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A variable annuity (VA) is a popular life insurance product created by insurance companies. The companies often apply hedging to mitigate the financial risk. In order to predict the performance VA products, insurance companies need to use Monte Carlo to calculate the Greeks (i.e., the sensitivities of the fair market values of the guarantees on major market indices) at future time points. However, such simulation comes with huge computational cost. In this project, you will apply machine learning models to predict the simulated values. You will be able to acquire highly in-demand skills in machine learning and data science, and apply such skills to solve a very important problem to the insurance industry. At the end of project, you will accumulate sufficient evidence to showcase your technical skills and achievements to potential employers, and likely a research publication.
Title page including name, course, unit, supervisory team;? Table of content ? Short Abstract summarizing thesis? Introduction – overview of research area and project? Background to your research area and project topic – what has been done to date? Use the literature synthesis you prepared to assist you in justifying this? Motivation / Rationale for this research project – why is it important?? Problem statement – what are key unsolved research issues in this problem domain?? Related work – a critical analysis of the literature, including review of key related work, limitations to date, areas the current research project is addressing? Research methodology you used – what method(s), why chosen, how carried out the research project described in this minor thesis? Problem analysis, assumptions, main technical contributions that you have made? Results, evaluation, discussion of your results? Conclusions, contributions of your research findings, key future work directions and possibilities? Bibliography – references to all literature using consistent and complete referencing – only references cited in the minor thesis should be included? Appendices (if needed)
could you please gather the information using ICML conference papers and sequence prediction should be used to overcome the problem and please mention what are the problems facing using those, because i need to submit thesis threw those papers based on sequence prediction.
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