Caio Marchesani has been involved 
in trading and analytics for the past fifteen years, working for top-tier investment banks and hedge funds while managing over 300m dollars in AUM. Marchesani was a partner in developing the quantitative trading framework for Oil Analytics, which, upon completion, became a Bloomberg Data provider.
Over this period, Marchesani employed his quantitative macro trading methodology to generate exceptional risk-adjusted returns. During this time, Marchesani established his reputation for the accuracy of his trading signals with a network of fundamental commodity macro investors in London. Marchesani began his career at Deutsche Bank after receiving a Master of Engineering (MEng) in Mechanical Engineering and Applied Mathematics from University College London.
Over the past several years, Marchesani has successfully applied his trading and analytics skills to the cryptocurrency industry, achieving returns exceeding a staggering 2200%, which attracted the attention and envy of his peers.
We recently had the opportunity to connect with Caio Marchesani, who shared some insights from his career and advice for finding success in a complex, largely unregulated market.
Can you share insights or pivotal moments from your 15-year journey in trading and analytics that influenced your path in cryptocurrency?
Crypto trading is similar to modelling any other dataset. Given the liquidity of some assets in the space, they tend to behave like financial markets.
Financial markets are cyclical and composed of a series of ‘Phases’ and ‘Trends.’ Phases and trends can be identified and exhibit similar characteristics (a beginning, an end, and a duration) that can theoretically be found across all timescales. This naturally occurring phenomenon is described in mathematics as fractal patterns. By applying mathematical and statistical analysis to fractal patterns, trading opportunities can be precisely identified.
How did your Master’s degree in Mechanical Engineering from UCL shape your approach to crypto trading?
Not only in crypto but in trading generally, engineering is a very mathematical degree. It helps you develop mathematical and analytical skills to solve real-life problems from first principles.
In essence, trading is all about using mathematical approaches to model and manage your risks.
What techniques and strategies from your time at Oil Analytics became the foundation for your crypto success, and how did your unique quantitative macro trading methodology help you navigate and succeed in the crypto markets?
Crypto is popular for hedging against inflation. Sometimes, Bitcoin may be considered digital gold due to its liquid and speculative nature.
It is no surprise that there is an inverse or negative correlation with inflation-adjusted bond yields, and the yield curve can be used for these analyses.
To gain fundamental insight into the above analysis, it is vital to have a comprehensive understanding of macroeconomic trends.
During my time at OA, we developed unprecedented refinery and petrochemical models that emulate Linear Programming (LP). LP is a mathematical optimiser used by refineries/crackers to make economic decisions for the plant.
As part of modelling the asset base of oil companies (majors), we developed detailed models for calculating ethylene crackers. As key plastics producers, ethylene crackers stand at the base of the manufacturing supply chain. Therefore, depressed ethylene cracker margins are usually an early indicator of weakness in the PMI and IP numbers that precede an economic slowdown, and the inverse is also true, which could fuel inflation. OA thus had timely insight into fundamentally induced macro trend movements.
Combining a macroeconomic edge with quantitative modelling is key to outperforming anyone in the business, whether it is in crypto or any other asset class where you see an opportunity.
What fundamental principles contributed to your trading prowess and the remarkable 2200% ROI in the crypto space?
The previous crypto bull market was unique in many ways.
I have been analysing economic trends for most of my adult life. During my research, I always paid significant attention to the debt crisis and monetary policy responses.
It all began by looking for an inflation trade, fuelled by the excessive money printing seen by central banks worldwide over the past decade. I knew this situation would be aggravated further by the additional money printing and stimulus cheques sent to households during the pandemic.
This excess liquidity in the money supply, combined with supply chain constraints and the potential re-election of Donald Trump with his infrastructure spending plans, created a unique scenario for an exponential bubble to begin.
During the Dutch Golden Age, the contract price for fashionable tulip bulbs reached extremely high levels, to the point where you could buy a house on the Amsterdam canal for the price of a bulb. This was known as the famous tulip mania.
Ultimately, the tulip mania was more of a then-unknown socio-economic phenomenon than a significant economic crisis. It had no critical influence on the prosperity of the Dutch Republic, the leading economic and financial power in the 17th century.
I believed history was repeating itself in many ways. Exchanges like Binance recklessly offered platforms to trade crypto without a proper compliance framework, allowing people to trade using only an email address.
The lack of regulations in the space kept institutional money out of the party, thereby not posing a systemic risk to the leading economies, which kept central banks at ease with the situation.
This provided a unique opportunity for professional traders to act independently in an unregulated space.
The combination of fundamental and quantitative skills was crucial for achieving those results. This represented both the intrinsic value of the opportunity and instinct.
What innovative strategies or goals can we expect from you in the future of crypto trading?
Crypto is not my primary trading space. I never believed in the fundamentals of crypto. However, this should not stop a trader from taking advantage of a unique opportunity to profit from a bubble.
– Caio Marchesani