3 Equity and ETF Scripts Long Term Growth Model Portfolio | Theme – Long Innings Companies | Rebalancing Monthly | Future Risk may Exceed 40% | Commodity ETFs Composition is 70% | 12 Months Subscription Plan

“Investment Objective:
Target companies with long operational histories, demonstrating resilience and sustainable competitive advantages.

Investment Rationale:
Enhanced Growth Potential over Long Horizons: Long innings companies typically have sustained competitive advantages, allowing them to capitalize on India’s economic growth over decades, offering superior long-term earnings potential compared to more cyclical or short-term assets.

Resilience and Stability: These companies often demonstrate consistent revenue streams, strong market positioning, and adaptability, making them less vulnerable to economic fluctuations and providing safer, stable returns compared to more volatile industries.

Significant Value Creation and Compounding: With their proven track record of enduring for decades, long innings companies benefit from compounding growth, delivering high cumulative returns and wealth accumulation over extended periods, outperforming many other asset classes focused on shorter-term gains.

Investment Methodology:
1. The broad universe for securities comprises of listed companies within the NSE 500 Index and all ETFs, which are meticulously filtered qualitatively in accordance with the predefined investment objective and investment rationale.
2. Proprietary algorithms, advanced quantitative models, and technical analysis are applied to systematically identify securities with the highest likelihood of delivering superior returns.
3. These models, extensively validated across various asset classes and time horizons, incorporate customized proprietary indicators of momentum, volume, volatility, and trend, ensuring that portfolio construction is entirely driven by objective data and high-quality signals, free from biases, prejudices, or emotional influence.
4. The selection of securities and their respective weightings within the model portfolio is further optimized based on factors including the target portfolio size, ETF allocation, average daily trading turnover, available investment capital, rebalancing frequency, as well as the number of quantitative and technical criteria met by each security.”