W-Mrt
Quant Developer - Data Scientist Reasearch fields of interest: Finance, Complex Systems and Machine Learning M.Sc. Physics
Deutsche Bank
Pinned Repositories
A-Game-Theoretical-Approach-to-Smart-Grid-Energy-Cooperation
We present two game-theoretic models for energy transfer between service gateways of a smart grid, and find the conditions on the payoffs for reaching an energy cooperation scenario.
information_bottleneck
LaboratoryOfComputationalPhysics_Y4
Repo for Laboratory of Computational Physics, year 21-22
Low-Mass-X-ray-Binaries
The chief objective of this project is filtering the systems of our interest from datasets which were drawn from the SEVN population-synthesis code. The second part is to understand the population of low-mass X-ray binary systems (LMXBs) in young star clusters.
Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original
Machine Learning for Algorithmic Trading, Second Edition - published by Stefan Jansen
Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
R-for-stocks-analysis-simulations-and-portfolio-optimization
A project to analyze stocks, run simulations based on historical data, price forecasting and optimal portfolio building using Sharpe ratio and genetic algorithm
Simulation-of-a-positron-induced-Muon-Source
Investigate a possible muon source for high brilliance muon beam
Stochastic-Methods-for-Finance
Excel/Python application of stochastic methods for financial analysis
Wassersteain_Gan_financial_time_series
Neural Network and Deep Learning course
W-Mrt's Repositories
W-Mrt/Stochastic-Methods-for-Finance
Excel/Python application of stochastic methods for financial analysis
W-Mrt/A-Game-Theoretical-Approach-to-Smart-Grid-Energy-Cooperation
We present two game-theoretic models for energy transfer between service gateways of a smart grid, and find the conditions on the payoffs for reaching an energy cooperation scenario.
W-Mrt/information_bottleneck
W-Mrt/LaboratoryOfComputationalPhysics_Y4
Repo for Laboratory of Computational Physics, year 21-22
W-Mrt/Low-Mass-X-ray-Binaries
The chief objective of this project is filtering the systems of our interest from datasets which were drawn from the SEVN population-synthesis code. The second part is to understand the population of low-mass X-ray binary systems (LMXBs) in young star clusters.
W-Mrt/Machine-Learning-for-Algorithmic-Trading-Second-Edition_Original
Machine Learning for Algorithmic Trading, Second Edition - published by Stefan Jansen
W-Mrt/Machine-Learning-for-Asset-Managers
Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
W-Mrt/R-for-stocks-analysis-simulations-and-portfolio-optimization
A project to analyze stocks, run simulations based on historical data, price forecasting and optimal portfolio building using Sharpe ratio and genetic algorithm
W-Mrt/Simulation-of-a-positron-induced-Muon-Source
Investigate a possible muon source for high brilliance muon beam
W-Mrt/Wassersteain_Gan_financial_time_series
Neural Network and Deep Learning course
W-Mrt/Machine-Learning-for-Computational-Physics
Machine learning applications
W-Mrt/MAPD-B
W-Mrt/Mini-batch-k-Means-Clustering
Implement mini-batch k-means in PySpark distributed framework and test the performance of the algorithm on standard synthetic datasets
W-Mrt/Portfolio-Optimization-using-Machine-Learning
This repository is the result of our work for the course CSCI-SHU 360 Machine Learning
W-Mrt/Quant-Finance-With-Python-Code
Repo for code examples in Quantitative Finance with Python by Chris Kelliher
W-Mrt/R-for-Statistical-Analysis
R coding application for statistical analysis
W-Mrt/rpscrape
Scrape horse racing results data and racecards.
W-Mrt/sql_book
Code repository for the book SQL for Data Analysis
W-Mrt/Time-series-analysis-for-finance
Project for Business Economics and Financial Data (Unipd prof. M.Guidolin)