stéphane Crépey (LPSM (UMR_8001) - Laboratoire de Probabilités, Statistiques et Modélisations - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique - UP - Université de Paris, UFR 929 - Sorbonne Université - UFR de Mathématiques - SU - Sorbonne Université); Samuel Drapeau (University of Shanghai [Shanghai], Shanghai Jiaotong University, SAIF - Shanghai Advanced Institute of Finance); Mekonnen Tadese (Woldia University) |
| Abstract: | We present a one-period XVA model encompassing bilateral and centrally cleared trading in a unified framework with explicit formulas for most quantities at hand. We illustrate possible uses of this framework for running stress test exercises on a financial network from a clearing member's perspective or for optimizing the porting of the portfolio of a defaulted clearing member. |
| Date: | 2022–02–11 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03554577&r= |
| By: | David Dillenberger (University of Pennsylvania); Daniel Gottlieb (London School of Economics); Pietro Ortoleva (Princeton University) |
| Abstract: | We study how the separation of time and risk preferences relates to a behavioral property that generalizes impatience to stochastic environments: Stochastic Impatience. We show that, within a broad class of models, Stochastic Impatience holds if and only if risk aversion is "not too high" relative to the inverse elasticity of intertemporal substitution. This result has implications for many known models. For example, for those of Epstein and Zin (1989) and Hansen and Sargent (1995), Stochastic Impatience is violated for all commonly used parameters. |
| Keywords: | Stochastic Impatience, Epstein-Zin preferences, Separation of Time and Risk preferences, Risk Sensitive preferences, Non-Expected Utility |
| JEL: | D81 D90 G11 E7 |
| Date: | 2020–04 |
| URL: | http://d.repec.org/n?u=RePEc:pri:econom:2020-54&r= |
| By: | Toshiko Matsui; Ali Al-Ali; William J. Knottenbelt |
| Abstract: | This paper examines the determinants of the volatility of futures prices and basis for three commodities: gold, oil and bitcoin -- often dubbed solid, liquid and digital gold -- by using contract-by-contract analysis which has been previously applied to crude oil futures volatility investigations. By extracting the spot and futures daily prices as well as the maturity, trading volume and open interest data for the three assets from 18th December 2017 to 30th November 2021, we find a positive and significant role for trading volume and a possible negative influence of open interest, when significant, in shaping the volatility in all three assets, supporting earlier findings in the context of oil futures. Additionally, we find maturity has a relatively positive significance for bitcoin and oil futures price volatility. Furthermore, our analysis demonstrates that maturity affects the basis of bitcoin and gold positively -- confirming the general theory that the basis converges to zero as maturity nears for bitcoin and gold -- while oil is affected in both directions. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.09845&r= |
| By: | Lin Qi |
| Abstract: | This paper discusses the role that stock market volatility plays in the linkages between the U.S. stock and Treasury bond markets through liquidity under different regimes of investor sentiment in a threshold vector autoregression model. The baseline analysis shows that the interaction between volatility and illiquidity dynamics coincides with the flight-to-safety phenomenon. Moreover, the empirical evidence in the high investor sentiment regime points to the potential existence of flight-from-maturity where market participants tend to shorten their lending maturities for precautionary purposes. This result is robust under either an exogenously or an endogenously chosen investor sentiment threshold value. Further analysis verifies this relationship in the period after the Global Financial Crisis (GFC) and finds evidence of flight-from-maturity in the medium-term and the short-term bond markets. Finally, this paper finds that an adverse stock market volatility shock increases the probability of moving from a high sentiment to a low sentiment regime. This probability gets higher in the post-GFC era. |
| Keywords: | Liquidity, Flight-from-maturity, Flight-to-safety |
| JEL: | G10 G12 G40 C32 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:een:camaaa:2022-24&r= |
| By: | Gérard Mondello (UCA - Université Côte d'Azur) |
| Abstract: | The amendments made to CERCLA in 1996 reinforced the exemption of lenders that finance ultra-hazardous activities. Then, they become involved in liability only if they manage or own polluting activities. The paper compares strict liability and negligence rule in an agency model of vicarious liability type, and proposes to restore lenders as principal by applying negligence rules to them while operators would resort to a strict liability rule. This scheme leads the lender to propose to the borrower the most favorable loan level that induces the latter to provide the socially optimal security level. |
| Keywords: | risky activities.,lenders,judgment-proof,moral hazard,negligence rule,Strict liability,Negligence Rule,Strict Liability,ASYMETRIC INFORMATION,TORT LAW,CERCLA,Lenders,Banks |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-03502693&r= |
| By: | Avezum, Lucas (Tilburg University, School of Economics and Management) |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:tiu:tiutis:ecf0bc59-8366-46c4-bdfa-8f09123dcaee&r= |
| By: | Taiga Saito (Graduate School of Economics, The University of Tokyo); Akihiko Takahashi (Graduate School of Economics, The University of Tokyo) |
| Abstract: | This paper considers a new problem for portfolio optimization with a choice of a probability measure, particularly optimal investment problem under sentiments. Firstly, we formulate the problem as a sup-sup-inf problem consisting of optimal investment and a choice of a probability measure expressing aggressive and conservative attitudes of the investor. This problem also includes the case where the agent has conservative and neutral views on risks represented by Brownian motions and degrees of conservativeness differ among the risk. Secondly, we obtain an expression of the volatility process of a backward stochastic differential equation related to the conservative sentiment in order to investigate cases where the sup-sup-inf problem is solved. Specifically, we take a Malliavin calculus approach to solve the problem and obtain an optimal portfolio process. Finally, we provide an expression of the optimal portfolio under the sentiments in two examples with stochastic uncertainties in an exponential utility case and investigate the impact of the sentiments on the portfolio process. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:cfi:fseres:cf534&r= |
| By: | Zexuan Yin; Paolo Barucca |
| Abstract: | We propose Neural GARCH, a class of methods to model conditional heteroskedasticity in financial time series. Neural GARCH is a neural network adaptation of the GARCH 1,1 model in the univariate case, and the diagonal BEKK 1,1 model in the multivariate case. We allow the coefficients of a GARCH model to be time varying in order to reflect the constantly changing dynamics of financial markets. The time varying coefficients are parameterised by a recurrent neural network that is trained with stochastic gradient variational Bayes. We propose two variants of our model, one with normal innovations and the other with Students t innovations. We test our models on a wide range of univariate and multivariate financial time series, and we find that the Neural Students t model consistently outperforms the others. |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.11285&r= |
| By: | Imane Ouadghiri; Mathieu Gomes (CleRMa - Clermont Recherche Management - ESC Clermont-Ferrand - École Supérieure de Commerce (ESC) - Clermont-Ferrand - UCA [2017-2020] - Université Clermont Auvergne [2017-2020]); Jonathan Peillex; Guillaume Pijourlet |
| Abstract: | This study investigates whether investor attention to the fossil fuel divestment (FFD) movement is related to the stock returns of firms involved in extracting fossil fuels. We consider three complementary indicators of investor attention to the FFD movement: (1) the US weekly Google Search Volume Index on the topic "fossil fuel divestment," (2) the US weekly media coverage of fossil fuel divestment, and (3) the number of weekly visits to the "fossil fuel divestment" page on Wikipedia. Based on a sample of weekly returns on 1,850 US firms over the period 2012-2020, our econometric estimations report a positive relationship between investor attention to FFD and excess stock returns for US fossil fuel-related firms. Therefore, contrary to what the FFD campaigners might expect, the stigmatization of the fossil fuel industry does not drive down the stock returns on fossil fuel-related firms. |
| Keywords: | fossil fuel-related firms,investor attention,stock returns,fossil fuel divestment |
| Date: | 2022–01–29 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03549713&r= |