2 Mutual Funds Long Term Growth Portfolio | MutualFunds_AllFunds | Rebalancing Quarterly | 12 Months Subscription Plan

₹1,500.00 for 1 year

Telegram Bot Command for @ShubhaangBot : /mfall_2_60000_n_0

Portfolio Parameters

Parameter	Value
Scripts Group Title	MutualFunds_AllFunds
Portfolio Size	2 Mutual Funds {2 Mutual Funds and 0 Equities or ETFs}
ETFs Composition Percentage	Equities and ETFs Composition is 0%
Portfolio Risk	Future Risk may Exceed 40%
Minimum Annual Investment Capital	₹ 60,000
Optimal Investment Tenure	8 or more years.
Rebalancing Frequency	Rebalancing Quarterly
Subscription Tenure	12 Months Subscription Plan
Backtest – Sharpe Ratio	Hist. Sharpe Ratio above 1.2
Backtest – Annualised Returns	Hist. Annualised Returns Under 35%
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 20.5 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	** 20.58	7.09	2.60	1.09	0.83	0.72
99% Probability	38.76	12.30	4.10	1.50	1.07	0.84
98% Probability	48.54	14.97	4.82	1.69	1.17	0.88
95% Probability	68.00	20.06	6.13	2.00	1.34	0.96
90% Probability	92.14	26.09	7.60	2.33	1.50	1.03
80% Probability	134.69	36.18	9.90	2.81	1.74	1.12
75% Probability	156.65	41.19	10.99	3.02	1.84	1.15
50% Probability	371.50	84.67	19.26	4.39	2.43	1.34

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

To enhance wealth through a diversified mutual fund portfolio that balances growth and risk across multiple investment strategies.

Diversification: Investing in a range of mutual funds allows you to spread your investment across different asset classes, such as equities, debt, and hybrid funds. This diversification can help reduce risk and volatility in your portfolio, as different types of funds may respond differently to market conditions.
Professional Management: Indian mutual funds are managed by experienced professionals who conduct in-depth research and analysis to make informed investment decisions. By investing in mutual funds, you gain access to their expertise and can benefit from their strategic asset allocation, which can enhance your potential for returns.
Liquidity and Flexibility: Mutual funds in India offer a high degree of liquidity, allowing you to buy or sell shares easily at the prevailing market price. This flexibility makes it easier for investors to adjust their portfolios based on changing financial goals or market dynamics, ensuring they can respond promptly to opportunities and risks.

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.