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Yingzi Zhu

Publications and source records attributed to Yingzi Zhu.

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Interpretable Factors of Firm Characteristics

We develop a new framework for constructing factors from firm characteristics that balances statistical efficiency and economic interpretability. Instead of using all characteristics equally, our method groups related characteristics and derives one factor per group. The grouping combines economic intuition with data-driven clustering. Applied to the IPCA model by Kelly et al. (2019), our approach yields economically meaningful factors that match or exceed standard IPCA in pricing performance. Using 94 characteristics from Gu et al. (2020), we show that our parsimonious, transparent factors outperform benchmarks in out-of-sample tests, demonstrating the value of embedding economic structure into statistical modeling.

q-fin.PR

Market Crowds' Trading Behaviors, Agreement Prices, and the Implications of Trading Volume

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor's attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd's trading action in terms of behavior analysis, and test two adaptive hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade a stock in efficient adaptation except for simple heuristics, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction and competition among themselves no matter whether it is highly overestimated or underestimated. This suggests that asset prices include not only a fundamental value but also private information, speculative, sentiment, attention, gamble, and entertainment values etc. Moreover, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes.

q-fin.GN