Every term used as an inline tooltip in the Mutual Funds Sahi Hai article β one-sentence definitions for fast scanning.
The annual fee a fund charges, deducted daily from NAV. Lower is better; 0.1% historically outperformed 1.5% by ~21x over 30 years.
Includes dividends reinvested, unlike plain price indices. The correct benchmark for comparing active fund returns.
The smoothed annual return if your investment grew at a steady rate over a period. Gold standard for strategy comparison.
Total market value of investments a fund or AMC manages on behalf of investors.
Fixed periodic (usually monthly) investment into a mutual fund, automating rupee-cost averaging.
A mutual fund's IPO. AMCs launch NFOs to raise fresh capital, often during peak market enthusiasm.
The entity that manages a mutual fund (e.g., SBI MF, HDFC MF, Axis MF).
Return generated above a benchmark (e.g., Nifty 50). Positive alpha = higher return than benchmark; negative alpha = lower return than benchmark in this measurement period.
Peak-to-trough decline in portfolio value. A -55% max drawdown means the portfolio nearly halved from its peak before recovering.
How closely a fund follows its benchmark index. High tracking error = more deviation from the index, for better or worse.
The distortion caused by only measuring funds that survived β erasing failed or merged funds from performance averages, inflating category returns by ~1β1.5%/yr.
Rules-based investing targeting documented return drivers: momentum, value, low-volatility, quality, or combinations thereof.
Returns calculated over every possible overlapping period of a given length β more honest than cherry-picked point-to-point returns.
The hypothetical start of an index's backtest history β often years before it launched live and could actually be invested in.
When an index began calculating in real-time. Only from this date forward is the track record actually investable.
See these terms in context β
The Mutual Funds Sahi Hai article uses every one of these as live tooltips.
20 terms with full NSE context, backtest implications, and links to the specific research studies where each concept is tested.
The National Stock Exchange of India (NSE) is the largest stock exchange in India by trading volume, listing over 2,000 companies. It provides the primary platform for equity, derivatives, and debt trading, with data from December 2006 used in BacktestIndia's 18+ year backtests.
For factor investing, NSE data is commonly used in academic research as it includes real-time prices, corporate actions, and delisted stocks to avoid survivorship bias. All BacktestIndia strategies use NSE EOD data for accurate simulations.
The Bombay Stock Exchange (BSE) is India's oldest stock exchange, established in 1875, and the second-largest by volume. It lists around 5,000 companies, including many small-caps not on NSE.
While NSE dominates backtesting, BSE data complements for broader coverage. BacktestIndia focuses on NSE for liquidity but cross-references BSE for complete Indian market analysis in factor studies.
Long-Term Capital Gains (LTCG) tax is levied at 12.5% on equity gains from holdings over 1 year (post-2024 Finance Act), with a βΉ1.25 lakh annual exemption. This is a tax-efficient structure commonly used for factor strategies.
In backtests, annual rebalancing maximises LTCG qualification, boosting net returns by 2β4% vs frequent trading. BacktestIndia automatically applies this for realistic post-tax CAGR calculations.
Short-Term Capital Gains (STCG) tax is 20% on equity gains from holdings under 1 year. This applies to frequent rebalancing in momentum strategies.
STCG drag can reduce momentum returns by 3β5% annually. Our tax modelling shows low-vol strategies minimise this through annual holds, which may reduce tax drag.
The Nifty 50 is India's benchmark index tracking the top 50 companies by market cap on NSE, representing 60%+ of market value. Used as the default comparison for all factor backtests.
Factor strategies like low-vol consistently historically outperformed Nifty 50 (e.g., +3.67% CAGR in 10Y rolling). BacktestIndia shows net-of-tax outperformance to highlight real edges.
Momentum investing buys stocks with strong recent price performance (e.g., 12-month returns) expecting trends to continue. A core factor in Carhart's 4-factor model.
In BacktestIndia's historical simulation (Dec 2006βDec 2025), base momentum delivered 14.60% net CAGR but with -70.61% drawdowns. Crucially, all alpha appears concentrated in illiquid (low-turnover) stocks at 19.43% net CAGR β liquid momentum returned just 8.51%, below Nifty 50. Past performance does not guarantee future results.
Value investing targets stocks trading below intrinsic value, using metrics like low P/E, P/B, and high dividend yield. Warren Buffett's classic approach.
Value underperformed post-2020 in India due to growth bias, but our 18Y backtest shows recovery in high-inflation regimes. Combine with quality when analyzing company fundamentals.
The quality factor selects stocks with strong fundamentals: high ROE, low debt, stable earnings, and consistent profitability. Often overlaps with low-vol.
Quality delivered 13.5% CAGR in NSE tests with low drawdowns. BacktestIndia's multi-factor uses it as a core filter for balanced portfolios.
Low volatility selects stocks with the lowest 12-month price swings, betting on 'defensive' outperformance. The anomaly where risk doesn't equal reward.
In BacktestIndia's historical backtest, low volatility achieved a 100% win rate across 102 rolling 10-year periods (14.24% avg CAGR vs Nifty 10.57%). Fastest post-2008 recovery (7 months) and tax-efficient with annual rebalancing. Past performance does not guarantee future results.
The Carhart 4-factor model extends Fama-French (market, size, value) with momentum. Explains 90%+ of stock returns via these systematic factors.
BacktestIndia implements this for India: Low-vol (risk), value (cheap), momentum (trends), quality (fundamentals). Our multi-factor historically outperformed single-factor approaches by 2% CAGR.
P/E ratio divides stock price by earnings per share. Low P/E signals value; high P/E growth. Key for value factor screening.
In NSE, value portfolios target <15 P/E. BacktestIndia filters dynamically, adjusting for sector (e.g., banks vs tech) to avoid value traps.
ROE measures profitability: net income / shareholders' equity. High ROE (>15%) indicates efficient management, core to quality factor.
Quality screens require ROE >20% consistently. Our backtests show it reduces drawdowns by 15β20% vs pure value.
Beta measures stock volatility vs market (Nifty 50 = 1.0). Low beta (<0.8) = defensive; high beta (>1.2) = aggressive.
Low-vol strategies target beta 0.6β0.8. BacktestIndia shows low-beta historically outperformed high-beta in 80% of periods, especially during crashes.
Alpha is excess return over benchmark after risk adjustment. Positive alpha means higher return than benchmark in this measurement period due to skill or factor, not luck.
Factor alphas in India: Momentum +4%, Low-Vol +3%. BacktestIndia calculates rolling alpha to validate strategies over time.
Sharpe ratio = (return β risk-free) / volatility. Higher = better risk-adjusted performance. Risk-free rate often 7% (Indian bonds).
Multi-factor hits 0.48 Sharpe vs Nifty 0.35. BacktestIndia displays it to compare: Low-vol often leads (0.38 in standard config).
Maximum drawdown is the largest peak-to-trough decline (e.g., -44% for low-vol in 2008). Key risk metric.
Low-vol's 7-month recovery vs Nifty's 60 months is a factor in its historical performance. BacktestIndia flags max drawdown for every strategy.
CAGR is the smoothed annual return over time, accounting for compounding. A commonly used metric for strategy comparison.
Our net-of-tax CAGRs: Low-vol 12.38%, Multi 14.61%. BacktestIndia always shows pre/post-tax to set real expectations.
SIP is monthly fixed investments, averaging rupee costs over time. Popular for retail but doesn't fix poor underlying strategies.
Our Lost Decade SIP test: Low-vol +3.31% CAGR vs Nifty. BacktestIndia simulates SIPs with full tax for real-world scenarios.
Rupee cost averaging buys more shares when prices fall, less when high. The core SIP benefit in volatile markets.
It reduces timing risk but our tests show strategy > averaging: Low-vol SIP historically outperformed Nifty by βΉ9.86L over a decade.
Survivorship bias ignores failed companies, inflating backtest returns. Delisted stocks must be included for accuracy.
BacktestIndia includes 1,700+ stocks with delistings, avoiding the 2β3% return overstatement common in other tools.
This glossary is for educational purposes only. BacktestIndia is NOT SEBI-registered and does NOT provide investment advice. All terms and backtest references are hypothetical simulations. Before implementing any strategy, consult a SEBI-registered Investment Adviser.
Find SEBI-Registered Advisers βRun backtests using these concepts on 18 years of NSE data β with real LTCG/STCG taxes, delisted stocks, and every drawdown included.
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