Risk Management in Energy Trading Market: 3 Key Challenges

Risk Management in Energy Trading Market: 3 Key Challenges

Risk Management in Energy Trading Market: 3 Key Challenges

Security, Speed, Reliability

How do systems address those and what are the areas for improvement?

As stated in McKinsey’s article The Future of Commodity Trading, “recent market developments include increased price transparency, greater access to structured and unstructured data […], contract standardization, new exchanges and platforms, and regulations“ resulting in “higher market participation, transaction volumes and costs, and speed to market”.

This results in increased volatility of the traded financial and physical products, and demands a more flexible response to the constantly changing market conditions. Given this, commodity traders and risk managers are facing new challenges and demanding more and more support for technologies. In this article we are going to focus on the top three of them, how systems address those and the room for improvement.


In the energy industry we operate, the risk of hacker attacks has increased due to recent geopolitical events. Data is the core of every trading business and analysis nowadays. Predictions and strategies based on this data are proprietary goods and key to financial success. The main challenge for every company is security. This becomes even more important given the regulations in the energy sector and the requirements for anonymization encryption and disclosure/reporting of transactions to the supervising authorities.

Volumes of digital, online and algorithmic trading are increasing and are supported by tools, systems or AI. The online exchange of sensitive data, as well as investments in IT security also escalate. The setup of proper encryptions, proxies, gateways, VPN tunnels and procedures to protect your data and trading systems becomes a must for every key player in the industry. With that, the area becomes more attractive for software engineers too.

As systems evolve, so do encryption algorithms. Hackers’ creativity grows and the IT security teams must follow. With the increased usage of nearshoring and consultancy services outside of a particular trading company, teams become more global. Data protection and the usage of proper authorization and authentication mechanisms are inevitable. Therefore, step number one in developing any new product, component or whole architecture is setting up the proper structures for granting functional and data permissions and securing the data transfer protocols.

This is an area where IT companies can provide expertise to trading companies, either by ways to customize the usage of already known systems and tools or by helping with the development of in-house systems to ensure the protection of this precious data.


Given the increasing data flows, speed becomes a significant challenge across the whole cycle: accessing, transforming, synchronizing, processing, storing, querying, and exchanging data. The companies that manage to implement the aforementioned process-cycle the fastest, would usually unlock trade potentials and arbitrages inaccessible to the ones who are slower. By using tools, systems and AI-based, self-learning and training programs, it is no longer a matter of minutes or even seconds – but milliseconds. The maximum response times become a key non-functional requirement in every new development. This is the area where an IT specialist can provide significant value not only for traders but for risk managers as well.

Position management in highly volatile market environments requires not only real-time monitoring and very frequent updates of data. It also requires quick reactions to new market trends. Full excellence and high efficiency can only be achieved by optimizing the whole chain of data flows to ensure maximum speed of data handling and decision making – and respectively, taking the appropriate actions. It is possible to improve in the following areas:

  • Optimizing access to data by caching or querying. This can be done either directly on a database level or via the usage of web-based services;
  • Acceleration of data transformation or processing via standardized ETL tools or own programs/algorithms;
  • Ensuring proper visualization of data to drive informed decisions using proper monitoring and BI tools;
  • Optimization of data exchange protocols and interfaces;
  • Applying proper data storage procedures provides maximum efficiency when trying to extract a particular data set;
  • Last but not least: ensure a proper orchestration of all components driving the data flows

The maximum speed in the above areas often results in maximizing profits and minimizing risks (sticking to the predefined limits) by quickly reacting to market changes, one-off events or reversing trends. This is where investments in IT can provide value and returns.


Speed, of course, means nothing, if you cannot rely on the data and the systems. This data should be of the desired quality and without errors or gaps. The systems should be constantly available. With that said, the next challenge is reliability. Without proper validations or constant and continuous/uninterrupted access to it, even the best data becomes worthless.

With the rise of cloud-based technologies, it is possible to deploy services to new services, restart or restore not running machines, and increase computational power remotely within a couple of minutes to avoid long-lasting disruptions or outages. IT specialists can help design the cloud architecture in the best and most reliable way, increase availability and minimize infrastructure/system costs. If traders or risk managers base their decisions on outdated or faulty data, there is a high chance that the decisions are wrong as well, sometimes with significant financial implications.

That is why energy (trading) companies increasingly invest in cloud-based architectures, while still keeping the above requirements on security and speed in mind in addition to reliability and availability. Minimum availabilities are becoming part of almost every contract for IT infrastructure or components. The need for 24/7 incident management and monitoring services increases as well, as trading happens in different locations and markets around the clock.

In summary, with the increased flows and availabilities of data, the volatile market conditions and the ever-increasing online trading, investments in proper IT infrastructure become very important. To maximize returns and minimize risks supported by the proper software and experts, companies need to tackle the challenges related to those continuously and with diligence. IT systems are a powerful weapon – however, if misused, their usage may lead to self-destruction.

Author: Konstantin Grigorov

Gas Storage – Always a Good Challenge

Gas Storage – Always a Good Challenge

Gas Storage – Always a Good Challenge

In my book, gas storage is among the most complex types of contracts to implement in an ETRM system. Below, you will find the challenges that an implementation will face when gas storage is concerned.

Contract terms

There are three main aspects of a storage contract:

  • Working gas volume (WGV) – how much gas you can have in the storage at any given point during the contract period
  • Injection capacity (IC) – how fast you can inject – typically per hour or per day
  • Withdrawal capacity (WC) – how fast you can withdraw

Some operators also have additional options or limitations:

  • Overrun penalties (balance going above WGV or injecting more per hour or per day than your IC or withdrawing faster than WC)
  • Seasonal limitations on IC and WC – depending on technology and whether overall the system is in “injection mode” or “withdrawal mode”. Essentially, if you are going against the flow, it either cannot happen fast enough, you have to pay more for it – or both of these

Capturing the different terms for the payments of the above conditions are typically complex to understand and model – they may be:

  • lump sums (typical for WGV)
  • volumetric payments – price per injected or withdrawn unit (for IC and WC)
  • a combination of the above
  • based on a fixed price or indexed to pretty much anything – I have encountered summer winter gas spreads, power indexing against year ahead contract, and a combination of the two

Volume movements

Once the storage contract is captured in a system, the more interesting movements affecting the balance also require some thinking.

To start with, capturing the initial fill level may be a challenge. There are two key items to it. You have to adjust the balance under a specific storage contract, but this is not an injection – gas is already there when you sign the contract – however, if you model the contracts separately in a system, you have to move from one to the other. Also, the value at which it enters the storage is a question – especially for the initial capture of a storage deal that may have ran for years.

In storage transfers are also a topic to consider, which is similar in terms of how it affects the balance – and easier to value. With them, gas is changing hands in the storage facility itself – often done with counterparties as a swap against a hub position to save injection and withdrawal fees. The complexity coming from these is to adjust the balance without adding in the system an injection or a withdrawal. Besides affecting the balance in the facility, the actual transaction with the counterparty has to be captured – and it may be a challenge to do these in one step for some systems.

Normal injections and withdrawals are usually straightforward to capture. The interesting part is what happens when a storage user goes into overrun. Ideally, the ETRM system should automatically calculate the penalty.


For the trading/portfolio management purposes, storage is typically valued as a time spread:

MTM (storage) = (Pwth*Qwth – Pinj*Qinj) – Total Storage Costs


Pwth, Pinj  are the market prices at the times respectively of withdrawal and of injection.

Qwth, Qinj are the quantities withdrawn and injected in the storage

Total Storage Costs are the payments for WGV, IC, WC, and overruns and other penalties

Note that for the calculation to make sense, Qwth has to be equal to Qinj – otherwise there is an unaccounted for imbalance between injections and withdrawals. This means that an estimation of when injected gas will be withdrawn has to exist and be marked against a forward curve. This is often counterintuitive – and sometimes an egg or a hen question arises – do you plan injections and withdrawals and then hedge against the plan, or do you buy and sell gas, and then see how storage fits in… Both ways are valid – again, depending on market conditions and company tactics.

In the case when injections and withdrawals are planned after some optimization process, the question of how you arrive at the plan comes up. And is the optimization part of the ETRM system – or a separate tool used for inputs.

Overall, storage is a really good exercise in stretching software capabilities. In my experience, the multiple views you can have on a storage (from the market perspective, an injection is a short position, but from the storage perspective, it increases the balance), and the complexity of the contractual terms and volume movements are not covered in any system completely.

Written by Ventsislav Topuzov