The Blushing Quants Podcast
The Blushing Quants Podcast offers a candid, no-nonsense look at the intersection of quantitative finance and machine learning. Hosts and guests discuss the real-world challenges of building ML-based investment systems, covering what works, what fails, and why. Topics include neural networks, time series analysis, and statistical learning, with an emphasis on practical insights over hype. The show includes a disclaimer that all content is for educational purposes only and not financial advice.
Episodes
Nam Nguyen: Sell-Side vs Buy-Side Quants, Monte Carlo and AI | Blushing Quants #34
Nam Nguyen is a career quantitative finance professional with experience across both the sell side and buy side. Based in Toronto and working across North America and Asia, Nam began his career during the global financial crisis, building models for complex financial derivatives before moving into model validation, risk management, and eventually buy-side quantitative research.
In this episode of
Antonio Marrazzo: How to Build Robust Factors with Data and Machine Learning | Blushing Quants #33
Antonio Marrazzo is a quantitative researcher with a background in economics and actuarial science, focused on factor investing, portfolio construction, market regimes, data analysis, and machine learning in financial markets.
Originally from Argentina, Antonio began applying quantitative methods to investing before formally discovering the quant profession. He translated concepts such as Markowit
Vincent Randazzo: Market Breadth, Risk and Systematic Portfolio Management | Blushing Quants #32
Vincent Randazzo, CMT, is a portfolio manager and technical market strategist with more than 25 years of experience across firms including Morgan Stanley, UBS, ICAP, CFRA Research, and Lowry Research.
After observing that investors have access to more market data than ever but often lack clarity on how to use it, Vincent developed Defender, a quantitative, rules-based framework designed to support
Jerome Busca: Inside Citadel, Alpha Decay and the Future of Quant | Blushing Quants #31
Jerome Busca is a quantitative trader with more than 25 years of experience across mathematics, quantitative research, portfolio management, global futures, foreign exchange, and crypto markets.
After beginning his career in academic mathematics and applied research in France, Jerome moved into quantitative finance and later joined Citadel’s hedge fund business. Working on the mortgage desk before
Paul Chalmers: Trading Education Done Right - AI, Risk & Real Market Education | Blushing Quants #30
Paul Chalmers, CEO of UK Trading Academy, for a raw and practical conversation about what most traders misunderstand about the markets.
Paul breaks down why trading education often fails, why theory alone is not enough, and how real market experience, risk management, psychology, and disciplined execution separate serious traders from the crowd.
We discuss how markets have changed, the role of AI
Jonathan Davies: The Theory That Challenges Every Trader and Investor | Blushing Quants #29
Jonathan Davies is an economist with over 30 years of experience in financial services.
Jonathan has worked across several areas of the investment world, including fixed-income research, portfolio strategy, and portfolio management. His career has focused mainly on the macroeconomic side of markets, examining areas such as interest rates, bond yields, currency movements, equity-versus-bond allocat
Eren Biri: How Volatility Traders Think and What Defines AI-Native Hedge Fund | Blushing Quants #28
Eren Biri is the founder of OneEye Capital, a volatility-focused investment firm built around a strong mix of quantitative research, discretionary overlays, and deeply engineered infrastructure. With a background in computer engineering, experience at Goldman Sachs and multiple hedge funds, and a career that moved from quant research into trading and portfolio management, he brings a highly practi
Nikolai Nowaczyk: Credit Risk and Quant Infrastructure | Blushing Quants #27
Nikolai Nowaczyk is a mathematician, published researcher, and quantitative risk professional with a background spanning academia, consulting, and banking. With deep experience in counterparty credit risk, model development, and validation, he brings a rare perspective on how highly technical mathematical ideas are actually implemented inside major financial institutions.
In this episode, we get i
Ufuk Tasdan: Physics, Crypto, and Energy Market Complexity | Blushing Quants #26
Ufuk Tasdan is a quantitative researcher with an unconventional background spanning physics, philosophy of physics, cryptocurrency trading, and energy market analytics. After studying physics and completing a PhD in philosophy of physics, he moved into applied quantitative work, first in crypto and later in European energy markets, where he focuses on price forecasting, market analysis, and model
Oded Shimoni: Low-Correlation Strategies, Research, and ETF Innovation | Blushing Quants #25
Oded Shimoni is the CEO of AlphaBeta, a quantitative R&D company focused on systematic, low-correlation investment strategies across products such as mutual funds, alternative ETFs, hedge funds, and tracking funds. His work sits at the intersection of quantitative research, portfolio construction, factor investing, and the growing world of liquid alternative investment vehicles.
In this episod
Ben Charoenwong: Academia, Hedge Funds, AI, and Applied Finance | Blushing Quants #24
Ben Charoenwong is a finance professor, researcher, and fund manager working at the intersection of academia, quantitative investing, and applied market practice. As an associate professor at INSEAD and co-founder of Chicago Global, he brings a rare perspective shaped by both rigorous academic training and the real constraints of building and managing investment strategies in live markets.
In this
Garret Brennan: Deterministic AI for Institutional Quant Workflows | Blushing Quants #23
Garret Brennan is the co-founder and CEO of Epoch, an AI-native quantitative research startup building tools for institutional investors who want to integrate AI into their workflows without sacrificing rigor, determinism, or trust. With a background on the fixed income desk at Bank of Montreal in New York, Garret brings both market experience and startup urgency to the problem of making quantitat
Roman Isachenko: Alpha Decay, Derivatives, and the Reality of Quant | Blushing Quants #22
Roman Isachenko is a quantitative researcher with a background in applied mathematics and rocket science who moved from engineering into finance, derivatives, and systematic trading. His experience spans risk management, derivative pricing, asset management, and small hedge fund environments, giving him a grounded view of how quant research actually works when capital, time, and market reality put
Zach Marx: Where Retail Sentiment Meets Systematic Equities | Blushing Quants #21
Zach Marx is the Chief Investment Officer of Vineyard Quant Capital, where he works at the intersection of systematic equity investing, institutional flow, and data-driven portfolio construction.
In this episode, we get into what it actually takes to build a quantitative investment process around how institutions and retail investors make decisions, and how that can be turned into a systematic equ
Mark Aron Szulyovszky: Crypto, Alpha Factors, and Market Neutrality | Blushing Quants #20
Mark Aron Szulyovszky is a crypto quant and an entrepreneur focused on cross-sectional alpha factors in digital assets. He works to surface crypto-native factors, build market-neutral portfolios, and turn research on derivatives, microstructure, and token-specific behavior into tradable products for both internal use and external clients.
In this episode, we get into what it actually takes to buil
Manuel Ritsch: AI, Asset Management, and the Business of Funds | Blushing Quants #19
Manuel Ritsch is the founder of Alpha Rho Technologies, where he is building AI-native investment infrastructure for asset management. After seeing how much of the industry still relied on outdated tools and manual processes, he set out to replicate the work of human analysts with AI and turn that into a real operating model for funds.
In this episode, we step slightly outside pure quant research
Francisco Prack: Tape Reading, RL, and Sequential Decision-Making | Blushing Quants #18
Francisco Prack is a quant, economist, and portfolio manager with 30+ years of experience across financial markets, and a background spanning traditional finance, quantitative research, algorithmic trading, and crypto.
In this episode, we get into how a deeply model-driven way of thinking can shape an entire career in markets, from economics and traditional finance to algorithmic trading, reinforc
Denis Lukyanov: Quant Research, GenAI Agents, and Trading Systems | Blushing Quants #17
Denis Lukyanov is a quantitative researcher and AI/ML practitioner working at the intersection of finance, machine learning, and agentic systems.
In this episode, we get into what it really takes to integrate agentic systems and large language models into quant workflows, and why the hard part is not generating ideas quickly, but building something structured, testable, and useful in practice.
We
Toby Morris: Trading Desk Operations, Market Execution, and Sales Trading | Blushing Quants #16
Toby Morris works across multi-asset trading, client coverage, sales trading, and trading desk operations, helping clients execute effectively while keeping the desk, workflow, and decision-making process aligned behind the scenes.
In this episode, we go beyond job titles to explore what the trading desk actually looks like when clients, liquidity, technology, and judgment collide in real time.
We
Mattia Spreafico: AI Is Rewriting Quant Workflows | Blushing Quants #15
Mattia Spreafico is a quant based in Switzerland with an MSc in Quant Finance and a background in Mathematical Engineering from Politecnico di Milano.
In this episode, we go beyond job titles and get into what the next generation of quants is actually dealing with day to day inside large institutions, where speed, correctness, and deployment constraints collide.
We talk about how AI is already cha
Robert Tratt: 25 Years in Markets - From Prop Trader to Sharpe 4 Systems | Blushing Quants #14
Robert is a London-based systematic trader with 25+ years in markets. He started in the early 2000s prop trading futures, survived the no-simulator era, and evolved from discretionary trading into fully systematic research and automation. Today, he builds short-term strategies across equity indices and rates futures, and has recently helped a large institution stand up a proprietary trading team.
Haris Chalvatzis: From Fast Quant Research to Alpha, Execution, and Portfolio | Blushing Quants #13
Haris is a quantitative equity researcher and portfolio manager with experience across top-tier institutions, including BlackRock. Born in Greece, he studied applied computer science and applied mathematics, worked at the European Central Bank, then moved to the US for a Master's in Financial Engineering, and later built systematic equity models in the industry.
In this episode, we go into how qua
Israel Bergenstein: Systematic Strategy Design to Deployable Trading Models | Blushing Quants #12
Israel Bergenstein is a quant researcher with an MSc from Oxford, focused on building hedge-fund-style systematic strategies and translating research into deployable trading models. His work bridges the gap between academic quantitative thinking and real-world market implementation, with an emphasis on rigorous research, systematic strategy development, and the practical challenges of taking model
Carl Wells: The Quant System That Spots “Quality” Before Markets Do | Blushing Quants #11
Carl Wells is a systematic equity researcher and entrepreneur building an investment analytics platform focused on company quality, using CFROI and return on invested capital, along with deep accounting adjustments, to reveal the true economics behind financial statements.
In this episode, Carl shares his journey from physics to hedge funds, and how the 2008 crisis pushed him to unify fundamentals
Paul Bilokon: Backtesting, RL, and Robust Quant Research | Blushing Quants #10
Paul Bilokon is a veteran quant, educator, and entrepreneur with experience across major banks and systematic trading.
In this episode, we go deep into what actually makes research deployable: building a backtesting framework you can trust, cleaning and normalizing data correctly (rolls, corporate actions, microstructure effects), and stress-testing strategies against execution lags, transaction c
Raffaele Ghigliazza: Backtesting, LLMs, and Explainable Deployment | Blushing Quants #9
A sit-down with Raffaele Ghigliazza, a quant with a PhD background in mechanical engineering and deep work across applied math, dynamical systems, and neuroscience. He has spent about 20 years in finance, split between risk and asset management, and currently works as a macro-systematic researcher.
We discuss quant research after LLMs: what LLMs really changed, how to think about backtesting, and
Orlando Gemes: Market Efficiency, Dirty Data, and Pricing Beyond Black Scholes | Blushing Quants #8
Episode 8 with Orlando explores where market models work and where they fail, especially in credit markets where pricing is less observable, and data is often dirty. We cover how to find edge through data cleaning, why end-of-day pricing can mislead risk systems, and how to think about VaR and stress testing when liquidity shifts. We also discuss the limits of the Black-Scholes model for long-date
Matthias Bouquet: Systematic Macro and Volatility Trading Explained | Blushing Quants #7
Episode 7 features Matthias Bouquet, a quant who moved from a computer vision PhD into asset management, prop trading, banks, and hedge funds across Tokyo, London, and Singapore.
We cover why market ML is harder than vision, how overfitting shows up, and what actually helps in practice: solid validation, simpler models, better features, and strict risk management.
He also explains an options lens
Meir Barak: The Truth About Learning the Financial Markets | Blushing Quants #6 [HEBREW]
In Episode 6, we host Meir Barak, a veteran day trader, author, and the founder and chairman of Tradenet, where he focuses on building structured training programs for traders worldwide. We discuss what his day-to-day work looks like, including turning market behavior into repeatable frameworks, prioritizing risk discipline, and developing traders through process.
*DISCLAIMER*
The information sh
Marco Santanché: Quantitative Research in Practice - From KPIs to Live Trading | Blushing Quants #5
Marco Santanché, founder of Unbiased Alpha, joins the show to unpack what truly matters in quantitative research. We explore the key differences between institutional and retail trading, the real risks behind CFDs and leverage, and how quants turn vague client objectives into clear, actionable KPIs. The conversation also dives into realistic backtesting, why overfitting is so common, and when mach
Jared Broad: QuantConnect CEO and the Open-Source Quant Trading Stack | Blushing Quants #4
A sit-down with Jared Broad, CEO of QuantConnect, to unpack how one platform turned quant research, backtesting, and live execution into an end-to-end workflow. Jared explains why QuantConnect went open source in an industry that usually keeps everything secret, and why hedge funds waste years rebuilding the same infrastructure instead of focusing on alpha.
We break down what makes Lean “instituti
Oren Tapiero: How Machine Learning Works in Live Trading | Blushing Quants #3
A focused conversation with Oren Tapiero, a quantitative researcher at Tidal, on how machine learning is truly used in live trading. The discussion covers why the research question matters more than the model itself, how to approach feature engineering and causality instead of simple correlation, and why walk-forward backtesting and regime awareness are essential. A clear, reality-driven perspecti
Oz Pirvandy: The "S&P 500 Algorithm" Most Traders Don’t Understand | Blushing Quants #2
Oz Pirvandy is a Tel Aviv-based systematic fund manager and the founder of Elevate Algo Fund. With a background across economics, political science, mathematics, and data science, Oz brings a research-driven approach to portfolio construction, shaped by both academia and real-world experience in banks, where risk management is the primary priority.
In this episode, Oz explains why the S&P 500
Ryan Ling: Inside the Market Maker Playbook | Blushing Quants #1
Ryan Ling is a London-based systematic short-term interest rate (STIR) trader. Ryan studied Mathematics and Data Science, blending statistics and computer science, and has built his career across several parts of quantitative trading. He began in banking, structuring and exotics, then moved into crypto trading, including market-making and HFT, before transitioning into interest rate futures.
In th
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