Risk Management Machine Learning

Home Address: * ********* *****, ***** ******, Putney, SW15 3LU

Daniel Bloch

Contact: 074**-****** – ***.*****@*****.**

https://www.linkedin.com/in/daniel-bloch-60098a22/ https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=802495 Consulting History

Quant Finance Ltd: Director (founding member) Mar 2013 – Pioneering Quantitative Trading with AI and Advanced Forecasting Models

• Systematic Strategy Design: Crafts systematic strategies across equities, futures, ETFs, and options, providing tools to quantify arbitrage opportunities and assess relative market value.

• Designed and developed the RMA strategy, delivering exceptional risk-adjusted returns with Sharpe Ratios exceeding 20 and Sortino Ratios above 30.

• Demonstrated RMA’s scalability and robustness, achieving increasing risk-return metrics as portfolio size grows and ensuring seamless adaptability across global markets and timeframes.

• Advanced Pricing Models: Developed innovative pricing models to tackle real trading challenges in option pricing, market making, volatility trading, and risk management.

• AI-Driven Strategy Creation: Built quantitative strategies with AI and ML to forecast return distributions, supported by a dedicated, high-performance backtesting engine.

• Next-Gen Backtesting: Engineered a backtesting platform using ML for synthetic scenarios, distribution analysis, and probabilistic risk/return profiling.

Teaching

VinUniversity: Distinguished Visiting Professor (College of Engineering and Computer Science) Jun 2025 –

• Research and Mentorship: Active engagement through lectures, supervision, and collaborative projects. University Paris 1 Pantheon Sorbonne: Lecturer (M2 IRFA and MMMEF) Sep 2025 –

• Algorithmic Trading course at Master in Applied Mathematics and Financial methods.

• Advanced Algorithmic Trading course at Master in Applied Mathematics and Financial methods. CQF: Expert Lecturer in Reinforcement Learning May 2024 –

• Guiding Tomorrow’s Innovators: Leading an advanced module on Reinforcement Learning, bringing real-world insights and expertise to equip professionals with cutting-edge skills in dynamic decision-making models and AI-driven solutions. https://www.cqf.com/why-cqf/lecturers/our-faculty/dr-daniel-bloch. Employment History

Blu Analytics: Head of Quantitative Strategies (founding member) Oct 2021 – Apr 2024 Driving Market Insight with NLP, Reinforcement Learning, and Advanced ML

• NLP for Market Signals: Led a specialized team using Natural Language Processing to anticipate market movements from news data, generating actionable trading signals.

• Quant Strategies & Risk Management: Developed quantitative trading strategies and a robust risk management system leveraging Reinforcement Learning and stochastic calculus.

• Strategic Financial Modelling: Built sophisticated financial strategies, including option pricing, advanced quant models, and a dedicated backtesting engine.

• Automated Event-Driven Trading: Achieved a competitive edge by deploying state-of-the-art machine learning techniques, fully automating our event-driven trading platform, and enhancing risk management. Wipro: Jan 2020 – Jul 2021

AI & Machine Learning Strategist Digital Transformation Leader

• AI Strategy & Business Alignment: Translated business vision into AI and data-driven solutions, ensuring seamless integration with existing processes and scaling AI capabilities across organizations.

• Digital Transformation & Governance: Designed execution roadmaps, program governance models, and transition strategies to drive digital transformation initiatives.

• Cutting-Edge AI & NLP Development: Developed AI response systems leveraging state-of-the-art models (GPT, BERT, ELMo, MASS) to enhance natural language understanding and generation.

• AI-Driven Public Sector Innovation: Led AI/ML initiatives for NHS-NSS, deploying predictive models for healthcare applications

(e.g., demand forecasting, patient risk prediction, and fraud detection) using Azure ML.

• Advanced Data Science & ML Solutions: Delivered AI-powered solutions for financial institutions, including entity resolution, fraud detection, and NLP-driven sentence pair modelling with deep learning architectures. Home Address: 5 Magdalene House, Manor Fields, Putney, SW15 3LU Heuris Capital LLP: Portfolio Manager, Alternative Trading Strategies Group (founding member) Oct 2013 – Apr 2016 Global Multi-Asset Trading Powered by Advanced AI and Multifractal Analysis

• Multi-Asset Global Strategy: Directed systematic trading across regions, using multifractal analysis and machine learning to drive insights across markets.

• AI-Driven Forecasting: Developed forecasting models that integrate stochastic calculus, fractal theory, and multifractal networks with recurrent neural networks and reinforcement learning.

• Precise Market Predictions: Built advanced models to predict absolute returns and market direction with each trading step.

• Enhanced Option Trading: Elevated systematic options trading by applying a no-arbitrage volatility surface that accounts for time and spatial dynamics.

• Sophisticated Vanilla Option Strategies: Implemented high-precision systematic strategies for vanilla options trading. ANZ (HK): Global Head of the Equity Quant Team Aug 2011 – Nov 2012 Advanced Pricing and Risk Solutions in Equity and Options

• Exotic Equity Pricing and Risk Management: Led the integration of stochastic and local volatility models for exotic equity products, implementing dynamic volatility surfaces to enhance precision.

• Systematic Trading Innovations: Developed robust strategies, supervised the vanilla options trading platform, and validated the Murex platform for streamlined performance.

• Collaborative Risk Review: Partnered closely with Model Validation and Market Risk teams to review models, conduct risk assessments, and establish trading limits for fortified risk control. Mizuho Securities (Tokyo): Global Head of the Equity & Hybrid Quant Team Jun 2007 – Aug 2011 Global Portfolio Valuation and Risk Mastery

• Comprehensive Pricing and Risk Solutions: Directed the global pricing and risk management library, integrating stochastic interest and FX rate models with local volatility for accurate valuation and hedging of the bank’s portfolio.

• Strategic Risk Partnership: Collaborated with Model Validation and Market Risk teams to rigorously review models, perform in-depth risk assessments, and set precise trading limits to reinforce portfolio security. Education

Université de Paris 6: PhD in Applied Mathematics to Finance 2001-2006

• Continuation of PhD in Applied Mathematics to Finance from École Polytechnique.

• Passed with highest distinction, supervised by Prof N. El Karoui. École Polytechnique: PhD in Applied Mathematics to Finance, supervised by Prof. N. El Karoui 1994-1996 University of Oxford: MPhil in Applied Mathematics to Finance 1993-1995

• Combination of MSc in Modelling and Numerical Analysis, and MSc in Probability and Statistics.

• Thesis in mathematics applied to the modelling and the pricing of options, supervised by Prof. P. Wilmott Books

• Artificial intelligence in Mathematics, with Miquel Noguer i Alonso. Edited by Springer Q2 2026

• Artificial intelligence in Finance (Vol 2), with Miquel Noguer i Alonso. Edited by Risk Q2 2025

• Artificial intelligence in Finance (Vol 1), with Miquel Noguer i Alonso. Edited by Risk, https://riskbooks.com/artificial-intelligence- in-finance-volume-1-fundamentals-and-applications Q4 2024

• Futuretesting Quantitative Strategies, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4647103 Nov 2023

• Option Pricing: Theory and applications, http://ssrn.com/abstract_id=3467551 Oct 2019

• Machine Learning: Models and Algorithms, http://ssrn.com/abstract=3307566 Jan 2019 Publications

Currently ranked among the top authors on SSRN, placing 909th out of 2,214,517—an achievement that positions me in the top 0.041% of contributors globally.

• False Confidence in Systematic Trading: Illusion of Speed and Mirage of Performance, SSRN Aug 2025 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5393135

• False Findings in Finance: The Hidden Costs of Misleading Results in the Age of AI, SSRN Jul 2025 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5345109

• A Course On Systematic Trading With RMA, SSRN Jun 2025 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5278107

• Why AI will Never Predict Financial Markets, Risk Magazine Apr 2025 Home Address: 5 Magdalene House, Manor Fields, Putney, SW15 3LU

• Dynamically Characterising Time Series with Relative Moving Moments, Wilmott Magazine Mar 2025

• Artificial Neural Networks in Finance, Wilmott Magazine Jan 2025 https://wilmott.com/wilmott-magazine-january-2025-issue/

• Detecting and Predicting Price Jumps with Consecutive Signature Distance, Wilmott Magazine Nov 2024 https://wilmott.com/wilmott-magazine-november-2024-issue/

• Optimal trading with OST-TDBP, SSRN Oct 2024

• Pricing American Options with OST-TDBP, SSRN Oct 2024

• DeepNet Jump Models: Detecting and Predicting Price Jumps with Mahalanobis Distance and Signatures Jan 2024 http://ssrn.com/abstract=4702829

• Stocks and Options Portfolio Optimisation with Reinforcement Learning, Wilmott Magazine Jul 2024 https://wilmott.com/wilmott-magazine-july-2024-issue/

• American Options: Models and Algorithms Aug 2023 http://ssrn.com/abstract=4532952

• A Review of “The Pricing of Options and Corporate Liabilities”, Wilmott Magazine Jul 2023 https://wilmott.com/wilmott-magazine-july-2023-issue-50th-anniversary-of-black-scholes-merton-part-2/

• Modelling and trading the Effects of Corporate Events, SSRN Feb 2023

• Learning the Pricing Kernel: Applications, SSRN Feb 2023

• Option Prices Expansions and Applications, Wilmott Magazine Jan 2023 https://wilmott.com/wilmott-magazine-january-2023-issue/

• Smiling in Action, Wilmott Magazine Jul 2022

https://wilmott.com/wilmott-magazine-july-2022-issue/

• Hedging Climate Risk, Wilmott Magazine Jan 2013

• Introducing the Climate Credit Mechanism, Wilmott Magazine Nov 2013

• From Implied Volatility Surface to Quantitative Options Relative Value Trading, Wilmot Magazine Aug 2013 Conference Talks

• Agents, algorithms, and market intelligence: Rethinking AI in finance, Risk Live Europe Jun 2025 https://europe.risklive.net/speakers/6811fba60abd62f2a0b19d85

• Integrating digital transformation across a fragmented regulatory landscape, Risk Live Europe Jun 2025 https://europe.risklive.net/speakers/6811fba60abd62f2a0b19d85

• Detecting and Predicting Price Jumps with Mahalanobis Distance and Signatures, CQF Machine learning in Sep 2024 quant finance, Quant Insights Conference

https://www.cqfinstitute.org/content/industry-talk-detecting-and-predicting-price-jumps-mahalanobis-distance-and-signatures

• Results on Pricing American Options with Reinforcement Learning, CQF Machine learning in quant finance, Sep 2023 Quant Insights Conference

https://www.qiconference.com/machine-learning-and-quantum-computing/

• Learning the Pricing Kernel: Applications to Option Pricing, Mathematical Finance, NYU May 2023 https://cims.nyu.edu/dynamic/calendars/seminars/mathematical-finance-financial-data-science-seminar/3813/

• AI Innovation in Finance Roundtable, Blu Analytics Nov 2022

• Modelling the dynamics of the entire implied volatility surface with deep learning, CQF Institute Talk Aug 2022 https://www.cqfinstitute.org/content/modeling-dynamics-entire-implied-volatility-surface-deep-learning

• From carbon allowances to climate derivatives, Energy Risk, London Oct 2012

• Pricing options on CDOs, Quant Congress USA, New York Jul 2006

• Equity derivatives/stochastic volatility, option on variance and equity hybrids, WBS, London Apr 2006

• Euro Quant Congress, Risk, London Oct 2005

Skills

• Quantitative Finance: Option Pricing, Systematic Trading

• Mathematics: Stochastic Calculus, Stochastic Control, Signatures Methods

• Programming Languages: Python, C++, C, R, VBA

• Machine Learning:

o Techniques: Reinforcement Learning, NLP, Multifractal Networks, Ensemble Models, Constrained Optimisation, Associative Reservoir Computing, Probabilistic Networks, Recurrent Neural Networks, Artificial Neural Networks, Complex Networks, Supervised Learning, Unsupervised Learning o Python Libraries: PyTorch, JAX, LAX, RLAX, TensorFlow, Keras

• Languages: Fluent in French and English

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