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on Financial Markets |
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Issue of 2022‒04‒18
ten papers chosen by |
| By: | Mark Mink; Frans J. de Weert |
| Abstract: | The hedging argument of Black and Scholes (1973) hinges on the assumption that a continuously rebalanced asset portfolio satisfies the continuous-time self-financing condition. This condition, which is a special case of the continuous-time budget equation of Merton (1971), is believed to mathematically formalize the economic concept of an asset portfolio that is rebalanced continuously without requiring an inflow or outflow of external funds. Although we sometimes find it hard to believe our results, we believe that we show with three alternative mathematical proofs that the continuous-time self-financing condition does not hold for rebalanced portfolios. In addition, we pinpoint the mistake in the derivation that Merton (1971) uses to motivate the continuous-time budget equation. Specifically, by inadvertently equating a deterministic variable to a stochastic one, Merton (1971) implicitly assumes that the portfolio rebalancing does not depend on changes in asset prices. If correct, our results invalidate the continuous-time budget equation of Merton (1971) and the hedging argument and option pricing formula of Black and Scholes (1973). |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.05671&r= |
| By: | Yuxuan Huang; Luiz Fernando Capretz; Danny Ho |
| Abstract: | Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks historical data. Most of these existing approaches have focused on short term prediction using stocks historical price and technical indicators. In this paper, we prepared 22 years worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for stock prediction based on fundamental analysis. In addition, we applied RF based feature selection and bootstrap aggregation in order to improve model performance and aggregate predictions from different models. Our results show that RF model achieves the best prediction results, and feature selection is able to improve test performance of FNN and ANFIS. Moreover, the aggregated model outperforms all baseline models as well as the benchmark DJIA index by an acceptable margin for the test period. Our findings demonstrate that machine learning models could be used to aid fundamental analysts with decision-making regarding stock investment. |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2202.05702&r= |
| By: | Antonio Gargano (C.T. Bauer College of Business/University of Melbourne); Juan Sotes-Paladino (Universidad de los Andes/University of Melbourne); Patrick Verwijmeren (Erasmus School of Economics/University of Melbourne) |
| Abstract: | How synchronized are short sellers? We examine a unique dataset on the distribution of profits across a stock’s short sellers and find evidence of substantial dispersion in the initiation of their positions. Consistent with this dispersion reflecting “synchronization risk,” i.e., uncertainty among short sellers about when others will short sell (Abreu and Brunnermeier, 2002, 2003), more dispersed short selling signals (i) greater stock overpricing; and (ii) longer delays in overpricing correction. These effects are prevalent even among stocks facing low short-selling costs or other explicit constraints. Overall, our findings provide novel cross-sectional evidence of synchronization problems among short sellers and their pricing implications. |
| Keywords: | Short Selling, Limits to Arbitrage, Synchronization Risk |
| JEL: | G12 G14 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:aoz:wpaper:108&r= |
| By: | Ryan, Ellen |
| Abstract: | The investment fund sector has expanded dramatically since the crisis of 2008-2009. As the sector grows, so do the implications of its risk-taking for the wider financial system and real economy. This paper provides empirical evidence for the existence of widespread risk-taking incentives in the investment fund sector, with a particular focus on incentives for synchronised, cyclical risk-taking which could have systemic effects. Incentives arise from the positive response of investors to returns achieved through cyclical risk-taking and non-linearities in the relationship between fund returns and fund flows, which may keep managers from fully internalising the effects of adverse outcomes on their portfolios. The fact that market discipline may not be sufficient to ensure prudential behaviour among managers, combined with the externalities of this risk-taking for the wider system, creates a clear case for macroprudential regulatory intervention. JEL Classification: G23, G11, G28 |
| Keywords: | Financial stability, incentive, investment funds, macroprudential policy, risk-taking |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20222652&r= |
| By: | Bauckloh, Michael Tobias; Beyer, Victor; Klein, Christian |
| Abstract: | This research examines whether stocks of firms operating in highly polluting industries ('dirty stocks') are treated like sin stocks. We assume that investors shun dirty stocks based on non-pecuniary preferences and employ screening approaches that lead to the exclusion of entire industries. Using emission data of the U.S. Toxics Release Inventory, we show that dirty stocks are held in lower proportions by institutional investors and are followed by fewer financial analysts than other stocks. The shunning leads to an outperformance of dirty stocks in cross-sectional and time-series return analyses. These observations affect all firms within a dirty industry, regardless of whether they have high or low TRI emissions. This means that comparatively clean firms are shunned by capital market participants simply because of their industry affiliation, which can result in financing disadvantages and low incentives to improve sustainability performance. Thus, our findings contribute to the understanding of environmental preferences of investors and their consequences for asset pricing. |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cfrwps:2207&r= |
| By: | Antonio Gargano (University of Houston); Juan Sotes-Paladino (Universidad de los Andes); Patrick Verwijmeren (Erasmus School of Economics/University of Melbourne) |
| Abstract: | We provide evidence that losses constrain short sellers but not the transmission of information to prices. Using unique data on U.S. equity lending, we document a negative impact of the mark-tomarket losses of a stock’s short sellers, but no impact of their gains, on the future shorting of the stock. Consistent with funding and institutional constraints limiting short selling, we further show that the effect is highly asymmetric across different loss levels and stronger among stocks facing higher margin requirements. However, loss-making short selling has no predictive power for returns, suggesting a low impact of these constraints on the transmission of short sellers information to prices. |
| Keywords: | Short Selling, Margin Constraints, Limits to Arbitrage, Informed Trading |
| JEL: | G12 G14 |
| Date: | 2022–02 |
| URL: | http://d.repec.org/n?u=RePEc:aoz:wpaper:116&r= |
| By: | Ilaria Gianstefani; Luigi Longo; Massimo Riccaboni |
| Abstract: | The short squeeze of Gamestop (GME) has revealed to the world how retail investors pooling through social media can severely impact financial markets. In this paper, we devise an early warning signal to detect suspicious users' social network activity, which might affect the financial market stability. We apply our approach to the subreddit r/WallStreetBets, selecting two meme stocks (GME and AMC) and two non-meme stocks (AAPL and MSFT) as case studies. The alert system is structured in two stpng; the first one is based on extraordinary activity on the social network, while the second aims at identifying whether the movement seeks to coordinate the users to a bulk action. We run an event study analysis to see the reaction of the financial markets when the alert system catches social network turmoil. A regression analysis witnesses the discrepancy between the meme and non-meme stocks in how the social networks might affect the trend on the financial market. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2203.13790&r= |
| By: | John Cotter (Smurfit School of Business, University College Dublin); Enrique Salvador (Universitat Jaume I) |
| Abstract: | We estimate a discrete approximation of the risk-return trade-off for the US market by using the whole universe of stocks from July 1963 to September 2017. We find the relationship between return and total risk to be time-varying and also dependent on the level of risk considered. The proposed positive trade-off is mainly observed during low volatility periods and when we move from low risk up to medium-high risk investments. However, the direction of the trade-off is inverted for the highest risk alternatives especially during high volatility periods. The temporal variation of the risk- return trade-off can be explained by a series of sentiment, macro, credit risk, liquidity and corporate variables. All these determinants suggest that the positive relationship between return and risk is more evident during periods where economic, financial and market conditions improve. |
| Keywords: | time-varying risk-return trade-off, non-linear dependence, cyclical variation, panel regressions, asset pricing |
| JEL: | G10 G12 G15 |
| Date: | 2022–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:ucd:wpaper:202203&r= |
| By: | Eichfelder, Sebastian; Noack, Mona; Noth, Felix |
| Abstract: | We investigate the impact of the French 2012 financial transaction tax on trading activity, volatility, and price efficiency measured by first-order autocorrelation. We extend empirical research by analysing anticipation and reallocation effects. In addition, we consider measures for long-run volatility and first-order autocorrelation that have not been explored yet. We find robust evidence for anticipation effects before the effective date of the French FTT. Controlling for short-run effects, we only find weak evidence for a long-run reduction of trading activity due to the French FTT. Thus, the main impact of the French FTT on trading activity is short-run. We find stronger reactions of low-liquidity treated stocks and a reallocation of trading activity to high-liquidity stocks participating in the Supplemental Liquidity Provider Programme, which is both in line with liquidity clientele effects. Finally, we find weak evidence for a persistent volatility reduction but no indication for a significant FTT impact on price efficiency measured by first-order autocorrelation. |
| Keywords: | anticipation effect,financial transaction tax,long-run treatment effect,market quality,short-run treatment effect |
| JEL: | G02 G12 H24 M4 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwhdps:122022&r= |
| By: | Ivanov, Ivan T.; Zimmermann, Tom; Heinrich, Nathan W. |
| Abstract: | We examine recent regulation requiring US municipal governments to disclose private debt. We show that governments fail to disclose 55-80% of reportable debt events and that, conditional on disclosure, filings often omit contract details essential for bond pricing. Non-compliant issuers are also riskier than compliers, with disclosure decreasing in the potential of private debt to adversely affect bondholders. Event studies suggest that disclosure reveals positive news and is especially informative to investors in low-rated bonds or during market turmoil episodes. Overall, private debt disclosure remains largely voluntary, highlighting challenges to recent federal initiatives to increase transparency for municipal bond investors. |
| Keywords: | Bond pricing,disclosure regulation,private debt |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cfrwps:2205&r= |