cme
There are 0 repository under cme topic.
NDelventhal / cot_reports
cot_reports is a Python library for fetching the Commitments of Trader reports of the Commodity Futures Trading Commission (CFTC). The following COT reports are supported: Legacy Futures-only, Legacy Futures-and-Options Combined, Supplemental Futures-and-Options Combined, Disaggregated Futures-only, Disaggregated Futures-and-Options Combined, Traders in Financial Futures (TFF) Futures-only and Traders in Financial Futures (TFF) Futures-and-Options Combined.
Language:Python 102epam / java-cme-mdp3-handler
Java Market Data Handler for CME Market Data (MDP 3.0)
Language:Java 69dod38fr / config-model
Perl module to create configuration editor with semantic validation
Language:Perl 58vincent212 / CME-Market-Data-Handler
A minimalist, low-latency, HFT CME MDP 3.0 C++ market data feed handler implementing all required features
Language:C++ 29bbcho / risktools-dev
Risk tools for commodities trading and finance
Language:Jupyter Notebook 25databricks-industry-solutions / customer-er
Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence of each match
Language:Python 18Bootstrap your large scale forecasting solution on Databricks with Many Models Forecasting (MMF) Project.
Language:Python 15johan12345 / gcs_python
Graduated cylindrical shell CME model in Python
Language:Python 15imandra-ai / cme-mdp
Imandra Modelling Language CME MDP Model
Language:Jupyter Notebook 13Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.
Language:R 11FIX order manager client for fix order routing in C++ using QuickFIX engine can be used for Trading Technologies (TT) or CQG and others
Language:C++ 11- Language:JavaScript 8
- Language:Python 8
Connect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.
Language:Python 7CJuanvip / CMEOptions
Analyze the CME grain options markets in python
Language:Python 6LiXiang618 / Scrape-Futures-Specs-From-CME
Use futures symbols to search and get their contract specs From CME website
Language:Python 6- Language:HTML 5
Survival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.
Language:Python 5Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.
Language:Python 5Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated
Language:Python 4Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.
Language:Python 4pachterlab / biophysics
Repository for Pachter Lab Biophysics
Language:Python 4astronish16 / DBM--Drag-Based-Model
This repository provides the python-based code for Coronal Mass Ejection(CME) arrival forecast using Drag Based Model(DBM).
Language:Jupyter Notebook 3Clutchisback1 / GIT_THEM
Just a quick and dirty little script import all the github goodies I like to play with.
Language:Shell 3Identifying Campaign Effectiveness For Forecasting Foot Traffic
Language:Python 3- Language:Python 3
This repository provides a python code to infer morphological parameters of Coronal Mass Ejection using Cone model given by Xie et al.,2004.
Language:Python 2From display to video, the value of an impression can only be realized if an ad is viewed by a user. Therefore, when using programmatic advertising to buy inventory, it’s important to take viewability into account. In this Solution Accelerator, learn how to predict ad viewability to optimize your real-time bidding strategy.
Language:Python 2kolybelkin / java-cme-mdp3-handler
Java Market Data Handler for CME Market Data (MDP 3.0)
Language:Java 2Preempt churn with the Databricks Solution Accelerator for predicting subscriber attrition. Learn how to analyze behavioral data to identify subscribers with an increased risk of cancellation. Then use machine learning to quantify the likelihood to churn as well as indicate which factors explain that risk.
Language:Python 1Increase viewer retention through data-driven engagement strategies: analyze both streaming and batch data sets to ensure a performant streaming content experience that drives engagement and loyalty.
Language:Python 1DexterHaslem / cme-tools
various scripts to parse CME group end of day settlements and such
Language:Python 1lcn-m / cme-ms17-010-module
Fixed ms17-010 module for Crackmapexec
Language:Python 1pupak250194 / Physical-Methods-of-Biology---Enzyme-Reactions
Project for Physical Methods of Biology based on Kim JK, Tyson JJ (2020) Misuse of the Michaelis–Menten rate law for protein interaction networks and its remedy. PLoS Comput Biol 16(10): e1008258. https://doi.org/10.1371/journal. pcbi.1008258.
Language:C++ 1RosesHaveThorns / LASCOdownloader
Download images from the LASCO coronagraphs for CME analysis
Language:Python 1
