LIMIT-TO-ARBITRAGE FACTORS AND IVOL RETURNS PUZZLE: EMPIRICAL EVIDENCE FROM TAIWAN BEFORE AND DURING COVID-19

2021 ◽  
pp. 2150004
Author(s):  
KHOA DANG DUONG ◽  
QUI NHAT NGUYEN ◽  
TRUONG VINH LE ◽  
DIEP VAN NGUYEN
Keyword(s):  
Transaction Costs ◽  
Stock Returns ◽  
Trading Volume ◽  
Negative Relationship ◽  
Idiosyncratic Volatility ◽  
Individual Investors ◽  
Limits To Arbitrage ◽  
Trading Activities ◽  
Using Data ◽  
The Relationship

This paper examines the impacts of limit-to-arbitrage factors on the returns of the idiosyncratic volatility (IVOL) puzzle in Taiwan before and during the Covid-19 pandemic. Although various studies explore the relationship between stock returns and IVOL, the empirical findings are mixed. We are motivated by unique market microstructures in Taiwan, such as individual investors’ aggressive trading volume and low transaction costs in Taiwan, discouraging arbitrary trading activities. Our empirical results indicate a negative relationship between IVOL and stock returns by using data from the Taiwan stock market. However, the IVOL anomaly does not exist during the Covid-19 pandemic, even in the small stocks sample. Besides, our findings suggest that four proxies of limits-to-arbitrage, such as reversal, transaction costs, turnover and Amihud’s Illiquidity, have statistically significant impacts on the return of IVOL anomaly in Taiwan except for the pandemic period. Finally, our finding suggests that the stock turnover is the only limit-to-arbitrage factor that helps investors earn arbitrary profits during the COVID-19 period.

Heterogeneous beliefs and idiosyncratic volatility puzzle: evidence from China

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mao He ◽  
Juncheng Huang ◽  
Hongquan Zhu
Keyword(s):  
Stock Returns ◽  
Trading Volume ◽  
Factor Model ◽  
Heterogeneous Beliefs ◽  
Idiosyncratic Volatility ◽  
Chinese Stock Market ◽  
Content Type ◽  
Volatility Puzzle ◽  
The Relationship ◽  
Idiosyncratic Volatility Puzzle

PurposeThe purpose of our study is to explore the “idiosyncratic volatility puzzle” in Chinese stock market from the perspective of investors' heterogeneous beliefs. To delve into the relationship between idiosyncratic volatility and investors' heterogeneous beliefs, and uncover the ability of heterogeneous beliefs, as well as to explain the “idiosyncratic volatility puzzle”, we construct our study as follows.Design/methodology/approachOur study adopts the unexpected trading volume as proxies of heterogeneity, the residual of Fama–French three-factor model as proxies of idiosyncratic volatility. Portfolio strategies and Fama–MacBeth regression are used to investigate the relationship between the two proxies and stock returns in Chinese A-share market.FindingsInvestors' heterogeneous beliefs, as an intermediary variable, are positively correlated with idiosyncratic volatility. Meanwhile, it could better demonstrate the negative correlation between the idiosyncratic volatility and future stock returns. It is one of the economic mechanisms linking idiosyncratic volatility to subsequent stock returns, which can account for 11.28% of the puzzle.Originality/valueThe findings indicate that idiosyncratic volatility is significantly and positively correlated with heterogeneous beliefs and that heterogeneous beliefs are effective intervening variables to explain the “idiosyncratic volatility puzzle”.

scholarly journals DOES DEFAULT RISK MATTER FOR INVESTORS IN REITS

2020 ◽  
Vol 24 (5) ◽  
pp. 1-14
Author(s):  
Yezhou Sha ◽  
Zilong Wang ◽  
Ziwen Bu ◽  
Nick Mansley
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Default Risk ◽  
Negative Relationship ◽  
Investment Strategy ◽  
Idiosyncratic Volatility ◽  
Asset Growth ◽  
Capm Beta ◽  
The Relationship

We investigate the relationship between default risk and REIT stock returns. A default risk long-short investment strategy generates a return of 15% per annum. We also evaluate a large number of potential explanations for the negative relationship between default risk and subsequent stock returns. We do not find robust evidence that the default risk premium can be explained by firm size, book-to-market equity, asset growth and idiosyncratic volatility. However, CAPM beta shows some promise in explaining the default risk premium. Our results shed further light on the role of default risk in investment in REITs.

scholarly journals Hubungan Perilaku Perdagangan Investor Dengan Volume Perdagangan Di Bursa Efek Indonesia

2009 ◽  
Vol 2 (1) ◽  
Author(s):  
Ghazali Syamni
Keyword(s):  
Trading Volume ◽  
Stock Exchange ◽  
Time Interval ◽  
Time Intervals ◽  
Using Data ◽  
Changes Over Time ◽  
Relationship Of ◽  
The Relationship ◽  
Order Pattern ◽  
Over Time

This paper examines the relationship of behavior trading investor using data detailed transaction history-corporate edition demand and order history in Indonesia Stock Exchange during period of March, April and May 2005. Peculiarly, behavior placing of investor order at trading volume. The result of this paper indicates that trading volume order pattern to have pattern U shape. The pattern happened that investors have strong desires to places order at the opening and close of compared to in trading periods. While the largest orders are of market at the opening indicates that investor is more conservatively when opening, where many orders when opening has not happened transaction to match. In placing order both of investor does similar strategy. By definition, informed investors’ orders more large than uninformed investors. If comparison of order examined hence both investors behavior relatively changes over time. But, statistically shows there is not ratio significant. This implies behavior trading of informed investors and uninformed investors stable relative over time. The result from regression analysis indicates that informed investors to correlate at trading volume in all time intervals, but not all uninformed investors correlates in every time interval. This imply investor order inform is more can explain trading volume pattern compared to uninformed investor order in Indonesia Stock Exchange. Finally, result of regression also finds that order status match has greater role determines trading volume pattern intraday especially informed buy match and informed sale match. While amend, open and withdraw unable to have role to determine intraday trading volume pattern.

scholarly journals The relationship between inter-organizational trust and performance

2012 ◽  
Vol 60 (4) ◽  
pp. 89-98 ◽  
Author(s):  
Roman Fiala ◽  
Martin Prokop ◽  
Iva Živělová
Keyword(s):  
Structural Equation ◽  
Organizational Trust ◽  
Negative Relationship ◽  
Fit Indices ◽  
Supplier Performance ◽  
Significant Negative Relationship ◽  
Model Fit Indices ◽  
And Performance ◽  
Using Data ◽  
The Relationship

The article deals with an investigation of the relationship between inter-organizational trust and performance. Using data obtained in a questionnaire survey in 373 organizations with more than 20 employees with their seat in the Czech Republic, we found the relationship between inter-organizational trust and supplier performance, mediated by the level of conflict. Also, the statistically significant negative relationship between inter-organizational trust and costs of negotiation and the statistically significant positive relationship between supplier performance and perceived performance were confirmed. The hypothesis on the statistically significant relationship between inter-organizational trust and negotiating costs was not confirmed. The structural equation modelling technique was used in the calculations. The calculated model fit indices (CFI, NFI, NNFI) with values over 0.9 demonstrate a very good quality of the model.

scholarly journals The Impact of Investor Sentiment on Return of Different Industries in Pakistan

2017 ◽  
pp. 1-23
Author(s):  
Sumayya Chughtai Et al.,
Keyword(s):  
Stock Returns ◽  
Principle Component Analysis ◽  
Negative Relationship ◽  
Investor Sentiment ◽  
Differential Impact ◽  
Future Period ◽  
Market Sentiment ◽  
Available Information ◽  
The Impact ◽  
The Relationship

We classify stocks in different industries to measure industrial sentiment based on principle component analysis in order to examine whether investor sentiment exerts a differential impact on stock returns across different industries. After having constructed industry-level sentiment indices we construct a composite investor sentiment index. Our results suggest that investor sentiment negatively affects current as well as future stock returns in Pakistan over the examined period. However, we find that the influence of investor sentiment varies substantially across different industries. We also find that the market sentiment index has a negative relationship with both current and future stock returns. We also show that the direction of the relationship between return and sentiment remains same for the current and future period. This indicates that investors overreact to the available information and mispricing exists for a prolonged time. Our results confirm that sentiment driven mispricing persists for upcoming time and stock markets are not fully efficient to adjust instantaneously.

More than just Noise? Examining the Information Content of Stock Microblogs on Financial Markets

2018 ◽  
Vol 33 (1) ◽  
pp. 50-69 ◽  
Author(s):  
Ting Li ◽  
Jan van Dalen ◽  
Pieter Jan van Rees
Keyword(s):  
Financial Markets ◽  
Stock Returns ◽  
Information Content ◽  
Computational Linguistics ◽  
Trading Volume ◽  
Abnormal Returns ◽  
Feature Reduction ◽  
Individual Investors ◽  
Market Sentiment ◽  
Aggregation Of Information

Scholars and practitioners alike increasingly recognize the importance of stock microblogs as they capture the market discussion and have predictive value for financial markets. This paper examines the extent to which stock microblog messages are related to financial market indicators and the mechanism leading to efficient aggregation of information. In particular, this paper investigates the information content of stock microblogs with respect to individual stocks and explores the effects of social influences on an interday and intraday basis. We collected more than 1.2 million stock-related messages (i.e., tweets) related to S&P 100 companies over a period of 7 months. Using methods from computational linguistics, we went through an elaborate process of message feature reduction, spam detection, language detection, and slang removal, which has led to an increase in classification accuracy for sentiment analysis. We analyzed the data on both a daily and a 15-min basis and found that the sentiment of messages is positively affected with contemporaneous daily abnormal stock returns and that message volume predicts 15-min follow-up returns, trading volume, and volatility. Disagreement in microblog messages positively influences stock features, both in interday and intraday analysis. Notably, if we give a greater share of voice to microblog messages depending on the social influence of microbloggers, this amplifies the relationship between bullishness and abnormal returns, market volume, and volatility. Following knowledgeable investors advice results in more power in explaining changes in market features. This offers an explanation for the efficient aggregation of information on microblogging platforms. Furthermore, we simulated a set of trading strategies using microblog features and the results suggest that it is possible to exploit market inefficiencies even when transaction costs are included. To our knowledge, this is the first study to comprehensively examine the association between the information content of stock microblogs and intraday stock market features. The insights from the study permit scholars and professionals to reliably identify stock microblog features, which may serve as valuable proxies for market sentiment and permit individual investors to make better investment decisions.

Sign in / Sign up

Export Citation Format

Share Document