The Sophron Network

The Sophron Network
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Direct insights from experts in the trading, quant, and finance industry.

  1. 4d ago

    Luciano França – Is Brazil A Hidden Gem For Quants?

    Luciano Boudjoukian França joins The Sophron® Network to answer a question most quants never get to ask: is Brazil a hidden gem, or a trap dressed up as one? A factor strategy backtested on Brazilian equities can show roughly three times the alpha of the same strategy in the United States. Most of it never reaches the investor. This is a conversation about the gap between the backtest and the live book, and why that gap is the entire business in an emerging market. Luciano Boudjoukian França is a founding partner, Chief Investment Officer and portfolio manager at Avantgarde Asset Management, the São Paulo firm he founded in 2015 and one of the pioneers of factor investing in Brazil. Avantgarde runs a data-driven, systematic process across a family of multifactor equity and multi-asset funds, designed to remove emotion from investment decisions. The approach traces directly to his MSc dissertation at Insper on the low-volatility anomaly in Brazilian equities. Before asset management, Luciano spent his early career in derivatives and structured products for corporate clients at Banco BBM, and in corporate and real estate finance at ABN AMRO (formerly Banco CR2), Banco Pine and Even, where he structured capital-markets instruments such as CRIs, CCIs and REITs. He has served on the boards of Inepar and Resale, where he led the first Brazilian crowdfunding exit through a strategic acquisition. He holds an MSc in Economics from Insper, a Bachelor's in Economics from the University of São Paulo, and the CFP® certification. Follow Luciano Boudjoukian FrançaLinkedIn: https://www.linkedin.com/in/lucianobfranca/ Avantgarde Asset Management: https://www.avantgardeam.com.br/ Core Timestamps00:00 - Welcome and introductions02:04 - Pioneering systematic factor investing in Brazil05:34 - Why Brazil behaves like an island market06:59 - Vale, Petrobras and a value market of 150 names10:38 - From options market making to systematic factors15:42 - Why active ETFs are banned in Brazil20:07 - Why discretionary firms struggle to become systematic23:58 - Competing with AQR for the same Brazilian spread29:13 - Factor crowding and what breaks in emerging markets34:59 - Three times the backtested alpha, eaten by costs41:11 - Is the model ever overridden?43:56 - The 2020 crash and a 30% drawdown50:16 - Why he would rather play in the minors league53:56 - What AI changed in the research process1:03:39 - Rapid fire: overrated and underrated factors1:12:34 - São Paulo, Brazil and Dutch DJs Main Topics CoveredFactor investing and the low-volatility anomaly in Brazilian equitiesWhy implementation quality, not signal discovery, drives emerging-market alphaLiquidity, spreads and hidden trading costs as the binding constraintData hygiene: point-in-time data, survivorship controls, corporate actionsPortfolio construction in a market of roughly 150 listed namesWhy discretionary managers fail to transition to systematic processesModel autonomy and the limits of human overrideDrawdown management and low-beta factor exposure through the 2020 crashCapacity constraints of a boutique systematic managerAI in the quantitative research workflowScaling a factor process into other emerging marketsConnect With UsInstagram: https://instagram.com/amsterdaminvestLinkedIn: https://linkedin.com/company/amsterdam-investment-clubX: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  2. Jul 11

    Rob de Rozario – The Trillion Dollar Gap In Financial Markets

    Rob de Rozario joins The Sophron® Network to explain why the gap between a sub 3 trillion dollar digital asset market and the roughly 200 trillion dollar world of traditional finance gets closed on risk and education, not on returns. After two decades structuring exotic and FICC derivatives, Rob moved into digital assets because most participants could describe extraordinary returns but could not talk about risk. This conversation is about the bridge between those two worlds. Rob de Rozario is the Founder, CEO and Chief Trading Officer of Alphaparty, an Amsterdam based asset management and trading firm running alpha rich strategies across digital asset markets. Before Alphaparty he led trading at a digital asset firm across DeFi, derivatives and market making. His earlier career spans Lehman Brothers in Tokyo and Singapore (commodity exotics and hybrids), Nomura in Singapore (FX structured products across Asia ex Japan), and Leonteq in Zurich as Head of FICC Structuring. He holds a BSc with Honours in Applied Mathematics and Astrophysics from Monash University and pursued doctoral research in Financial Mathematics at UNSW. We get into counterparty credit risk and the FTX lesson, the education gap that keeps allocators on the sidelines, tokenized real world assets and stablecoin payments, structured products settled on chain, where alpha still hides for small funds, running risk in a 24/7 market, and how AI is reshaping who wins. We also discuss the Citi tokenization report, crypto volatility trading and Deribit, the reality of building companies, which tokens have genuine utility, and where derivatives volume sits five years out. Follow Rob de RozarioLinkedIn: https://www.linkedin.com/in/rob-d-93a43316/ Core Timestamps00:00 - Welcome and introductions02:54 - From FICC structuring to digital assets05:27 - Counterparty credit risk and the FTX lesson07:17 - A sub 3 trillion asset class next to 200 trillion in equities08:48 - The education gap and the FX University story13:00 - The Citi tokenization report and equities on chain by 203015:10 - Structured products settled by smart contract22:15 - Where alpha hides: prediction markets, Hyperliquid, smaller venues25:55 - How mature is crypto volatility trading34:19 - Running risk in a 24/7 market and three lines of defense36:30 - Inside Alphaparty: team, structure and returns42:40 - From astrophysics to markets, and where AI actually helps51:46 - Which tokens have real utility, and which go to zero57:16 - Building companies before finance65:40 - Rapid fire and the future of on chain settlement Main Topics CoveredThe trillion dollar gap between digital assets and global equitiesCounterparty credit risk as the most underpriced danger in cryptoTranslating exotic and FICC derivatives experience into digital assetsInstitutional adoption, education and the risk committeeTokenized real world assets and stablecoin paymentsStructured products settled on chainWhere durable alpha still hides for small fundsRisk management in 24/7, venue fragmented marketsAI as a tool that favors small, fast teamsUtility as the test for which tokens surviveConnect With UsInstagram: https://instagram.com/amsterdaminvestLinkedIn: https://linkedin.com/company/amsterdam-investment-clubX: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  3. Jun 30

    Jeremy Kadouch – How Close Are We to Fully Autonomous Trading?

    Jeremy Kadouch, Portfolio Manager at MN Fund, joins The Sophron® Network to answer a deceptively simple question: how close are we to fully autonomous trading? MN Fund runs a 24/7 systematic volatility engine that reads the market, reasons about it, and executes on its own. But the trade decision is deliberately kept away from AI, and the honest answer on autonomy is fewer decision makers rather than none. Jeremy Kadouch is Portfolio Manager at MN Fund, an Amsterdam liquid digital asset fund, where he runs the fund's trading strategies and capital deployment alongside founders Michaël van de Poppe and Esmee Sikkens. He brings more than eight years in digital assets across trading, tokenization and product development. He also built Quorum Index, an autonomous, LLM powered market intelligence platform, and founded Cask Capital, which tokenizes cask aged spirits. He began as a retail crypto trader and has completed Yale University's Financial Markets course. We go from MN Fund's three pillar book to the move from discretionary to systematic trading, where AI does and does not belong in execution, why the fund benchmarks against Bitcoin, and how to think about risk and drawdown. We close on tokenizing real world assets and building a Bloomberg for retail out of AI agents. We also discuss realized volatility harvesting, leverage and tail risk, the maturation of crypto markets over eight years, and the discipline of not tokenizing everything. Follow Jeremy KadouchLinkedIn: https://linkedin.com/in/jeremy-kadouch Core Timestamps00:00 - Welcome and introductions03:32 - What MN Fund is, and the multi strategy single fund model06:40 - The three pillar system and allocation by regime08:39 - From manual trading to a systematic engine11:37 - The intelligence layer, and why it is not fully autonomous yet12:35 - Trading realized volatility, and why not Bitcoin or meme coins16:41 - Systematizing discretion, and AI's real role21:15 - An algorithm that reads and reasons, with no AI in execution23:52 - Eight years in crypto: maturation and regulation36:04 - Why MN Fund benchmarks against Bitcoin39:42 - Cask Capital and tokenizing cask aged spirits49:24 - The discipline of not tokenizing everything52:18 - Quorum Index and how close we are to full autonomy Main Topics CoveredSystematic vs discretionary tradingAlgorithmic volatility harvesting in cryptoRisk, drawdown control, and R multiplesWhere AI belongs in a trading stack, and where it does notAgentic systems and autonomous market intelligenceBitcoin as a benchmarkTokenization and real world assetsRegulation, liquidity, and how crypto markets have maturedConnect With UsInstagram: https://instagram.com/amsterdaminvestLinkedIn: https://linkedin.com/company/amsterdam-investment-clubX: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  4. Jun 23

    Aditya Shetty – Can the Internet Replace the NASDAQ?

    Aditya Shetty joins The Sophron® Network to talk through "internet capital markets": the idea that with a phone and an internet connection you can access any asset, any market, regardless of your location, your politics or your investment size. Recorded the same week tokenized SpaceX went live, the conversation is grounded in a concrete example and an honest distinction every finance listener needs.Aditya Shetty is Lead at Superteam Global, the talent and community network for the Solana ecosystem, which runs programs such as Superteam Earn, Idea Bank and Instagrants to help builders ship and get funded. He is based in Mumbai and works across the global Solana community.We start with Solana framed as technical and financial infrastructure, an internet capital market positioned as a successor to NASDAQ. From there we get concrete with SpaceX on Solana: how Backpack built a full-stack wallet, exchange and regulated securities brokerage, why the launch partner Sunrise mattered for liquidity, and how that creates a single liquid market where price arbitrage is close to risk free. We draw the line between owning the underlying stock and holding a synthetic price tracker, separate the three layers of Solana, and close on composability, fees, Superteam's community model and the bridge between TradFi and DeFi.Follow Aditya Shetty on LinkedIn: https://www.linkedin.com/in/aditya-shetty-97ab5258/ Core Timestamps 00:00 - Welcome and introductions: Superteam and internet capital markets 01:02 - Buying SpaceX 24/7: ownership versus synthetics 02:37 - What SpaceX on Solana did differently 02:57 - Internet capital markets versus the US capital markets 03:31 - Backpack: wallet, exchange and a regulated securities brokerage 05:05 - One liquid market and risk-free arbitrage 05:17 - Decentralization and the case for investor education 06:43 - Education, KYC and DeFi trust assumptions 07:54 - Synthetics and mimicking: what you actually own 10:02 - The three layers of Solana: token, network and infrastructure 12:18 - Limited inventory, one-to-one minting and fees 14:08 - Composability: trading the weekend and borrowing against shares 15:40 - The Superteam model and community-driven investing 18:42 - Closing vision: reimagining access and the TradFi to DeFi bridge Main Topics Covered Internet capital markets as a successor to NASDAQ Tokenized equities and buying SpaceX on Solana Real ownership versus synthetic price exposure Backpack's wallet, exchange and regulated brokerage stack Single liquid markets and risk-free arbitrage Investor protection, education and KYC in an open-access model The three layers of Solana: token, network, infrastructure Composability: borrowing against and staking tokenized shares Fees across wallets, DEXs and aggregators Superteam's bottoms-up community model The bridge between TradFi and DeFi Connect With Us Instagram: https://instagram.com/amsterdaminvest LinkedIn: https://linkedin.com/company/amsterdam-investment-club X: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  5. Jun 10

    Amay Patel – Running A Market-Neutral Hedge Fund At 24

    Amay Patel joins The Sophron® Network for our first in-person episode on what it takes to build and run a market-neutral crypto hedge fund. An OG member of Amsterdam Investment Club, Amay went from independent quant trader, to an Amsterdam-based fund, to launching his own fund. We dig into the strategies, deal-making, and risk discipline behind that path. Amay Patel is Partner and Head of Investments at Atomic Digital, launched in 2025. The fund runs market-neutral strategies across OTC structured products, DeFi, quantitative, fixed income, and credit markets. Its flagship Market Neutral Fund is offered in USD and Bitcoin-denominated share classes, alongside separately managed accounts for institutional clients, aiming for consistent, low-volatility returns across market regimes. Before Atomic Digital, Amay was a Quantitative Developer at an Amsterdam-based fund and spent five years as an independent quantitative trader. He studied Finance at the University of Amsterdam and now splits his time between London and Dubai. We cover the honest version of becoming a trader: starting at 16, years of losses he calls "paying tuition to the market," and the jump from retail size to deploying seven and eight figures at a fund. From there, we move into the mechanics that matter at institutional scale: capital efficiency, borrow rates, margining, and why two funds running the same signal can post very different returns. We also discuss Atomic Digital, multi-strategy crypto investing, locked-token and OTC structured-product deals, risk discipline, managing inflows with flex capital, durable yield, airdrops, liquidity risk, and flying. Follow Amay PatelLinkedIn: https://linkedin.com/in/amaypatel Core Timestamps00:00 - Welcome and introductions 02:26 - Trading your own book vs trading for a fund 03:17 - From equities to crypto in the COVID crash 05:23 - DeFi yields, Pendle and Boros 10:03 - Why capital efficiency separates funds 18:51 - Atomic Digital: multi-strategy from day one 21:05 - Locked-token edge and OTC products 30:31 - Risk discipline and the Turkish bond trade 39:22 - Managing inflows with flex capital 44:35 - Will DeFi become as efficient as TradFi 49:22 - Rapid fire: airdrops, liquidity risk, flying Main Topics CoveredLaunching a market-neutral hedge fundMulti-strategy digital asset portfoliosOTC structured products and locked-token dealsDeFi yield trading, Pendle, Boros, and basis tradesCapital efficiency, margining, and borrow ratesDeal negotiation and counterparty relationshipsLiquidity risk and flex capitalScaling from seed capital to external LPsIndependent trader to fund founder at 24Connect With UsInstagram: https://instagram.com/amsterdaminvest LinkedIn: https://linkedin.com/company/amsterdam-investment-club X: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  6. May 29

    Yves Hilpisch – What Happens to Quants in the AI Era?

    Dr. Yves Hilpisch joins The Sophron® Network to discuss what happens to quants in the AI era. We trace two decades of Python in quantitative finance, from a language barely on the radar in 2005 to today's industry standard, and ask how generative AI and agentic coding are reshaping quant careers. The conversation moves from the practical gap between a backtest and a live strategy to the skills that stay valuable no matter how fast the tools change. Dr. Yves Hilpisch is the Founder and CEO of The Python Quants and The AI Machine. He holds a diploma in business administration and a PhD in mathematical finance, with a long-standing focus on derivatives analytics and risk-neutral pricing. He is the author of several standard references published by O'Reilly and Wiley, including Python for Finance, Derivatives Analytics with Python, Listed Volatility and Variance Derivatives, Artificial Intelligence in Finance, Reinforcement Learning for Finance, and Financial Theory with Python. He directs the Certificate in Python for Finance and the Data Scientist, AI Engineer, and Crypto Engineer programs, and has run developer meetups and training for financial institutions across Europe for over fifteen years. We examine how Python went from a hobby project to the backbone of modern quant work, with pandas and bank-wide migrations displacing MATLAB and a patchwork of proprietary tools. The conversation then shifts to AI: why the bar for junior quants has risen rather than fallen, why "you can outsource your thinking but not your understanding," and what agentic coding means for entry-level roles. We dig into the backtest-to-live "last-mile problem," economic profit versus a statistical edge, why FX is a sensible starting point for retail algo trading, and why anyone selling a strategy is a red flag. We conclude with the timeless skills, math, programming, and judgment, and why a GitHub portfolio is worth more than a polished CV. Follow Dr. Yves Hilpisch on LinkedIn: https://www.linkedin.com/in/dyjh/ Listen on Spotify: SPOTIFY_LINK_HERE Core Timestamps 02:02 – Founding The Python Quants in 2005, and Python's early signal 06:45 – From hobby to business: pandas and the rise of Python 08:37 – Bank-wide migrations and the displacement of MATLAB 10:51 – The four programs: Python for Finance, Data Scientist, AI Engineer, Crypto Engineer 17:32 – Where AI demand is heading, and the uncertainty in the job market 19:35 – "Coding is solved" and the raised bar for juniors 23:52 – Outsourcing thinking versus understanding 25:33 – Backtest to live: the last-mile problem 28:07 – Why you should not backtest to death 36:31 – Why FX is the natural starting point for retail algo trading 40:12 – The red flag of selling strategies 43:28 – The superquant and the end of the model quant 51:13 – From evangelist to guide through the jungle 60:16 – Timeless skills and portfolios over CVs Main Topics Covered • Twenty years of Python in quantitative finance • pandas, Wes McKinney, and the displacement of MATLAB • Generative AI and the rising bar for junior quants • Agentic coding and "outsourcing thinking versus understanding" • The backtest-to-live last-mile problem • Economic profit versus a statistical edge • FX as a starting point for retail algorithmic trading • The crypto engineering discipline beyond price speculation • The superquant and timeless, durable skills Connect With Us Instagram: / amsterdaminvest LinkedIn: / amsterdam-investment-club X: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  7. May 12

    Marc Ostwald – Reading Markets Like a Forty-Year Macro Veteran

    Marc Ostwald joins The Sophron® Network to discuss how the drivers of markets have changed across four decades, why the financial economy has drifted from the real one, and where the next generation of edge will come from. The conversation moves from central bank evolution and conditioned buy-the-dip behaviour into refining bottlenecks, the helium and rare-earth chokepoints behind the AI boom, and the rise of resource nationalism. We also examine what cross-asset relationships still work in this regime — and where investors are still trading from a 2010s playbook that no longer applies. Marc Ostwald is Chief Economist and Global Strategist at ADM Investor Services International, with more than forty years of experience across FX, fixed income, commodities, equities and global asset allocation. He is one of the most senior macro voices in the City of London, with a regular media presence on Bloomberg, CNBC, Reuters and the BBC. Marc is known for cross-asset, positioning-aware reading of markets rather than orthodox macro — placing physical flows, processing capacity and geopolitics on equal footing with monetary policy. Follow Marc Ostwald on LinkedIn: https://www.linkedin.com/in/marcostwald/ Core Timestamps 02:31 – Forty years of markets: what has actually changed 03:34 – From Volcker's opacity to the Greenspan put 06:22 – Active to passive: the ETF regime and Pavlovian flows 07:23 – Four crises in six years and the buy-the-dip reflex 09:21 – Why the post-2008 banking system only looks safer 11:32 – Andy Haldane: risk dissipates but doesn't disappear 13:50 – Buffett, valuations, and what "cheap" really means now 17:41 – $20 of credit, $1 to the real economy — then and now 19:23 – Cooperation breaking down between crises 20:14 – Processing and refining: the bottleneck most investors miss 22:31 – Nitrogen, sulfur and helium out of the Persian Gulf 24:31 – AI infrastructure, helium prices and semiconductor costs 25:28 – Rare earths, derivatives, and why China owns the chain 29:14 – AI capex, power, water and the new era of scarcity 36:21 – Where helium actually comes from 38:50 – Single points of failure and the move to just-in-case 42:32 – Europe's internal trade barriers and the ECB tariff study 45:01 – Resource nationalism, paper vs physical oil, spike volatility 51:44 – Cross-asset: FX, crypto, commodities, shipping 55:11 – Momentum trading and what's missing under the surface 55:48 – Advice for the next generation: psychology, engineering, power Main Topics Covered • Forty years of structural change across FX, rates, commodities and equities • Central bank evolution from Volcker opacity to unconventional QE • Buy-the-dip behaviour as a conditioned response to four recent crises • The illusion of post-2008 banking stability and where risk really sits • The widening gap between the financial system and the real economy • Refining and processing bottlenecks in commodity and energy value chains • Helium, sulfur and nitrogen as hidden inputs to the AI capex cycle • Rare earths, supply chain control, and why no proper derivatives market exists • Resource nationalism, single points of failure and just-in-case inventory • Europe's internal trade barriers and the ECB's hidden-tariff study • Cross-asset relationships that still work versus the 2010s playbook • What the next generation of traders and investors should master first Connect With Us Instagram: / amsterdaminvest LinkedIn: / amsterdam-investment-club X: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

  8. Mar 31

    Nikita Granger – The Most Complex Markets in Finance? – Quant explains commodities trading

    Nikita Granger joins The Sophron® Network to discuss how quantitative finance operates in physical commodity markets — from pricing exotic structured derivatives in power and gas to managing risk across Shell's global infrastructure portfolio. We explore why energy markets function fundamentally differently from equities, how spread options and compound options are used to model real assets, and what it takes to hedge in some of the most illiquid markets in finance. Nikita Granger is a Quantitative Developer at Shell, working across algorithmic trading, energy markets, and structured derivatives. He started his career as a Data Analyst at Priogen Energy, supporting front-office power trading, before joining Shell as a Data Scientist. At Shell, he built reinforcement learning models for gas and power trading, developed price forecasts across US and European markets, and worked on derivatives linked to green certificates and flexible demand assets. He then moved into deal structuring, designing and pricing complex energy contracts, before transitioning into his current role building trading algorithms around exotic structured products in power markets. Outside of Shell, Nikita is developing a honey futures market to help beekeepers manage credit and price risk. Follow Nikita Granger on LinkedIn:   https://www.linkedin.com/in/nikita-granger-27831389/ Core Timestamps 00:00 – Introduction and Nikita's background 02:44 – How Nikita's path led to energy markets 05:04 – Why commodity markets are fundamentally different from equities 06:19 – Energy assets as options: gas plants, pipelines, and the financial-to-physical transition 08:49 – Grid constraints, alternating frequency, and power market design 15:22 – Types of deals at Shell: leasing pipelines, transmission cables, gas plants, batteries 18:00 – Kirk's approximation and spread options as the workhorse of commodity pricing 20:19 – Exotic structured contracts: compound options on gas plants 24:18 – Biggest pricing challenges: parameterization, correlation, and compute time 26:35 – Liquidity problems and dirty hedging with proxy instruments 29:32 – Hedge simulators and risk premiums in illiquid markets 33:09 – Shell as a risk warehouse: how large commodity traders create value 35:51 – Full deal lifecycle: origination, structuring, term trading, cash trading, and scheduling 43:37 – P&L attribution challenges and mark-to-market accounting 45:39 – Collateral, margin calls, and the 2022 European energy crisis 50:10 – Building a honey futures market: credit risk, colony collapse, and commodity innovation 56:22 – Why commodities trading has real-world impact on energy prices and infrastructure Main Topics Covered • Commodity markets as futures-driven systems shaped by physical storage constraints • Energy assets modeled as spread options and compound options • Kirk's approximation for pricing multi-commodity spread options • Liquidity challenges and dirty/proxy hedging strategies • Shell's risk warehouse model: leasing infrastructure and absorbing market risk • Deal lifecycle from origination through real-time grid scheduling • Mark-to-market accounting and collateral requirements • Grid frequency control, resource adequacy, and power market design • Honey futures: applying derivatives innovation to agricultural commodities • Real-world impact of doing commodities trading well Connect With Us Instagram: https://instagram.com/amsterdaminvest LinkedIn: https://www.linkedin.com/company/amsterdam-investment-club X: https://x.com/amsterdaminvest Subscribe for more conversations at the intersection of markets, research, and technology.

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Direct insights from experts in the trading, quant, and finance industry.

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  • Creator
    The Sophron Network
  • Years Active
    2026
  • Episodes
    14
  • Rating
    Explicit
  • Copyright
    © The Sophron Network
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    The Sophron Network