Macro variables and international stock return predictability

By David E. Rapach, M. Wohar, Jesper Rangvid. 2005

340 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/286cadf4b1d45162b93a4905c28ed21f0f73d11c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Muhammad Shahbaz
2. Rangan Gupta
3. Paresh Kumar Narayan
4. Ilhan Ozturk
5. N. Apergis
6. Afees A. Salisu
7. Sakiru Adebola Solarin
8. Russell Smyth *

In Finance

1. Rangan Gupta
2. Paresh Kumar Narayan
3. Allan G. Timmermann
4. N. Apergis
5. Afees A. Salisu
6. Kari Heimonen
7. Clement Kyei
8. Vania Stavrakeva

Citations in the corpus

• Impact of Macroeconomic Variables on Stock Markets: Evidence from Emerging Markets (2015, background): “These four variables are the most reliable macroeconomic variables that can explain stock markets fluctuations (Graham & Harvey, 2001; Kim, 2003; Rapach et al., 2005; Yau & Nieh, 2006; Adrangi et al., 2011).”
• Democracy, Political Risks and Stock Market Performance (2015, positive): “…the effects of macroeconomic factors and their relationship to equity returns (see e.g., Chen et al. (1986), Flannery and Protopapadakis (2002) and Rapach et al. (2005) and references therein) and has found monthly evidence, for example, that inflation, industrial production, term spread and…”
• Does the choice of estimator matter when forecasting returns (2012, methodology): “Many studies of predictive ability take as their benchmark the historical average forecast (see for example Rapach et al., 2005; Flood and Rose, 2010).”
• Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach (2017, result): “The decision to use a model of order one is to be not only consistent with the laglength choice of the Nishiyama et al. (2011) test which by design can only be estimated based on one lag, but also, we are in line with the stock returns predictability literature (see Rapach, Wohar, and Rangvid 2005).”
• Instability of Return Prediction Models (2006, background): “In contemporaneous research, Rapach and Wohar (2002) nd complementary evidence of instability in return regressions using US data and a broad set of forecasting variables.”
• The Continuing Puzzle of Short Horizon Exchange Rate Forecasting (2008, background): “(49)For example, Rapach and Wohar (2004) provide empirical evidence against pooling the monetary model coefficient across countries.”