Although any measurement of risk shows the volatility of a market, investors demand an accurate, reliable way to understand the comparative risk of losing money.
In times of volatile market swings, companies and investors demand an accurate, reliable way to understand their financial risk.
Value at Risk (VaR) is a statistical measure used to quantify the potential risk of loss on any market exposure. It probabilistically answers the questions ‘what is my worst-case scenario, and how much could I lose if things go really badly?’
VaR is defined as the worst loss over a given time period, with a specified confidence level. So, for example, if VaR (1-day, 95%) is calculated at $1M, it means that we have 95% confidence we won’t lose more than $1M in a single trading day.
There are several methods used to calculate VaR, they tend to differ from company to company and are usually calibrated to suit their specific portfolio needs.
The Challenge for Vine Advisors
Our client had already been using a simple VaR model for a while. However, during the spring of 2020, several commodity prices – quite unexpectedly – turned negative. This behavior could not be modeled in their existing VaR model. Rather than adjust or refine the existing model, the client saw the need to take a new perspective.
They asked Vine Advisors to review their VaR approach in the context of their business. It was clear that a fundamental change was needed to accommodate negative commodity prices. Moreover, we were also able to see that the existing model had become outdated and difficult to maintain.
A key issue for their existing VaR model was that it required data to be manually fed in from very different systems. The company used two separate Energy Trading Risk Management Systems (ETRMs) for different product groups and business units. Each system had a different framework and format, and they couldn’t “talk” to each other easily. This meant the client had to painstakingly pull data from each system manually and feed it into a complex shared spreadsheet. This process was time-consuming, difficult to manage, and fraught with human error.
The Vine Advisors VaR Solution
From the start, we could see that this was not about simply changing the underlying mathematical engine to account for negative commodity prices. By redesigning the entire process, we took the opportunity to look at more automation, better process control, and much improved general ease-of-use.
The new VaR model we designed is able to access data from each of the two ETRM systems. It automatically makes key calculations and saves results into a database held in the cloud. This allows the client to generate the reports they need whenever they need them – from anywhere in the world.
As per the client’s request, we made sure that the outputs we developed would be familiar, comfortable spreadsheets that they would find intuitive and easy to follow. We also developed more modern, interactive Tableau dashboards to expand the client’s ability to interact with the data.
The Updated VaR Model Results
Vine Advisors hit the brief precisely. We handed over a system that now responds to negative pricing and changing conditions while automating manual processes–making the complex simple.
- It saves time. The client company used to spend up to an hour every day manually working through reports. The new automated system takes a few minutes.
- It saves money. The new system gives their management team vital, high-level insights across different business units, helping them understand and communicate risks more quickly and effectively.
- It’s more accurate. Where the old model reduced the portfolio to a few representative products, our improved system tracks the risk of hundreds of individual curves, so the client can trade with complete confidence.
