| ABSTRACT |
This paper introduces the Smart Portfolio Optimizer, a decision-support framework engineered to
empower Indian retail investors by delivering data-driven, optimal asset allocation strategies. The system addresses the
critical challenge individ- uals face in balancing investment risk and return, a task compounded by the inherent volatility
and diverse asset landscape of the Indian stock market. By integrating a suite of advanced statistical and financial
models—including Markowitz Mean-Variance Optimization, the Black-Litterman model, Risk Parity, and Minimum
Variance Portfolio—the framework provides personalized portfolio recommendations tailored to user-defined risk
tolerance and financial objectives. Unlike generic investment platforms that often provide opaque recommendations,
this solution prioritizes transparency and ex- plainability. It equips investors with a comprehensive suite of risk
analytics, such as Value at Risk (VaR) and Conditional VaR (CVaR), and robust validation through a historical
backtesting engine. The core contribution of this work lies in bridging the gap between sophisticated quantitative
finance theory and practical, actionable investment guidance. By pro- viding a rational, logic-based alternative to
emotionally driven decision-making, the Smart Portfolio Optimizer enables investors to understand the rationale behind
their portfolio construction, manage risk effectively, and systematically pursue long-term wealth creation within the
specific context of the Indian market. |
