nep-fmk New Economics Papers
on Financial Markets
Issue of 2020‒06‒15
fifteen papers chosen by

  1. When Selling Becomes Viral: Disruptions in Debt Markets in the COVID-19 Crisis and the Fed’s Response By Valentin Haddad; Alan Moreira; Tyler Muir
  2. Market shocks and professionals' investment behavior - Evidence from the COVID-19 crash By Christoph Huber; Jürgen Huber; Michael Kirchler
  3. Stock return comovement when investors are distracted: more, and more homogeneous By Ehrmann, Michael; Jansen, David-Jan
  4. Zeroing in on the Expected Returns of Anomalies By Andrew Y. Chen; Mihail Velikov
  5. Equity Financing Risk By Mamdouh Medhat; Berardino Palazzo
  6. Burned by leverage? Flows and fragility in bond mutual funds By Molestina Vivar, Luis; Wedow, Michael; Weistroffer, Christian
  7. Monitoring the Liquidity Profile of Mutual Funds By Sirio Aramonte; Chiara Scotti; Ilknur Zer
  8. On bid and ask side-specific tick sizes By Baldacci Bastien; Bergault Philippe; Derchu Joffrey; Rosenbaum Mathieu
  9. Capital market liberalization and equity market interdependence By Renée Fry-McKibbin; Ziyu Yan
  10. Applications of Machine Learning to Estimating the Sizes and Market Impact of Hidden Orders in the BRICS Financial Markets By Maake, Witness; Van Zyl, Terence
  11. Deep Learning for Portfolio Optimisation By Zihao Zhang; Stefan Zohren; Stephen Roberts
  12. Dynamic Spillovers between REITs and Stock Markets in Global Financial Markets By Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge
  13. The Extended Holiday Effect on US capital market By Dumitriu, Ramona; Stefanescu, Răzvan
  14. Canadian Financial Stress and Macroeconomic Conditions By Thibaut Duprey
  15. Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets By Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge; Uribe, Jorge M.

  1. By: Valentin Haddad; Alan Moreira; Tyler Muir
    Abstract: We study disruptions in debt markets during the COVID-19 crisis. The safer end of the credit spectrum experienced significant losses that are hard to fully reconcile with standard default or risk premium channels. Corporate bonds traded at a large discount to their corresponding CDS, and this basis widened most for safer bonds. Liquid bond ETFs traded at a large discount to their NAV, more so for Treasuries, municipal bonds, and investment-grade corporate than high-yield corporate. These facts suggest investors tried to sell safer, more liquid securities to raise cash. These disruptions disappeared nearly as fast as they appeared. We trace this recovery back to the unprecedented actions the Fed took to purchase corporate bonds rather than its interventions in extending credit. The March 23rd announcement to buy investment-grade debt boosted prices and lowered bond spreads (particularly at shorter maturities and the safer end of investment-grade) while having virtually no effect on high-yield debt. April 9th, in contrast, had a large effect on both investment-grade and high-yield, even for the riskier end of high yield which would only indirectly benefit from the policy. These facts highlight the importance of financial frictions early on in the crisis, but also challenge existing theories of these frictions.
    JEL: E5 E58 G01 G1 G12 G18 G21 G23
    Date: 2020–05
  2. By: Christoph Huber; Jürgen Huber; Michael Kirchler
    Abstract: In this paper we investigate how the experience of stock market shocks, like the COVID-19 crash, influences risk taking behavior. To isolate changes in risk taking from a variety of other confounding factors during stock market crashes, we ran controlled experiments with finance professionals in December 2019 and March 2020. We observe that their investments in the experiment were 12 percent lower in March 2020 than in December 2019, even though their future price expectations did not change. This finding is supported by the behavior of students who do not change risky behavior, supposedly because most of them were not invested.
    Keywords: Experimental finance, reinforcement learning, countercyclical risk aversion, finance professionals
    JEL: C91 G01 G11
    Date: 2020–11
  3. By: Ehrmann, Michael; Jansen, David-Jan
    Abstract: This paper tests whether fluctuations in investors' attention affect stock return comovement with national and global markets, and which stocks are most affected. We measure fluctuations in investor attention using 59 high-profile soccer matches played during stock market trading hours at the three editions of the FIFA World Cup between 2010 and 2018. Using intraday data for more than 750 firms in 19 countries, we find that distracted investors shift attention away from firm-specific and from global news. When movements in global stock markets are large, the pricing of global news reverts back to normal, but firm-specific news keep being priced less, leading to increased comovement of stock returns with the national stock market. This increase is economically large, and particularly strong for those stocks that typically comove little with the national market, thereby leading to a convergence in betas across stocks. JEL Classification: G12, G15, G41
    Keywords: comovement, investor attention, stock returns
    Date: 2020–05
  4. By: Andrew Y. Chen; Mihail Velikov
    Abstract: We zero in on the expected returns of long-short portfolios based on 120 stock market anomalies by accounting for (1) effective bid-ask spreads, (2) post-publication effects, and (3) the modern era of trading technology that began in the early 2000s. Net of these effects, the average anomaly's expected return is a measly 8 bps per month. The strongest anomalies return only 10-20 bps after accounting for data-mining with either out-of-sample tests or empirical Bayesian methods. Expected returns are negligible despite cost optimizations that produce impressive net returns in-sample and the omission of additional trading costs like price impact.
    Keywords: Trading costs; Mispricing; Stock return anomalies; Anomaly zoo
    JEL: G10 G11 G12 G14
    Date: 2020–05–22
  5. By: Mamdouh Medhat; Berardino Palazzo
    Abstract: A risk factor linked to aggregate equity issuance conditions explains the empirical performance of investment factors based on the asset growth anomaly of Cooper, Gulen, and Schill (2008). This new risk factor, dubbed equity financing risk (EFR) factor, subsumes investment factors in leading linear factor models. Most importantly, when substituted for investment factors, the EFR factor improves the overall pricing performance of linear factor models, delivering a significant reduction in absolute pricing errors and their associated t-statistics for several anomalies, including the ones related to R&D expenditures and cash-based operating profitability.
    Keywords: Equity returns; R&D; Factor models; Equity issuances; Financing constraints
    JEL: G12 G31 G35
    Date: 2020–05–20
  6. By: Molestina Vivar, Luis; Wedow, Michael; Weistroffer, Christian
    Abstract: Does leverage drive investor flows in bond mutual funds? Leverage can increase fund returns in good times, but it can also magnify investors’ losses and their response to bad performance. We study bond fund flows to provide new evidence for the link between mutual fund leverage and financial fragility. We find that outflows are greater in leveraged funds during stressed periods and after bad performance, compared with unleveraged funds. We provide supporting evidence that leverage exacerbates the negative externality in investors' redemption decisions. In this regard, we find that fund managers in leveraged funds react more procyclically to net outflows compared with fund managers in unleveraged funds. Such procyclical security sales in leveraged funds may increase investors’ first-mover advantages and their response to bad performance. These findings suggest that leverage amplifies fragility in the bond mutual fund sector. JEL Classification: G01, G20, G23
    Keywords: bond funds, financial fragility, fund leverage
    Date: 2020–05
  7. By: Sirio Aramonte; Chiara Scotti; Ilknur Zer
    Abstract: Policymakers and academics have been particularly attuned to the issues of liquidity transformation and first mover advantage at open-end mutual funds.Open-end mutual funds engage in liquidity transformation because they promise one-day redemptions on their assets, even when the invested assets have low or uncertain liquidity.
    Date: 2020–05–29
  8. By: Baldacci Bastien; Bergault Philippe; Derchu Joffrey; Rosenbaum Mathieu
    Abstract: The tick size, which is the smallest increment between two consecutive prices for a given asset, is a key parameter of market microstructure. In particular, the behavior of high frequency market makers is highly related to its value. We take the point of view of an exchange and investigate the relevance of having different tick sizes on the bid and ask sides of the order book. Using an approach based on the model with uncertainty zones, we show that when side-specific tick sizes are suitably chosen, it enables the exchange to improve the quality of liquidity provision.
    Date: 2020–05
  9. By: Renée Fry-McKibbin; Ziyu Yan
    Abstract: This paper uses tests drawn from the literature on financial market contagion measured by changes in higher-order comoments to establish the patterns in the interdependence between equity markets in Shanghai and Shenzhen with Hong Kong as mainland China liberalized their capital market. On the announcement of the opening of the Shanghai market correlations rise, but subside by the launch. Following the launch changes in coskewness, cokurtosis and covolatility emerge. The liberalization process is complete by mid-September 2016.
    Keywords: Shanghai-Hong Kong Stock Connect, Shenzhen Hong-Kong Stock Connect, Contagion, Spillovers
    JEL: G15
    Date: 2020–05
  10. By: Maake, Witness; Van Zyl, Terence
    Abstract: The research aims to investigate the role of hidden orders on the structure of the average market impact curves in the five BRICS financial markets. The concept of market impact is central to the implementation of cost-effective trading strategies during financial order executions. The literature of Lillo et al. (2003) is replicated using the data of visible orders from the five BRICS financial markets. We repeat the implementation of Lillo et al. (2003) to investigate the effect of hidden orders. We subsequently study the dynamics of hidden orders. The research applies machine learning to estimate the sizes of hidden orders. We revisit the methodology of Lillo et al. (2003) to compare the average market impact curves in which true hidden orders are added to visible orders to the average market impact curves in which hidden orders sizes are estimated via machine learning. The study discovers that : (1) hidden orders sizes could be uncovered via machine learning techniques such as Generalized Linear Models (GLM), Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forests (RF); and (2) there exist no set of market features that are consistently predictive of the sizes of hidden orders across different stocks. Artificial Neural Networks produce large R^2 and small MSE on the prediction of hidden orders of individual stocks across the five studied markets. Random Forests produce the ˆ most appropriate average price impact curves of visible and estimated hidden orders that are closest to the average market impact curves of visible and true hidden orders. In some markets, hidden orders produce a convex power-law far-right tail in contrast to visible orders which produce a concave power-law far-right tail. Hidden orders may affect the average price impact curves for orders of size less than the average order size; meanwhile, hidden orders may not affect the structure of the average price impact curves in other markets. The research implies ANN and RF as the recommended tools to uncover hidden orders.
    Keywords: Hidden Orders; Market Features; GLM; ANN; SVM; RF; Hidden Order Sizes; Market Impact; BRICS(Brazil, Russia, India, China, and South Africa)
    JEL: C4 C8 D4
    Date: 2020–02–28
  11. By: Zihao Zhang; Stefan Zohren; Stephen Roberts
    Abstract: We adopt deep learning models to directly optimise the portfolio Sharpe ratio. The framework we present circumvents the requirements for forecasting expected returns and allows us to directly optimise portfolio weights by updating model parameters. Instead of selecting individual assets, we trade Exchange-Traded Funds (ETFs) of market indices to form a portfolio. Indices of different asset classes show robust correlations and trading them substantially reduces the spectrum of available assets to choose from. We compare our method with a wide range of algorithms with results showing that our model obtains the best performance over the testing period, from 2011 to the end of April 2020, including the financial instabilities of the first quarter of 2020. A sensitivity analysis is included to understand the relevance of input features and we further study the performance of our approach under different cost rates and different risk levels via volatility scaling.
    Date: 2020–05
  12. By: Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge
    Abstract: We study spillovers between REITs and stock markets in a global context. We compute both directional and net spillover indexes in a global and dynamic setting. Our findings indicate that connectedness between these markets has increased importantly over time. On average stock markets are net transmitters and REITs markets are net receivers. Considerable time variation is observed. Spillovers are higher during crises and REITs were net spillover transmitters to stock markets during the Subprime Financial Crisis. Our results have important implications for global investors.
    Keywords: Spillovers; Market connectedness; REITs markets; Stock markets; LASSO methods
    JEL: G01 G15 C32
    Date: 2020–06
  13. By: Dumitriu, Ramona; Stefanescu, Răzvan
    Abstract: Studies on the financial markets proved that not all calendar anomalies are persistent in time. Some of them experienced various types of changes, including passing from the classical form to an extended one, with an enlarged specific time interval. This paper approaches the Holiday Effect extended form on the United States capital market. In its classical form, the Holiday Effect refers to abnormal stock returns on a trading day before a public holiday and a trading day after. We study the behavior of stocks returns for a time interval that starts four trading days before a public holiday and it ends four trading days after. In this investigation we employ the daily closing values of four important indexes from the United States capital market: Dow Jones Industrial Average, Standard & Poor's 500, Russell 2000 and NASDAQ Composite. In order to capture the changes experienced in time by the Extended Holiday Effect we analyze the returns of these indexes for three periods: January 1990 - December 1999, January 2000 – December 2009 and January 2010 – April 2020. The investigation revealed, for some trading days from the enlarged specific time interval, returns that were, in average, significant larger or smaller than those of the days outside of this interval. We found especially high abnormal returns on four or three trading days before public holidays and low abnormal returns on one or two trading days after public holidays. The results also suggest that the Extended Holiday Effect was more visible in relative quiet periods than in the turbulent ones and it influences especially the stock returns of small cap companies.
    Keywords: Calendar Anomalies, Extended Holiday Effect, US capital markets
    JEL: G02 G10 G14
    Date: 2020–05–15
  14. By: Thibaut Duprey
    Abstract: I construct a new composite measure of systemic financial market stress for Canada. Compared with existing measures, it better captures the 1990 housing market correction and more accurately reflects the absence of diversification opportunities during systemic events. The index can be used for monitoring. For instance, it reached a peak during the COVID-19 pandemic second only to the 2008 global financial crisis. The index can also be used to introduce non-linear macrofinancial dynamics in empirical macroeconomic models of the Canadian economy. Macroeconomic conditions are shown to deteriorate significantly when the Canadian financial stress index is above its 90th percentile.
    Keywords: Central bank research; Financial markets; Financial stability; Monetary and financial indicators
    JEL: C3 C32 E4 E44 G0 G01
    Date: 2020–06
  15. By: Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge; Uribe, Jorge M.
    Abstract: We explore the higher order linkages between energy commodity markets and global financial markets. Our focus is on spillovers of realized good and bad volatilities, realized signed jump variation, realized skewness and realized kurtosis. Our results show that the measurement of risk spillovers is sensitive to the definition of risk used in their construction. Asymmetries between good and bad volatility transmission matter, and results when jumps and higher order risk measures are considered are substantially different from those obtained when traditional volatility measures are used. We provide empirical support for theoretical asset pricing models that conduct the optimization required for portfolio balancing in the mean-variance-skewness space by showing that risk diversification opportunities vary greatly when one considers variance or skewness as the fundamental proxy for risk.
    Keywords: Energy commodity markets; Risk spillover; Higher order risk measure; LASSO methods
    JEL: E44 F31 G01 G12 G15
    Date: 2020–06

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