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on Financial Markets |
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Issue of 2021‒10‒11
eight papers chosen by |
| By: | Guglielmo Maria Caporale; Abdurrahman Nazif Catik; Mohamad Husam Helmi; Coskun Akdeniz; Ali Ilhan |
| Abstract: | This paper examines the effects of the COVID-19 pandemic on stock returns, CDS and economic activity in the US and the five European countries (the UK, Germany, France, Italy, and Spain) which have been most affected. The sample period covers the dates from the first confirmed COVID-19 cases in these countries to February 19, 2021. Specifically, we estimate first benchmark linear VAR models and then, given the evidence of parameter instability, TVP-VAR models with stochastic volatility which are ideally suited to capturing the changing dynamics in both financial markets and the real economy. The empirical findings can be summarised as follows. The linear VAR responses of electricity consumption (a proxy for real economic activity) to a one-standard-deviation shock to the number of COVID-19 cases are statistically insignificant, except for France, whilst the CDS ones are positive and significant only in a few periods, and there are very mixed results for those of stock returns. As for the TVP-VAR results, these indicate that COVID-19 cases had a negative and significant effect on economic activity in all countries in the early stages of the pandemic (especially in Italy), and a positive one on CDS at the same time (with cross-country differences). Finally, the negative impact on stock markets was felt only initially and it had tapered off by mid-April 2020. |
| Keywords: | Covid-19, stock markets, CDS, economic activity, TVP-VAR |
| JEL: | G10 G14 G15 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9316&r= |
| By: | Duffy, John (University of California); Rabanal, Jean Paul (University of Stavanger); Rud, Olga (University of Stavanger) |
| Abstract: | We report on an experiment studying market reactions to stock splits and reverse splits. In the first environment, two assets have increasing fundamental values, and one asset is subject to a 2-for-1 share split while the other is not. In the second environment, the fundamental values of both assets are decreasing, and one asset is subject to a 1-for-2 reverse split while the other is not. We find that share prices do not fully adjust to changes in fundamental values per share following both types of splits and we relate this phenomenon to difficulties that traders have with proportional thinking. |
| Keywords: | Stock splits; behavioral finance; |
| JEL: | C92 G10 G40 G41 |
| Date: | 2021–09–29 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:stavef:2021_001&r= |
| By: | Jianying Xie |
| Abstract: | One of the most important studies in finance is to find out whether stock returns could be predicted. This research aims to create a new multivariate model, which includes dividend yield, earnings-to-price ratio, book-to-market ratio as well as consumption-wealth ratio as explanatory variables, for future stock returns predictions. The new multivariate model will be assessed for its forecasting performance using empirical analysis. The empirical analysis is performed on S&P500 quarterly data from Quarter 1, 1952 to Quarter 4, 2019 as well as S&P500 monthly data from Month 12, 1920 to Month 12, 2019. Results have shown this new multivariate model has predictability for future stock returns. When compared to other benchmark models, the new multivariate model performs the best in terms of the Root Mean Squared Error (RMSE) most of the time. |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2110.01873&r= |
| By: | Emanuele Citera (Department of Economics, New School for Social Research) |
| Abstract: | This paper attempts to develop a theory of statistical equilibrium based on an entropy-constrained framework, that allow us to explain the distribution of stock returns over different market trends. By making use of the Quantal Response Statistical Equilibrium model (Scharfenaker and Foley, 2017), we recover the cross-sectional distribution of daily returns of individual company listed the S&P 500, over the period 1988-2019. We then make inference on the frequency distributions of returns by studying them over bull markets, bear markets and corrections. The results of the model shed light on the microscopic as well as macroscopic behavior of the stock market, in addition to provide insights in terms of stock returns distribution. |
| Keywords: | Stock returns, statistical equilibrium, information theory, stock market, maximum entropy |
| JEL: | C10 C70 D84 G10 G40 |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:new:wpaper:2116&r= |
| By: | Dimitriadou, Athanasia (University of Derby); Agrapetidou, Anna (Democritus University of Thrace, Department of Economics); Gogas, Periklis (Democritus University of Thrace, Department of Economics); Papadimitriou, Theophilos (Democritus University of Thrace, Department of Economics) |
| Abstract: | Credit Rating Agencies (CRAs) have been around for more than 150 years. Their role evolved from mere information collectors and providers to quasi-official arbitrators of credit risk throughout the global financial system. They compiled information that -at the time- was too difficult and costly for their clients to gather on their own. After the 1929 big market crash, they started to play a more formal role. Since then, we see a growing reliance of investors on the CRAs ratings. After the global financial crisis of 2007, the CRAs became the focal point of criticism by economists, politicians, the media, market participants and official regulatory agencies. The reason was obvious: the CRAs failed to perform the job they were supposed to do financial markets, i.e. efficient, effective and prompt measuring and signaling of financial (default) risk. The main criticism was focusing on the “issuer-pays system”, the relatively loose regulatory oversight from the relevant government agencies, the fact that often ratings change ex-post and the limited liability of CRAs. Many changes were implemented to the operational framework of the CRAs, including public disclosure of CRA information. This is designed to facilitate "unsolicited" ratings of structured securities by rating agencies that are not paid by the issuers. This combined with the abundance of data and the availability of powerful new methodologies and inexpensive computing power can bring us to the new era of independent ratings: The not-for-profit Independent Credit Rating Agencies (ICRAs). These can either compete or be used as an auxiliary risk gauging mechanism free from the problems inherent in the traditional CRAs. This role can be assumed by either public or governmental authorities, national or international specialized entities or universities, research institutions, etc. Several factors facilitate today the transition to the ICRAs: the abundance data, cheaper and faster computer processing the progress in traditional forecasting techniques and the wide use of new forecasting techniques i.e. Machine Learning methodologies and Artificial Intelligence systems. |
| Keywords: | Credit rating agencies; banking; forecasting; support vector machines; artificial intelligence |
| JEL: | C02 C15 C40 C45 C54 E02 E17 E27 E44 E58 E61 G20 G23 G28 |
| Date: | 2021–10–04 |
| URL: | http://d.repec.org/n?u=RePEc:ris:duthrp:2021_009&r= |
| By: | Astaiza-Gómez, José Gabriel |
| Abstract: | I estimate a demand model for online services of financial data, from a random parameters or mixed logit model, using a sample with searches at Bloomberg Terminals and at the EDGAR system. My preliminary results suggest that the substitution investors make of financial information providers, are affected by the subscription prices, investors' expectations on stock returns, and investors' income. |
| Keywords: | random parameters, open access services, subscription providers, market shares. |
| JEL: | D80 D82 D83 D84 G00 G14 G23 L86 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110008&r= |
| By: | Robin Fritsch |
| Abstract: | We examine how the introduction of concentrated liquidity has changed the liquidity provision market in automated market makers such as Uniswap. To this end, we compare average liquidity provider returns from trading fees before and after its introduction. Furthermore, we quantify the performance of a number of fundamental concentrated liquidity strategies using historical trade data. We estimate their possible returns and evaluate which perform best for certain trading pairs and market conditions. |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2110.01368&r= |
| By: | Simon Rudkin; Wanling Qiu; Pawel Dlotko |
| Abstract: | Norms of Persistent Homology introduced in topological data analysis are seen as indicators of system instability, analogous to the changing predictability that is captured in financial market uncertainty indexes. This paper demonstrates norms from the financial markets are significant in explaining financial uncertainty, whilst macroeconomic uncertainty is only explainable by market volatility. Meanwhile, volatility is insignificant in the determination of norms when uncertainty enters the regression. Persistence norms therefore have potential as a further tool in asset pricing, and also as a means of capturing signals from financial time series beyond volatility. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2110.00098&r= |