State-space models for statistical mortality projections
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Updated
Jul 15, 2022 - R
State-space models for statistical mortality projections
Artigo finalizado em 06/08/2021 como membro do Núcleo de Riscos & Derivativos, para o Clube de Finanças, Liga Acadêmica de Mercado Financeiro da UDESC & UFSC.
Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.
Useful graphs for financial projects
Essential techniques to assess financial risks
This project is a basic look into using R Programming to work on stocks.
Single and multi-assets portfolio analysis and forecast of Value at Risk (VaR) and Expected Shortfall (ES).
Repository for the course 'Financial Risk' at Gothenburg University
R package for nonparametric estimation of CES
Parts of code from my MSc. dissertation project. Uses yahoo API to load past stock data for training and backtesting various traditional and experimental models for VaR calculation. Written in R & Python.
To provide complete workflow from Inferential Analytics, Predictive Analytics, Prescriptive Analytics and Evaluate the performance of prescriptions
The goal of esreg is to simultaneously model the quantile and the expected shortfall of a response variable given a set of covariates.
Analyzer for Instruments of Dhaka Stock Exchange
The repo contains the main topics carried out in my master's thesis on operational risk. In particular, it is described how to implement the so called Loss Distribution Approach (LDA), which is considered the state-of-the-art method to compute capital charge among large banks.
R package providing functions for computing Expected shortfall (ES) and Value at risk (VaR)
Backtesting my current US stocks portfolio
Portfolio level (un)conditional risk measure estimation for backtesting using Vine Copula and ARMA-GARCH models.
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