Pinned Repositories
anomaliesinoptions
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
Begin-Python
Learn to Use Github and enhance my Python skills
CardioGoodFitness---Descriptive-Statistics
Cardio Good Fitness Case Study - Descriptive Statistics
demo
Documents
General Stuff to read up on
Dynamic-Delta-Hedging
Project on Simulating Stock Paths and Option Prices and Dynamic Hedging along its lifetime
Exotic-Option-Pricing
Looking at Valuations of Barrier Call Options, Lookback Put and Vertical Spread (with Transaction Costs)
GuviPractise
Deep Learning Basics
mastering-python-for-finance-second-edition
Sources codes for: Mastering Python for Finance, Second Edition
Vanilla_Option_Pricing
Pricing a Simple European Call from Black Scholes PDE using numerical Method
suvrasoumya's Repositories
suvrasoumya/Dynamic-Delta-Hedging
Project on Simulating Stock Paths and Option Prices and Dynamic Hedging along its lifetime
suvrasoumya/Exotic-Option-Pricing
Looking at Valuations of Barrier Call Options, Lookback Put and Vertical Spread (with Transaction Costs)
suvrasoumya/anomaliesinoptions
In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
suvrasoumya/Begin-Python
Learn to Use Github and enhance my Python skills
suvrasoumya/CardioGoodFitness---Descriptive-Statistics
Cardio Good Fitness Case Study - Descriptive Statistics
suvrasoumya/demo
suvrasoumya/Documents
General Stuff to read up on
suvrasoumya/GuviPractise
Deep Learning Basics
suvrasoumya/mastering-python-for-finance-second-edition
Sources codes for: Mastering Python for Finance, Second Edition
suvrasoumya/Vanilla_Option_Pricing
Pricing a Simple European Call from Black Scholes PDE using numerical Method
suvrasoumya/minimal_flask_example_heroku
suvrasoumya/myscratchbook
suvrasoumya/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
suvrasoumya/olap
Python package to access OLAP data sources.
suvrasoumya/pytorch-mnist-GAN
suvrasoumya/QCF_Modelling
suvrasoumya/quantify-2016
Our submission for GS Quantify 2016
suvrasoumya/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.
suvrasoumya/suvrasoumya.github.io
suvrasoumya/Time-Series-Analysis-Statistical-Arbitrage
This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.