at-tan Goto Github PK
Name: A. T. Tan
Type: User
Company: RBC Capital Markets
Bio: Financier by profession. Economist by training. Data scientist & essayist by inclination. Articles at https://at-tan.medium.com
Location: Singapore
Name: A. T. Tan
Type: User
Company: RBC Capital Markets
Bio: Financier by profession. Economist by training. Data scientist & essayist by inclination. Articles at https://at-tan.medium.com
Location: Singapore
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
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
Crafting & testing a dynamic Recency-Frequency-Monetary model as published in Towards Data Science on Medium.com
Analysing the diversification benefit of EM bonds in a global portfolio, as published in Towards Data Science on Medium.com
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
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
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 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
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 returns and crash risk for the S&P500 Index using long-run historical data, as published in Towards Data Science on Medium.com
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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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
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JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.