adityaaryan24 Goto Github PK

algorthmic-trading-using-cnn

This project is essentially the implementation of the paper “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach”

amer_op_neural_net

Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions: Source Code (CPU version)

books_forked

some books

btgym

Scalable, event-driven, deep-learning-friendly backtesting library

cte-sem2

Contains files that I used for teaching purposes

deep-reinforcement-learning-hands-on

Hands-on Deep Reinforcement Learning, published by Packt

deep_reinforcement_learning_course

Implementations from the free course Deep Reinforcement Learning with Tensorflow

fangoosterlee

Price options analytically given stock price characteristic function

financialengineering

Projects from Financial Engineering class

gs-quantify

interviewroom

Contains all important data structure and algorithms problems asked in interviews

longstaff_schwartz

A Python implementation of the Longstaff-Schwartz linear regression algorithm for the evaluation of call rights an American options.

machine-learning-for-finance

Machine Learning for Finance, published by Packt

machine-learning-for-trading

Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.

nnfsix

Neural Networks from Scratch in various programming languages

qualib-1

The one single library for all the quants out there.

quant_wing

Projects that I worked on as a member of the Quant Wing of the Wall Street Club

reinforcement-learning

Minimal and Clean Reinforcement Learning Examples

reinforcement_learning_for_stock_prediction

This is the code for "Reinforcement Learning for Stock Prediction" By Siraj Raval on Youtube

rl

My RL Journey. This repo contains some of the codes based on RL that I have written =.

rl-adventure

Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

rlstocks

Attempts to learn reinforcement learning on the stock market

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.

tutorials

Ipython notebooks for math and finance tutorials

wsc-quant-division