Liya Chu

ORCID: 0000-0003-2605-9361
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About
Contact & Profiles
Research Areas
  • Financial Markets and Investment Strategies
  • Stock Market Forecasting Methods
  • Complex Systems and Time Series Analysis
  • Market Dynamics and Volatility
  • Corporate Finance and Governance
  • Financial Reporting and Valuation Research
  • Financial Risk and Volatility Modeling
  • Data Stream Mining Techniques
  • Monetary Policy and Economic Impact
  • Banking stability, regulation, efficiency
  • Rough Sets and Fuzzy Logic
  • Sustainable Finance and Green Bonds

East China University of Science and Technology
2016-2022

Singapore Management University
2017

This study investigates the impact of investor sentiment on excess equity return forecasting. A high (low) may weaken connection between fundamental economic (behavioral-based nonfundamental) predictors and market returns. We find that although variables can be strong when is low, they tend to lose their predictive power high. Nonfundamental perform well during high-sentiment periods while ability deteriorates low. These paradigm shifts in forecasting provide a key understanding resolving...

10.1287/mnsc.2020.3834 article EN Management Science 2022-04-05

There is a recent debate and even doubt about whether fundamental economic variables can predict equity premium or not. Some remedies seem working well help in restoring the confidence on predictability. However, we show that those are fragile irrelevant some sense. The predictability gone again, with utilized, once market sentiment kicks to distort link between premium. In contrast, without using any remedies, still predicting power as long stays low not link. addition, many non-fundamental...

10.13140/rg.2.1.2949.7844 article EN SSRN Electronic Journal 2016-11-21

We examine the relation between firms' environmental, social, and governance (ESG) performance aggregate stock market returns. Based on 38 ESG scores, we construct a market-level index find its strong positive predictive power returns both in- out-of-sample, predictability stems from cash flow discount rate channels. Our findings are robust to alternative machine learning methods number of controls. novel result market-wide impact provides support for economy-wide importance associated policies.

10.2139/ssrn.3869272 article EN SSRN Electronic Journal 2020-01-01
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