nep-fmk New Economics Papers
on Financial Markets
Issue of 2021‒03‒22
thirteen papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. Why Did Bank Stocks Crash During COVID-19? By Viral V. Acharya; Robert F. Engle III; Sascha Steffen
  2. The Liquidity and Sustainability Facility for African Sovereign Bonds: a good ECA/PIMCO idea whose time has come? By Gabor, Daniela
  3. "Rethinking Asset Pricing with Quantile Factor Models". By Jorge M. Uribe; Montserrat Guillen; Xenxo Vidal-Llana
  4. High-Frequency Trading and Price Informativeness By Jasmin Gider; Simon N. M. Schmickler; Christian Westheide
  5. Leveraged ETF Investing By Tal Miller
  6. Asset Bubbles and Product Market Competition By Francisco Queirós
  7. Portfolio risk allocation through Shapley value By Patrick S. Hagan; Andrew Lesniewski; Georgios E. Skoufis; Diana E. Woodward
  8. Stock Market Beliefs and Portfolio Choice in the General Population By Christian Zimpelmann
  9. Procyclical asset management and bond risk premia By Barbu, Alexandru; Fricke, Christoph; Moench, Emanuel
  10. Predicting the Behavior of Dealers in Over-The-Counter Corporate Bond Markets By Yusen Lin; Jinming Xue; Louiqa Raschid
  11. The Welfare Cost of Ignoring the Beta By Gollier, Christian
  12. Optimizing Expected Shortfall under an $\ell_1$ constraint -- an analytic approach By G\'abor Papp; Imre Kondor; Fabio Caccioli
  13. Risk-dependent centrality in the Brazilian stock market By Michel Alexandre; Kau\^e Lopes de Moraes; Francisco Aparecido Rodrigues

  1. 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
  2. By: Gabor, Daniela
    Abstract: This paper maps the balance of benefits and risks underpinning the ECA/PIMCO proposal for a Liquidity and Sustainability Facility that would provide “concessional” repo financing to private investors in African sovereign bonds. In market speak, investors would finance their African sovereign debt holdings with LSF repo loans. The brief first examines the macrofinancial risks for African government bond issuers and for central banks that the LSF repo instrument engenders, as well as the developmental impact of a private-finance-led development paradigm that seeks the structural transformation of local financial systems towards bond-based finance. It then fleshes out the “Reform” and “Rethink” approaches to the ECA/PIMCO proposal. A reform of the institutional design of the LSF can minimise these macrofinancial risks. The Rethink approach in turn maps out alternative development pathways that prioritise local development banking instead of bond finance.
    Date: 2021–01–25
  3. By: Jorge M. Uribe (Universitat Oberta de Catalunya.); Montserrat Guillen (Universitat de Barcelona.); Xenxo Vidal-Llana (Universitat de Barcelona.)
    Abstract: Traditional empirical asset pricing focuses on the average cases. We propose a new approach to analyze the cross-section of the returns. We test the predictive power of market-beta, size, book-to-market ratio, profitability, investment, momentum, and liquidity, across the whole conditional distribution of market returns. Our results indicate that the relevant characteristics to explain the winners’ tail, the losers’ tail and the center of the distribution, in a given period, differ. Indeed, some characteristics can be discarded from our specification if our main interest is to model expected extreme losses (such as traditional momentum), and some others should be kept even if they do not seem particularly significant for the average scenario, because they become significant at the tails (such as size). Book-to-market is mainly a left tail factor, in the sense that it explains to a greater extent the loser’s tail than either the center or the tail of the winners. On the contrary, liquidity and investment are right-tail factors, because they explain in greater proportion the winners’ tail than the rest of the distribution. Market beta is relevant throughout the whole cross-section, but affect winners and losers in diametrically opposite ways (the effect is positive on the right tail and negative on the left tail). We show that the practice of adding characteristics to our pricing equation should be clearly informed by our particular interests regarding the cross-sectional distribution of the returns, that is, whether we are more interested in a certain fragment of the distribution than in other parts. Our results emphasize the need to consider carefully what factors to include in the pricing equation, which depends on the dynamics that one wants to understand and even on one attitude towards risk. In short, not all factors serve all purposes.
    Keywords: Factor models, Asset characteristics, Tail-risks, Quantile regression. JEL classification: G1, G11, G12, C38.
    Date: 2021–03
  4. By: Jasmin Gider; Simon N. M. Schmickler; Christian Westheide
    Abstract: We study how stock price informativeness changes with the presence of high-frequency trading (HFT). Our estimate is based on the staggered start of HFT participation in a panel of international exchanges. With HFT presence market prices are a less reliable predictor of future cash flows and investment, even more so for longer horizons. Further, idiosyncratic volatility decreases, mutual funds trade less actively and their holdings deviate less from the market-capitalization weighted portfolio. These findings suggest that price informativeness declines with HFT presence, consistent with theoretical models of HFTs' ability to anticipate informed order flow, reducing incentives to acquire fundamental information.
    Keywords: High-Frequency Trading, Price Efficiency, Information Acquisition, Information Production
    JEL: G10 G14
    Date: 2021–01
  5. By: Tal Miller
    Abstract: It is common knowledge that leverage can increase the potential returns of an investment, at the expense of increased risk. For a passive investor in the stock market, leverage can be achieved using margin debt or leveraged-ETFs. We perform bootstrapped Monte-Carlo simulations of leveraged (and unleveraged) mixed portfolios of stocks and bonds, based on past stock market data, and show that leverage can amplify the potential returns, without significantly increasing the risk for long-term investors.
    Date: 2021–03
  6. By: Francisco Queirós (Università di Napoli Federico II and CSEF)
    Abstract: This paper studies the interactions between asset bubbles and competition. I first document a negative industrylevel relationship between measures of stock market overvaluation and indicators of market power: larger overvaluation is associated with an increase in the number of firms, lower markups and a higher probability of negative earnings. I then construct multi-industry growth model featuring imperfect competition and rational bubbles that sheds light on these findings. By providing an entry or production subsidy, bubbles stimulate competition and reduce monopoly rents. When they are sufficiently large they can, however, lead to excessive entry and competition. I also show that imperfect competition depresses the interest rate, thereby relaxing the conditions for the emergence of rational bubbles.
    Keywords: Rational Bubbles, Competition, Market Power, British Railway Mania, Dotcom Bubble
    JEL: E44 L13 L16
    Date: 2021–03–17
  7. 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
  8. By: Christian Zimpelmann
    Abstract: The amount of risk that households take when investing their savings has long-term consequences for their financial well-being. However, a substantial share of observed heterogeneity in financial risk-taking remains unexplained by factors like risk aversion and wealth levels. This study explores whether subjective beliefs about stock market returns can close this knowledge gap. I make use of a unique data set that comprises incentivized, repeated elicitations of stock market beliefs and high-quality administrative asset data for a probability-based population sample. Households with more optimistic stock market expectations hold more risk in their portfolio, where the effect size is about half of the effect size of risk aversion. Furthermore, changes in expectations over time are related to changes in portfolio risk, which demonstrates that cross-sectional correlations are not driven by a time-invariant third variable. The results suggest that stock market expectations are an important component of portfolio choice. More generally, the study shows that subjective beliefs can be reliably measured in surveys and are related to actual high-stakes decisions.
    Keywords: Surveys, Subjective Expectations, Behavioral Finance, Household Finance
    JEL: D14 D84 E21 G11 G4 G5
    Date: 2021–01
  9. By: Barbu, Alexandru; Fricke, Christoph; Moench, Emanuel
    Abstract: We use unique institutional securities holdings data to examine the trading behaviour of delegated institutional capital and its impact on bond risk premia. We show that institutional fund managers trade strongly procyclically: they actively move into higher yielding, longer duration and lower rated securities as yields fall and spreads compress, and vice versa. Funds more exposed to negative yields increase their risk-taking more strongly, and this effect is particularly pronounced for those offering explicit minimum return guarantees. Institutional funds' investments have large and persistent price impact in both corporate and sovereign bond markets. We provide evidence that this procyclical behaviour is driven by career concerns among institutional fund managers. JEL Classification: G11, G23, E43
    Keywords: asset price volatility, career concerns, demand pressures, institutional accounts, institutional funds, portfolio rebalancing, price impact, procyclical asset management
    Date: 2021–03
  10. By: Yusen Lin; Jinming Xue; Louiqa Raschid
    Abstract: Trading in Over-The-Counter (OTC) markets is facilitated by broker-dealers, in comparison to public exchanges, e.g., the New York Stock Exchange (NYSE). Dealers play an important role in stabilizing prices and providing liquidity in OTC markets. We apply machine learning methods to model and predict the trading behavior of OTC dealers for US corporate bonds. We create sequences of daily historical transaction reports for each dealer over a vocabulary of US corporate bonds. Using this history of dealer activity, we predict the future trading decisions of the dealer. We consider a range of neural network-based prediction models. We propose an extension, the Pointwise-Product ReZero (PPRZ) Transformer model, and demonstrate the improved performance of our model. We show that individual history provides the best predictive model for the most active dealers. For less active dealers, a collective model provides improved performance. Further, clustering dealers based on their similarity can improve performance. Finally, prediction accuracy varies based on the activity level of both the bond and the dealer.
    Date: 2021–03
  11. By: Gollier, Christian
    Abstract: Because of risk aversion, any sensible investment valuation system should value less projects that contribute more to the aggregate risk, i.e., that have a larger income elasticity of net benefits. In theory, this is done by adjusting discount rates to consumption betas. But in reality, for various reasons (Arrow-Lind and WACC fallacies, market failures), most public and private institutions and people use a discount rate that is rather insensitive to the risk profile of their investment projects. I show in this paper that the economic consequences of the implied misallocation of capital are dire. To do this, I calibrate a Lucas model in which the investment opportunity set contains a myriad of projects with different expected returns and risk profiles. The welfare loss of using a single discount rate is equivalent to a permanent reduction in consumption that lies somewhere between 15% and 45%, depending upon which familiar discounting system is used. Economists should devote more energy to support a reform of public discounting systems in favor of what has been advocated by the normative interpretation of modern asset pricing theories over the last four decades.
    Keywords: Risk and Uncertainty
    Date: 2021–03–16
  12. 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
  13. 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

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