Quantitative finance is the discipline that uses mathematical models, statistical analysis, and computational methods to understand financial markets and support investment decisions. By translating complex market behaviour into measurable patterns, it allows investors to evaluate risk, return, and correlation relationships within portfolios. This approach replaces subjective interpretation with data-driven reasoning, leveraging time-series analysis, probability theory, econometrics, and machine learning to uncover consistent relationships in prices and volatility. Quantitative models estimate the likelihood of outcomes, assess performance stability, and support systematic portfolio construction across asset classes. In portfolio management, quantitative finance helps align risk exposure with expected returns through rigorous modelling of uncertainty, diversification, and market dynamics. It enables managers to test strategies, identify structural patterns in data, and respond objectively to changing conditions. The result is more transparent, repeatable, and risk‑controlled investment performance based on statistical evidence rather than sentiment. Techniques derived from quantitative finance underpin modern asset pricing, risk management, and automated trading systems. They provide the analytical foundation behind hedging strategies, performance attribution, factor investing, and scenario testing—allowing portfolios to adapt efficiently to new information and shifting correlations within complex markets.