nep-fmk New Economics Papers
on Financial Markets
Issue of 2022‒06‒27
eleven papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. What moves markets? By Kerssenfischer, Mark; Schmeling, Maik
  2. Do Sell-Side Analysts Say “Buy” While Whispering “Sell”? By David Hirshleifer; Yushui Shi; Weili Wu
  3. Stock Return Predictability: Evaluation based on interval forecasts By Amélie Charles; Jae Kim; Olivier Darné
  4. Univariate and Multivariate LSTM Model for Short-Term Stock Market Prediction By Vishal Kuber; Divakar Yadav; Arun Kr Yadav
  5. Fiscal Consolidation under Market´s Scrutiny: How Do Fiscal Announcements Affect Bond Yields By Josef Sveda; Jaromir Baxa; Adam Gersl
  6. Research on the correlation between text emotion mining and stock market based on deep learning By Chenrui Zhang
  7. How Is the Corporate Bond Market Responding to Financial Market Volatility? By Nina Boyarchenko; Richard K. Crump; Anna Kovner; Or Shachar
  8. Preference for Wealth and Life Cycle Portfolio Choice By Campanale Claudio; Fugazza Carolina
  9. Retail CBDC and U.S. Monetary Policy Implementation: A Stylized Balance Sheet Analysis By Matthew Malloy; Francis Martinez; Mary-Frances Styczynski; Alex Thorp
  10. The relevance of banks to the European stock market By Kick, Andreas; Rottmann, Horst
  11. Evaluating the Impact of Bitcoin on International Asset Allocation using Mean-Variance, Conditional Value-at-Risk (CVaR), and Markov Regime Switching Approaches By Mohammadreza Mahmoudi

  1. By: Kerssenfischer, Mark; Schmeling, Maik
    Abstract: What share of asset price movements is driven by news? We build a large, time-stamped event database covering scheduled macro news as well as unscheduled events. We find that news account for about 50% of all bond and stock price movements in the United States and euro area since 2002, suggesting that a much larger share of return variation can be traced back to observable news than previously thought. Moreover, we provide stylized facts about the type of news that matter most for asset prices, the persistence of news effects, and spillover effects between the US and euro area.
    Keywords: Macro news,Asset prices,High-Frequency Identification,Event Database
    JEL: E43 E44 G12 G14
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:zbw:bubdps:162022&r=
  2. By: David Hirshleifer; Yushui Shi; Weili Wu
    Abstract: We examine how sell-side equity analysts strategically disclose information of differing quality to the public versus the buy-side mutual fund managers to whom they are connected. We consider cases in which analysts recommend that the public buys a stock, but some fund managers sell it. We measure favor trading using mutual fund managers’ votes for analysts in a Chinese “star analyst” competition. We find that managers are more likely to vote for analysts who exhibit more “say-buy/whisper-sell” behavior with these managers. This suggests that analysts introduce noise in their public recommendations, making the more-precise information provided to their private clients more valuable. Analysts’ say-buy/whisper-sell behavior results in information asymmetry: the positive-recommendation stocks bought by the managers who vote for the analysts outperform the stocks sold by these managers after the recommendation dates. Our findings help explain several puzzles regarding analysts’ public recommendations.
    JEL: G12 G14 G2 G23 G24 G3 M41
    Date: 2022–05
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30032&r=
  3. By: Amélie Charles (Audencia Business School); Jae Kim (La Trobe University [Melbourne]); Olivier Darné (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - Nantes Univ - IAE Nantes - Nantes Université - Institut d'Administration des Entreprises - Nantes - Nantes Université - pôle Sociétés - Nantes Univ - Nantes Université - IUML - FR 3473 Institut universitaire Mer et Littoral - Nantes Université - pôle Sciences et technologie - Nantes Univ - Nantes Université - UBS - Université de Bretagne Sud - UM - Le Mans Université - UA - Université d'Angers - CNRS - Centre National de la Recherche Scientifique - IFREMER - Institut Français de Recherche pour l'Exploitation de la Mer - Nantes Univ - ECN - Nantes Université - École Centrale de Nantes - Nantes Univ - Nantes Université)
    Abstract: This paper evaluates the predictability of monthly stock return using out-of-sample interval forecasts. Past studies exclusively use point forecasts, which are of limited value since they carry no information about intrinsic predictive uncertainty. We compare the empirical performance of alternative interval forecasts for stock return generated from a naïve model, univariate autoregressive model, and multivariate model (predictive regression and VAR), using U.S. data from 1926. It is found that neither univariate nor multivariate interval forecasts outperform naïve forecasts. This strongly suggests that the U.S. stock market has been informationally efficient in the weak-form as well as in the semi-strong form.
    Keywords: Autoregressive Model,Bootstrapping,Financial Ratios,Forecasting,Interval Score,Market Efficiency
    Date: 2022–04
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-03656310&r=
  4. By: Vishal Kuber; Divakar Yadav; Arun Kr Yadav
    Abstract: Designing robust and accurate prediction models has been a viable research area since a long time. While proponents of a well-functioning market predictors believe that it is difficult to accurately predict market prices but many scholars disagree. Robust and accurate prediction systems will not only be helpful to the businesses but also to the individuals in making their financial investments. This paper presents an LSTM model with two different input approaches for predicting the short-term stock prices of two Indian companies, Reliance Industries and Infosys Ltd. Ten years of historic data (2012-2021) is taken from the yahoo finance website to carry out analysis of proposed approaches. In the first approach, closing prices of two selected companies are directly applied on univariate LSTM model. For the approach second, technical indicators values are calculated from the closing prices and then collectively applied on Multivariate LSTM model. Short term market behaviour for upcoming days is evaluated. Experimental outcomes revel that approach one is useful to determine the future trend but multivariate LSTM model with technical indicators found to be useful in accurately predicting the future price behaviours.
    Date: 2022–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2205.06673&r=
  5. By: Josef Sveda (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech National Bank, Prague, Czech Republic); Jaromir Baxa (Institute of Economic Studies, Faculty of Social Sciences, Charles University & The Czech Academy of Sciences, Institute of Information Theory and Automation, Prague, Czech Republic); Adam Gersl (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague, Czech Republic)
    Abstract: We estimate the short-run reactions of bond spreads of selected EU member states vis-a-vis the German bund on fiscal announcements from January 2000 till December 2019. To avoid selection bias, the announcements are scrapped from the Factiva database, and then, depending on their tone, they are classified as hawkish or dovish. We show that announcements of fiscal consolidation decrease the spreads - however, the full-sample result masks substantial time and country variation. The impact of fiscal consolidation is statistically significant, namely in the post-crisis period since the Draghi´s "whatever it takes" speech, but not before the Great Recession or during the European Debt Crisis.
    Keywords: fiscal announcements, bond spreads, EU debt crisis, fiscal consolidation
    JEL: E62 G01 G12
    Date: 2022–06
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2022_11&r=
  6. By: Chenrui Zhang
    Abstract: This paper discusses how to crawl the data of financial forums such as stock bar, and conduct emotional analysis combined with the in-depth learning model. This paper will use the Bert model to train the financial corpus and predict the Shenzhen stock index. Through the comparative study of the maximal information coefficient (MIC), it is found that the emotional characteristics obtained by applying the BERT model to the financial corpus can be reflected in the fluctuation of the stock market, which is conducive to effectively improve the prediction accuracy. At the same time, this paper combines in-depth learning with financial texts to further explore the impact mechanism of investor sentiment on the stock market through in-depth learning, which will help the national regulatory authorities and policy departments to formulate more reasonable policies and guidelines for maintaining the stability of the stock market.
    Date: 2022–05
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2205.06675&r=
  7. By: Nina Boyarchenko; Richard K. Crump; Anna Kovner; Or Shachar
    Abstract: The Russian invasion of Ukraine increased uncertainty around the world. Although most U.S. companies have limited direct exposure to Ukrainian and Russian trading partners, increased global uncertainty may still have an indirect effect on funding conditions through tightening financial conditions. In this post, we examine how conditions in the U.S. corporate bond market have evolved since the start of the year through the lens of the U.S. Corporate Bond Market Distress Index (CMDI). As described in a previous Liberty Street Economics post, the index quantifies joint dislocations in the primary and secondary corporate bond markets and can thus serve as an early warning signal to detect financial market dysfunction. The index has risen sharply from historically low levels before the invasion of Ukraine, peaking on March 19, but appears to have stabilized around the median historical level.
    Keywords: corporate bond market conditions; invasion of Ukraine
    JEL: E5 G12
    Date: 2022–06–01
    URL: http://d.repec.org/n?u=RePEc:fip:fednls:94285&r=
  8. By: Campanale Claudio (Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) and CERP (CCA) University of Torino, Italy); Fugazza Carolina (Department of Economics, Social Studies, Applied Mathematics and Statistics (ESOMAS) and CERP (CCA) University of Torino, Italy)
    Abstract: Do participation and investment in risky assets increase with wealth? Do the wealthiest households save at higher rates than the median households and is wealth more concentrated than earnings? Based on survey data, this paper shows that this is the case. Moreover, the paper provides a theoretical framework based on an extended version of the life-cycle model of consumption and portfolio choice that enables to explain differences in behavior between the wealthiest and others.
    Keywords: Life-cycle, Portfolio Choice, Preference over Wealth, Wealth Inequality
    JEL: D15 E21 G11
    Date: 2022–06
    URL: http://d.repec.org/n?u=RePEc:tur:wpapnw:075&r=
  9. By: Matthew Malloy; Francis Martinez; Mary-Frances Styczynski; Alex Thorp
    Abstract: This paper discusses how a Federal Reserve issued retail central bank digital currency (CBDC) could affect U.S. monetary policy implementation. Using a stylized balance sheet analysis, we analyze the effect a retail CBDC could have on the balance sheets of the Federal Reserve, commercial banks, and U.S. households. Then we consider how these balance sheet changes could affect monetary policy implementation for the Federal Reserve. We illustrate that the potential effects on monetary policy implementation from a retail CBDC are highly dependent on the initial conditions of the Federal Reserve’s balance sheet. Moreover, the analysis demonstrates how the Federal Reserve may use its existing tools to manage the effects of a retail CBDC on monetary policy implementation.
    Keywords: Bank behavior; Central banking; Households; Monetary policy implementation; Retail CBDC
    Date: 2022–05–31
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfe:2022-32&r=
  10. By: Kick, Andreas; Rottmann, Horst
    Abstract: Banks have always played an ambivalent role in financial markets. On the one hand, they provide essential services for the market; on the other hand, problems in the banking sector can send shock waves through the entire economy. Given this prominent role, it is not surprising that Pereira and Rua (2018) found that the health of the banking sector exerts an influence on stock returns in the US. Understanding the relationship between banks and their impact on the asset prices of non-financials is essential to evaluate the risk emanating from an unhealthy banking sector and should be considered in new regulatory requirements. The aim of this study is to determine if the health of European banks is of such importance for the European stock market so that spillover effects are visible. Our results show that none of our banking-health variables have explanatory power on the cross-section of European stock returns. These findings contrast those for the US. The reasons may be manifold, from an unimportant liquidity provisioning channel over reduced room for actions due to regulatory requirements up to a moral hazard situation in Europe, where investors strongly rely on the governmental bailouts of distressed banks.
    Keywords: asset pricing,banking,spillover,errors-in-variables,individual stocks,distance-to-default
    JEL: G12 G21
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:zbw:hawdps:84&r=
  11. By: Mohammadreza Mahmoudi
    Abstract: This paper aims to analyze the effect of Bitcoin on portfolio optimization using mean-variance, conditional value-at-risk (CVaR), and Markov regime switching approaches. I assessed each approach and developed the next based on the prior approach's weaknesses until I ended with a high level of confidence in the final approach. Though the results of mean-variance and CVaR frameworks indicate that Bitcoin improves the diversification of a well-diversified international portfolio, they assume that assets' returns are developed linearly and normally distributed. However, the Bitcoin return does not have both of these characteristics. Due to this, I developed a Markov regime switching approach to analyze the effect of Bitcoin on an international portfolio performance. The results show that there are two regimes based on the assets' returns: 1- bear state, where returns have low means and high volatility, 2- bull state, where returns have high means and low volatility.
    Date: 2022–04
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2205.00335&r=

This nep-fmk issue is ©2022 by Kwang Soo Cheong. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at http://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.