From the course: The Data Science of Economics, Banking, and Finance
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Bias and risk in financial and economic modeling
From the course: The Data Science of Economics, Banking, and Finance
Bias and risk in financial and economic modeling
- [Narrator] In 1972, Luther Ingram had a hit with the song "If Loving You Is Wrong, I Don't Want to Be Right." And when it comes to data, maybe you don't want to be right either, at least not in the strictest possible sense of the word. You may be familiar with the famous line from the statistician George Box who said, "All models," all statistical models, "are wrong, but some are useful." What he meant by that is the analysis will never mirror the data exactly perfectly a hundred percent, but that's okay. It's okay to be approximate as long as it is useful. You think about this. Analysis is by necessity, by its nature, a simplification of the original data. And it makes me think of the simplifications in a game. You see these icons here. You know what they all are even though they are extremely low resolution. The game can still be enormously engaging even when it has low resolution representations like this. The simplifications are useful. They allow the game to run faster and on…
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Contents
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Data science and money8m 3s
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AI and LLMs in the financial world7m 33s
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Social trading and finance influencers5m 24s
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Social payment apps and informal banking4m 15s
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Cryptocurrencies and blockchain in finance11m 56s
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Responding to financial scams and frauds6m 46s
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Algorithmic and human-in-the-loop trading8m
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Automated reviews for loan, credit, and job applications6m 55s
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Correlation and causality in economic data8m 2s
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Privacy regulations and explainable AI7m 4s
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Bias and risk in financial and economic modeling7m 6s
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Careers for data scientists in economics, banking, and finance5m 17s
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