Utilities and information for the signals.numer.ai tournament

Related tags

Deep Learningdsignals
Overview

dsignals

Utilities and information for the signals.numer.ai tournament

using eodhistoricaldata.com

eodhistoricaldata.com provides excellent historical price coverage for the signals universe. There are two main challenges with it:

  1. Ticker mapping from bloomberg to eod tickers
  2. Lack of coverage for Japan, Czech Republic and New Zealand

Building the ticker map

To build the mapping from bloomberg_ticker to eodhd, use:

python build_eodhd_map.py

This will retrieve:

  • live_universe (a small 40 KB file just listing the ~5,340 tickers in current round)
  • historical_targets (a large 150 MB file, and extract ~13,370 unique historical tickers)
  • the bloomberg to yahoo map courtesy of Liam @ numerai

And follow the conversion logic in the python code and manual overrides in db/eod-overrides.csv to build eodhd-map.csv in the following format:

bloomberg_ticker yahoo data_provider signals_ticker
MONY LN MONY.L eodhd MONY.LSE
ANIM3 BZ ANIM3.SA eodhd ANIM3.SA
CAO US eodhd CAO.US
7013 JP 7013.T yahoo 7013.T

Download quotes from the correct data_provider

First find EODHD_TOKEN = "put_your_token_here" in the download_quotes.py file and insert your eodhd api token. Then running:

python download_quotes.py

will download each quote from the appropriate source (eodhd or yahoo) saving each ticker to a separate pickle file under ./data/ticker_bin. As of October 2021, this results in 10,900+ ticker histories.

How you can help

  • Some amount of experimentation is needed with Korean tickers (KO vs KQ extension) to get better fills for ~50 tickers.
  • Bloomberg Singapore ticker prefixes are very different than the yahoo or eodhd tickers. We are extracting the live universe prefixes from numerai yahoo map, but historical Singapore tickers would need to be manually mapped if anyone is up for the challenge.
  • The rest of the tickers seem to work well -- all feedback and advice is appreciated.
Owner
Degerhan Usluel
Degerhan Usluel
A generalist algorithm for cell and nucleus segmentation.

Cellpose | A generalist algorithm for cell and nucleus segmentation. Cellpose was written by Carsen Stringer and Marius Pachitariu. To learn about Cel

MouseLand 733 Dec 29, 2022
A project for developing transformer-based models for clinical relation extraction

Clinical Relation Extration with Transformers Aim This package is developed for researchers easily to use state-of-the-art transformers models for ext

uf-hobi-informatics-lab 101 Dec 19, 2022
Relaxed-machines - explorations in neuro-symbolic differentiable interpreters

Relaxed Machines Explorations in neuro-symbolic differentiable interpreters. Baby steps: inc_stop Libraries JAX Haiku Optax Resources Chapter 3 (∂4: A

Nada Amin 6 Feb 02, 2022
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression

Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec

17 Dec 05, 2022
Extension to fastai for volumetric medical data

FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari

Keno 26 Aug 22, 2022
This repo contains the official code of our work SAM-SLR which won the CVPR 2021 Challenge on Large Scale Signer Independent Isolated Sign Language Recognition.

Skeleton Aware Multi-modal Sign Language Recognition By Songyao Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li and Yun Fu. Smile Lab @ Northeastern

Isen (Songyao Jiang) 128 Dec 08, 2022
Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On

UPMT Generate fine-tuning samples & Fine-tuning the model & Generate samples by transferring Note On See main.py as an example: from model import PopM

7 Sep 01, 2022
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel

KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v

File systems and Storage Lab (FSL) 186 Nov 24, 2022
Efficient 3D Backbone Network for Temporal Modeling

VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and

102 Dec 06, 2022
This is a collection of our NAS and Vision Transformer work.

AutoML - Neural Architecture Search This is a collection of our AutoML-NAS work iRPE (NEW): Rethinking and Improving Relative Position Encoding for Vi

Microsoft 832 Jan 08, 2023
Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Fbone (Flask bone) is a Flask (Python microframework) starter/template/bootstrap/boilerplate application.

Wilson 1.7k Dec 30, 2022
dataset for ECCV 2020 "Motion Capture from Internet Videos"

Motion Capture from Internet Videos Motion Capture from Internet Videos Junting Dong*, Qing Shuai*, Yuanqing Zhang, Xian Liu, Xiaowei Zhou, Hujun Bao

ZJU3DV 98 Dec 07, 2022
REGTR: End-to-end Point Cloud Correspondences with Transformers

REGTR: End-to-end Point Cloud Correspondences with Transformers This repository contains the source code for REGTR. REGTR utilizes multiple transforme

Zi Jian Yew 108 Dec 17, 2022
Source Code for ICSE 2022 Paper - ``Can We Achieve Fairness Using Semi-Supervised Learning?''

Fair-SSL Source Code for ICSE 2022 Paper - Can We Achieve Fairness Using Semi-Supervised Learning? Ethical bias in machine learning models has become

1 Dec 18, 2021
[ICCV '21] In this repository you find the code to our paper Keypoint Communities

Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,

Duncan Zauss 262 Dec 13, 2022
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021

Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan

Jiaqi Gu 2 Jan 04, 2022
A state of the art of new lightweight YOLO model implemented by TensorFlow 2.

CSL-YOLO: A New Lightweight Object Detection System for Edge Computing This project provides a SOTA level lightweight YOLO called "Cross-Stage Lightwe

Miles Zhang 54 Dec 21, 2022
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021

LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie

Hieu Duong 7 Jan 12, 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 03, 2023