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Financial Machine Learning
Kelly, Bryan T.; Xiu, Dacheng - National Bureau of Economic Research - 2023
We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...
Persistent link: https://www.econbiz.de/10014322889
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The Technological Elements of Artificial Intelligence
Taddy, Matt - 2018
We have seen in the past decade a sharp increase in the extent that companies use data to optimize their businesses. Variously called the `Big Data' or `Data Science' revolution, this has been characterized by massive amounts of data, including unstructured and nontraditional data like text and...
Persistent link: https://www.econbiz.de/10012453413
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A Theory of Payments-Chain Crises
Bigio, Saki - National Bureau of Economic Research - 2023
This paper introduces an endogenous network of payments chains into a business cycle model. Agents order production in … bilateral relations. Some payments are executed immediately. Other payments, chained payments, are delayed until other payments … are executed. Because production starts only after orders are paid, chained payments induce production delays. In …
Persistent link: https://www.econbiz.de/10013537753
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How Abundant Are Reserves? Evidence from the Wholesale Payment System
Afonso, Gara; Duffie, Darrell; Rigon, Lorenzo; Shin, … - National Bureau of Economic Research - 2022
Before the era of large central bank balance sheets, banks relied on incoming payments to fund outgoing payments in … order to conserve scarce liquidity. Even in the era of large central bank balance sheets, rather than funding payments with … abundant reserve balances, we show that outgoing payments remain highly sensitive to incoming payments. By providing a window …
Persistent link: https://www.econbiz.de/10013477228
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The Virtue of Complexity in Return Prediction
Kelly, Bryan T.; Malamud, Semyon; Zhou, Kangying - National Bureau of Economic Research - 2022
The extant literature predicts market returns with "simple" models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to "complex" models in which the number of parameters exceeds the...
Persistent link: https://www.econbiz.de/10013334435
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Estimating the Impact of the Age of Criminal Majority : Decomposing Multiple Treatments in a Regression Discontinuity Framework
Mueller-Smith, Michael; Pyle, Benjamin; Walker, Caroline - National Bureau of Economic Research - 2023
This paper studies the impact of adult prosecution on recidivism and employment trajectories for adolescent, first-time felony defendants. We use extensive linked Criminal Justice Admin- istrative Record System and socio-economic data from Wayne County, Michigan (Detroit). Using the discrete age...
Persistent link: https://www.econbiz.de/10014337757
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Machine Forecast Disagreement
Bali, Turan G.; Kelly, Bryan T.; Mörke, Mathis; … - National Bureau of Economic Research - 2023
We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...
Persistent link: https://www.econbiz.de/10014337816
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CBDCs, Payment Firms, and Geopolitics
Berg, Tobias; Keil, Jan; Martini, Felix; Puri, Manju - National Bureau of Economic Research - 2024
: enhanced autonomy in payments …
Persistent link: https://www.econbiz.de/10015056184
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Machine-Learning the Skill of Mutual Fund Managers
Kaniel, Ron; Lin, Zihan; Pelger, Markus; Nieuwerburgh, … - National Bureau of Economic Research - 2022
We show, using machine learning, that fund characteristics can consistently differentiate high from low-performing mutual funds, as well as identify funds with net-of-fees abnormal returns. Fund momentum and fund flow are the most important predictors of future risk-adjusted fund performance,...
Persistent link: https://www.econbiz.de/10012938692
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Selecting Directors Using Machine Learning
Erel, Isil - 2018
Can an algorithm assist firms in their hiring decisions of corporate directors? This paper proposes a method of selecting boards of directors that relies on machine learning. We develop algorithms with the goal of selecting directors that would be preferred by the shareholders of a particular...
Persistent link: https://www.econbiz.de/10012453279