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Name: Ivan Letteri
Type: User
Company: AI/ML solution 4 Algorithmic Trading
Bio: Machine Learning for Algorithmic Trading
Location: University of L'Aquila
Name: Ivan Letteri
Type: User
Company: AI/ML solution 4 Algorithmic Trading
Bio: Machine Learning for Algorithmic Trading
Location: University of L'Aquila
Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).
The S&P 500 Market Index is analysed using popular statistical models such as SARIMA, ETS and GARCH. Additionally, a powerful open source forecasting package from Facebook, called Prophet, is also used.
Find the best time to buy and sell stock with transaction fe using Dynamic Programming, implementation in Python.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
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.
Tool to automate the daily review of trades
supertrend bot using python, pandas, and ccxt
Python API for interacting with the Switcheo decentralized exchange
Python wrapper for TA-Lib (http://ta-lib.org/).
telegram group scraper tool. fetch all information about group members
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
A use-case focused tutorial for time series forecasting with python
Grid search for multilayer perceptron neural network for modelling time series data
Trading journal that automatically generates statistics
Trading212 API
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges
TradingView Strategy Alert Webhook that buys and sells crypto with the Binance API
Let Python optimize the best stop loss and take profits for your TradingView strategy.
A collection of the various technical indicators implemented in Pine Script Language
A lightweight app for practicing your trading on Tradingview
⚙️ This bot listens to TradingView alerts via webhooks and sends them instantly to Telegram, Discord, Twitter and/or Email.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.