Quantitative analysis

Tag: NumPy

  • Statistical arbitrage – cointegration – pairs

    Statistical arbitrage – cointegration – pairs

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    by

    Bogdan Ciocoiu
    in

    Statistical arbitrage (or stat-arb) has become a powerful strategy for quantitative traders to exploit price discrepancies between financial instruments. By harnessing Python’s robust data analysis and statistical libraries, quantitative developers can implement sophisticated trading strategies, including pairs trading, to find and profit from mispricings.  Python libraries Python has emerged as the go-to programming language for quantitative finance due to…

  • Kalman filter

    Kalman filter

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    by

    Bogdan Ciocoiu
    in

    As a quantitative analyst in financial markets, it is crucial to deploy models that can efficiently manage missing or noisy data and extract meaningful trends. The Kalman filter is one of the most robust tools for this purpose. Originating from control theory, the Kalman filter is now extensively used in finance to smooth out noise in time…