# Yiyang Zhang's Research and Paper Reading Notes ## Introduction This website is an evolving archive of my research and paper-reading notes in finance, economics, econometrics, and related quantitative fields. It connects individual papers to broader research questions, methods, and debates. My primary focus is financial economics, especially asset pricing, behavioral finance, institutional investors, market microstructure, and option markets. I am particularly interested in how information, attention, investor demand, market design, and institutional constraints affect trading and asset prices. Notes in econometrics, economics, mathematics, machine learning, and artificial intelligence provide supporting theory and methods. Most paper notes include bibliographic information, a summary, key results, and methodology. Some also contain model derivations, identification assumptions, figures, code, or replication resources. These are working notes rather than formal literature reviews; readers should verify important claims and citations in the original papers. ## Explore - [[Finance]] — including [[Asset Pricing]], [[Behavioral Finance]], [[Institutional Investors]], [[Market MicroStructure]], [[Option Market]], and other finance fields. - [[Econometrics]] — research design, causal inference, and empirical methods. - [[Econ]] — microeconomics, macroeconomics, labor economics, and political economy. - [[Math for Finance]] — mathematical and statistical foundations. - [[CS & ML & AI]] — computer science, machine learning, and artificial intelligence. ## How to Use and Search the Notes 1. **Browse by topic:** Start from one of the research areas above and follow the links to narrower topics and papers. 2. **Search directly:** Use the magnifying-glass icon to search by paper title, author, journal, method, or keyword—for example, `investor attention`, `option demand`, or `difference-in-differences`. 3. **Try shorter terms:** If a full title gives no result, remove punctuation or search two or three distinctive words. 4. **Follow connections:** Use links, backlinks, or the graph view, when available, to discover related papers and methods. When using these notes for academic work, consult and cite the original paper. If referring specifically to my synthesis, cite the relevant webpage and include the access date.