This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market.

[email protected]">

Last update: Dec 25, 2022

Overview

GPlearn_finiance_stock_futures_extension

This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market. More specifically, this is an implementation that uses the GPlearn's symbolic transformer to find the alpha factors of the PTA futures contract listed in the Zhengzhou Commodity exchange located in China. Although this implementation has successfully found some alpha factors that have some ability to predict, there is always risk involved in any kind of financial trading.

The definiation and related resources surrounding GPlearn and alpha factors are also included in the notebook.

Be cautious while trading.
Be cautious while trading.
Be cautious while trading.
Be cautious while trading.

Owner

Chengwei [email protected]

I have just finished my economic studies undergraduate degree at UCSC and applying for master's degree.

[email protected]">

GitHub Repository

General Assembly Capstone: NBA Game Predictor

Project 6: Predicting NBA Games Problem Statement Can I predict the results of NBA games from the back-half of a season from the opening half of the s

1 Jan 14, 2022

You Only Look One-level Feature (YOLOF), CVPR2021, Detectron2

You Only Look One-level Feature (YOLOF), CVPR2021 A simple, fast, and efficient object detector without FPN. This repo provides a neat implementation

273 Jan 03, 2023

IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL.

IJON SPACE EXPLORER IJON is an annotation mechanism that analysts can use to guide fuzzers such as AFL. Using only a small (usually one line) annotati

146 Dec 16, 2022

Code for the paper Learning the Predictability of the Future

Learning the Predictability of the Future Code from the paper Learning the Predictability of the Future. Website of the project in hyperfuture.cs.colu

139 Nov 18, 2022

Constructing Neural Network-Based Models for Simulating Dynamical Systems

Constructing Neural Network-Based Models for Simulating Dynamical Systems Note this repo is work in progress prior to reviewing This is a companion re

21 Nov 25, 2022

Deep GPs built on top of TensorFlow/Keras and GPflow

GPflux Documentation | Tutorials | API reference | Slack What does GPflux do? GPflux is a toolbox dedicated to Deep Gaussian processes (DGP), the hier

107 Nov 02, 2022

Ranger deep learning optimizer rewrite to use newest components

Ranger21 - integrating the latest deep learning components into a single optimizer Ranger deep learning optimizer rewrite to use newest components Ran

266 Dec 28, 2022

[CVPR2021] Look before you leap: learning landmark features for one-stage visual grounding.

LBYL-Net This repo implements paper Look Before You Leap: Learning Landmark Features For One-Stage Visual Grounding CVPR 2021. Getting Started Prerequ

45 Dec 12, 2022

This repository is for DSA and CP scripts for reference.

dsa-script-collections This Repo is the collection of DSA and CP scripts for reference. Contents Python Bubble Sort Insertion Sort Merge Sort Quick So

9 Nov 22, 2022

Riemannian Geometry for Molecular Surface Approximation (RGMolSA)

Riemannian Geometry for Molecular Surface Approximation (RGMolSA) Introduction Ligand-based virtual screening aims to reduce the cost and duration of

11 Nov 15, 2022

Extreme Dynamic Classifier Chains - XGBoost for Multi-label Classification

Extreme Dynamic Classifier Chains Classifier chains is a key technique in multi-label classification, sinceit allows to consider label dependencies ef

6 Oct 08, 2022

Advances in Neural Information Processing Systems (NeurIPS), 2020.

What is being transferred in transfer learning? This repo contains the code for the following paper: Behnam Neyshabur*, Hanie Sedghi*, Chiyuan Zhang*.

36 Aug 26, 2022

Python PID Tuner - Based on a FOPDT model obtained using a Open Loop Process Reaction Curve

PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e

6 Jan 14, 2022

RLDS stands for Reinforcement Learning Datasets

RLDS RLDS stands for Reinforcement Learning Datasets and it is an ecosystem of tools to store, retrieve and manipulate episodic data in the context of

135 Jan 01, 2023

This code is 3d-CNN model that can predict environmental value

Predict-environmental-value-3dCNN This code is 3d-CNN model that can predict environmental value. Firstly, I built a model that can create a lot of bu

1 Jan 06, 2022

The project is associated with the recently-launched ICASSP 2022 Multi-channel Multi-party Meeting Transcription Challenge (M2MeT) to provide participants with baseline systems for speech recognition and speaker diarization in conference scenario.

M2MeT challenge baseline -- AliMeeting This project provides the baseline system recipes for the ICASSP 2020 Multi-channel Multi-party Meeting Transcr

81 Dec 08, 2022