scholarly journals A New Investor Sentiment Indicator Based on Return Decomposition

2016 ◽  
Vol 4 (2) ◽  
pp. 121-130
Author(s):  
Yuan Liu ◽  
Yan Shang ◽  
Jianming Shi ◽  
Shouyang Wang
Keyword(s):  
Financial Market ◽  
Explanatory Power ◽  
Investor Sentiment ◽  
Price Impact ◽  
Idiosyncratic Volatility ◽  
Capital Asset ◽  
Return Decomposition ◽  
Daily Data ◽  
Section Model ◽  
Asset Mispricing

AbstractThis paper extends the DSSW model to accommodate rational arbitrageurs, optimistic investors and pessimistic investors. We model the price impact by using daily data and create a new methodology to calculate the optimistic and the pessimistic. The new sentiment indicator has high correlation with the other traditional ones, and as a proxy variable of individual share or financial market on daily, it could distinguish the optimistic and the pessimistic. In the empirical research, we develop a time-series model and a cross-section model respectively to explore the explanatory power of highly frequent investor sentiment to idiosyncratic volatility and capital asset mispricing. The results show that the new sentiment indicator can explain 21.31% of idiosyncratic volatility to individual share on average, and it has a great explanation of 36% to capital asset mispricing.

Investor Sentiment and Flows into Treasury Funds

2018 ◽  
Keyword(s):  
Mutual Funds ◽  
Financial Market ◽  
Mutual Fund ◽  
Explanatory Power ◽  
Investor Sentiment ◽  
Fund Flows ◽  
Inflation Expectations ◽  
Relative Response ◽  
Financial Market Risk ◽  
Blue Chip

The author compares the relative response of Treasury fund flows to the sentiment-prone Michigan Survey of Inflation Expectations and to the Blue Chip Survey of Financial Forecasts, a professional forecast of inflation. The Treasury market is an ideal subject for examining whether or not sentiment affects flows: it is highly liquid, making it unlikely that it is hard to arbitrage, and inflation is the primary factor affecting its returns. Using mutual fund inflows into TIPs and Treasury mutual funds that occurred between January 1991 and June 2011, the author finds that the Michigan Survey is insignificantly related to flows into inflation-indexed TIPs and is positively related to flows into nominal Treasury funds. The Blue Chip Survey does not have incremental explanatory power. The evidence is consistent with a combination of a hedging motive and a flight to liquidity triggered by information in the Michigan Survey about households’ perception of financial market risk. The two motives reinforce each other in driving flows into nominal Treasury funds when the Michigan forecast of inflation is high, while they appear to cancel each other out in determining flows into the illiquid TIPS market.

Freedom Indices and Capital Asset Pricing Model: Some Malaysian Evidence

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Ying Tay Lee ◽  
Devinaga Rasiah ◽  
Ming Ming Lai
Keyword(s):  
Human Rights ◽  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Explanatory Power ◽  
Least Square ◽  
Press Freedom ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Cross Sectional

Human rights and fundamental freedoms such as economic, political, and press freedoms vary widely from country to country. It creates opportunity and risk in investment decisions. Thus, this study is carried out to examine if the explanatory power of the model for capital asset pricing could be improved when these human rights movement indices are included in the model. The sample for this study comprises of 495 stocks listed in Bursa Malaysia, covering the sampling period from 2003 to 2013. The model applied in this study employed the pooled ordinary least square regression estimation. In addition, the robustness of the model is tested by using firm size as a controlled variable. The findings show that market beta as well as the economic and press freedom indices could explain the cross-sectional stock returns of the Malaysian stock market. By controlling the firm size, it adds marginally to the explanation of the extended CAP model which incorporated economic, political, and press freedom indices.

What Drove the Increase in Idiosyncratic Volatility during the Internet Boom?

2010 ◽  
Vol 45 (5) ◽  
pp. 1253-1278 ◽  
Author(s):  
Jason Fink ◽  
Kristin E. Fink ◽  
Gustavo Grullon ◽  
James P. Weston
Keyword(s):  
Investor Sentiment ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
The Internet ◽  
Present Evidence ◽  
Public Firms ◽  
Specific Risk ◽  
Increasing Trend ◽  
Public Firm ◽  
Firm Maturity

AbstractAggregate idiosyncratic volatility spiked nearly fivefold during the Internet boom of the late 1990s, dwarfing in magnitude a moderately increasing trend. While some researchers argue that this rise in idiosyncratic risk was the result of changes in the characteristics of public firms, others argue that it was driven by the changing sentiment of irrational traders. We present evidence that the marketwide decline in maturity of the typical public firm can explain most of the increase in firm-specific risk during the Internet boom. Controlling for firm maturity, we find no evidence that investor sentiment drives idiosyncratic risk throughout the Internet boom.

scholarly journals Investor Sentiment In The Financial Market: A Survey

2021 ◽  
Author(s):  
Charles A. Aziegbemhin
Keyword(s):  
Neural Networks ◽  
Risk Management ◽  
Financial Market ◽  
Investor Sentiment ◽  
Management Tool ◽  
Market Behavior ◽  
Market Returns ◽  
Wide Acceptance ◽  
Comprehensive Survey ◽  
Alternative Markets

Many techniques like technical analysis, fundamental analysis, neural networks etc are used to forecast market behavior but none of these methods has been consistently acceptable forecasting tool. This thesis surveys more than 200 related published articles that study investor sentiment techniques as derived and applied to forecasting equity, debt and alternative markets. From the literatures, it shows that the application of investor sentiment for evaluating market behavior is gaining wide acceptance. Changes in investor sentiment can trigger changes in the valuation and pricing of assets, therefore offering the ability to forecasting market directions more accurately than other techniques. This study is the most comprehensive survey on investor sentiment techniques and its impact on forecasting a panel of assets in the equity, debt, derivative and other alternative investment markets. It examines forecasting as it affects sentiment, investor sentiment, it influence on market returns, news analytics and its use as profit and risk management tool.

scholarly journals Transactions Volume, Exchange Direction and Asymmetry of Volatility in Emerging Market: Evidence From Tunisian Stock Exchange

2020 ◽  
Vol 11 (6) ◽  
pp. 318
Author(s):  
Jaber Yasmina
Keyword(s):  
Stock Market ◽  
Financial Market ◽  
Stock Exchange ◽  
Emerging Market ◽  
Explanatory Power ◽  
Trading Activity ◽  
Auto Correlation ◽  
The Asymmetry ◽  
The Impact ◽  
The Relationship

This study is an attempt to explain the relationship between intraday return and volume in Tunisian Stock Market. Indeed, former researches avow that the trading activity have the main explanatory power for volatility. However, most theories measure the activity of transactions through the size of exchange or the number of transactions. Nevertheless, these components are not aware enough of the importance of the direction of exchange when explaining the phenomenon of asymmetry of volatility. In the most of studies, the technique “Augmented Tick Test” (ATT) is employed so as to identify the direction of exchange. Such technique is adapted for the markets directed by orders like the Tunisian financial market. Again, this paper shows that the impact of the direction of exchange differs according to the market trend. In other words, if the returns are positive, the transactions of sale (of purchase) generate a decrease (increase) of volatility; whereas, they induce an increase (drop) of volatility if returns are negative. This result stresses the significance of exchange direction in explaning the asymmetry of volatility. Moreover, throughout this study, one may affirm that “Herding trades” are at the origin of the increase of volatility, while the “Contrarian trades” reduce volatility. Similarly, the identification of the direction of exchange enables us to affirm that the transactions of the initiates are characterized by the absence of returns auto- correlation; whereas, the transactions carried out by uninformed investors present an auto- correlation of the returns. In fact, the sign of this correlation varies according to transaction direction.

Reinvestigate the Bid–Ask Bounce Effect and Pricing of Idiosyncratic Volatility: The Case of the Australian Market

2019 ◽  
Vol 22 (01) ◽  
pp. 1950004
Author(s):  
Bin Liu ◽  
Monica Tan ◽  
Marie-Anne Cam
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Explanatory Power ◽  
Idiosyncratic Volatility ◽  
Stock Liquidity ◽  
Stock Size ◽  
Country Specific

We investigate the bid–ask bounce effect on estimation of idiosyncratic volatility (IVOL) from asset pricing perspective using a comprehensive country-specific sample. We find that the idiosyncratic volatility–return relationship remains significant while controlling for stock size. However, the explanatory power of IVOL disappears completely when stock liquidity is controlled for. These findings support our argument that the bid–ask bounce effect on pricing of IVOL is strongly influenced by stock liquidity. Our results indicate that mid-price is the “true” price to measure IVOL of the least liquid stocks in the Australian stock market.

Revisiting Fama–French’s asset pricing model with an MCB volatility risk factor

2020 ◽  
Vol 21 (3) ◽  
pp. 233-251
Author(s):  
Xiaoying Chen ◽  
Nicholas Ray-Wang Gao
Keyword(s):  
Risk Factor ◽  
Asset Pricing ◽  
Explanatory Power ◽  
Investor Sentiment ◽  
Size Factor ◽  
Pricing Model ◽  
Volatility Risk ◽  
Content Type ◽  
Asset Pricing Model ◽  
Market Factor

Purpose Since the introduction of VIX to measure the spot volatility in the stock market, VIX and its futures have been widely considered to be the standard of underlying investor sentiment. This study aims to examine how the magnitude of contango or backwardation (MCB volatility risk factor) derived from VIX and VIX3M may affect the pricing of assets. Design/methodology/approach This paper focuses on the statistical inference of three defined MCB risk factors when cross-examined with Fama–French’s five factors: the market factor Rm–Rf, the size factor SMB (small minus big), the value factor HML (high minus low B/M), the profitability factor RMW (robust minus weak) and the investing factor CMA (conservative minus aggressive). Robustness checks are performed with the revised HML-Dev factor, as well as with daily data sets. Findings The inclusions of the MCB volatility risk factor, either defined as a spread of monthly VIX3M/VIX and its monthly MA(20), or as a monthly net return of VIX3M/VIX, generally enhance the explanatory power of all factors in the Fama and French’s model, in particular the market factor Rm–Rf and the value factor HML, and the investing factor CMA also displays a significant and positive correlation with the MCB risk factor. When the more in-time adjusted HML-Dev factor, suggested by Asness (2014), replaces the original HML factor, results are generally better and more intuitive, with a higher R2 for the market factor and more explanatory power with HML-Dev. Originality/value This paper introduces the term structure of VIX to Fama–French’s asset pricing model. The MCB risk factor identifies underlying configurations of investor sentiment. The sensitivities to this timing indicator will significantly relate to returns across individual stocks or portfolios.

Equity fund performance

2016 ◽  
Vol 33 (3) ◽  
pp. 359-376 ◽  
Author(s):  
Bin Liu ◽  
Amalia Di Iorio ◽  
Ashton De Silva
Keyword(s):  
Explanatory Power ◽  
Fund Performance ◽  
Idiosyncratic Volatility ◽  
Size Factor ◽  
Momentum Effect ◽  
Content Type ◽  
Fund Managers ◽  
Equity Funds ◽  
Fama And French ◽  
Fund Size

Purpose This paper aims to investigate whether idiosyncratic volatility is priced in returns of equity funds while controlling for fund size and return momentum. Design/methodology/approach Following Fama and French (1993), an idiosyncratic volatility mimicking factor and a fund-size factor are constructed. The pricing ability of this idiosyncratic volatility mimicking factor is investigated in the context of Carhart (1997). Findings Idiosyncratic volatility is an important pricing factor even when controlling for fund size and momentum. In addition, idiosyncratic volatility is strongly and positively associated with the momentum effect. Further, when controlling for the association between the momentum effect and idiosyncratic volatility, the explanatory power of the momentum factor almost disappears, which suggests the pricing of idiosyncratic volatility mediates momentum and returns. Originality/value These findings imply that both the idiosyncratic volatility factor and the fund-size factor should not be ignored by fund managers when evaluating the performance of the equity funds.

Worldwide security market anomalies

1994 ◽  
Vol 347 (1684) ◽  
pp. 495-509 ◽  
Keyword(s):  
Portfolio Management ◽  
Risk Measures ◽  
Explanatory Power ◽  
Investor Sentiment ◽  
Cash Flows ◽  
Security Market ◽  
Investment Performance ◽  
Other Information ◽  
Yield Factor ◽  
Earnings Trends

Systematic violations of security market efficiency occur in equity markets because of the timing and reaction to cash flows and other information, institutional constraints and policies, and investor behaviour. They lead to significantly different risk-adjusted returns to those expected. Taking these anomalies into account provides opportunity for superior investment performance. Classifying anomalies as fundamental or seasonal differentiates between individual securities and market timing with indices. Seasonal anomalies include the January small-firm, turn-of-the-month, holiday, and day-of-the-week effects. Seasonality calendars combine the various effects to provide daily return forecasts. Fundamental anomalies include price to earnings, price to book, market capitalization, dividend yield, earnings trends and surprises, and mean reversion effects. These variables add explanatory power to that from risk measures and yield factor models to separate the best from the worst performing individual securities. Anomalies are controversial, difficult to measure and variable in time through investor sentiment and futures anticipation. Their study is interesting and challenging, and they are useful in various areas of portfolio management.

scholarly journals On the Causes of the Eurozone Crisis

2016 ◽  
pp. 332-349 ◽  
Author(s):  
Tomasz Serwach
Keyword(s):  
Market Structure ◽  
Financial Market ◽  
Current Account ◽  
Explanatory Power ◽  
Institutional Quality ◽  
Quality Measures ◽  
Current Account Balance ◽  
Eurozone Crisis ◽  
Fundamental Causes ◽  
The Current Account

The paper examines the causes of the Eurozone crisis – they are divided into two categories: proximate and fundamental causes. Regarding the former, it seems that the current account balance should be seen as a crucial determinant of the GDP dynamics of the Eurozone members during 2008–2012. As far as the fundamental causes are concerned, the financial market structure and institutional quality measures are of the highest explanatory power. Econometric results indicate that measures taken to tackle the crisis (austerity and internal devaluation) may be ineffective in restoring growth and stability.

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