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Our log-likelihood function is dependent on our β coefficient and the OU model's parameters theta, mu, and sigma. Visit Hudson and Thames Quantitative Research Blog to read the next steps in this tutorial, such as maximizing the log-likelihood function by applying maximum likelihood estimation (MLE) and establishing optimal stopping problem.
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Hudson and Thames Quantitative Research is a company known for its contributions to the field of quantitative finance, particularly in the development and application of advanced mathematical and statistical methods to financial data.
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The mission of Hudson and Thames is to promote the scientific method within investment management by codifying frameworks, algorithms, and best practices to build the world's central repository of ready to use implementations and intellectual property. For more information, see the Hudson and Thames website.
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Hudson & Thames is an engineering company that builds out quant python libraries consisting of the top algorithms found in the academic literature. We create cutting-edge solutions that are easy to integrate and provide an extensive variety of additional materials to make this process effortless for our clients. LEARN MORE
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Hudson & Thames 807 views1 year ago Advances in Financial Machine Learning Lecture Series Play all This lecture series covers many of the chapters in the textbook: Advances in Financial Machine.
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