Quantitative Research Fund
The Club de Trading HEC’s Quantitative Research Fund is a student-led initiative dedicated to the research, implementation, and backtesting of trading strategies. The fund operates under the supervision of faculty members and provides a structured environment that connects academic theory with applied quantitative research.
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This year, the fund is organized into three research teams. One team focuses on multifactor strategies, another on forecasting strategies, and a third on cointegration-based strategies. Each team explores distinct quantitative approaches while contributing to a cohesive and collaborative research framework.
Factor Investing Strategy
The Factor Investing strategy is developed and managed within a student-led research framework at the Club de Trading HEC. It is based on the systematic study of well-established investment factors such as value, momentum, low volatility, quality, and size. These factors have been extensively documented in academic research and are widely used in professional asset management.
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Students design and implement a multifactor approach that combines these complementary sources of return into a single portfolio framework. Through structured research, portfolio construction, and disciplined rebalancing, the strategy aims to apply academic theory to real market data while developing strong quantitative, analytical, and risk-management skills.
Cointegration-Based Pair Trading Strategy
The Pair Trading strategy relies on a cointegration-based framework to identify pairs of assets that exhibit a stable long-term relationship. By focusing on relative price movements rather than market direction, the strategy seeks to detect temporary deviations from equilibrium that may present trading opportunities.
When such deviations occur, long/short positions are established to benefit from mean reversion while maintaining a market-neutral exposure. This approach allows students to explore statistical arbitrage techniques and emphasizes rigorous model validation, risk control, and disciplined execution.
Forex Quantitative Trading Strategy
The Forex strategy focuses on the systematic analysis of currency markets using quantitative methods and machine learning techniques. It targets major currency pairs in highly liquid markets and integrates market data, macroeconomic indicators, and alternative information sources to simulate price predictions.
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Students develop and test predictive models to generate trading signals and evaluate their performance through structured backtesting. The strategy emphasizes robustness, out-of-sample validation, and disciplined risk management, providing hands-on experience with machine learning applications in foreign exchange markets.