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A. T. Tan's Projects

bitcoin_since_pandemic icon bitcoin_since_pandemic

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

cracking_ames_housing_ols icon 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

dynamic_customer_analytics icon dynamic_customer_analytics

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

em_bonds_diversification icon em_bonds_diversification

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

forecasting_air_pollution icon 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

hierarchical_clustering_of_currencies icon 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

latent_factors_in_stocks icon 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.

predicted_probabilities_bank_marketing icon 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

seasonality_treatments icon 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

simulating_spx_returns icon 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

top_python_hacks icon 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

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