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

₹1,125.00 for 1 year

Telegram Bot Command for @ShubhaangBot : /mfeqst_2_45000_n_0

Portfolio Parameters

Parameter	Value
Scripts Group Title	MutualFunds_Equity_SectoralThematic
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 45%
Minimum Annual Investment Capital	₹ 45,000
Optimal Investment Tenure	9 or more years.
Rebalancing Frequency	Rebalancing Quarterly
Subscription Tenure	12 Months Subscription Plan
Backtest – Sharpe Ratio	Hist. Sharpe Ratio above 0.8
Backtest – Annualised Returns	Hist. Annualised Returns Under 25%
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 4.2 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	** 4.25	2.28	1.27	0.79	0.70	0.70
99% Probability	7.51	3.70	1.90	1.06	0.88	0.80
98% Probability	9.19	4.40	2.19	1.17	0.96	0.84
95% Probability	12.44	5.71	2.71	1.36	1.08	0.91
90% Probability	16.30	7.22	3.27	1.56	1.19	0.96
80% Probability	22.83	9.65	4.14	1.84	1.36	1.04
75% Probability	26.09	10.81	4.54	1.96	1.43	1.07
50% Probability	55.33	20.27	7.44	2.73	1.83	1.22

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

To achieve targeted returns by investing in equity sectoral/thematic mutual funds that focus on specific industries or market trends expected to outperform.

Targeted Exposure to Specific Sectors: Sectoral and thematic mutual funds allow investors to focus on specific industries or themes, such as technology, healthcare, or environmental sustainability. This targeted investment approach enables investors to benefit from growth trends within particular sectors that may outperform the broader market, potentially leading to higher returns.
Capitalizing on Market Trends: By investing in sectoral or thematic funds, investors can align their portfolios with current market trends and economic cycles. For example, if a particular sector is expected to experience significant growth due to technological advancements or regulatory changes, these funds can capitalize on those opportunities, allowing investors to enhance their returns when the sector performs well.
Diversification within a Specific Theme: While sectoral and thematic funds focus on specific areas, they still offer diversification within that focus. For example, a sectoral fund may invest in multiple companies across various subsectors or industries within a particular theme. This diversification helps spread risk while still providing the potential for substantial gains related to the chosen sector or theme, enhancing the overall investment strategy.

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.