3 Equity and ETF Scripts Long Term Growth Portfolio | Mixed Sectors 11 – Electrical Equipment – NBFCs – Industrial Manufacturing – Iron & Steel Products – Metals & Mining | Rebalancing Monthly | Commodity ETFs Composition is 40% | 12 Months Subscription Plan

₹3,875.00 for 1 year

Telegram Bot Command for @ShubhaangBot : /ms11_3_155000_c_40

Portfolio Parameters

Parameter	Value
Scripts Group Title	Mixed Sectors 11 – Electrical Equipment – NBFCs – Industrial Manufacturing – Iron & Steel Products – Metals & Mining
Portfolio Size	3 Equity and ETF Scripts {2 Equities and 1 Commodity ETF}
ETFs Composition Percentage	Commodity ETFs Composition is 40%
Portfolio Risk	Future Risk may Exceed 60%
Minimum Annual Investment Capital	₹ 1,55,000
Optimal Investment Tenure	12 or more years.
Rebalancing Frequency	Rebalancing Monthly
Subscription Tenure	12 Months Subscription Plan
Backtest – Sharpe Ratio	Hist. Sharpe Ratio above 1.3
Backtest – Annualised Returns	Hist. Annualised Returns Under 65%
Backtest – Annualised Risk	Hist. Annualised Risk Exceeding 40%
Backtest – Max. Drawdown	Hist. Max. Drawdown Exceeding 35%
Backtest – Max. Recovery Time	Hist. Max. Recovery Time Exceeding 10 Quarters
Simulation – Lumpsum Capital Growth Multiple	** More than 127 times in 20 yrs with 99.9% probability

Probability Levels (%)	20 Years	15 Years	10 Years	5 Years	3 Years	1 Year
99.9% Probability	** 127.54	18.68	3.21	0.73	0.49	0.42
99% Probability	554.83	66.79	9.16	1.54	0.86	0.60
98% Probability	942.19	106.35	13.33	2.00	1.06	0.68
95% Probability	2,110.23	213.49	23.36	2.98	1.44	0.82
90% Probability	4,395.35	401.38	38.91	4.27	1.90	0.96
80% Probability	11,140.84	891.49	74.00	6.66	2.67	1.17
75% Probability	16,265.99	1,230.95	95.87	7.96	3.06	1.26
50% Probability	2,55,439.77	11,369.34	505.71	22.51	6.48	1.86

Refer to the “Backtests & Simulations” tab for further details on their operational settings.

Target electrical equipment, NBFCs, industrial manufacturing, and metals/mining companies driven by industrial growth and infrastructure investments.

Strong Economic Backbone: These sectors are foundational to India’s growth, driven by infrastructure expansion, urbanization, and industrialization, providing long-term growth prospects compared to more cyclical or less strategic industries.
Government and Policy Support: Sectors like electrical equipment, metals, and mining benefit from supportive government policies, infrastructure upgrades, and increasing investment in renewable energy and manufacturing, reducing regulatory and market risks.
Global Commodity Price Linkages and Value Chains: These sectors are closely linked to global demand for metals and steel, enabling them to capitalize on international growth trends, offering higher return potential and diversification compared to other asset classes such as fixed income or traditional consumer sectors.

Universe Definition: The investment universe encompasses securities from listed companies within the NSE 500 Index and all exchange-traded funds (ETFs), which are rigorously filtered based on qualitative measures aligned with predefined investment objectives and rationales.
Systematic Identification: Proprietary algorithms, advanced quantitative models, and technical analysis are utilized to systematically identify securities with a high probability of delivering superior returns.
Data-Driven Framework: These models, thoroughly validated across diverse asset classes and various time horizons, integrate customized proprietary indicators such as momentum, volume, volatility, and trend analysis. This approach ensures that the portfolio construction process is entirely based on objective data and high-quality signals, devoid of biases, prejudices, or emotional factors.
Optimisation of Security Selection: The selection of securities and their corresponding weightings within the Equity/ETF portfolio are further refined based on critical factors, including target portfolio size, ETF allocation, average daily trading turnover, available investment capital, rebalancing frequency, and the number of quantitative and technical criteria met by each security.

Backtest models are constructed using a limited set of assumptions about market conditions and portfolio characteristics; therefore, backtest results should not be interpreted as indicative of actual past performance in real-world conditions.
Backtest results and Simulation results should never be used as a basis for comparing the actual performance of other intermediaries.
Backtest and simulation outputs are provided solely as factual data to support comparative assessment of my subscription plans. They highlight the model’s potential in relation to the portfolio’s investment rationale and parameters under the stated investment methodology.
Simulation results are derived from 10,00,000 trials and represent potential future scenarios based on normalised inputs (average returns and return volatility) obtained from backtesting.
Users are strongly advised to exercise extreme caution when using this information.
These back-test results and simulation have not been verified by PaRRVA (Past Risk and Return Verification Agency) or any other SEBI-recognized agency.
The impact of periodic portfolio rebalancing and transaction costs has been factored into these back-test results.
"Backtesting and simulation results do not serve as indicators of future performance or guarantees of returns and they should not be interpreted as an endorsement or advertisement."

Monthly Portfolio Returns are assumed to follow a normal distribution over a 20-year horizon, with mean returns and volatility presumed to mirror historically observed levels.
Portfolios are rebalanced once monthly.
Portfolio risk level and Sharpe ratio are assumed to remain unchanged over the 20-year period.
Other than the initial lump sum investment, no additional contributions or withdrawals are made over the 20 years period.
Portfolio rebalancing is assumed to be unconstrained by liquidity over the 20‑year period: required quantities of each security can be bought or sold at competitive prices on every rebalancing, and transaction volumes are assumed to have a negligible impact on market prices.
Earnings from dividends are ignored.
Simulation results are not adjusted for inflation rates.
Effects of taxes on the capital appreciation (Capital Gains Tax & Taxes on Dividends) are not accounted.

Transactional costs are included in the Sharpe ratio calculations.
Risk free rate is assumed to be 6.5% p.a.
Each simulation value is resulted from 10,00,000 simulation trials using the Monte Carlo method.
Simulation results are derived for probability levels (confidence levels) of 99.9%, 99%, 98%, 95%, 90%, 80%, 75%, and 50%.
Simulation values do not predict or reflect future market conditions; they represent only possible future outcomes.