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Web application for pricing different commidity orders based on analytical models
Brief description
The project targets to support the product owner in developing an internal web application in context of energy trading. The focus is on analysing technical requirements, maintaining the product backlog and supporting technical tests. The aim of the application is to price customer orders for energy demands. Pricing is based on market data from energy trading exchanges as well as price forward curves, which are developed based on in-house analytical models.
Supplement
An application is being developed to support traders in preparing deals for energy trading exchanges. These deals originate in customer orders that are either provided automatically via an API or manually maintained based on e-mail information. Orders are priced internally in order to assess when and how they can best be hedged on the exchange market. A classic web application provides both an interface API for importing orders from upstream systems and the option of entering orders manually. In addition to general order data, it is also possible to upload the customer's specific energy demand for the desired time period of the order as a load profile in CSV format. Priced orders are stored in the application database so that they can be prepared and processed for further booking in the trading system.
Subject description
In order to be able to fulfil customer orders, these are hedged by placing respective deals on energy trading exchanges. To prepare and evaluate these hedges, key risk figures based on in-house analytical models are calculated as part of the order pricing process. These key figures support traders in the design and placement of hedge deals. Both price risks and proposals for financial hedges, which are value-neutral, are calculated as key figures. These hedges thus hedge the price (value) of an order. Alternatively, volume-neutral hedges would be possible, which would hedge the quantity of ordered energy instead of the price. So-called standard products are traded on the exchange, i.e. deals on a monthly, quarterly and annual basis.
Overview
- Industries Energy trading
- Specialist tasks energy trade
- DV tasks Requirements Engineering
- System environment multitier-architecture
- Procedure model Scrum
- Programming language Anaconda (Python), Python, Python pandas
- Development/ test tools Jupyter Notebook
- Standard software JIRA
Project start11.12.2024
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