Filters (kalman, hodrick-prescott, moving average) together with comparison and sensitivity analysis (in notebook filters_with_parameters)+var analysis and granger causality test. Test for random walk (CE currencies using yfinance API)

Developed predictive models like ARIMA and logistic regression to analyze market trends and forecast movements. Employed statistical techniques like moving averages for trend insights and binary outcome predictions in financial analysis.

dual MA strategy. MA for moving average, May 2017

Series de tiempo - Julio César Martínez Sánchez

Exploring Weather Trends - Data Analyst Nanodegree with Udacity

This repository provides a Node.js application that calculates the Relative Strength Index (RSI) and other technical indicators like Moving Average (MA) for cryptocurrency pairs. The application uses WebSockets to stream live RSI and MA data.

To be paired with our models (Multivariate GARCH, Brownian Motion and Monte Carlo). My favorite two algorithms in this repository are the TWAP (Time Weighted Average Price) and VWAP (Volume Weighted Average Price) algorithms that combine and apply time series, with the afformentioned models to predict the random fluctuations in equity index pricing

In this project I have analyzed local and global temperature data and compare the temperature trends where I live (Amsterdam) to overall global temperature trends.

Summer research June 2020- September 2020. This repository contains code for the model and machine learning for growth control.