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Chongfeng Wu

Researcher at Shanghai Jiao Tong University

Publications -  50
Citations -  3338

Chongfeng Wu is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Volatility (finance) & China. The author has an hindex of 25, co-authored 39 publications receiving 2649 citations.

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Political connections, tax benefits and firm performance: Evidence from China

TL;DR: Li et al. as mentioned in this paper investigated the different effects of political connections on the firm performance of state-owned enterprises (SOEs) and privately owned enterprises and found that private firms with politically connected managers outperform those without such managers.
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Oil Price Shocks and Stock Market Returns: Evidence from Oil-Importing and Oil-Exporting Countries

TL;DR: In this paper, a structural VAR analysis of the stock market response to oil price shocks is presented, showing that the magnitude, duration, and even direction of response by stock market in a country to price shocks highly depend on whether the country is a net importer or exporter in the world oil market, and whether changes in oil price are driven by supply or aggregate demand.
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Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries

TL;DR: In this paper, a structural VAR analysis of the stock market response to oil price shocks is presented, showing that the magnitude, duration, and even direction of response by stock market in a country to price shocks highly depend on whether the country is a net importer or exporter in the world oil market, and whether changes in oil price are driven by supply or aggregate demand.
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Oil price shocks and agricultural commodity prices

TL;DR: In this article, a structural VAR analysis of agricultural commodity prices to oil price changes was conducted, and it was shown that the responses of agricultural prices to price changes depend greatly on whether they are caused by oil supply shocks, aggregate demand shocks or other oil-specific shocks mainly driven by precautionary demand.
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Forecasting realized volatility in a changing world: A dynamic model averaging approach

TL;DR: In this article, a dynamic model averaging (DMA) approach is used to combine the forecasts of the individual models, which can generate more accurate forecasts than individual model in both statistical and economic senses.