Advancing
Quantitative Insight
Through hands-on projects, collaborative learning sessions, and lectures led by industry practitioners, we equip our members with the tools and experience to understand, model, and innovate in today’s global financial markets.
Only at FBA Quant
We challenge conventional thinking in quantitative finance through research, projects, and peer-driven learning. United by curiosity and ambition, we pursue initiatives that thrive in the unique, collaborative environment only FBA Quant can offer.
Our Competitive Advantage
Exceptional Talent
FBA Quant brings together individuals in finance, math, and data science to tackle real-world problems through collaboration and research.
Hands-On Experience
We offer research-focused internships and run a proprietary trading project with realistic backtesting and mid- to high-frequency infrastructure.
Structured, Scalable Learning
Our curriculum combines core concepts with specialized tracks, delivering scalable, rigorous training for future leaders in quant finance.
Expertise Across Quantitative Domains
Our curriculum is designed to build the core knowledge and technical skills essential in today’s quantitative finance industry.
Through one foundational core session and four specialized sessions, members gain comprehensive exposure to the diverse fields that drive modern quant research and trading.
Curriculum
Core 1. Financial Engineering
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Financial Derivatives
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Computational Methods
This session introduces the application of stochastic models for pricing derivative securities across various asset classes, including equities, fixed income, and credit. Participants will explore numerical techniques and Monte Carlo simulation methods for solving practical problems in derivative pricing. The session also covers portfolio optimization and advanced topics in financial engineering, such as algorithmic trading strategies and real options valuation.
Spec 1. Fixed Income & Foreign Currency
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Term-Structure Models
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Volatility Derivatives
Learn the basic structure and the pricing of interest rates and related contracts such as LIBOR, bonds, interest rate swap (IRS), forward rate agreement (FRA), cap/floor, overnight index swap (OIS), and swaptions. Cross-currency interest rate swap (CCS) and FX swap will be covered in detail. We will learn to apply the basic tools duration and convexity for managing the interest rate risk of interest-rate derivatives trading.
Spec 2. Asset Pricing
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Factor Models
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Mean-Variance Analysis
Learn the overview of asset pricing. We will start from the classic factor pricing model and then expand to further concepts, including the consumption-based model, GMM, and the application of regression-based tests of linear factor models. Estimating the risk and return and optimizing the portfolio will be covered. We will also use machine learning techniques to design more robust and dynamic asset pricing models.
Spec 3. Market Microstructure
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Market Microstructure
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Stochastic Optimization
Learn to develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. We will also learn the combination of sophisticated mathematical modeling, empirical facts, and financial economics to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms.
Spec 4. Trading-System Development
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Trading System
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System Architecture
Learn to develop trading system. This course aims to develop high performance and stable trading systems. We learn trading system architecture components like gateways for receiving price data and order management. And we develop programs to communicate with exchanges using WebSocket and REST API protocols. We also deal with high level programming techniques to optimize trading systems, including multi-processing, multi-threading and asynchronous I/O.
