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on Financial Markets |
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Issue of 2021‒09‒13
ten papers chosen by |
| By: | Hakan Yilmazkuday (Department of Economics, Florida International University) |
| Abstract: | This paper investigates the effects of the coronavirus disease 2019 (COVID-19) cases in the U.S. on the S&P 500 Index using daily data covering the period between January 21st, 2020 and August 10th, 2021. The investigation is achieved by using a structural vector autoregression model, where a measure of the global economic activity and the spread between 10-year treasury constant maturity and the federal funds rate are also included. The empirical results suggest that having 1% of an increase in cumulative daily COVID-19 cases in the U.S. results in about 0.01% of a cumulative reduction in the S&P 500 Index after one day and about 0.03% of a reduction after one week. Historical decomposition of the S&P 500 Index further suggests that the negative effects of COVID-19 cases in the U.S. on the S&P 500 Index have been mostly observed during March 2020. |
| Keywords: | Coronavirus, COVID-19, S&P 500 Index, Baltic Dry Index |
| JEL: | F44 G15 I10 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:fiu:wpaper:2117&r= |
| By: | Mönch, Emanuel; Stein, Tobias |
| Abstract: | The equity premium follows a pronounced v-shape pattern around the beginning of recessions. It sharply drops into negative territory just before business cycle peaks and then strongly recovers as the recession unfolds. Recessions are preceded by an inverted yield curve. Thus probit models using the term spread as predictor time the beginning of recessions well. We show that such model-implied recession probabilities strongly improve equity premium prediction out-of-sample. We document a structural break in the mean of the term spread in 1982. When correcting for this break, the forecast performance further strengthens, outperforming other recently proposed benchmark predictors. |
| Keywords: | Recession predictability,return predictability,business cycle,probit model,term spread |
| JEL: | E32 E37 C53 G11 G17 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:252021&r= |
| By: | Ullah, Irfan; Ahmed, Mumtaz |
| Abstract: | Previous empirical literature supports that stock bubbles have impacts on efficient allocation of wealth. Researchers targeted various economies in the past using various methods to explore bubble phenomenon. This study uses generalized SADF test which is admitted by empirical literature as the most successful technique to explore stock bubbles in three countries included in European Free Trade Association (EFTA) not studied before. This paper takes a lead and tests for the existence of bubbles in monthly end index prices of respective countries based on latest available time series data from January 2001 to September 2019. Based on empirical results, it is concluded that all three countries stock markets experienced multiple bubbles in study period. The case of Iceland is worse where comparatively more fluctuations in stock prices are seen. To avoid occurrence of further stock price bubbles in these countries policy recommendations are provided as well. |
| Keywords: | periodically collapsing bubbles; generalized supremum ADF; explosivity |
| JEL: | C22 E44 G15 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109633&r= |
| By: | Cho, Thummim |
| Abstract: | Using data on asset pricing anomalies, I test the idea that the act of arbitrage turns “alphas” into “betas”: Assets with high initial abnormal returns attract more arbitrage and covary endogenously more with systematic factors that arbitrage capital is exposed to. This channel explains the exposures of 40 anomaly portfolios to aggregate funding liquidity shocks and arbitrageur wealth portfolio shocks. My results highlight that financial intermediaries that act as asset market arbitrageurs not only price assets given risks, but also actively shape these risks through their trades. |
| Keywords: | endogenous risk; factor beta; financial intermediaries; arbitrage; asset pricing anomalies; Paul Woolley Centre at the LSE |
| JEL: | G11 G12 G23 |
| Date: | 2020–08–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:102085&r= |
| By: | Salisu, Afees; Ogbonna, Ahamuefula; Oloko, Tirimisiyu |
| Abstract: | This study examines the effect of a pandemic-induced uncertainty on cryptocurrencies (specifically, Bitcoin, Ethereum and Ripple). It employs a predictive model by Westerlund and Narayan (2012, 2015) to examine the predictability of a pandemic-induced uncertainty as a predictor, as well as the forecast performance of our predictive model for cryptocurrency returns. We examine the role of asymmetry in uncertainty and the sensitivity of our results to alternative measures of uncertainty due to pandemics, using the recently developed Global Fear Index (GFI) by Salisu and Akanni (2020). Our results indicate that cryptocurrencies could act as hedge against uncertainty due to pandemics, albeit with reduced hedging effectiveness in the COVID-19 period. Accounting for asymmetry is found to improve the predictability and forecast performance of the model, which indicates that failure to account for asymmetry in modeling the effect of a pandemic-induced uncertainty on cryptocurrency may lead to incorrect conclusion. The results seem to be sensitive to the choice of measure of pandemic-induced uncertainty. |
| Keywords: | COVID-19; Cryptocurrency; Distributed Lag Model; Pandemic; Uncertainty |
| JEL: | C5 G1 |
| Date: | 2020–07–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109597&r= |
| By: | Julius O. Campeci\~no |
| Abstract: | This manuscript presents a mathematical relationship between the coefficient of variation (CV) and security investment risk, defined herein as the probability of occurrence of negative returns. The equation suggests that there exists a range of CV where risk is zero and that risk never crosses 50% for securities with positive returns. It was found that at least for stocks, there is a strong correlation between CV and stock performance when the CV is derived from annual returns calculated for each month (as opposed to using, for example, only annual returns based on end-of-the-year closing prices). It was found that a low nonnegative CV of up to ~ 1.0 (~ 15% risk) correlates well with strong and consistent stock performance. Beyond this CV, share price growth gradually shows plateaus and/or large peaks and valleys. The efficient frontier was also re-examined based on CV analysis, and it was found that the direct relationship between risk and return (e.g., high risk, high return) is only robust when the correlation of returns among the portfolio securities is sufficiently negative. At low negative to positive correlation, the efficient frontier hypothesis breaks down, and risk analysis based on CV becomes an important consideration. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.03977&r= |
| By: | Schmidhammer, Christoph |
| Abstract: | For the DAX index market, this paper analyses the development of return differences between exchange traded funds (ETFs) and the DAX index from the perspective of long-term investors. The newly introduced methodology provides the opportunity to continuously identify long-term costs of passively managed products independent from the information of annual financial statements. This enables to test for product-specific return differences and to identify relevant cost drivers such as index returns and market makers. Results reveal that on average, DAX ETFs costs considerably exceed total expense ratios. Product-specific return differences are significant, however, differences tend to converge over time. For all ETFs, deviations are significantly influenced by index returns. Product characteristics deliver valuable arguments to explain these findings. Also market makers significantly contribute to return differences. |
| Keywords: | Exchange Traded Funds,Net Asset Value,market maker prices,return differences,Total Expense Ratio,ETF issuers,rolling window |
| JEL: | G12 G13 G14 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:282021&r= |
| By: | Ravi Kashyap |
| Abstract: | We consider in detail an investment strategy, titled "The Bounce Basket", designed for someone to express a bullish view on the market by allowing them to take long positions on securities that would benefit the most from a rally in the markets. We demonstrate the use of quantitative metrics and large amounts of historical data towards decision making goals. This investment concept combines macroeconomic views with characteristics of individual securities to beat the market returns. The central idea of this theme is to identity securities from a regional perspective that are heavily shorted and yet are fundamentally sound with at least a minimum buy rating from a consensus of stock analysts covering the securities. We discuss the components of creating such a strategy including the mechanics of constructing the portfolio. Using simulations, in which securities lending data is modeled as geometric brownian motions, we provide a few flavors of creating a ranking of securities to identity the ones that are heavily shorted. An investment strategy of this kind will be ideal in market scenarios when a downturn happens due to unexpected extreme events and the markets are anticipated to bounce back thereafter. This situation is especially applicable to incidents being observed, and relevant proceedings, during the Coronavirus pandemic in 2020-2021. This strategy is one particular way to overcome a potential behavioral bias related to investing, which we term the "rebound effect". |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.03740&r= |
| By: | Sheridan Titman; Chishen Wei. Wei; Bin Zhao |
| Abstract: | We identify a group of “suspicious” firms that use stock splits—perhaps, along with other activities—to artificially inflate their share prices. Following the initiation of suspicious splits, share prices temporarily increase, and subsequently decline below their pre-split levels. Using account level data from the Shanghai Stock Exchange, we find that small retail investors acquire shares in firms initiating suspicious splits, while more sophisticated investors accumulate positions before suspicious split announcements and sell in the post-split period. We also find that insiders sell large blocks of shares and obtain loans using company stock as collateral around the initiation of suspicious splits. |
| JEL: | G12 G14 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:29212&r= |
| By: | R, Sreelakshmi; Sinha, Apra; Mandal, Sabuj Kumar |
| Abstract: | Akin to the global markets, the Indian stock market also nosedived in response to the COVID-19 pandemic. However, this drastic fall was not persistent; rather a sharp recovery was witnessed as a result of sweeping investor enthusiasm and wide-ranging speculation. In this paper, we explore the relationship between investor sentiment, stock returns and important macro variables during the COVID-19 period spanning from January, 2020 to May, 2021. We have also conducted event analysis to see the significance of major events during the period. While the Great Lockdown and first fiscal package impacted the stock returns significantly, the first case reported, second fiscal package, vaccination drive and the second wave failed to create a commendable impact. The event analysis also suggests that the Indian stock market responds negatively to an increase in interest rate uncertainty. Our empirical analysis shows evidence of significant effect of investor sentiment on stock returns during all periods, except the period of extreme volatility. Moreover, the stock return is positively related to oil price and negatively related to the exchange rate. We also find mixed evidence of COVID-19 related information on stock market. |
| Keywords: | COVID-19 pandemic, uncertainty, investor sentiment, stock returns, event analysis, India |
| JEL: | G01 G02 G11 G14 |
| Date: | 2021–08–09 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:109549&r= |