Modeling & Statistical Methods
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Maximizing Communication in Excel 365 with Dynamic Arrays, Lambda Functions, and ChatGPT
This article explains the benefits of using Let, Lambda, and Lambda Helper Functions in your Excel workbooks. The benefits discussed are extracting logic from cell references, version-controlling business logic, and using AI to convert logic to other languages for faster development of products. -
Model Validation 101: Bring Your Calculus Mindset!
Ideas for using calculus concepts to validate actuarial models. Focus is on reserve valuation models under PBR. Includes examples based on a simple Excel model. -
Illusion of Rationality
This article explores the fundamental differences between human thinking and the way Large Language Models (LLMs) generate responses. It illustrates how human decision-making involves multiple, often evolving, acceptance criteria, whereas LLMs rely on statistical probabilities to determine the most likely next word. -
Quantum Actuary：Reshaping Insurance Cognition
This article will mainly explore the quantum characteristics in some insurance phenomena. By using the quantum theory, this article will aim to revolutionize traditional insurance thinking, reshape the insurance cognition, and explore the new paths for modern actuarial science. -
Factorization Machines for High Cardinality Features (Part 4 of 4)
This is the fourth in a 4-part series where Anders Larson and Shea Parkes discuss predictive analytics with high cardinality features. In the prior episodes we focused on approaches to handling individual high cardinality features, but these methods did not explicitly address feature interactions. Factorization Machines can responsibly estimate all pairwise interactions, even when multiple high cardinality features are included. With a healthy selection of high cardinality features, a well tuned Factorization Machine can produce results that are more accurate than any other learning algorithm. -
Meet Hybrid Data: A Blend of Alternative and Traditional Data. A Case Study to Construct an Improved Inflation Index
In the following article, I introduce the concept of “hybrid data,” a combination of alternative and traditional data, which I illustrate through an example on inflation, to be of better value than considering purely a traditional data or alternative data source alone. We present a case where we use alternative data from Zillow, to improve upon the Consumer Price Index (CPI), and thus create an index that is more pertinent to consumers and investors alike. -
Deep Learning in Segregated Fund Valuation: Part 2
This article is the second part of an article that appeared in April 2022 on the Emerging Topics Community webpage. It will discuss the data preparation, hyperparameter tuning and selection, and the training and testing process of the deep learning models. To reach the final conclusions, the article will continue to compare the projected cash flow results from LSTM and LSTM-Attn with those from the traditional method, and evaluate the time series generations of interest rates and equity returns by WGAN and TCN-GAN -
The Probability Principle of Group Testing: The Full-Scale Nucleic Acid Testing in Tianjin
On January 9 2022, a full-scale nucleic acid testing in Tianjin was launched. Over 10 millions of people were tested with the results announced within 2 days. The speedy efficiency was partly due to group testing with 10 persons per group. With this background, the aim of this article is to explain the probabilistic principle underlying group testing. To make the expository vivid, some numerical results and figures were provided using R language, a popular software in actuarial science and statistics. -
Anders vs. Shea, Part 4: A Champion is Crowned
Shea Parkes, FSA, MAAA, and Anders Larson, FSA, MAAA, reveal the results of the competition and share some final thoughts on the 2021 Milliman Health Practice Hackathon. -
Anders vs. Shea, Part 2: Anders’ Story
Shea Parkes, FSA, MAAA, and Anders Larson, FSA, MAAA, are joined by Nick Vander Heyden to discuss the approach used by Anders’ team in the 2021 Milliman Health Practice Hackathon.
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