ZoQuant Solutions

Fintech · Asset management · Web3

Quantitative research for financial technology — in traditional markets and on-chain.

ZoQuant Solutions turns quantitative research into working software. We build the investment signals, risk models and pricing tools that fintechs, asset managers and on-chain protocols need — applied to traditional markets and to DeFi.

Start a conversation Selected engagements

Approach

The same quantitative edge. Two markets.

ZoQuant Solutions develops investment signals, risk models and decision tools across traditional finance and on-chain markets.

Traditional finance

In traditional finance, the firm has delivered robo-advisory and portfolio-optimization solutions for wealth-technology platforms, multifactor ETF research and backtesting infrastructure for global asset managers, and risk frameworks for banks and financial advisers. It also applies machine learning to commercial forecasting problems such as sales, competitor activity and market share.

Digital assets

In digital assets, the work spans real-time measures of implied impermanent loss, derivatives-based hedging tools for liquidity providers, cryptocurrency yield and options strategies, prediction-market research, yield farming and tokenized money-market funds.

Each engagement is grounded in rigorous academic research, translated into practical solutions and delivered as working tools clients can use and own.

Services

What clients ask for.

Most engagements begin with a forecasting or a risk question. We turn research into signals, risk models and pricing tools — portfolio construction and strategy design at one end, risk frameworks scaled to the mandate at the other. Where the literature stops, we build: a published method becomes a running prototype, validated against data and handed over as code you own, documented and tested.

Selected engagements

Where the work has landed.

Protocols, asset managers and fintechs — most recent first.

  • Signal exploration and research for prediction-market strategies
  • Yield-generating strategies using cryptocurrency derivatives
  • Signal exploration and research for option strategies in cryptocurrencies

Derive.xyz

Builder Grant Recipient · Research & Prototyping

Leading on-chain crypto derivatives protocol — options, perpetuals and spot, settled trustlessly on its own OP Stack chain.

Two builder grants

  • Real-time implied impermanent loss index (IILX), turning option-implied variance and correlation into a forward-looking benchmark for LP compensation
  • Impermanent-loss hedging tool built with on-chain derivatives

Fincite GmbH

Quantitative Research & Advisory Frankfurt am Main

Wealth-management and robo-advisory technology for banks and asset managers.

  • Robo advising, portfolio optimization and machine learning for portfolio advisory
  • Quantitative research across investment and risk management
  • Prototyping quantitative solutions in Python
  • Mentoring, supervising and developing the quant team

OppenheimerFunds, Inc. (now Invesco)

Quantitative Research New York City

Global asset manager, merged with Invesco in 2019.

  • Signal exploration for a multifactor ETF strategy
  • Translating and aligning legacy code and spreadsheets into Python
  • Development of a backtesting tool for portfolio management and the sales team

Cheil

Data Science & Forecasting Frankfurt am Main
  • Analysing and forecasting consumer traffic, sales, competitor trends and market share with machine learning
  • Ad-hoc big-data reporting
  • Marketing KPI development and target setting in the dashboard management system

Selected clients & partners

Derive.xyz DY — Derivatives & Yield Liquifund Fincite OppenheimerFunds Cheil

Applied research

From paper to prototype.

Grant-funded work that ended in running code, not only a paper.

Derive.xyz · Builder grant

Implied impermanent loss index (IILX)

A real-time, option-implied benchmark for the loss a liquidity provider can expect — built for the leading on-chain derivatives protocol.

Derive.xyz · Builder grant

Impermanent-loss hedging tool

A derivatives-based hedge for liquidity providers, built on the same option-implied measure.

2023 · The Avalanche Foundation

“The Impermanent Loss in Yield Farming”

Extracting the market's forward-looking expectation of liquidity-provider shortfall from option prices, rather than measuring it after the fact.

2022 · The Graph Foundation

“Yield Farming for Liquidity Provision”

The strategy side of the same problem: what a liquidity provider actually earns, and when providing liquidity is worth the risk.

Selected research grants

Competitively funded research.

Awarded by central-bank, industry and academic research programs.

  1. 2026

    OEE — European Savings Observatory

    “Mainstreaming Tokenized Finance: How Money Market Funds are Going Digital”

  2. 2025

    Hong Kong Institute for Monetary and Financial Research

    “Tokenized Money Market Funds (TMMFs) in Decentralized Finance”

  3. 2025

    Europlace Institute of Finance Foundation

    “Decentralized Options Trading”

  4. 2023

    Cboe Options Institute & S&P Dow Jones Indices

    The economics of option-implied factor dispersion

About

Who you are actually hiring.

Dr. Lorenzo Schönleber

Founder
Academic position
Assistant Professor of Finance, Collegio Carlo Alberto & University of Turin
Doctorate
PhD in Finance, Frankfurt School of Finance & Management
Research focus
Option-implied information · Decentralized finance
From 2027
Professor of Practice, Centre for Digital Economics, Frankfurt School of Finance & Management
Personal website LinkedIn

Lorenzo is Assistant Professor of Finance at Collegio Carlo Alberto and the University of Turin, and holds a PhD in Finance from Frankfurt School of Finance & Management. His academic work is on option-implied information and decentralized finance — the two subjects this firm exists to apply.

That research appears in peer-reviewed journals and in BIS Bulletin No. 115 on tokenized money market funds, and his work on the implied impermanent loss in decentralized liquidity provision is what the IILX prototype for Derive.xyz was built from. Before and alongside academia he has worked as a quantitative researcher and developer in Frankfurt, New York and Paris — for an asset manager, a wealth-technology firm and, most recently, crypto-derivatives and prediction-market ventures.

The practical consequence for a client is a short path from an open question to a defensible answer, and from a defensible answer to something running in production.

Contact

Tell us what you need to price, forecast or hedge.

A short description of the problem is enough to start. If it is not something we should take on, we will say so and point you somewhere better.

lorenzo@zoquantsolutions.com

Typical engagements run from a scoped two-week prototype to an ongoing research retainer. Working languages: English, German, Italian.