at-tan
Financier by profession. Economist by training. Data scientist & essayist by inclination. Articles at https://at-tan.medium.com
RBC Capital MarketsSingapore
Pinned Repositories
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
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
Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com
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
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
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
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
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
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
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
at-tan's Repositories
at-tan/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
at-tan/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
at-tan/Dynamic_Customer_Analytics
Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com
at-tan/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
at-tan/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.
at-tan/EM_Bonds_Diversification
Analysing the diversification benefit of EM bonds in a global portfolio, as published in Towards Data Science on Medium.com
at-tan/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
at-tan/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
at-tan/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
at-tan/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
at-tan/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