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, Tr…

Java Market Data Handler for CME Market Data (MDP 3.0)

Perl module to create configuration editor with semantic validation

A minimalist, low-latency, HFT CME MDP3.0 C++ market data feed handler and pcap file reader (MDP 3.0)

Accelerator for customer incentive investment using causal inference techniques

Risk tools for commodities trading and finance

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

Graduated cylindrical shell CME model in Python

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.

Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Lakehouse Platform.

FIX order manager client for fix order routing in C++ using QuickFIX engine can be used for Trading Technologies (TT) or CQG and others

Imandra Modelling Language CME MDP Model

From 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.

CME Arrival Time Prediction Using Convolutional Neural Network

CME iLINK3 Connectivity

Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.

Analyze the CME grain options markets in python

Use futures symbols to search and get their contract specs From CME website

Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.