Stockholm (HedgeNordic) – The might of compound interest has become part of asset management pop-culture at least since Albert Einstein’s quotation that compound interest was the most powerful force in the universe. “Compound interest is the 8th wonder of the world,” Einstein once famously said. “He who understands it, earns it; he who doesn’t, pays it.”
One asset manager operating out of Sweden’s southern town of Malmö holds this credo especially high. Backed by six family offices, quantitative asset management firm OQAM is managing a multi-strategy systematic hedge fund named ia with capital preservation and uninterrupted compounding at the heart of their philosophy. “We have different targets and goals that we want to achieve for our clients with ia’s strategy,” Andreas Olsson, Co-Founder and CEO of OQAM, tells HedgeNordic. “But we do everything with capital preservation in the back of our minds and focus on limiting drawdowns to enable compounding,” he continues. “ia is firmly in the absolute-return space,” emphasizes Olsson. “We actively manage total risk and from there, we exploit investment opportunities.”
“We do everything with capital preservation in the back of our minds and focus on limiting drawdowns to enable compounding.”
Before setting up OQAM with CIO Thorbjörn Wallentin in 2016, Olsson co-founded and managed award-winning hedge fund Stella Nova for nearly ten years until its closure in 2012. Wallentin joined Olsson from Nordea, where he managed multi-billion euro cross-asset mandates as a senior investment manager in the unit responsible for the bank’s treasury operations and asset and liability management. Wallentin took up his first role at Nordea just one week before the bankruptcy of Lehman Brothers sent markets spinning, an experience he describes as “learning by burning.” Olsson and Wallentin joined forces after realizing that “a quantitative framework is probably the future of investing, and we saw huge opportunities in utilizing that framework.”
Specialist Knowledge in a Quantitative Framework
Olsson describes ia as an algorithm-based human hedge fund. “We combine our human experience and knowledge with a quantitative framework to create a quantamental investment approach,” the CEO of OQAM tells HedgeNordic. “We built everything from scratch, utilizing our experiences and backgrounds.” The duo leveraged on their experience to build “a multi-strategy approach across different asset classes, markets, holding periods and instruments” that can deliver returns in both risk-on and risk-off environments, according to Wallentin. “We deploy different, purely systematic strategies that have strengths and weaknesses in different market environments.”
“We combine our human experience and knowledge with a quantitative framework to create a quantamental investment approach.”
ia currently employs about 20 different models, which can be grouped into four broader categories: asset allocation, short-term trading, trend strategies, and relative-value strategies across fixed-income, foreign exchange, equity and commodities (metals) markets. Some of these strategies play the role of return generators in risk-on environments, while others have the potential to generate positive returns in risk-off environments. “Typically, our trend-following strategies are designed to perform in risk-off environments,” explains Wallentin. “Short-term trading strategies, which are well diversified in nature and have a decent turnover per day, and some of our relative-value strategies are also designed to have a risk-off profile.”
The asset allocation strategies, meanwhile, are designed to serve as longer-term return generators by allocating across fixed income, precious metals, equity index futures and Nordic single stocks. “We still believe in risk premia going forward, so we want to be exposed to these sources of return,” explains Wallentin. “We are trying to dynamically capture risk premia across asset classes over time.”
“All our models and sub-strategies exhibit a regime focus, with each sub-strategy or model deploying a different amount of risk depending on prevailing market conditions.”
The allocation between each of the 20 and growing number of models is performed in a systematic manner. “All our models and sub-strategies exhibit a regime focus, with each sub-strategy or model deploying a different amount of risk depending on prevailing market conditions,” says Wallentin. Some models take on more risk in risk-off environments. The process of implementing new strategies or scraping off existing ones is the only discretionary component in managing ia. “Once a model is implemented, we do not take discretionary decisions,” explains Olsson. “Then it is 100 percent systematic.”
Innovation and OQAM’s Own “Other Bets” Incubator
“ia is our innovation engine,” according to Olsson. Besides these four main strategy categories, “we also have a special vehicle called LAB, where we deploy different models in the market more quickly,” says Wallentin. “We start from developing a suitable model for a specific thesis on the market,” he tells HedgeNordic. “We like to iterate and think fast, and we try to improve from there or scrap the model depending on how it works.”
“ia is our innovation engine. This whole innovation process around extending the range of strategies and models is something we constantly work on.”
“This whole innovation process around extending the range of strategies and models is something we constantly work on,” highlights Olsson. “We are always trying to use our backgrounds and experiences to find new models and enhance the current ones.” The team running ia puts more focus on whether a specific model or strategy will work going forward rather than backtest. “We don’t rely on back-testing in the way many others do,” emphasizes Wallentin. “One of the models that served us really well earlier this year had never been back-tested.”
Olsson emphasizes that “every strategy we employ is developed by us, so we really try to find new ways to do things that will add value to the fund.” Although OQAM is a relatively small asset management company, “we are really focused on research and work hard on that side.” OQAM collaborates with Lund University to engage students in a lot of ongoing projects, “which is a great way for us to work on different concepts and strategies.” This collaboration, which sets the stage for other potential collaborations with Danish universities across the Øresund Bridge, “increases our research capabilities quite a lot.”
ia’s set of systematic strategies requires a large amount and variety of data. “We are very dependent on price data and a lot of indicators built on that data, but we basically use all the data one can find,” explains Wallentin. ia also relies on a wide range of macroeconomic data, crowding data to get a sense of how market participants are positioned, as well as in-house-built data. “We feel alternative data is a very promising and interesting area,” reckons Wallentin. “It is an area we have channelled a lot of effort and time in the past year.”
Risk Management and Performance
“You can always be wrong as an asset manager,” considers Wallentin. “The quantamental approach, however, will limit your downside if you are wrong.” Because ia seeks to operate as a diversifier that protects capital in any market environment, “true active risk management is our starting point and incorporated into everything, reaching from risk filters to the sizing of positions.” Also, if ia’s portfolio loses more than ten percent, the size of the positions and the risk allocated is decreased with a manual override. “This is an important signal to send to our investors,” reckons Wallentin. “It is crucial for our investors to feel that they are not invested in an asset that might end up dropping 20 percent.”
“It is crucial for our investors to feel that they are not invested in an asset that might end up dropping 20 percent.”
Heavily relying on the OQAM team’s experience and background, scenario analysis complements their use of other traditional risk management tools. “We can never be 100 percent prepared for all scenarios coming our way, but we always try to prepare for the scenarios that can hurt us most,” says Wallentin. This scenario assessment enabled ia to perform well in February and March this year. “According to one of our scenarios, the market was one-sided at the beginning of the year as CTAs were very long in an uptrend and equities were rallying for an extended period,” recalls Wallentin. “For that reason, we wanted to have models that could capture a quite sudden drop in asset prices early on.”
“We were prepared for the environment that came along, and our short-term strategies and trend strategies indeed performed quite well,” explains Wallentin. ia gained 2.2 percent in the first quarter of 2020. “For us, this innovative quantamental approach where we utilize specialist knowledge within a quantitative approach truly adds value,” reckons Olsson. “We are taking the best of both worlds.”
This article featured in HedgeNordic’s report Systematic Strategies: When Numbers are the Key!
