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| “Good” Uncertainty, “Bad” Uncertainty, and Stock Market Pricing:High-frequency Data in the Chinese Stock Market |
| CHEN Guojin, DING Jie, ZHAO Xiangqin
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| School of Economics, Xiamen University |
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Abstract In recent years, the relationship between stock market uncertainty and stock pricing has attracted widespread attention. One question is whether uncertainty is always “bad.” In fact, “good” uncertainty does exist. A typical example is when a company is ready to launch a new product; the market is optimistic about the new product, but uncertain how much profit it will ultimately bring. Thus, uncertainty can be decomposed into “good” uncertainty and “bad” uncertainty. Investors prefer stocks with “good” uncertainty exposure and dislike stocks with “bad” uncertainty exposure. To obtain stocks with high “good” uncertainty, investors must pay higher prices and accept lower expected returns. In comparison, stocks with high “bad” uncertainty have lower stock prices and high expected returns.
Following Barndorff-Nielsen et al. (2010), we use the realized positive semi-variance and realized negative semi-variance to represent “good” and “bad” uncertainty, respectively. “Good” uncertainty has a positive impact on stock prices. However, uncertainty also results in large fluctuations in stock prices. As positive semi-variance measures the price volatility as it relates to positive returns, it can effectively reflect the “good” uncertainty. A similar reasoning applies to the use of negative semi-variance to measure “bad” uncertainty. We further subtract the realized negative semi-variance from the positive semi-variance and then standardize it to get our key indicator – relative signed variation (RSV).
This study uses a sample of China's A-shares from the 2007 to 2017 period. High-frequency stock data are drawn from CSMAR, and non-high-frequency stock data are from RESSET. In addition, China's Economic Prospective Index is obtained from CEIC. The main conclusions of this study are as follows. First, consistent with our theoretical analysis, regardless of the sorting method we apply (single sort method and double sorts method), there is a significantly negative relationship between RSV and stock portfolio returns. When the sample is divided into five portfolios based on the RSV in ascending order, we find that the corresponding returns monotonically decrease from Portfolio 1 to Portfolio 5. This pattern remains even after we apply controlling variables such as realized volatility and realized skewness using a double sorting method, indicating that RSV is an important stock pricing factor independent of these variables. In comparison, the higher the RSV level, the higher the absolute value of the high-minus-low portfolio returns based on realized volatility. In addition, realized skewness loses its stock pricing capability after controlling for RSV. Second, we use a firm-level cross-sectional regression method to further verify the negative relationship between RSV and stock returns. After controlling for common pricing factors such as realized volatility, realized skewness, market beta, firm size, book-to-market ratio, momentum, and illiquidity, the significantly negative relationship between RSV and stock returns remains. Third, the relationship between “good” and “bad” uncertainty and risk premium is state-dependent. Based on the China's Economic Prospective Index, we separate the full sample into periods of high economic prosperity and low economic prosperity. The RSV corresponds to lower stock risk premiums during periods of high economic prosperity, but higher stock risk premiums in periods of low economic prosperity, which suggests that the stock risk premium is more sensitive to “good” and “bad” uncertainty risk exposures during period of low economic prosperity. Finally, using the “good” uncertainty and the “bad” uncertainty, we construct a low-minus-high portfolio and find that our constructed portfolio outperforms the market excess return portfolio, SMB portfolio, and HML portfolio as measure by the mean return and Sharpe ratio.
This study makes three academic contributions. First, the study decomposes the uncertainty at the micro level into “good” uncertainty and “bad” uncertainty, and finds that RSV is an important pricing factor in China's stock market. To the best of our knowledge, this is the first study to discuss the impact of “good” and “bad” uncertainty on Chinese stock market pricing. Second, a large number of studies have proven that skewness is a significant stock pricing factor. Although in economic logic there are some similarities between realized skewness and RSV, this study demonstrates that RSV has a stronger stock pricing power than realized skewness. Third, this study finds that the impact of “good” and “bad” uncertainty on stock prices is state-dependent, and RSV leads to a higher stock risk premium when the economy is less prosperous.
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Published: 23 July 2019
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