Backtesting investment strategies in minutes — not days — show how far fintech has come in enabling financial institutions to get value from their raw data. It means anyone can now take advantage of quant investing.
- Backtesting an investment strategy requires managing tens-of-thousands or more of data points, with pricing and financial data across many decades.
- Thomson Reuters QA Point, powered by Elsen, is a fintech product for financial institutions that anyone can use in quant investing.
- The cloud-based platform cuts the usually lengthy process of backtesting an investment strategy from days to minutes.
If you think back to the glow of green blinking rectangles on mainframe terminals, it’s easy to see that there have been major leaps in the way we interact with technology.
In the finance world, the ubiquity of the internet forced developers and designers to think hard about how to make online banking easy for everyone to use.
As people of all different ages, backgrounds and levels of tech-savviness came online, banks that built the most user-friendly sites gained an advantage in keeping existing customers and attracting new ones.
Introducing Thomson Reuters QA Point
In the early days, being able to check a balance online was really exciting, but we’re well past that now.
For example, with today’s mobile banking and financial apps, you can deposit checks from anywhere, monitor positions in your portfolio in real time, and execute trades with a few taps or swipes.
Heck, I can pay someone digitally now without even using my hands! A quick, “Hey Siri, pay Jane 5 dollars for coffee,” and Venmo will make the transfer immediately.
But here’s the problem. These really cool fintech advancements have mostly impacted personal finance.
Financial services caution
When it comes to the user experience of fintech, the consumer side has moved much faster than the business side.
For finance professionals that rely on technology to do their job every day, it might still feel like they’re back in the mainframe days when they compare personal fintech to what they’re using in their professional lives.
There are a lot of really good reasons for this.
For one, security and compliance has always been a primary concern in the financial services industry, causing institutions to rightfully take a more slow-moving and cautious approach to changing any core system.
And on top of that, the sheer complexity of changing these systems is just as much of a concern.
The volume of financial and market data that these systems process is massive and the same systems have been in place for decades because even the smallest disruption in access could have severe consequences for firms and their clients.
Quant investing challenges
Instead of “fixing” what’s not broken, the industry has taken a slow and cautious approach to patching or updating systems.
This has worked well in achieving the ultimate goal of providing an extremely stable technical foundation, but the dated technology is starting to impose real limits on user experience.
In other words, it’s not easy for people to access and use data in ways they want to and requires help from specialists and programmers with a high level of technical expertise.
Take the process of backtesting an investment strategy, for example.
When an asset or portfolio manager develops an idea they’d like to test, they talk to an analyst who then brings the request to an engineer or programmer.
They would then have to prepare datasets, comb through massive volumes of data to find the handful of companies they should be looking at, and perform the analysis.
It’s a process that can take days or weeks to return models that answer a portfolio manager’s questions.
Getting value from raw data
Figuring out new ways for people to work with so much data in an elegant manner is an immensely hard problem to solve.
It requires managing tens-of-thousands or more of data points with each of them covering pricing and financial data for every company globally for decades.
This data can’t just be thrown at a user with an expectation that they’ll figure out how to use it on their own.
That’s the exact problem firms are facing now where only engineers and programmers know how to get value from raw data.
There’s a lot of technical work that has to happen in the background to modernize systems and provide the technical foundation for a more streamlined user experience.
Figuring out how to best structure that data and provide an interface to make it useable can only happen after that modernization takes place.
Thomson Reuters QA Point, powered by Elsen, addresses both of these challenges, providing a fintech product for financial institutions that anyone can use.
Driving investment performance with Thomson Reuters QA Point, powered by Elsen
Friendlier user experience
Building on top of the modern technology offered by the Elsen nPlatform is what allowed Elsen and Thomson Reuters to create a friendlier user experience — one that’s been recognized for its innovative design alongside consumer applications.
Initial research involved speaking to a dozen financial firms representing a cross-section of different sizes and types of companies.
These included both quantitative funds that were already using some sort of systematic or data-driven investment approach, and fundamental investors who use a more traditional means for guiding investments.
Incorporating the needs, views and feedback of such a wide sample of the investment world helped to drive design decisions and ensure that the end product aligned with the goal of making Thomson Reuters data more accessible and usable to the widest range of customers.
Next, spending time with the Thomson Reuters team that provides data to institutional investors provided a top-down and bottom-up approach to creating the application and a 360-degree view of the workflows it needed to address.
Backtesting in minutes
The result is a point and click interface that, when combined with Elsen’s custom-developed command language, can serve everyone along the continuum from fundamental managers to those with more experience of quant investing.
It turns the days (and sometimes weeks) long process of backtesting into something that anyone can accomplish in minutes.
Making it simple for anyone to work with such vast amounts of data is no easy task, and it’s been a major barrier to giving institutional users the experience they need and deserve from their technology.
To see for yourself how this can be done with quant investing, take a closer look at Thomson Reuters QA Point, powered by Elsen.