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In the aftermath of the 2008 financial crisis and the recent explosion of algorithmic trading, one truth has become undeniable: modern finance is a quantitative science. Gone are the days of gut feelings and ticker-tape reading. Today, the world’s most sophisticated hedge funds, investment banks, and regulatory bodies rely on a rigorous framework of equations, simulations, and data.
Traditional financial models assume markets follow specific mathematical distributions. Machine learning algorithms, however, can find non-linear patterns in vast alternative datasets (like satellite imagery or social media sentiment) without rigid prior assumptions. Quantum Computing mathematical modeling and computation in finance pdf