IPOR Labs Talent Spotlight: Mau Hernandes, Chief Scientist
A short Q&A session with one of IPOR Labs’ math PhDs — Mauricio Hernandes.
Half-Brazilian, half-Portuguese, Mauricio “Mau” Hernandes went to Japan 10+ years ago to study mathematics and has stayed there since. He is a quant and data scientist who holds a PhD in computer science, is a fellow member of the Royal Statistics Society, and has professional experience in Latin America and Asia.
He was formerly a Board Member and R&D with SBI Bits, the crypto exchange of the Japanese SBI Holdings, and founded a boutique quant consultancy, Obolus, as Chief Data Scientist.
When he is not tackling some of the hardest challenges in decentralized finance, he enjoys building models. In other words, he is not building models only while he is sleeping. But we don’t have definite proof of that.
As a mathematician, what do you think are the biggest challenges the DeFi industry will have to overcome for institutions to join it? Will it ever happen?
My years working in Japan in the crypto industry have taught me that regulation and regulators often have their own pace. While this might not be popular with crypto enthusiasts, it often makes sense. Having lived in Asia for so long, I can appreciate the progress made in places like Hong Kong, Singapore, and even Japan in terms of acceptance and institutionalization. It might not be at the level that crypto fans would like, but as a mathematician, I wonder if I could find a better solution.
What are the main reasons for joining the IPOR Labs team?
Fixed income* modeling is very interesting, and the IPOR team has the vision to build on that space. There is a tremendous room to grow. Fixed income is huge in TradFi and it’s only just starting in DeFi. We are very early. As the Japanese say:
“Wake early and gain three mon.”
What makes DeFi exciting for a quant with a computer science doctorate? Why is it hard to price interest rate swaps in DeFi?
What makes DeFi exciting for me as a quant with a computer science doctorate is the easier access to data compared to traditional finance, as well as the challenges of fitting old models to new markets.
Pricing interest rate swaps in DeFi can be difficult, mainly due to liquidity issues. If one is not careful, it is easy to miscalibrate the model using the sparse data in some markets.
Are there assets easier/harder to price interest rate swaps for?
Liquidity plays a key role in asset pricing. For example, it would be much easier to price interest rate swaps between the US Dollar and Japanese Yen than between the Brazilian Real and Argentinian Pesos. In the crypto world, one should expect more reliable pricing for ETH than EOS, for example.
What are your favorite crypto assets? Other projects you are following in the space?
One of my favorite aspects of the crypto space is analyzing Uniswap V3. With the right equations, one can treat the liquidity provided to Uniswap as the same as entering two options contracts. We can also extract interest rates from a whole Uniswap pool with a few more equations. It’s great fun.
Do you have any predictions about what will happen in the crypto space in 2024?
Looking into the future, my prediction for the crypto space in 2024 is that on-chain interest rates will have a surge of interest as central banks start easing their interest rates. DeFi rates are once again above TradFi rates, which makes the space attractive to outsiders.
Mau co-authored IPOR’s original white paper published in March 2021 and laying out the vision of an interest rate benchmark in DeFi. His later research focused on interest rate swap pricing models and IPOR request-for-quote automated market maker (AMM). Access them all in the IPOR Docs:
*Fixed income is a class of assets and securities that pay investors a set level of cash flows, typically in the form of fixed interest or dividends.
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