LIN WILLIAM CONG
DIGITAL ECONOMY AND
FINANCIAL TECHNOLOGY
Research Lab
Open Codes/Data Repositories
Panel Tree Package in R, TreeFactor on GitHub
https://github.com/Quantactix/TreeFactor
Based on "Growing Panel Trees to Harvest Basis Assets and Pricing Kernels" by Cong, Feng, He, & He (2022)
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Textual Factors Package in Python on GitHub
https://github.com/textualfactor/Text_Analysis
Based on "Textual Factors: A Scalable, Interpretable, and Data-Driven Approach to Analyzing Unstructured Information" by Cong, Liang, & Zhang (2019)
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Ethereum Ecosystem: Data and Visualization
http://drzhaoxi.org/DefiPaper/
Based on "Inclusion and Democratization Through Web3 and DeFi? Initial Evidence from the Ethereum Ecosystem" by Cong, Tang, Wang, & Zhao (2022)
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Value-Price Divergence Factor (1978-2018)
Download the factors here. ReadMe.
Based on "RIM-based Value Premium and Factor Pricing Using Value-Price Divergence" by Cong, George, & Wang (2022)
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Research Databases
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Crypto/Blockchain/DeFi-Related (primarily via DEFT Lab)
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Chainalysis​
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DeFiLama
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DeFi Pulse
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Dune Analytics
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Ethereum Improvement Proposals
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Etherscan
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Kaiko
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Moonstream
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Tronscan
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General Financial Markets Data (via DEFT Lab and FinTech Initiative)
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ETF Global​
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E-Commerce Transactions and Online Merchant Survey from JD.com
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WIND (for Chinese Financial and Economic Data)
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Corporate Data (via WRDS for SC Johnson affiliates)
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BoardEx (North America)​
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CRSP
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Compustat
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I/B/E/S Factset ownership v5
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OptionMetrics
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RavenPack
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RepRisk
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Others (via SC Johnson Research Servers or Johnson Research Library)
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FISD​
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ShortInterest (1997-2012)
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TAQ/DATQ
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Financial Times fDi markets (thanks to EMI and M&O area)
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Other Datasets:
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Bloomberg​
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Capital IQ Pro
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Edgar
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Eikon
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SDC Platinum
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Enterprise Survey Data in China from Peking University
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Online Survey of Micro-and-small Enterprises in China (OSOME)
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Computing and Storage Resources
Cornell resources
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CISER - Cornell Center for Social Sciences
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Six publicly shared high-powered virtual machines available to all Cornell University students. This resource is sufficient for most CPU- and memory-intensive applications.
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Johnson Management research server
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A collection of three virtual machines hosted by Johnson. Access is limited to Cornell students in the field of Management (Johnson Graduate School of Management).
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Cornell CAC - Cornell University Center for Advanced Computing
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The only Cornell service offering GPU-powered (as well as conventional CPU-powered) instances. Rates depend on the type of instance created.
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Cornell BOX service for Unlimited Storage
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Details available upon request.
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Outside resources
Limited computing resources are provided free of charge by Amazon (Amazon Web Services - AWS), Google (Google Cloud Services - GCS) and Microsoft (Microsoft Azure). Each service has a similar but different set of free services available.
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AWS - Amazon Web Services (free tier)
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GCS - Google Cloud Services (free tier)
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Azure - Microsoft Azure (free tier or through lab grants)
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Xi'an Jiaotong University Computer Clusters for Data from the Ethereum Ecosystem (through lab collaboration)
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Dropbox Professional (details available upon request)
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