There are 1 repository under financial-econometrics topic.
Foreign Exchange Forecasting Model created for the paper "Can Interest Rate Factors Explain Rate Fluctuations?"
Companion to publication "Understanding Jumps in High Frequency Digital Asset Markets". Contains scalable implementations of Lee / Mykland (2012), Ait-Sahalia / Jacod (2012) and Ait-Sahalia / Jacod / Li (2012) Jump tests for noisy high frequency data
SMARTboost (boosting of smooth symmetric regression trees)
In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.
Code and documents from Econ 690 at Duke
Code for the paper "Realized Semi(Co)Variation: Signs that All Volatilities are Not Created Equal"
My project (in R) about analyzing the effect of the first COVID-19 outbreak to the Vietnam's stock market.
Bayesian inference for Generalized Autoregressive Score models.
This is a project replicating the result of John Cochrane's famous paper about return's predictability (https://www.jstor.org/stable/40056861)
This repository includes different R scripts (with the data used) for the study and application of different topics from the study of Econometrics.
Coding projects I have worked on, in R and Python. Predominantly includes utilizing code to recreate the Black Sholes Model, Greek Option calculator, Stochastic Process and Brownian Motion and other data science applications for finance. Python was also used primarily for machine learning applications in finance, using various functions from sklearn, random forests, among others to perform predictive analysis on data such as forecasting bitcoin prices, predicting loan default probability, and building neural networks with TensorFlow. R project involves importing datasets from excel as well as using R functions to relabel and tweak datasets that were initially incompatible. R was predominantly used to perform econometric analysis of data as well as basic statistical functions like finding P value and T value.
SMARTboost (boosting of smooth symmetric regression trees)
This is my personal website code
This repo contains a compiled dataset of Ethereum prices and R code for the detection of speculative bubbles using backward supremum augmented Dickey-Fuller procedure.