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
ESL: Event-based Structured Light

ESL: Event-based Structured Light Video (click on the image) This is the code for the 2021 3DV paper ESL: Event-based Structured Light by Manasi Mugli

Robotics and Perception Group 29 Oct 24, 2022
AoT is a system for automatically generating off-target test harness by using build information.

AoT: Auto off-Target Automatically generating off-target test harness by using build information. Brought to you by the Mobile Security Team at Samsun

Samsung 10 Oct 19, 2022
Negative Interactions for Improved Collaborative Filtering:

Negative Interactions for Improved Collaborative Filtering: Don’t go Deeper, go Higher This notebook provides an implementation in Python 3 of the alg

Harald Steck 21 Mar 05, 2022
WRENCH: Weak supeRvision bENCHmark

🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development

Jieyu Zhang 176 Dec 28, 2022
Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment This repository shows two tasks: Face landmark detection and Fac

BoomStar 51 Dec 13, 2022
QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

QQ Browser 2021 AI Algorithm Competition Track 1 1st Place Program

249 Jan 03, 2023
Audio2Face - Audio To Face With Python

Audio2Face Discription We create a project that transforms audio to blendshape w

FACEGOOD 724 Dec 26, 2022
Modelisation on galaxy evolution using PEGASE-HR

model_galaxy Modelisation on galaxy evolution using PEGASE-HR This is a labwork done in internship at IAP directed by Damien Le Borgne (https://github

Adrien Anthore 1 Jan 14, 2022
CVPR2021 Content-Aware GAN Compression

Content-Aware GAN Compression [ArXiv] Paper accepted to CVPR2021. @inproceedings{liu2021content, title = {Content-Aware GAN Compression}, auth

52 Nov 06, 2022
g2o: A General Framework for Graph Optimization

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

Rainer Kümmerle 2.5k Dec 30, 2022
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

Peter Baylies 55 Sep 13, 2022
Datasets, Transforms and Models specific to Computer Vision

vision Datasets, Transforms and Models specific to Computer Vision Installation First install the nightly version of OneFlow python3 -m pip install on

OneFlow 68 Dec 07, 2022
ECCV2020 paper: Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards. Code and Data.

This repo contains some of the codes for the following paper Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards. Code

Xuewen Yang 56 Dec 08, 2022
Awesome Remote Sensing Toolkit based on PaddlePaddle.

基于飞桨框架开发的高性能遥感图像处理开发套件,端到端地完成从训练到部署的全流程遥感深度学习应用。 最新动态 PaddleRS 即将发布alpha版本!欢迎大家试用 简介 PaddleRS是遥感科研院所、相关高校共同基于飞桨开发的遥感处理平台,支持遥感图像分类,目标检测,图像分割,以及变化检测等常用遥

146 Dec 11, 2022
CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

CausalNLP CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable. Install pip install -U

Arun S. Maiya 95 Jan 03, 2023
Code for technical report "An Improved Baseline for Sentence-level Relation Extraction".

RE_improved_baseline Code for technical report "An Improved Baseline for Sentence-level Relation Extraction". Requirements torch = 1.8.1 transformers

Wenxuan Zhou 74 Nov 29, 2022
[CVPR 2022] "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy" by Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Codes for this paper: [CVPR 2022] The Pr

VITA 16 Nov 26, 2022
Classify the disease status of a plant given an image of a passion fruit

Passion Fruit Disease Detection I tried to create an accurate machine learning models capable of localizing and identifying multiple Passion Fruits in

3 Nov 09, 2021
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search

CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is

Federico Galatolo 172 Dec 22, 2022
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight

Revisiting RCAN: Improved Training for Image Super-Resolution Introduction Image super-resolution (SR) is a fast-moving field with novel architectures

Zudi Lin 76 Dec 01, 2022