RBBRONDANI

Pinned Repositories

AI_Stock_Trading
Design pattern for critical stages in the development process of an AI Stock Trading Bot
Language:Python00
AIAlpha
Use unsupervised and supervised learning to predict stocks
Language:Python00
Algorithmic_Delta_Hedging
A library for black-scholes euro options pricing, algorithmic delta hedging, and visualization
Language:Python00
Algorithmic_Portfolio_Hedging
Algorithmic multi-greek hedges using Python
Language:Python10
AnalyzeTheChat
Python based whatsapp chat analyzer
Language:Python00
anomaliesinoptions
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
Language:Jupyter Notebook00
auction_project
Auction project, handling and classifying data
Language:Python00
Q-Fin
A Python library for mathematical finance
Language:Python10

RBBRONDANI's Repositories

RBBRONDANI/Algorithmic_Portfolio_Hedging
Algorithmic multi-greek hedges using Python
Language:Python10
RBBRONDANI/Q-Fin
A Python library for mathematical finance
Language:Python10
RBBRONDANI/AI_Stock_Trading
Design pattern for critical stages in the development process of an AI Stock Trading Bot
Language:Python00
RBBRONDANI/AIAlpha
Use unsupervised and supervised learning to predict stocks
Language:Python00
RBBRONDANI/AnalyzeTheChat
Python based whatsapp chat analyzer
Language:Python00
RBBRONDANI/Automatic_Portfolio_Optimization
A pipeline to optimize a portfolio of assets and test it against unseen data.
RBBRONDANI/Azure
Repositório para guarda de códigos desenvolvidos para Azure
Language:Python2 0
RBBRONDANI/bovespaStockRatings
Crawler for Fundamental analysis platform for BOVESPA stocks, generating a score for each share according to the selected criteria on the indicators.
RBBRONDANI/DegiroAPI
An unofficial API for the trading platform Degiro, with the ability to get real time data and historical data
Language:Jupyter Notebook
RBBRONDANI/Dynamic_Algorithmic_Trading_Systems
Dynamic algorithmic trading systems in Python using Interactive Broker's Python API
RBBRONDANI/finta
Common financial technical indicators implemented in Pandas.
RBBRONDANI/fundamentalista
Coletor de dados financeiros de empresas listadas na B3
RBBRONDANI/MarketAnalysis
Portfolio Theory, Options Theory, & Quant Finance
RBBRONDANI/MarkowitzPortfolioOptimization
Computing a solution for the optimal mean-variance tradeoff (maximising Sharpe Ratio) of a portfolio according to MPT.
RBBRONDANI/msg_parser
Python module to read, parse and converting Microsoft Outlook MSG E-Mail files.
RBBRONDANI/optionmatrix
Financial Derivatives Calculator with 168+ Models (Options Calculator)
RBBRONDANI/options_backtester
Simple backtesting software for options
RBBRONDANI/Pricing_Exotic_Options
Library for simulation and analysis of vanilla and exotic options
RBBRONDANI/public-apis
A collective list of free APIs for use in software and web development.
RBBRONDANI/pyBlackScholesAnalytics
Options and Option Strategies analytics for educational purpose using the Black-Scholes Model
RBBRONDANI/python_para_investimentos
Aplicações de Python para Finanças e Investimentos
RBBRONDANI/quantstats
Portfolio analytics for quants, written in Python
RBBRONDANI/Serverless-APIs
Guidance for building serverless APIs with Azure Functions and API Management.
RBBRONDANI/SmartThingsPublic
SmartThings open-source DeviceTypeHandlers and SmartApps code
RBBRONDANI/SP1500stockPicker
A machine learning approach to investment portfolio composition. The program analyzes the fundamentals of the listed companies on the S&P1500 in order to emit monthly buy signals.
RBBRONDANI/spacy-models
💫 Models for the spaCy Natural Language Processing (NLP) library
RBBRONDANI/stack-repo
Repositório para armazenamento de código e notebooks de postagens do blog e cursos.
RBBRONDANI/Stock-Market-Analysis
Analyzing stock market trends using several different indicators in quantum finance. I explore machine learning and standard crossovers to predict future short term stock trends.
RBBRONDANI/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
RBBRONDANI/Tutorials
Jupyter notebook tutorials from QuantConnect website for Python, Finance and LEAN.