Results-Oriented Solutions
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Emerging Topics Community Update
The article contains a description of the Emerging Topics Community. The focus of the article is what is a community, what makes the Emerging Topics Community special, and benefits of the Community. Included after the discussion on the community are ways to get involved and be a part of the community. -
Reproducible Research
This article summarizes use of programming collaboration tools and source and version control (SVC) to make research products reproducible. -
Deep Learning in Segregated Fund Valuation: Part I
Segregated Fund is a special investment fund to provide capital appreciation with embedded insurance features. The traditional methodology to estimate the capital reserve and pricing of contracts goes to Monte-Carlo based stochastic models due to its complexity. Recent research has introduced a deep learning model, Long Short-Term Memory (LSTM), to help cash flow projection for a Segregated Fund in its whole lifetime horizon. In this paper three new deep learning models are presented: Long Short-Term Memory with attention (LSTM-ATTN) to estimate the liability reserve and pricing Segregated Fund contracts, Wasserstein Generative Adversarial Network (WGAN) for stock return forecasting and Temporal Convolutional Network on GAN (TCN-GAN) for interest rate time series generation. As an example, the cash flow projection and Economic Capital for Segregated Fund portfolio are used to compare deep learning models against traditional models in terms of accuracy and computation efficiency. -
Actuaries Can Excel® at Data Science (Pun Absolutely Intended)
We explore the use of mito, a Python package that allows users to use excel-like point-and-click interface with large datasets in Python. -
Integrated and First Principles Modeling for Hybrid Life and Health Products
This article discusses the two main model types for modeling Hybrid Life and Health products - a claim cost model and an integrated first-principles model - and the pros and cons of each. This article also discusses how these models are constructed in practice, including common approaches and assumptions, and ways to model interplay of assumptions and sensitivities.
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