Zobrazeno 1 - 10
of 115
pro vyhledávání: '"CONG, LIN WILLIAM"'
Decentralized Finance (DeFi) is reshaping traditional finance by enabling direct transactions without intermediaries, creating a rich source of open financial data. Layer 2 (L2) solutions are emerging to enhance the scalability and efficiency of the
Externí odkaz:
http://arxiv.org/abs/2312.02660
Decentralized finance (DeFi) has the potential to disrupt centralized finance by validating peer-to-peer transactions through tamper-proof smart contracts, thus significantly lowering the transaction cost charged by financial intermediaries. However,
Externí odkaz:
http://arxiv.org/abs/2206.08401
Autor:
Cong, Lin William, Li, Siguang
Publikováno v:
In Journal of Economic Theory September 2024 220
Publikováno v:
Management Science, 2021
We build an endogenous growth model with consumer-generated data as a new key factor for knowledge accumulation. Consumers balance between providing data for profit and potential privacy infringement. Intermediate good producers use data to innovate
Externí odkaz:
http://arxiv.org/abs/2109.10028
We model a dynamic data economy with fully endogenous growth where agents generate data from consumption and share them with innovation and production firms. Different from other productive factors such as labor or capital, data are nonrival in their
Externí odkaz:
http://arxiv.org/abs/2109.10027
We build a deep-learning-based SEIR-AIM model integrating the classical Susceptible-Exposed-Infectious-Removed epidemiology model with forecast modules of infection, community mobility, and unemployment. Through linking Google's multi-dimensional mob
Externí odkaz:
http://arxiv.org/abs/2109.10009
We introduce systematic tests exploiting robust statistical and behavioral patterns in trading to detect fake transactions on 29 cryptocurrency exchanges. Regulated exchanges feature patterns consistently observed in financial markets and nature; abn
Externí odkaz:
http://arxiv.org/abs/2108.10984
This study reports on the current state-of-affairs in the funding of entrepreneurship and innovations in China and provides a broad survey of academic findings on the subject. We also discuss the implications of these findings for public policies gov
Externí odkaz:
http://arxiv.org/abs/2108.10982
We predict asset returns and measure risk premia using a prominent technique from artificial intelligence -- deep sequence modeling. Because asset returns often exhibit sequential dependence that may not be effectively captured by conventional time s
Externí odkaz:
http://arxiv.org/abs/2108.08999