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Quantitative trading strategies exploiting statistical mispricings between cointegrated assets while maintaining market neutrality.
Quantitative trading strategies exploiting statistical mispricings between cointegrated assets while maintaining market neutrality.
StatArb applies mathematical time-series modeling, PCA, and high-frequency algorithms to capture relative value price deviations across stock baskets or futures contracts.
Market neutral design eliminates broad index exposure.
High portfolio diversification across hundreds of asset pairs.
Algorithmic trading is the use of computer programs to automate order generation, submission, and execution in financial markets. It spans systematic strategies (where the algorithm decides what to trade), execution algorithms (where the algorithm decides how to trade an existing decision), and high-frequency market-making. The defining feature is that a machine not a human produces and manages the orders.
Market microstructure is the study of how exchange mechanics shape price formation, liquidity, and execution costs. The dominant academic reference is Harris (2003) and O'Hara (1995). The dominant practitioner applications are the design of execution algorithms and the design of market-making strategies, both of which depend on a quantitative model of the order book and its dynamics.