Rasmus Olsen's repositories
HighFrequencyEconometrics-HAR-vs.-Neural-Networks
Inspired by Hillebrand & Medeiros (2009) and Corsi (2009), I put neural networks in a High frequency environment, and tested the performance of the two models (HAR & Neural Networks). - The data used in this project is 2 years worth of intraday 5-minute realized volatility (See: Sheppard, Patton, Liu, 2012) from 20 Dow Jones stocks, that has been scrutinized using bivariate analysis and manipulation into a single dimension.
Covid19-And-HighfrequencyEconometrics
I wrote my master thesis on the impact of Covid-19 related sentiment variables on the DJIA, in High Frequency Econometrics. Something I wish to share with you!
TrumpTweetsForecastingStockMarket
Inspired by Meryll Lynch and Bloomberg setting up instruments that followed the tweeting patterns of president Donald Trump: I did a project on the correlation between Donald Trump's tweets and the stock market. The project wanted to answer what data was more powerful when forecasting using only twitter data; the qualitative sentiment data, or the quantitative data.
BasketAnalysis
This repository contains my code for a basket analysis study.
RecommendationEngine
Just like Amazon, Netflix and vacation planners, I created a recommendation engine from rankings of products, in R. (Work in progress)
TensorflowNeuralNetwork
I created a deep learning model in R using 'Tensorflow' (Work in progress)
UtilizingPCAonCovidAndFF
In November 2020, I started to delve deeper into the rabbit hole of sentiment analysis. And what better way is there, than to merge my two favorite things: High frequency data and Sentiment analysis. (Work in progress)