1 Mutual Fund Long Term Growth Portfolio | MutualFunds_Equity_LargeMid Cap | Rebalancing Quarterly | 12 Months Subscription Plan

₹375.00 for 1 year

Telegram Bot Command for @ShubhaangBot : /mfeqlm_1_15000_n_0

Portfolio Parameters

Parameter	Value
Scripts Group Title	MutualFunds_Equity_LargeMid Cap
Portfolio Size	1 Mutual Fund {1 Mutual Fund and 0 Equities or ETFs}
ETFs Composition Percentage	Equities and ETFs Composition is 0%
Portfolio Risk	Future Risk may Exceed 35%
Minimum Annual Investment Capital	₹ 15,000
Optimal Investment Tenure	7 or more years.
Rebalancing Frequency	Rebalancing Quarterly
Subscription Tenure	12 Months Subscription Plan
Backtest – Sharpe Ratio	Hist. Sharpe Ratio above 0.6
Backtest – Annualised Returns	Hist. Annualised Returns Under 20%
Backtest – Annualised Risk	Hist. Annualised Risk Exceeding 15%
Backtest – Max. Drawdown	Hist. Max. Drawdown Exceeding 10%
Backtest – Max. Recovery Time	Hist. Max. Recovery Time Exceeding 4 Quarters
Simulation – Lumpsum Capital Growth Multiple	** More than 2.3 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	** 2.33	1.45	0.97	0.71	0.67	0.70
99% Probability	3.91	2.30	1.41	0.93	0.83	0.80
98% Probability	4.71	2.70	1.60	1.02	0.89	0.83
95% Probability	6.22	3.43	1.95	1.17	0.99	0.89
90% Probability	7.99	4.26	2.33	1.33	1.09	0.94
80% Probability	10.90	5.57	2.89	1.55	1.23	1.01
75% Probability	12.33	6.19	3.15	1.64	1.29	1.03
50% Probability	24.44	10.99	4.94	2.22	1.61	1.17

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

To achieve capital appreciation by investing in equity large and mid-cap mutual funds that offer a blend of stability and growth potential across various market segments.

Balanced Growth Potential: Large and mid-cap mutual funds combine the stability of established large-cap companies with the growth prospects of mid-cap firms. This blend allows investors to benefit from the steady performance of larger companies while also capitalizing on the potential for higher returns that mid-cap stocks can provide, creating a well-rounded investment opportunity.
Diversification Across Market Capitalizations: Investing in both large and mid-cap stocks provides greater diversification within the equity portion of your portfolio. This diversification can help reduce risk, as different segments of the market may react differently to economic conditions, leading to more stable returns over time.
Access to High-Quality Growth Opportunities: Large and mid-cap mutual funds often focus on companies with strong fundamentals, good management, and growth potential. By investing in these funds, investors can tap into a selection of high-quality stocks that are well-positioned for future growth, thereby enhancing the potential for capital appreciation while maintaining a lower risk profile compared to small-cap investments.

Universe Definition: The investment universe comprises all open-ended equity-based mutual funds, providing a comprehensive range of options for portfolio construction.
Systematic Identification: Proprietary algorithms and advanced quantitative models are employed to rigorously identify mutual funds with the highest potential for superior returns. This assessment is grounded in historical performance and various fund characteristics.
Data-Driven Framework: The models, extensively validated across multiple fund types and time horizons, integrate customized proprietary indicators such as momentum, volatility, and trend analysis. This ensures that the portfolio construction process is strictly based on objective data and high-quality signals, devoid of biases, prejudices, or emotional influences.
Optimisation of Fund Selection: The selection of mutual funds, along with their respective weightings within the mutual fund portfolio, is optimized based on essential factors, including target portfolio size, expense ratio, minimum investment requirements, exit load, assets under management (AUM), and available investment capital.

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.