The Impact of the Euro on the Return Structure of European Equity Markets

CFA Digest ◽  
2002 ◽  
Vol 32 (3) ◽  
pp. 72-74
Author(s):  
Bruce D. Phelps
Keyword(s):  
Equity Markets ◽  
The Impact ◽  
European Equity

Modeling Common Volatility and Dynamic Risk Premia in European Equity Markets

2002 ◽  
Author(s):  
Gregory Koutmos ◽  
Johan Anders Knif ◽  
George C. Philippatos
Keyword(s):  
Equity Markets ◽  
Risk Premia ◽  
Dynamic Risk ◽  
European Equity

scholarly journals Slow Decay of Impact in Equity Markets

2015 ◽  
Vol 01 (02) ◽  
pp. 1550007 ◽  
Author(s):  
X. Brokmann ◽  
E. Sérié ◽  
J. Kockelkoren ◽  
J.-P. Bouchaud
Keyword(s):  
Power Law ◽  
Equity Markets ◽  
Impact Model ◽  
Market Impact ◽  
Temporal Dependence ◽  
Raw Data ◽  
Slow Decay ◽  
First Approximation ◽  
Information Contents ◽  
The Impact

Using a proprietary dataset of meta-orders and prediction signals, and assuming a quasi-linear impact model, we deconvolve market impact from past correlated trades and a predictable return component to elicit the temporal dependence of the market impact of a single daily meta-order, over a 10-day horizon in various equity markets. We find that the impact of single meta-orders is to a first approximation universal and slowly decays to zero (or to a small value), possibly as a power-law. We show that autocorrelated order-flows and trade information contents fully accounts for the apparent plateau observed in the raw data. We discuss the possible bias introduced by the quasi-linear assumption.

Risk, uncertainty and stock returns predictability – a case of emerging equity markets

2018 ◽  
Vol 10 (4) ◽  
pp. 438-455
Author(s):  
Rakesh Kumar
Keyword(s):  
Stock Returns ◽  
Stock Markets ◽  
Structural Break ◽  
Negative Relationship ◽  
Equity Markets ◽  
Growth Period ◽  
Risk And Uncertainty ◽  
Content Type ◽  
International Equity Markets ◽  
The Impact

Purpose This paper aims to investigate the predictability of stock returns under risk and uncertainty of a set of 11 emerging equity markets (EEMs) during the pre- and post-crash periods. Design/methodology/approach Listed indices are considered to serve the proxy of stock markets with a structural break in data for the period: 2000-2014. As preliminary results highlight the significant autocorrelations in stock returns, Threshold-GARCH (1,1) model is used to estimate the conditional volatility, which is further decomposed into expected and unexpected volatility. Findings Results highlight that the volatility has symmetric impact on stock returns during the pre-crash period and asymmetric impact during the post-crash period. While testing the relationship of stock returns, a significant positive (negative) relationship is found with expected volatility during the pre-crash (post-crash) periods. The stock returns are found positively related to unexpected volatility. Research limitations/implications Business, political and other market conditions of sample stock markets are fundamentally different. These economies were liberalized in different years, which may affect the degree of integration with international equity markets. Practical implications The findings highlight that investors consider the impact of expected volatility in forecasting of stock returns during the growth period. They realize returns in commensurate to risk of their portfolios. However, they significantly reduce their investments in response to expected volatility during the recession period. The positive relationship between stock returns and unexpected volatility highlights the fact that investors realize extra returns for exposing their portfolios to unexpected volatility. Originality/value Pioneer efforts are made by using T-GARCH (1,1) procedure to analyse the problem. Given the emergence of emerging equity markets, new insight in dynamics of stock returns provide interesting findings for portfolio diversification under risk and uncertainty.

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