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Systematic investment combines the best of active and passive styles

It’s data and science-based, and has pushed Prescient Investment Management into the top 10% of performers against various benchmarks.
Image: Shutterstock

Systematic investing is a rules-based investment strategy that follows a disciplined, evidence-based process, and it’s surprising that it hasn’t been adopted by more fund managers.

It’s been shown over time to deliver superior returns to pure active or passive investment styles. It is designed to take emotions out of investment. If the last year has demonstrated anything, it is that emotions are investors’ worst enemy. Making knee-jerk reactions to market events without a dispassionate inspection of the data can cost a portfolio hugely over time.

Perhaps one explanation for the slow adoption of systematic investing is its heavy reliance on data science, with an evidence-led approach that takes the emotion out of investing and allows for better investment outcomes as decisions are based on rules. It requires skills not easily found in the investment space, from data analytics to quantitative analysis and even engineering.

Advocates of passive and active styles will both swear they follow the same rules-based approach but, when pressed, will concede that there is an element of judgment involved in investment decisions.

Prescient Investment Management has been a ‘systematic investor’ since its founding in 1998 and its clients have seen a steady gain in investment performance since then.

“Ours is a very mathematical approach that is less art and more science,” says Bastian Teichgreeber, chief investment officer at Prescient Investment Management.

“Our investment approach combines the strengths of passive investments with those of active strategies. Passive investing offers the benefits of low fees, low transaction costs and a low tracking error relative to the benchmark. Meanwhile, active investing provides the potential to deliver additional alpha [returns that beat the market average], while facilitating efficient allocation of capital and capturing market dislocations.

“Combining the attributes of passive and active management in this way results in a portfolio with highly efficient market exposure that is in line with the costs of passive funds and more cost effective than active funds.”

To build a truly evidence-based approach to investing, Prescient extracts more than a million data points each day from different data providers, independent research sources, and even Google Analytics (Google search terms often provide early warning signals of market moves).

“We systematically analyse this data, which drives our decision-making and our fund positioning. The information we extract from these large datasets is simply not available to ordinary investment styles, we gain an information advantage per definition,” says Teichgreeber.

How systematic investment works in practice

The empirical evidence used to drive investment decision-making is based on data that can be distilled into four broad categories: valuations, economics, financial conditions, and sentiment. These factors are based on a range of other underlying measures that give a deep, as well as broad-based, picture of prevailing financial market risks and opportunities. The composition of these indicators is then set against the history of expected returns.

These indicators are further broken down into about 20 sub-factors, which can be quantified and analysed to determine allocation to different asset classes: equities, bonds, credit, income money market and cash, real assets and foreign exchange.

“For example, when we enter a period of stretched valuations, low economic growth, tight financial conditions and deteriorating sentiment, these factors allow us to make a statistical assessment of what this means for future returns of any individual asset class. This tells us whether the expected return of a particular asset class in such a scenario is likely to be higher or lower given the underlying conditions, but will also tell us whether an investment decision comes with more, or fewer, tail events. This systematic process increases the odds of achieving a high hit ratio in tactical asset allocation decisions,” adds Teichgreeber.

Systematic investing should not be confused with passive investing

Systematic investing shouldn’t be confused with passive investing. It is as active as any other active investment approach and does not mean fewer tilts, less trading, or less willingness to express views, says Teichgreeber.

It also differs from active investing in that asset allocation tilts take place within a predefined bandwidth. Risk management is more pronounced, and the probability of success of the trade is calculated beforehand. Unlike traditional active asset managers, systematic investors don’t engage in the selection of individual shares, but rather in an enhanced indexation process.

How data science is reshaping the investment sector

Data science is becoming an increasingly powerful driver of investment choices. Data was always critical to investment decision-making, but the outcomes were only as good as the universe of available data.

“Combined, comprehensive data science tools, scientific investment philosophies and creative and skilled minds make for a powerful combination. Investment managers that do make the most of the data available to them stand to gain a convincing competitive advantage in this fast-developing digital era,” says Teichgreeber.

“Constructing our portfolio asset weightings is a systematic process. We determine our assets of choice through exploratory analysis. Then, based on the portfolio constraints and investment objectives, we use statistical optimisation to generate a spectrum of weights for our assets across a range of targeted risk buckets.

“Interestingly, as a result of the sound logic of the algorithms used in optimisation, certain assets are rejected due to their high correlation with other assets,” says Teichgreeber.

“Some optimisation methods take considerable time to generate optimal results. However, the more repetitions the optimisation runs, the more accurate the results.”

There has always been a trade-off between the capital outlay for computational systems and their accuracy. “At Prescient, we never compromise on accuracy, and for that reason we direct our investments into enhanced computing power and substantial data sources.”

Teichgreeber says Prescient has made substantial investments into computational systems to give it the required edge in an increasingly competitive market. Its investment process is heavily data-driven, statistical and systematic.

The importance of data science in systematic investing

“As a systematic manager, we establish principles for what we believe to be sound investment practices, and we programme them into our in-house systems. This allows our investment team to simply trade towards model portfolios and spend the majority of their time improving the process. Unlocking the power of data science is a core component of our investment process.”

The Prescient investment team comprises investment professionals with strong data science and economic backgrounds. The ability to unlock the power of data science by receiving, consuming and computing masses of data daily is what gives it a competitive edge.

Freedom Paddle is proud to partner with such fantastic people and thanks Prescient Investment Management for their commitment to staying the course. 

Brought to you by Prescient Investment Management.

Moneyweb does not endorse any product or service being advertised in sponsored articles on our platform.

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As long as there is an able captain at the helm. Bear Stearns collapse killed off many “quant funds”.

My understanding is that the quant revolution – popularised by Renaissance Technologies – has gone from strength to strength post the GFC or post-Bear Stearns.

My Prescient RA is looking good, their approach must be working

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