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on Risk Management |
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Issue of 2021‒03‒22
nineteen papers chosen by |
| By: | Patrick S. Hagan; Andrew Lesniewski; Georgios E. Skoufis; Diana E. Woodward |
| Abstract: | We argue that using the Shapley value of cooperative game theory as the scheme for risk allocation among non-orthogonal risk factors is a natural way of interpreting the contribution made by each of such factors to overall portfolio risk. We discuss a Shapley value scheme for allocating risk to non-orthogonal greeks in a portfolio of derivatives. Such a situation arises, for example, when using a stochastic volatility model to capture option volatility smile. We also show that Shapley value allows for a natural method of interpreting components of enterprise risk measures such as VaR and ES. For all applications discussed, we derive explicit formulas and / or numerical algorithms to calculate the allocations. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.05453&r=all |
| By: | G\'abor Papp; Imre Kondor; Fabio Caccioli |
| Abstract: | Expected Shortfall (ES), the average loss above a high quantile, is the current financial regulatory market risk measure. Its estimation and optimization are highly unstable against sample fluctuations and become impossible above a critical ratio $r=N/T$, where $N$ is the number of different assets in the portfolio, and $T$ is the length of the available time series. The critical ratio depends on the confidence level $\alpha$, which means we have a line of critical points on the $\alpha-r$ plane. The large fluctuations in the estimation of ES can be attenuated by the application of regularizers. In this paper, we calculate ES analytically under an $\ell_1$ regularizer by the method of replicas borrowed from the statistical physics of random systems. The ban on short selling, i.e. a constraint rendering all the portfolio weights non-negative, is a special case of an asymmetric $\ell_1$ regularizer. Results are presented for the out-of-sample and the in-sample estimator of the regularized ES, the estimation error, the distribution of the optimal portfolio weights and the density of the assets eliminated from the portfolio by the regularizer. It is shown that the no-short constraint acts as a high volatility cutoff, in the sense that it sets the weights of the high volatility elements to zero with higher probability than those of the low volatility items. This cutoff renormalizes the aspect ratio $r=N/T$, thereby extending the range of the feasibility of optimization. We find that there is a nontrivial mapping between the regularized and unregularized problems, corresponding to a renormalization of the order parameters. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.04375&r=all |
| By: | Raymond C. W. Leung; Yu-Man Tam |
| Abstract: | How to hedge factor risks without knowing the identities of the factors? We first prove a general theoretical result: even if the exact set of factors cannot be identified, any risky asset can use some portfolio of similar peer assets to hedge against its own factor exposures. A long position of a risky asset and a short position of a "replicate portfolio" of its peers represent that asset's factor residual risk. We coin the expected return of an asset's factor residual risk as its Statistical Arbitrage Risk Premium (SARP). The challenge in empirically estimating SARP is finding the peers for each asset and constructing the replicate portfolios. We use the elastic-net, a machine learning method, to project each stock's past returns onto that of every other stock. The resulting high-dimensional but sparse projection vector serves as investment weights in constructing the stocks' replicate portfolios. We say a stock has high (low) Statistical Arbitrage Risk (SAR) if it has low (high) R-squared with its peers. The key finding is that "unique" stocks have both a higher SARP and higher excess returns than "ubiquitous" stocks: in the cross-section, high SAR stocks have a monthly SARP (monthly excess returns) that is 1.101% (0.710%) greater than low SAR stocks. The average SAR across all stocks is countercyclical. Our results are robust to controlling for various known priced factors and characteristics. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.09987&r=all |
| By: | Yuan Hu; W. Brent Lindquist |
| Abstract: | This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize expected tail loss and investigate both asset allocation (AA) and the selection effect (SE) as hard constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index; the benchmark is an equi-weighted portfolio of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures maximum drawdown, Sharpe ratio, and Rachev ratio. The results suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE, with SE constraints producing the larger performance enhancement. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.04432&r=all |
| By: | Michel Alexandre; Kau\^e Lopes de Moraes; Francisco Aparecido Rodrigues |
| Abstract: | The purpose of this paper is to calculate the risk-dependent centrality (RDC) of the Brazilian stock market. We computed the RDC for assets traded on the Brazilian stock market between January 2008 to June 2020 at different levels of external risk. We observed that the ranking of assets based on the RDC depends on the external risk. Rankings' volatility is related to crisis events, capturing the recent Brazilian economic-political crisis. Moreover, we have found a negative correlation between the average volatility of assets' ranking based on the RDC and the average daily returns on the stock market. It goes in hand with the hypothesis that the rankings' volatility is higher in periods of crisis. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.09059&r=all |
| By: | Caterina Mendicino (European Central Bank); Kalin Nikolov (European Central Bank); Juan Rubio-Ramirez (Emory University); Javier Suarez (CEMFI, Centro de Estudios Monetarios y Financieros); Dominik Supera (Wharton School) |
| Abstract: | We study the interaction between borrowers' and banks' solvency in a quantitative macroeconomic model with financial frictions in which bank assets are a portfolio of defaultable loans. We show that ex-ante imperfect diversification of bank lending generates bank asset returns with limited upside but significant downside risk. The asymmetric distribution of these returns and their implications for the evolution of bank net worth are important for capturing the frequency and severity of twin default crises - simultaneous rises in firm and bank defaults associated with sizeable negative effects on economic activity. As a result, our model implies higher optimal capital requirements than common specifications of bank asset returns, which neglect or underestimate the impact of borrower default on bank solvency. |
| Keywords: | Bank default, firm default, financial crises, bank capital requirements. |
| JEL: | G01 G28 E44 |
| Date: | 2020–06 |
| URL: | http://d.repec.org/n?u=RePEc:cmf:wpaper:wp2020_2006&r=all |
| By: | Hyunsu Kim |
| Abstract: | This paper introduces a potential application of deep learning and artificial intelligence in finance, particularly its application in hedging. The major goal encompasses two objectives. First, we present a framework of a direct policy search reinforcement agent replicating a simple vanilla European call option and use the agent for the model-free delta hedging. Through the first part of this paper, we demonstrate how the RNN-based direct policy search RL agents can perform delta hedging better than the classic Black-Scholes model in Q-world based on parametrically generated underlying scenarios, particularly minimizing tail exposures at higher values of the risk aversion parameter. In the second part of this paper, with the non-parametric paths generated by time-series GANs from multi-variate temporal space, we illustrate its delta hedging performance on various values of the risk aversion parameter via the basic RNN-based RL agent introduced in the first part of the paper, showing that we can potentially achieve higher average profits with a rather evident risk-return trade-off. We believe that this RL-based hedging framework is a more efficient way of performing hedging in practice, addressing some of the inherent issues with the classic models, providing promising/intuitive hedging results, and rendering a flexible framework that can be easily paired with other AI-based models for many other purposes. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.03913&r=all |
| By: | Paddrick, Mark; Young, H. Peyton |
| Abstract: | We propose a general framework for estimating the vulnerability to default by a central counterparty (CCP) in the credit default swaps market. Unlike conventional stress testing approaches, which estimate the ability of a CCP to withstand nonpayment by its two largest counterparties, we study the direct and indirect effects of nonpayment by members and/or their clients through the full network of exposures. We illustrate the approach for the U.S. credit default swaps market under shocks that are similar in magnitude to the Federal Reserve’s stress tests. The analysis indicates that conventional stress testing approaches may underestimate the potential vulnerability of the main CCP for this market. |
| Keywords: | credit default swaps; central counterparties; stress testing; systemic risk; financial networks |
| JEL: | D85 L14 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:101170&r=all |
| By: | Viral V. Acharya; Robert F. Engle III; Sascha Steffen |
| Abstract: | We study the crash of bank stock prices during the COVID-19 pandemic. We find evidence consistent with a “credit line drawdown channel”. Stock prices of banks with large ex-ante exposures to undrawn credit lines as well as large ex-post gross drawdowns decline more. The effect is attenuated for banks with higher capital buffers. These banks reduce term loan lending, even after policy measures were implemented. We conclude that bank provision of credit lines appears akin to writing deep out-of-the-money put options on aggregate risk; we show how the resulting contingent leverage and stock return exposure can be incorporated tractably into bank capital stress tests. |
| JEL: | G01 G21 |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:28559&r=all |
| By: | Michael Krisper |
| Abstract: | In this paper, we discuss various problems in the usage and definition of risk matrices. We give an overview of the general process of risk assessment with risk matrices and ordinal scales. Furthermore, we explain the fallacies in each phase of this process and give hints on which decisions may lead to more problems than others and how to avoid them. Among those 24 discussed problems are ordinal scales, semi-quantitative arithmetics, range compression, risk inversion, ambiguity, and neglection of uncertainty. Finally, we make a case for avoiding risk matrices altogether and instead propose using fully quantitative risk assessment methods. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.05440&r=all |
| By: | Nicole B\"auerle; Gregor Leimcke |
| Abstract: | Major events like natural catastrophes or the COVID-19 crisis have impact both on the financial market and on claim arrival intensities and claim sizes of insurers. Thus, when optimal investment and reinsurance strategies have to be determined it is important to consider models which reflect this dependence. In this paper we make a proposal how to generate dependence between the financial market and claim sizes in times of crisis and determine via a stochastic control approach an optimal investment and reinsurance strategy which maximizes the expected exponential utility of terminal wealth. Moreover, we also allow that the claim size distribution may be learned in the model. We give comparisons and bounds on the optimal strategy using simple models. What turns out to be very surprising is that numerical results indicate that even a minimal dependence which is created in this model has a huge impact on the control in the sense that the insurer is much more prudent then. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.05777&r=all |
| By: | Colombo, Jefferson A.; Cruz, Fernando I. L.; Paese, Luis H. Z.; Cortes, Renan X. |
| Abstract: | Using a sample of 21 developing and developed countries, we analyze whether a welldiversified investor of traditional assets (stocks, bonds, real estate, and commodities) may benefit from investing in cryptocurrencies. Country-specific analyses indicate that cryptocurrencies usually fit in the tangent portfolio (maximum Sharpe ratio) but no – or very little – in the minimum variance portfolio (MVP). Out-of-sample analysis indicates that even global portfolios that already benefits from international diversification may enjoy investing marginally in cryptocurrencies: mean-variance optimal and naive with cryptocurrencies outperformed otherwise identical portfolios in terms of risk-adjusted returns. Besides, exchange rate movements do not drive this better performance – it occurs for both local (all returns denominated in the local currency) and global perspectives (all returns in U.S. Dollars). We also find that cryptocurrencies’ diversification benefits occur both before and after the COVID-19 pandemics, with the 1/N portfolio with cryptocurrencies presenting the higher risk-adjusted returns. Our paper adds to the literature by analyzing the marginal effects of adding cryptocurrencies on a sample of developing and developed economies and considering up-to-date data following the COVID-19 crisis. |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:fgv:eesptd:542&r=all |
| By: | Baishuai Zuo; Chuancun Yin |
| Abstract: | In this paper, the multivariate tail covariance (MTCov) for generalized skew-elliptical distributions is considered. Some special cases for this distribution, such as generalized skew-normal, generalized skew student-t, generalized skew-logistic and generalized skew-Laplace distributions, are also considered. In order to test the theoretical feasibility of our results, the MTCov for skewed and non skewed normal distributions are computed and compared. Finally, we give a special formula of the MTCov for generalized skew-elliptical distributions. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.05201&r=all |
| By: | Mykola Babiak; Jozef Barunik |
| Abstract: | We examine the pricing of a horizon specific uncertainty network risk, extracted from option implied variances on exchange rates, in the cross-section of currency returns. Buying currencies that are receivers and selling currencies that are transmitters of short-term shocks exhibits a high Sharpe ratio and yields a significant alpha when controlling for standard dollar, carry trade, volatility, variance risk premium and momentum strategies. This profitability stems primarily from the causal nature of shock propagation and not from contemporaneous dynamics. Shock propagation at longer horizons is priced less, indicating a downward-sloping term structure of uncertainty network risk in currency markets. |
| Keywords: | foreign exchange rates; network risk; currency variance; predictability; term structure; |
| JEL: | G12 G15 F31 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:cer:papers:wp687&r=all |
| By: | Josselin Garnier |
| Abstract: | This paper is directed to the financial community and focuses on the financial risks associated with climate change. It, specifically, addresses the estimate of climate risk embedded within a bank loan portfolio. During the 21st century, man-made carbon dioxide emissions in the atmosphere will raise global temperatures, resulting in severe and unpredictable physical damage across the globe. Another uncertainty associated with climate, known as the energy transition risk, comes from the unpredictable pace of political and legal actions to limit its impact. The Climate Extended Risk Model (CERM) adapts well known credit risk models. It proposes a method to calculate incremental credit losses on a loan portfolio that are rooted into physical and transition risks. The document provides detailed description of the model hypothesis and steps. This work was initiated by the association Green RWA (Risk Weighted Assets). It was written in collaboration with Jean-Baptiste Gaudemet, Anne Gruz, and Olivier Vinciguerra (cerm@greenrwa.org), who contributed their financial and risk expertise, taking care of its application to a pilot-portfolio. It extends the model proposed in a first white paper published by Green RWA (https://www.greenrwa.org/). |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.03275&r=all |
| By: | Guohui Guan; Zongxia Liang; Yi xia |
| Abstract: | In this paper, we investigate the optimal management of defined contribution (abbr. DC) pension plan under relative performance ratio and Value-at-Risk (abbr. VaR) constraint. Inflation risk is introduced in this paper and the financial market consists of cash, inflation-indexed zero coupon bond and a stock. The goal of the pension manager is to maximize the performance ratio of the real terminal wealth under VaR constraint. An auxiliary process is introduced to transform the original problem into a self-financing problem first. Combining linearization method, Lagrange dual method, martingale method and concavification method, we obtain the optimal terminal wealth under different cases. For convex penalty function, there are fourteen cases while for concave penalty function, there are six cases. Besides, when the penalty function and reward function are both power functions, the explicit forms of the optimal investment strategies are obtained. Numerical examples are shown in the end of this paper to illustrate the impacts of the performance ratio and VaR constraint. |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2103.04352&r=all |
| By: | Muhammad Arif; Muhammad Abubakr Naeem; Saqib Farid; Rabindra Nepal; Tooraj Jamasb |
| Abstract: | Against the backdrop of the Covid-19 pandemic, this study explores the hedging and safe-haven potential of green bonds for conventional equity, fixed income, commodity, and forex investments. We use the cross-quantilogram approach that provides a better understanding of the dynamic relationship between assets under different market conditions. Our full sample results show that the green bond index could serve as a diversifier asset for medium- and long-term equity investors. Besides, it can also serve as a hedging and safe haven instrument for currency and commodity investments. Moreover, the sub-sample analysis of the pandemic crisis period shows a heightened short- and medium-term lead-lag association between the green bond index and conventional investment returns. However, the green bond index emerges as a significant hedging and safe-haven asset for the long-term investors of conventional financial assets. Our results offer insights for long-term investors whose portfolios comprise conventional assets such as equities, commodities, forex, and fixed income securities. Further, our findings reveal the potential role that the green bond investments could play in global financial recovery efforts without compromising the low-carbon transition targets. |
| Keywords: | Green bonds, hedge, safe-haven, cross-quantilogram, COVID-19 |
| JEL: | G10 G11 G19 Q01 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:een:camaaa:2021-20&r=all |
| By: | Delis, Manthos; Iosifidi, Maria; Hasan, Iftekhar; Tsoumas, Chris |
| Abstract: | We contend that economic preferences over risk-taking in different subnational regions worldwide affect fundamental aspects of firms’ corporate financing, namely financing costs and capital structure. We study this hypothesis, by hand-matching firms’ regions worldwide with the corresponding regional economic risk-taking preferences. Our baseline results show that credit and bond pricing increase with higher risk-taking preferences, whereas such preferences yield lower ratios of book leverage and short-term debt. We backup our baseline results with an instrumental variables approach, which is based on the premise that high-yield agricultural societies in the pre-industrial era exhibit low risk-taking preferences. |
| Keywords: | Economic preferences; Risk-taking; Financing costs; Loan spreads; Bond spreads; Capital structure |
| JEL: | G21 G32 Z13 |
| Date: | 2021–02–27 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:106321&r=all |
| By: | Bianchi, Benedetta |
| Abstract: | This paper is a first attempt to include credit derivatives in international macro-financial analysis. We document that gross credit derivatives holdings map to bilateral portfolio investment linkages. On a net basis, our results suggest an asymmetry between sectors and between net buyers and net sellers of CDSs. When a banking system is a net buyer of protection, the protection purchased is proportional to the debt securities held. Conversely, when a banking system is a net seller, the protection sold is proportional to the securities held. For investment funds, we find no aggregate relation between net CDSs and the debt securities held. JEL Classification: F34, F21 |
| Keywords: | CDS, cross-border positions, EMIR data, risk transfer |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:srk:srkwps:2021115&r=all |