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Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.

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ICvsML drawing

Done by Olesya Krasnukhina The main aim of this project is to investigate the impact of digital relational capital as a part of intellectual capital on the financial performance (exactly capitalization) of IT-companies from index NASDAQ-100 until the period between 2016-2020

The investigation relates to basic approaches of IC (intellectual capital) and BD (Big Data)

Research includes:

  1. Parsing, merging, dataset structure analysis, variables definition, proxi-indicators classification
  2. EDA: preprocessing data (imputation missing values with linear regression,kNN and random forests modeling, removing outliers by winsorizing, normalization by scaling), correlation analysis, descriptive statistics analysis, joint distribution analysis with pairplots, basic linear exploratory modeling
  3. Testing multicollinearity, heteroscedasticity, autocorrelation, cross-dependence
  4. Scpecification choice by testing hypothesis and hyperparameter tunning
  5. Model Estimation and validation
  6. Robustness analysis
  7. Conclusion

METHODOLOGY

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LINEAR SPECIFICATION CHOICE

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DATA

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RESULTS

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Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.

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