Posted inData

Refining historical data for investment strategies

Fund data

Covid-19 has put the relative merits of offensive and defensive investment strategies in the spotlight.

Uncertain market conditions may seem like the right time to play defence, shore up the balance sheet, and wait out the storm.

However, doing so risks losing out to firms that go on the offensive to capture growth, writes Andrew Barnett, global head of product strategy at Rimes.

What’s the plan?

Related to this topic is whether firms should invest in defensive or offensive data strategies.

The former prioritises operational and regulatory data demands, while offensive strategies leverage data to support core business objectives such as research, and the execution of investment strategies.

An offensive data strategy makes a more compelling case for investment because it can deliver tangible outputs against core business objectives.

However, what’s normally ignored in the busines case for such strategies is that the core data foundation of an organisation may not be in place or have the required flexibility.

For many firms, it may therefore make sense to source their defensive capabilities from a third-party provider so they can focus in-house resources and data science expertise on their offensive capabilities.

Building a foundation

Neither data capability should be seen as a stand-alone solution.

To deliver optimum value, firms need to put in place a strong, core data foundation that can feed both defensive and offensive use cases, and they need to be able to pivot between the two as the environment requires.

Here the volume and quality of historical data is important.

For defensive strategies, historical data must be easy to search and report on to meet relevant data requests from regulators.

For offensive strategies, historical data provides a rich source of signals for insights, analytics, and quantitative use cases.

However, sourcing high-quality market data for use in enterprise data management and market data management systems is often easier said than done.

This is particularly true of index and benchmark data, which is in a constant state of flux.

Most elements of an index or benchmark are liable to change including the methodologies used to calculate it and the file formats used to provide them.

Over time, even the ownership of benchmarks and indices can change.

Data that is delivered in a single benchmark or index today may well have been spread over several sources a few years ago.

The challenge for firms is therefore clear: to make sense of historical data from patchwork of formats, dispersed over a variety of systems, and of widely varying quality levels.

Firms without a chief data officer or the requisite data management skills may be completely unaware of this problem.

The presumption for many will be that their historical data is there when they need it, of the requisite quality level, and that the licenses associated with the data are unconstrained.

The reality will often fall far short of this expectation.

Putting the past in order

Firms need to quality control, validate, and standardise decades’ worth of market data and licenses if they are to optimise their data strategies.

This is a significant job of work and one which many firms today lack the resources to complete.

However, the cloud has opened the door to a range of managed data services that do the heavy lifting for firms.

By using third-party data experts, firms can access the skills and capabilities they need ‘as a service’, freeing them to focus on their core, alpha-generating, business activities.

Driving value tomorrow

Looking ahead, it seems likely that buy-side firms will increasingly look to such elastic services to support their data operations.

Andrew Barnett

In the short term, firms are having to manage a large portfolio of change at a time when their workforce is not always at 100% strength.

The ability to flexibly scale capabilities up and down as required will help mitigate this challenge.

If firms want to quickly put historical data to use to gain a competitive advantage in today’s market, then the elastic, cloud-based approach is a good bet.

Longer term, funds can use such services to drive down costs and increase operational efficiency.

As managed services leverage economies of scale they often cost less than in-house alternatives, savings that can be passed on to investors.

This would come as welcome news at a time when many investors seek reassurance.

Indeed, it’s likely that canny investors will see an advantage in investing in funds that take an offensive data strategy supported by managed data services.

After all, these are the funds that will be most proactive in seeking alpha and, freed from non-core data management tasks.

This article was written for Expert Investor by Andrew Barnett, global head of product strategy at managed data services and regtech solutions provider Rimes.

Part of the Bonhill Group.