Moments of Cross-Sectional Stock Market Returns and the German Business Cycle

2020 ◽  
Author(s):  
Jörg Döpke ◽  
Karsten Müller ◽  
Lars Tegtmeier
Keyword(s):  
Stock Market ◽  
Business Cycle ◽  
Market Returns ◽  
Cross Sectional ◽  
Stock Market Returns

SHORT-TERM HERDING EFFECT ON MARKET INDEX RETURNS

2019 ◽  
Vol 14 (01) ◽  
pp. 1950004
Author(s):  
ANDREY KUDRYAVTSEV
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Price ◽  
Herd Behavior ◽  
Market Returns ◽  
Short Term ◽  
Cross Sectional ◽  
Stock Market Returns ◽  
Market Return ◽  
Market Index

The study analyzes the predictability of stock market returns based on the previous day’s cross-sectional market-wide herd behavior. Assuming that herding may lead to stock price overreaction and result in subsequent price reversals, I suggest that daily stock market returns may be higher (lower) following trading days characterized by negative (positive) market returns and high levels of herding. Analyzing the daily price data for S&P 500 Index and all its constituents and employing two alternative market-wide herding measures based on cross-sectional daily deviation of stock returns, I document that the days of both positive and negative market returns tend to be followed by price reversals (drifts), if the market-wide levels of herding are high (low). The herding effect on the next day’s stock market returns is found to be more pronounced following the days when the sign of the market return corresponds to the direction of the longer-term stock market tendency and the days characterized by relatively large stock market movements. The effect also remains significant after accounting for the specific numerical value of the market return.

Information Content of Aggregate Implied Volatility Spread

2020 ◽  
Author(s):  
Bing Han ◽  
Gang Li
Keyword(s):  
Stock Market ◽  
Implied Volatility ◽  
Market Returns ◽  
Cross Sectional ◽  
Macroeconomic News ◽  
Equity Options ◽  
Stock Market Returns ◽  
Out Of Sample ◽  
Macro News ◽  
One Year

Aggregate implied volatility spread (IVS), defined as the cross-sectional average difference in the implied volatilities of at-the-money call and put equity options, is significantly and positively related to future stock market returns at daily, weekly, and monthly to semiannual horizons. This return predictive power is incremental to existing return predictors, and it is significant both in sample and out of sample. Furthermore, IVS can forecast macroeconomic news up to one year ahead. The return predictability concentrates around macro news announcement. Common informed trading in equity options offers an integrated explanation for the ability of IVS to predict both future stock market returns and real economic activity. This paper was accepted by Tyler Shumway, finance.

scholarly journals Business Cycle Forecasts and their Implications for High Frequency Stock Market Returns

2011 ◽  
Vol 31 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Horst Entorf ◽  
Anne Gross ◽  
Christian Steiner
Keyword(s):  
Stock Market ◽  
Business Cycle ◽  
High Frequency ◽  
Market Returns ◽  
Stock Market Returns

Relationship between Foreign Portfolio Investments (FPI), Domestic Institutional Investors, and Stock Market Returns in India

GIS Business ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. 1-9
Author(s):  
Dhananjaya Kadanda ◽  
Krishna Raj
Keyword(s):  
Stock Market ◽  
Institutional Investors ◽  
Negative Relationship ◽  
Trading Strategies ◽  
Market Returns ◽  
Stock Market Returns ◽  
Foreign Portfolio Investment ◽  
Stock Market Return ◽  
Indian Stock Market ◽  
Feedback Trading

The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.

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