Ipython script to exemplify the methodology of fuzzy scoring to model exposure
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Updated
Feb 20, 2019 - Jupyter Notebook
Ipython script to exemplify the methodology of fuzzy scoring to model exposure
The project addresses the limitations of traditional risk tolerance questionnaires, which are often subject to errors due to behavioral biases and lack automation. By leveraging machine learning and detailed financial data, the project seeks to provide a more accurate and automated approach to determining an investor's risk tolerance.
Project as part of the course Introduction to risk modeling and management at the ETH Risk Center at ETH Zurich, held in spring 2024
Analysis of the risk process and forecasts for the development of the insurance company over the years.
Moving Average Convergence Divergence (MACD) computation and visualisation of Australian Stock Exchange Securities
Project for the Advanced time-series analysis 2022/23 class at Faculty of Economic Sciences, University of Warsaw. In this project we build several GARCH-class models and compare their performance in assessing risk of a cryptocurrency portfolio.
Fire climate dataset creation from NOAA API based on location and time for use in machine learning model. Is the project that motivated the creation of the library simple_noaa.
Vulnerability (Risk) Calculator
Mapping countries' risk', vulnerability and exposure to illicit financial flows
Predicting and characterizing recidivism in Colombia as part of a group project (Team 77) for DS4A certification.
California Geological Survey maps of flooding tsunamis could produce in Los Angeles County.
Risk measure for cryptocurrencies.
Code base for the independent study of "A Machine Learning Approach for US Mortgage Risk Analysis" by Sam Shi
A misclassification cost function optimization approach to a lean credit risk affinity model
Copula fitting in Python.
Variable selection for heterogeneous populations using the vennLasso penalty
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