A small set of statistic and data-visualization function usefull for data science

My quant portfolio leverages quantitative finance and data-driven insights to optimize investment strategies. Using advanced models, statistical analysis, and machine learning, I develop systematic trading strategies to capitalize on market inefficiencies and generate alpha.

Supplemental materials and code from Park et al., 2018, "CFA of the Structure of Adult ADHD Symptoms"

Using PCA to reduce the dimension of data and for factor Analysis on Boston Housing Data

A graphical software for interactive rotational factor analysis and visualization of two-way data, mainly intended for vibrational spectra.

Código en R desarrollado en asesorías de investigación

MATLAB program and Tutorial Materials for SFA Prime

Recommendations on which characteristics are most important for determining whether a customer has a favourable perception of the microvan concept, to segment the market, and to determine which segment(s) would be good to target based on the analysis of data.

Explore the H1B Visa data from 2014 through a comprehensive multivariate analysis.

The project entailed identifying relevant items to wellbeing from the 'wellbeing module' of the World Values Survey questionnaire and running factor analyses to figure out the measurement structure of the identified scale.

Factor Analysis using PCA, SVD and BNN autoencoders

Life Expectancy Analysis (WHO)

This is a Multivariate Analysis Project in R. Here in I've taken Life Expectancy dataset which covers the data of 193 countries. On it I have applied techniques such as cleaning, EDA, Principal Component Analysis, Factor Analysis, Cluster Analysis and Regression.

Social Media Analysis using multivariate analysis in a Rutgers Business School Classroom

Analysis on characteristics of trending YouTube Videos – Using Data Visualization, Factor Analysis, Hierarchical Clustering and Text Mining in R.

Stepwise regression and factor analysis on world happiness data using SPSS