• This repository has been archived on 13/Feb/2022
  • Stars
    star
    6
  • Rank 2,539,965 (Top 51 %)
  • Language
    Jupyter Notebook
  • Created almost 3 years ago
  • Updated almost 3 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Statistical inference on the relationship between Bitcoin and several macro factors. The findings call into question two of the most widely-used arguments advocating further institutional investment in Bitcoin. Published in DataDrivenInvestor on Medium.com

More Repositories

1

Forecasting_Air_Pollution

Stacking a machine learning ensemble for multivariate time series forecasting, with the goal of predicting the one-period ahead PM 2.5 air pollution level, as published in Towards Data Science on Medium.com
Jupyter Notebook
40
star
2

Cracking_Ames_Housing_OLS

Linear regression modelling of the Ames housing dataset, with the goal of predicting the house sale price, as published in Towards Data Science on Medium.com
Jupyter Notebook
10
star
3

Dynamic_Customer_Analytics

Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com
Jupyter Notebook
9
star
4

Hierarchical_Clustering_of_Currencies

A clustering exercise of global currencies on three common financial market features using data from 2017 through 2019, as published in Towards Data Science on Medium.com
Jupyter Notebook
9
star
5

Latent_Factors_in_Stocks

Dynamic factor modeling to uncover the key latent factors driving the price behavior of some of the largest American large-cap equities. We examine how these factors affect individual stock prices, what they represent, and how they have fluctuated in the sample period. As published in the Data Driven Investor on Medium.com.
Jupyter Notebook
9
star
6

EM_Bonds_Diversification

Analysing the diversification benefit of EM bonds in a global portfolio, as published in Towards Data Science on Medium.com
Jupyter Notebook
8
star
7

Top_Python_Hacks

Data files and code for "Top Python Hacks for Finance" with Bitcoin and DXY Index daily data covering the five years through mid-July 2021, as published in Data Driven Investor on Medium.com
Jupyter Notebook
7
star
8

Predicted_Probabilities_Bank_Marketing

Predicted probabilities from machine learning classification algorithms may be used to tackle imbalance data. The study uses the Portuguese bank marketing dataset as a case study, as published in Towards Data Science on Medium.com
Jupyter Notebook
7
star
9

Simulating_SPX_Returns

Simulating returns and crash risk for the S&P500 Index using long-run historical data, as published in Towards Data Science on Medium.com
Jupyter Notebook
6
star
10

Seasonality_Treatments

Time and seasonality features are often ignored as an input in model calibration. Finding the optimal form of seasonality effects should be part of the model-building process. The study investigates the comparative performance of common seasonality treatments, as published in Towards Data Science on Medium.com
Jupyter Notebook
5
star