Technical experimentations to beat the stock market using deep learning :chart_with_upwards_trend:

Overview

DeepStock

Technical experimentations to beat the stock market using deep learning.

Experimentations

  1. Deep Learning Stock Prediction with Daily News Headline Analysis

    • An attempt to find the correlation between the daily news headlines and DJIA index.
    • More explained in this slide
  2. Automated Trading Bot using Deep Learning

    • Predicting a company's stock price based only on the price history of the company.
    • Recurrent Neural Networks
    • Convolutional Neural Networks
    • Deep Q NetWorks
    • In-progress
  3. Complex Analysis on Stock using Deep Learning

    • Take multiple features into account to predict the value of a company.
    • In-progress
  4. Portfolio Management using Deep Learning

    • Planned
  5. Macro Economics Analysis

    • Currency and Macro-Tracking-ETFs
    • Planned
You might also like...
End-to-end beat and downbeat tracking in the time domain.

WaveBeat End-to-end beat and downbeat tracking in the time domain. | Paper | Code | Video | Slides | Setup First clone the repo. git clone https://git

Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model

The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the

Predict stock movement with Machine Learning and Deep Learning algorithms

Project Overview Stock market movement prediction using LSTM Deep Neural Networks and machine learning algorithms Software and Library Requirements Th

Implementation of the bachelor's thesis "Real-time stock predictions with deep learning and news scraping".

Real-time stock predictions with deep learning and news scraping This repository contains a partial implementation of my bachelor's thesis "Real-time

Code for technical report "An Improved Baseline for Sentence-level Relation Extraction".

RE_improved_baseline Code for technical report "An Improved Baseline for Sentence-level Relation Extraction". Requirements torch = 1.8.1 transformers

🔥 TensorFlow Code for technical report:
🔥 TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"

🆕 Are you looking for a new YOLOv3 implemented by TF2.0 ? If you hate the fucking tensorflow1.x very much, no worries! I have implemented a new YOLOv

The implementation of our CIKM 2021 paper titled as:
The implementation of our CIKM 2021 paper titled as: "Cross-Market Product Recommendation"

FOREC: A Cross-Market Recommendation System This repository provides the implementation of our CIKM 2021 paper titled as "Cross-Market Product Recomme

Using python and scikit-learn to make stock predictions

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Forecasting directional movements of stock prices for intraday trading using LSTM and random forest
Forecasting directional movements of stock prices for intraday trading using LSTM and random forest

Forecasting directional movements of stock-prices for intraday trading using LSTM and random-forest https://arxiv.org/abs/2004.10178 Pushpendu Ghosh,

Comments
  • Syntax Error?

    Syntax Error?

    I ran the news analysis model, and after entering a headline, I got this:

    Traceback (most recent call last):
      File "predict.py", line 24, in <module>
        inp = input("type in today's news headline: ")
      File "<string>", line 1
        Stocks close down but post strong quarterly gains
                   ^
    SyntaxError: invalid syntax
    

    Note that I used python and python 3 as well

    opened by BasharAG 0
Owner
Keon
Keon
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.

Stock Trading Market OpenAI Gym Environment with Deep Reinforcement Learning using Keras Overview This project provides a general environment for stoc

Kim, Ki Hyun 769 Dec 25, 2022
Use deep learning, genetic programming and other methods to predict stock and market movements

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Linda MacPhee-Cobb 386 Jan 3, 2023
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies

Achilles Rasquinha 1.8k Jan 5, 2023
A Deep Reinforcement Learning Framework for Stock Market Trading

DQN-Trading This is a framework based on deep reinforcement learning for stock market trading. This project is the implementation code for the two pap

null 61 Jan 1, 2023
This project uses reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can learn to read tape. The project is dedicated to hero in life great Jesse Livermore.

Reinforcement-trading This project uses Reinforcement learning on stock market and agent tries to learn trading. The goal is to check if the agent can

Deepender Singla 1.4k Dec 22, 2022
Stock-history-display - something like a easy yearly review for your stock performance

Stock History Display Available on Heroku: https://stock-history-display.herokua

LiaoJJ 1 Jan 7, 2022
Time-series-deep-learning - Developing Deep learning LSTM, BiLSTM models, and NeuralProphet for multi-step time-series forecasting of stock price.

Stock Price Prediction Using Deep Learning Univariate Time Series Predicting stock price using historical data of a company using Neural networks for

Abdultawwab Safarji 7 Nov 27, 2022
The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in

Dinghan Shen 49 Dec 22, 2022
This is the codebase for Diffusion Models Beat GANS on Image Synthesis.

This is the codebase for Diffusion Models Beat GANS on Image Synthesis.

OpenAI 3k Dec 26, 2022
Codebase for Diffusion Models Beat GANS on Image Synthesis.

Codebase for Diffusion Models Beat GANS on Image Synthesis.

Katherine Crowson 128 Dec 2, 2022