Woonghyeon's passion project repository

Welcome to the DSLA Residency, the DAO testbed of DSLA Protocol!

Risk matrix vuetify component

This project employs ML algorithms for risk management to accurately predict credit defaults.

Vigilante Vixen has learned that there were many security vulnerabilities from their technical, behavioral, law, and human resources aspects. Despite us not being directly involved in offshore financial services or the legal profession, technology roles have a considerable amount of opportunity to review this case and implement security regulations

creating an ecommerce api using laravel

Excel/Python application of stochastic methods for financial analysis

Backtesting Algo-Trading Strategies, FinTech Analysis & Portfolio Optimization: NVDA, AMD, INTC, MSI vs S&P 500 Benchmark

Developed an end-to-end ML system on Azure to predict loan defaults, leveraging advanced data preprocessing, feature engineering, and machine learning models to optimize accuracy. This project includes a comprehensive suite of tools and techniques for robust financial risk assessment, deployed to enhance decision-making for high-risk exposures.

Variable Scale Evacuation Model, a tool for the design of risk mitigation strategies

🌎Tidyrisk Terraform stack

Portfolios. Made Better.

Efficient simulation in the CreditMetrics model with Julia

Taxonomy derived from APRA CPG 235 - Managing Data Risk (September 2013)

Portfolio project: Machine learning automation project for a lending company. Automated the calculation of fees that make each new transaction/customer profitable by predicting the expected financial loss based on probability of default, loss given default, and exposure at default risk models.

Risk Assessment Library

🌎Vulnpryer Terraform stack

Project Risk and Issue Tracking

In this repository, I will show to use the built-in R function to run Monte Carlo and how to make graphical user interface to calculate value at risk with Monte Carlo Simulation.

Paper where I try to achieve, by using information theory, a quantitative approach (this is, a unit measure well-defined) for performing evaluations that incorporates the inherent and residual risk into one probability.