Discount rate changes, stock market returns, volatility, and trading volume: Evidence from intraday data and implications for market efficiency

1999 ◽  
Vol 23 (6) ◽  
pp. 897-924 ◽  
Author(s):  
Carl R. Chen ◽  
Nancy J. Mohan ◽  
Thomas L. Steiner
2015 ◽  
Vol 29 (4) ◽  
pp. 3-8 ◽  
Author(s):  
Ulrike Malmendier ◽  
Timothy Taylor

This symposium provides several examples of overconfidence in certain economic contexts. Michael Grubb looks at “Overconfident Consumers in the Marketplace.” Ulrike Malmendier and Geoffrey Tate consider “Behavioral CEOs: The Role of Managerial Overconfidence.” Kent Daniel and David Hirshleifer discuss “Overconfident Investors, Predictable Returns, and Excessive Trading.” A number of insights and lessons emerge for our understanding of markets, public policy, and welfare. How do firms take advantage of consumer overconfidence? Might government attempts to rule out such practices end up providing benefits to some consumers but imposing costs on others? How are empirical measures of CEO overconfidence related to investment and the capital structure of firms? Can overconfidence among at least some investors help to explain prominent anomalies in stock markets like high levels of trading volume and certain predictable patterns in stock market returns?


2019 ◽  
pp. 097215091984522
Author(s):  
Kapil Choudhary ◽  
Parminder Singh ◽  
Amit Soni

Empirical evidence indicates that foreign institutional investors (FIIs) play a vital role in financial markets, and being the major players, they demonstrate positive feedback trading behaviour and usually follow one another’s actions. In order to examine this phenomenon, the present study endeavoured to unearth the relationship between foreign institutional investments (FIIs) and returns in the Indian stock market, trading volume and volatility. The return of the Nifty50 index has surrogated market returns, while volatility is represented by conditional volatility computed from Nifty50, from January 1999 to May 2017. The vector autoregression (VAR) results indicate a positive association between herding among FIIs and lagged market returns, while information asymmetry has no impact on herding. On the other hand, previous-day volatility has a significant bearing on the herding measure. Overall, the results portray a significant relationship between herding and stock market returns in India. The results of multivariate regression exhibit that market return was a primary factor for FII herding during the study period under consideration, while trading volume bore no relationship with herding. In case of market volatility, the empirical results are in congruence with the fact that during the period of the volatile market, FIIs prefer to not indulge in herding. Furthermore, the results of three sub-periods, that is, before, during and after the crisis, are similar to the results of the whole study period which indicates that the return is a prime and vital force for herding; on the contrary, market volatility appears to have a negative relationship with herding.


1999 ◽  
Vol 10 (06) ◽  
pp. 1149-1162 ◽  
Author(s):  
GIULIA IORI

We propose a model with heterogeneous interacting traders which can explain some of the stylized facts of stock market returns. A generalized version of the Random Field Ising Model (RFIM) is introduced to describe trading behavior. Imitation effects, which induce agents to trade, can generate avalanches in trading volume and large gaps in demand and supply. A trade friction is introduced which, by responding to price movements, creates a feedback mechanism on future trading and generates volatility clustering.


2021 ◽  
Vol 2 (2) ◽  
pp. 257-267
Author(s):  
Syed Usman Qadri ◽  
Naveed Iqbal ◽  
Syeda Shamaila Zareen

The purpose of this study is to determine the predictability of the Pakistani stock market's one-day forward returns by utilizing lagged daily returns for Pakistan, India, and Malaysia from 2006 to 2016. The findings indicate that lagged Pakistani market returns significantly predict Pakistani one-day ahead market returns. However, the other two growing stock markets, India and Malaysia, show no association with one-day ahead market returns. Mostly, stock market behavior in the pre-2008 and post-2008 eras was the same, although industry return behaviour was different due to the economic crisis of 2008. However, the Pakistani stock market one-day ahead returns predict the own Pakistani lag returns due to an inefficient market and prices do not follow a random walk. As a result, investors and financial analysts can foresee and generate anomalous returns by using previous data and information. Key words: Stock Market Returns Predictability, Stock Market crash, Market efficiency


2020 ◽  
pp. 0148558X2091341
Author(s):  
Panos N. Patatoukas

What is the link between stock returns and news about economic growth? Using consensus forecasts from the Philadelphia Fed’s Survey of Professional Forecasters, I find that the univariate association between stock returns and gross domestic product (GDP) growth forecast surprises is indistinguishable from zero. Although consistent with prior macro-finance research, this phenomenon is intriguing if one believes that the stock market should move in sync with the economy. I consider two non–mutually exclusive hypotheses for this puzzling phenomenon. The first hypothesis is that GDP growth forecast surprises are correlated with offsetting cash flow news and discount rate news. The second hypothesis is that GDP growth forecast surprises measure news about economic growth with noise. I extract a measure of market-level discount rate news using accounting data and find evidence consistent with the hypothesis of offsetting value-relevant news. Overall, this article makes an important step toward resolving evidence of a disconnect between stock market returns and news about economic growth. More broadly, this article illustrates how accounting constructs and methods can be applied to inform macro-finance questions.


GIS Business ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. 1-9
Author(s):  
Dhananjaya Kadanda ◽  
Krishna Raj

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.


Sign in / Sign up

Export Citation Format

Share Document