ARCH models in Python

Hurst exponent evaluation and R/S-analysis in Python

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"

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

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)

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

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

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

SMARTboost (boosting of smooth symmetric regression trees)

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…

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.

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.