Bayesian inference for Generalized Autoregressive Score models.

This repository includes different R scripts (with the data used) for the study and application of different topics from the study of Econometrics.

My project (in R) about analyzing the effect of the first COVID-19 outbreak to the Vietnam's stock market.

This is a project replicating the result of John Cochrane's famous paper about return's predictability (https://www.jstor.org/stable/40056861)

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 skl…

Code for the paper "Realized Semi(Co)Variation: Signs that All Volatilities are Not Created Equal"

Code and documents from Econ 690 at Duke

SMARTboost (boosting of smooth symmetric regression trees)

Foreign Exchange Forecasting Model created for the paper "Can Interest Rate Factors Explain Rate Fluctuations?"

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.

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.

Hurst exponent evaluation and R/S-analysis in Python

SMARTboost (boosting of smooth symmetric regression trees)

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

Find the best characteristics using various models to best predict the future returns

This is my personal website code

Employ linear and autoregressive models to forecast Ethereum prices based on historical data and lagged variables.

ARCH models in Python

Introduction to Python programming language, with a focus on basic data analysis and financial economics applications.

This repository supports the GSF-6053 - Financial Econometrics I course, which introduces students to the practical aspects of econometric methods and estimation techniques as applied in finance.