Can economic policy uncertainty predict stock returns? Global evidence

Phan, Dinh Hoang Bach; Sharma, Susan Sunila; Tran, Vuong Thao

doi:10.1016/j.intfin.2018.04.004

Cited by 212 publications

(104 citation statements)

References 82 publications

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“…3 We do not discuss the derivation of the NW-FGLS estimator in detail because this has been explicitly explained and discussed in number of journal articles (see for instance, Devpura et al, 2018;Sharma, 2016;Phan, Sharma, Tran, 2018). In addition, the model has been extensively explained in the original paper of Narayan (2012, 2015).…”

Section: B Methodologymentioning

confidence: 99%

“…3 The key advantage of the WN-FGLS is that it allows us to control for three statistical aspects of the data and model that are important to the forecasting exercise. These issues relate to endogeneity already recognized as an issue in the predictability literature (see Sharma, 2016); persistency of predictor variables such that instead of diluting the information contained in predictor variables, we can use the variables in their level form; and heteroscedasticity-an issue recognized as a stylized fact in financial time-series data (see, e.g., Devpura et al, 2018;Phan, Sharma, Tran, 2018;Sharma, 2016; among others).…”

Section: B Methodologymentioning

confidence: 99%

See 1 more Smart Citation

Which Variables Predict Indonesia's Inflation?

Sharma¹

2019

BEMP

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We use an exhaustive list of Indonesia’s macroeconomic variables in a comparative analysis to determine which predictor variables are most important in forecasting Indonesia’s inflation rate. We use monthly time-series data for 30 macroeconomic variables. Using both in-sample and out-of-sample predictability evaluations, we report consistent evidence of inflation rate predictability using 11 out of 30 macroeconomic variables.

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Section: B Methodologymentioning

confidence: 99%

Section: B Methodologymentioning

confidence: 99%

Which Variables Predict Indonesia's Inflation?

Sharma¹

2019

BEMP

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“…Macrovariables of economic policy uncertainty ( EPU ) [ 73 ] and implied volatility index ( VIX ) [ 74 ] are also proven to contain stock-market information. Therefore, in order to ensure the robustness of the regression results, and to examine whether network entropy provides a different perspective from the local network indicators or macro factors, we introduced four groups of local network indicators, and EPU and VIX as controlled variables in the regressions to test Hypothesis 2:

where

;

denotes a variable of diameter;

denotes a variable of average closeness centrality;

represents a variable of average degree or average clustering coefficient,

denotes a variable of average betweenness centrality or average path length;

is a 6 × 1 coefficient vector.…”

Section: Resultsmentioning

confidence: 99%

Stock Net Entropy: Evidence from the Chinese Growth Enterprise Market

Han

Wan

et al. 2018

Entropy

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By introducing net entropy into a stock network, this paper focuses on investigating the impact of network entropy on market returns and trading in the Chinese Growth Enterprise Market (GEM). In this paper, indices of Wu structure entropy (WSE) and SD structure entropy (SDSE) are considered as indicators of network heterogeneity to present market diversification. A series of dynamic financial networks consisting of 1066 daily nets is constructed by applying the dynamic conditional correlation multivariate GARCH (DCC-MV-GARCH) model with a threshold adjustment. Then, we evaluate the quantitative relationships between network entropy indices and market trading-variables and their bilateral information spillover effects by applying the bivariate EGARCH model. There are two main findings in the paper. Firstly, the evidence significantly ensures that both market returns and trading volumes associate negatively with the network entropy indices, which indicates that stock heterogeneity, which is negative with the value of network entropy indices by definition, can help to improve market returns and increase market trading volumes. Secondly, results show significant information transmission between the indicators of network entropy and stock market trading variables.

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“…In terms of economic policy uncertainty, scholars have put a great deal of effort into investigating the linkage between economic uncertainty and firm‐level variables in recent years such as investment (Gulen & Ion, 2015; Kang et al, 2014; Liu & Zhang, 2019), cash holding (Demir & Ersan, 2017; Phan, Nguyen, Nguyen, & Hegde, 2019), stock return (Chiang, 2019; Phan, Sharma, & Tran, 2018), dividend policy (Farooq & Ahmed, 2019), the cost of capital (Drobetz, El Ghoul, Guedhami, & Janzen, 2018; Kim, 2019), acquisition (Nguyen & Phan, 2017) and earnings management (Yung & Root, 2019). In addition, few studies examine the direct impact of economic uncertainty on firm performance; Madanoglu and Ozdemir (2019) is one of the first studies demonstrating the negative effect of economic policy uncertainty on firm performance, in the hotel industry, in particular, which is derived from reducing investments or difficulty in access to credit under high uncertainty.…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Economic uncertainty, ownership structure and small and medium enterprises performance

Doan

Tran

2020

Australian Economic Papers

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This paper investigates the effect of economic uncertainty on the performance of small and medium enterprises (SMEs) over the period 2007-2016. This paper also examines the effects of ownership structure on the relation between Economic Uncertainty and firm performance. We find that an increase in economic uncertainty is negatively associated with the performance of SMEs. Our results also reveal that increased economic uncertainty is associated with a lower performance level for state-owned SMEs, whereas foreign-owned SMEs can better mitigate the negative impact of on their performance than domestic-owned firms.

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Can economic policy uncertainty predict stock returns? Global evidence

Cited by 212 publications

References 82 publications

Which Variables Predict Indonesia's Inflation?

Which Variables Predict Indonesia's Inflation?

Stock Net Entropy: Evidence from the Chinese Growth Enterprise Market

Economic uncertainty, ownership structure and small and medium enterprises performance

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