slides.com/qplum/deep-learning-in-trading
Disclosures: qplum LLC is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and, unless otherwise stated, are not guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Past performance is not indicative of future performance.
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Disrupting two huge business lines:
Nationwide job postings of traders
Nationwide job postings of quantitative analysts
Nationwide postings of Machine Learning jobs
Nationwide postings of AI jobs
Nationwide postings of FinTech jobs
In future, we should be investing with a trustworthy tool and not experts.
The tool should look at every aspect of the data.
The tool should be affordable and efficient.
The tool should know what we have learned already."
- Benjamin Graham
Disclosures: qplum LLC is a registered investment adviser. Information presented is for educational purposes only and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. Investments involve risk and, unless otherwise stated, are not guaranteed. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy discussed herein. Past performance is not indicative of future performance.
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By Gaurav Chakravorty
In this talk at Univ. of Pennsylvania, Gaurav will talk about some job trends in financial services to start and cover the transformational impact of A.I. and Deep Learning in making trading a scientific process. Deep learning has been very successful in social sciences and specially areas where there is a lot of data. Trading and investment management fits this paradigm perfectly. It is a social science and not a pure science, and we are generating petabytes of data everyday making it tough to learn from. With the advent of Deep Learning and Big Data technologies for efficient computation, we are finally able to use the same methods in investment management as we would in face recognition or making chatbots. This focus on learning a hierarchical set of concepts is truly making investing a scientific process, a utility.
