Interview with Michael Hebenstreit: “Digitalization and automation in the asset management industry are just getting started”

My name is Emma Vinson, I’m an asset management intern at Lehner Investments. Today, I’m delighted to share an interview with Michael Hebenstreit, CMO and portfolio manager of Lehner Investments, on the use of AI & big data in the asset management industry, that was carried out for an academic research project in the FinTech field.

Interview Emma Vinson / Michael Hebenstreit / Asset Management Industry
Interview Emma Vinson & Michael Hebenstreit

AI-based trading is a fast-growing and promising sector in FinTech, which can be sub-divided into several branches. Indeed, while some researchers and financial analysts try to use AI to identify underlying trends in historical data, others, for instance, tried to analyze big data information in the press and on social media. This is the case of a FinTech start-up called Lehner Investments, and to explore this AI topic, its CMO and portfolio manager, Michael Hebenstreit, made me the pleasure to answer my questions.

1. To start with, could you please introduce us to AI trading using big data analysis and to what Lehner Investments is doing in this field?

Big Data / Artificial Intelligence / Asset Management Industry
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The use of artificial intelligence in the asset management industry is just at the beginning. Artificial intelligence tries to extract patterns from large data sets that can be used for forecasts. The sheer volume of data has exploded in recent years. At the same time, by using computer power and algorithms the information can be processed much faster. In addition, the data sources that are available today can be very different from the ones that were available a few years ago, when the data was mostly limited to price, economic or company information only.

Big data analysis can be used as a quantitative measure of emotions, attitude and mood of investors with respect to financial markets in general or specific sectors (respectively assets). Positivity and negativity drive price action and create trading and investment opportunities for active traders and long-term investors.

Data Intelligence Fund
Data Intelligence Fund managed by Lehner Investments

Lehner Investmentsutilizes such big data-based information and other data streams to develop technology driven and fully automated quantitative trading strategies. The independent trading signals generated from big data analysis, combined with artificial intelligence algorithms are then deployed by Lehner Investments within various investment funds and overlay strategies for institutional investors.

Lehner Investments Data Intelligence Fund and other upcoming investment funds are available to both institutional and retail investors.

2. How does it work once the machine generates a trading signal? Who is then investing and according to which strategies?

Asset Managers verify Trading Signals
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Once the algorithm generates trading signals based on big data scores and various other input factors, a team of portfolio managers monitors, verifies and then confirms the trading signals with a single click. This process happens either in real time or within only a few minutes.

However, it’s worth mentioning that the purpose of the verification process is only to rule out technical issues and to satisfy regulatory provisions. Trades are not rejected or confirmed based on discretionary decisions by portfolio managers which makes the process by Lehner Investments a truly automated AI and big data driven investment approach.

Legal Considerations / Asset Management Industry
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While the trading signals are generated by algorithms, the underlying logic behind the algorithms is based on input from our portfolio managers and researchers. In the end we’re using computer power to process huge amounts of data and information, which pure manpower would no longer be capable of processing. We then generate trading signals based on our trading ideas and research results.

It’s rather a highly effective symbiosis and collaboration between humans and machines. From a legal point of view Lehner Investmentsis a BaFin regulated and licensed asset management firm. That means legal wise there is no difference to traditional asset managers.

4. Why do we need such investment technologies? Why couldn’t we continue to rely on traditional ones?

Trading Room / Stock Quotes
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Within the automated investment process Lehner Investmentsuses market opinions from millions of tweets, social media posts and financial news sources with many years of experience and new technologies to process the flood of information in the 21st century in real time and thus creates competitive advantages over traditional forms of investment management and research. Processing these large amounts of data and information in real time isn’t possible within a traditional asset management environment.

5. Aren’t such types of technologies already being used in investment banks like JP Morgan or the Deutsche Bank? What makes Lehner Investments technologies different?

Business Team / Trading Desk
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The process of introducing new technologies and approaches to asset management is part of the digitalization and automation of the financial industry. However, while other industries have had a head start when it comes to digitalization and automation, the transition process in the asset management industry is just getting started.

While other asset managers and FinTechs are slowly jumping on the bandwagon, Lehner Investments has been a pioneer in the development of new technologies in asset management for many years. Our approach is ahead of other market participants due to alternative data sets and long-standing know-how.

Data / Information / Knowledge
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At other asset management companies, the AI term currently is often used as a marketing buzzword or for thematic funds that invest in companies that are using artificial intelligence in their products and services, like for example the popular FAANG stocks. Lehner Investments instead is actually using artificial intelligence for the automated investment process itself.

In addition, incumbents face increasing cost and regulatory pressure and, thus, are often not capable of allocating the required resources in terms of time, money and risk budgets for the development of such new technologies.

6. What is your investment universe, and why?

We’re in general not limited to a certain investment universe. However, as a FinTech startup you have to start somewhere. That’s why we, as a German asset management firm, decided to start with products that cover the European and especially the German equity markets.

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