How one man’s single minded obsession with improving the financial system worldwide led to an industry-changing company and created opportunities for smart, socially aware people across the globe.
Innovation is the hallmark of the modern world: Apple changed phones. Tesla is changing how we drive. Google changed how we get information.
By Anton Golub (Lykke), James Glattfelder (Department of Banking and Finance, UZH), Richard Olsen (Lykke)
The asset management industry and methodology
The asset management industry, with an estimated 64 trillion USD under management, is one of the largest industries in the world. Yet, asset managers suffer from the lack of a consistent and overarching framework because the systems they depend on have their origins in the 1950’s before computers.
In practice, today’s managers choose from a blend of theories with different interpretations, applying ad hoc rules that lack consistency. This lack of consensus in such a large industry is striking, especially when digital power provides an abundance of machine algorithms and big data techniques.
More than 30 years ago Richard Olsen argued that economic results depended on the underlying economic models and that perfecting these models could contribute to the well-being of society. This singular focus led Richard along an entrepreneurial and academic path that resulted in exhaustive testing of his theory and finally, in 2008, a major breakthrough that led to the 2015 formation of Lykke, the first truly global marketplace for all asset classes and instruments on the Blockchain.
Alpha engine innovation
We focused our research on the foreign exchange market, a complex network of interacting agents forming an intricate web of interdependence. With daily turnover of five trillion USD and price changes nearly every second, the foreign exchange market offers a unique platform of study; highly liquid, not constrained by exchange based rules, it is bigger than futures or equity markets.
The symmetry of one currency against another neutralizes effect of trends; therefore, currency markets are notoriously hard to trade profitably. Development of fully automated algorithmic trading strategies not only provides consistency and profitability to the foreign exchange market but is beneficial to other markets.
Investment strategies must be fully automated
Human based (intuition based) trading is naturally limited, unable to cope with the complexities of unlimited variables, and the concept of time; it is the concept of time that is most critical to trading efficiency yet not understood or effectively applied by traders.
Time is a dynamic concept with different meanings based on individual actions. For example, time passes very quickly when at a concert or sporting event, but may seem to move much more slowly when sitting quietly at home. Likewise, time to a trader may vary depending on the activity he or she is focusing on, and trading models or algorithms based on personal human based concepts are naturally limited.
A truly effective investment model must dynamically consider market changes in real time and adapt to those changes. Our goal, in our studies, has been to develop trading models based on multiple time horizons, not on agent limited time lines.
An innovative time perspective is the foundation
Richard Olsen’s ground breaking study of time led to the Alpha Engine, a trading model algorithm that provides liquidity by opening a market position when markets overshoot, and manages positions during pricing evolution to produce a profitable close. In other words, the limitations of broker time considerations are removed.
The building blocks of the efficient trading model include:
- An endogenous time scale, also called intrinsic time, that dissects the price curve continuously and allows for determination of position sizes by identifying market activity that deviates from normal behavior. Rather that action based on a specific time, action is more accurately measured by events.
- Patterns, called scaling laws (also observed in physics, biology, earth and planetary sciences, economics, finance, etc.), that measure an immense number of natural processes and adjust for them.
- Skewing of cascading and de-cascading coastline innovation to mitigate the risk of large inventory size during trending markets.
- Introduction of asymmetric thresholds by eliminating static and rigid guide points that arbitrarily limit directional change thresholds.
Conclusion and outlook
The essential methodology and innovation in Richard Olsen’s work, determined through decades of research and testing, was recasting of time as discrete and driven by activity, a recast unknown and unused in the trading industry.
This trading model is defined by a set of simple rules allowing effective execution by identifying specific events in the market. The result is an automated trading model that is robust, profitable, adaptive and provides liquidity to the market.
The key to long-term success with any methodology is a consistent, adaptive philosophy built on tested and proven research and applied in the real world. Today’s trading systems were built without the benefit of mathematical or computer science technology; Lykke incorporates both.
Originally published at www.lykke.com.
