Neural-Finance/Option_Pricing_Python Neural-Finance/Option_Pricing_Python

  • Stars
    star
    29
  • Rank 860,307 (Top 17 %)
  • Language
    Python
  • License
    MIT License
  • Created almost 4 years ago
  • Updated almost 4 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
Neural-Finance/Option_Pricing_Python
github

Neural-Finance

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

I use Python3 to try the experiments on the classic book <Options, Futures and other Derivatives>, the BS model and the sensitivity analysis on Greek Letters.

More Repositories

1

Financial_Feature_Engineering_cross_sample

【Framework】Let the neural network 'freely' learn the relationship between different stocks. An intuitive example in quantitative finance, tensorflow 1.3.0.
Python
25
star
2

XGboost_Index-Enhancement-Strategy

【Framework】A Multi Factor Strategy based on XGboost, its my homework project in Tsinghua, the Introduction to Quantitative Finance, 2019 Spring.
Python
15
star
3

Captcha-Recognition-Digit-Number

【Framework】This is a captcha recognition algorithm tailored for 4 length digit recognition. Written in CNN, Tensorflow 1.3-1.7.
Python
12
star
4

Tricks-in-Tensorflow

【Slide】Less attention questions about how to pruning a neural network.
Jupyter Notebook
9
star
5

Neural-Finance

【State-of-the-Art】Some truely worked idea, about how to use aritificial intelligence in quantitative finance.
HTML
8
star
6

Quantitative-Investment-Slide-THU

【Slide】It's a pre-class document for <Introduction to Quantitative Finance, Tsinghua, Master Program Course> written by me (Alex Fang). It includes statistics, prob, programming (python), visualization tools, etc.
Jupyter Notebook
7
star
7

Leading-Papers-Robustness-Oriented

Some leading papers in deep learning, which focused on robustness. I think it will be helpful to NeuralFinance.
2
star
8

Summary_LSTM_Stock_Price

【LSTM & Stock Price】Although all new birds proudly tell you that they can use lstm for stock prediction, all old bird will tell you the conclusion that LSTM can't do this job well. For me, I only want to tell you that, different settings really matter. You are sure about the best way to generalize the raw data, output length, network deepth, etc. These things worth your time and patience.
HTML
2
star