← MF leaderboard

Invesco India Large & Mid Cap Fund - Direct Plan - Growth

Invesco Mutual Fund · Equity · mandate: ≥35% in large-caps and ≥35% in mid-caps · benchmark: NIFTY LargeMidcap 250 TRI (TRI proxy)
AUM (all plans)
10,030 cr
Active return /yr (full)
Score
68
Rank (Score, pool)
#3 of 35
Percentile (full, pool)
IR vs benchmark
0.83
CAGR (absolute)
20.3%
Max drawdown
-26.4%
Months of data
163
Percentile ranks this fund within its peer pool; the leaderboard Score is the weighted average of its fiscal-year percentiles (equity: active-return-rank blended with IR-rank).

Cumulative active return

20222023202420252026-51024Cumulative active return vs benchmark, %
Growth of the fund relative to its benchmark: +10 means ₹100 in the fund is worth 10% more than ₹100 in the benchmark since the start of the line.

Equity curve

2013201420152016201720182019202020212022202320242025202689515940Fund (NAV=100)Benchmark: NIFTY LargeMidcap 250 TRICategory median (L&M)

Drawdown

20132014201520162017201820192020202120222023202420252026-26-130Drawdown %

Fiscal-year record

FYActive vs BMvs categoryIR%ileTEBenchmarkFund returnmonths
FY22-4.8%5018.6%12
FY230.1%-0.8%-0.04502.5%0.3%0.4%12
FY246.7%7.4%0.94814.8%45.3%52.1%12
FY259.0%5.6%1.18857.3%7.1%16.0%12
FY261.8%2.1%0.36656.2%-1.1%0.7%12
FY27*12.2%10.6%2.61949.7%16.2%28.4%5
Active/Fund returns are TOTALS over the months covered — never annualized (FY27* is year-to-date; a * row covers only part of the year). %ile is the fund's percentile within its peer pool for that year.

Monthly active returns (%)

JanFebMarAprMayJunJulAugSepOctNovDecYear
2022-0.6-1.3-0.6-1.3+0.7+0.3-1.0-0.6+1.2+0.6-0.4-0.1-3.2
2023-0.1+0.5+0.2-0.5+0.6-0.5-1.3+0.9-1.4+2.4+1.5-1.5+0.7
2024+1.0+2.4+0.8-0.0+0.3+3.0-1.1+2.4+2.3+0.5+2.0+3.0+17.8
2025-4.5+0.6+0.3+0.4+1.7+3.0+1.7+0.2-1.0-0.6-0.6-2.6-1.7
2026-2.4+2.6-0.3+2.5+1.4+6.7-0.6+0.6+10.8
Fund monthly return minus benchmark; the year column compounds each separately and differences them.

Monthly returns (%)

JanFebMarAprMayJunJulAugSepOctNovDecYear
2013-5.5-0.1+2.8+1.8-1.7-2.3-3.1+4.1+10.4-1.3+4.4+8.9
2014-2.3+2.4+6.4-0.4+8.1+8.3+1.5+3.6+4.1+3.3+4.6-0.7+45.6
2015+6.6+2.3-0.2-4.7+4.2+0.0+4.0-6.2+0.9-0.3-1.3+1.0+5.8
2016-4.8-9.3+11.7+2.0+3.9+2.2+4.8+2.9-1.4+0.6-5.1-0.9+5.2
2017+5.0+3.8+3.9+3.4+3.1-0.2+7.3-0.1-0.1+5.2+1.2+3.4+42.0
2018+2.4-3.4-1.9+7.3-2.6-1.9+5.5+4.5-9.5-3.3+4.5+0.9+1.2
2019-2.1+0.2+7.4-0.8+1.2-0.4-5.6+1.9+5.3+4.7-0.1+0.4+11.9
2020+1.4-3.6-23.7+12.3-2.8+6.5+6.1+2.7+3.0+0.7+9.0+7.3+14.6
2021-0.2+6.8-0.4+0.0+6.0+3.7+4.1+2.9+3.1+1.1-3.4+4.3+31.4
2022-1.5-6.2+3.7-1.6-3.6-4.7+9.4+4.6-1.4+3.8+2.4-2.8+0.9
2023-3.1-1.7+0.1+4.2+5.0+4.5+3.0+1.9+1.2-0.9+9.4+6.2+33.2
2024+3.7+3.4+1.5+4.3+1.7+10.2+3.4+3.2+4.3-6.1+2.1+2.5+39.1
2025-8.4-7.9+7.6+4.0+6.0+6.7-1.1-1.8+0.3+3.9+0.9-3.0+5.9
2026-5.6+3.5-11.6+13.5+2.2+8.0+1.5+1.0+10.9

Quarterly average AUM & estimated net flows

20132014201520162017201820192020202120222023202420252026305,03010,030AUM (quarter avg), ₹cr
-1,4121,345
Quarterly net flow estimate: AUM_q − AUM_(q−1)·(1+quarter return). AUM shown is the quarter AVERAGE (AMFI central disclosure). Positive = net inflows, ₹cr.
Source: AMFI's official all-scheme NAV history (portal report; official NAV history, net of TER by construction). Monthly returns are month-end NAV chains; stale prints (>7 days before month-end) drop out rather than carry. Benchmark series are the median of plain-vanilla direct-plan index funds tracking each index (TRI minus ~10-25bp/yr tracking drag — verified against true-TRI chains). Direct plans, growth option only. Sharpe uses rf 6%, arithmetic monthly convention. Independence: all figures are computed from mandatory public disclosures with a fixed methodology applied identically to every fund — no fund can pay for inclusion, exclusion, placement, or altered presentation, and any material commercial relationship will be disclosed on the affected pages. Nothing here is investment advice; past performance does not predict future returns. Generated 2026-08-25 05:37Z · data through Aug 2026 · leaderboard · PMS leaderboard
Feedback, inputs, or bug reports are appreciated — @vivekrmr on X · LinkedIn.