अApnaFunda

TEAM INDIA GUARANTY LIMITED (TEAMGTY)

Miscellaneous · figures to Nov '26

Share price

Closing priceAdjusted for splits and bonus issues.

₹230.06 latest close · −1.1% over the last 90 sessions

₹220₹230₹240₹250Jul 3Jul 29Aug 24Sep 17Oct 14Nov 9 ₹220₹230₹240₹250Jul 3Sep 4Nov 9

₹230.06 month-end · −13.2% over 12 months

₹225₹250₹275Nov '25Jan '26Apr '26Jun '26Sep '26Nov '26 ₹225₹250₹275Nov '25May '26Nov '26

₹230.06 month-end · +210.5% over 3 years

₹100₹200₹300Nov '23Jun '24Jan '25Sep '25Apr '26Nov '26 ₹100₹200₹300Nov '23May '25Nov '26

₹230.06 month-end · +644.5% since Jan '19

₹0₹100₹200₹300Jan '19Aug '20Mar '22Sep '23Apr '25Nov '26 ₹0₹100₹200₹300Jan '19Dec '22Nov '26

52-week range ₹210.00 to ₹332.55 · 1-year volatility 44.3%

How rough has the ride been?

Maximum drawdown-65.7%recovered 2021-04
1-year volatility44.3%annualised

Drawdown from peak

0%−20%−40%−60%2020202120222023202420252026−64.0% 0%−20%−40%−60%2020202220242026−64.0%
Largest drawdowns

-65.7% (2019-03 peak to 2020-03 low, recovered 2021-04)

-58.1% (2022-02 peak to 2022-06 low, recovered 2023-12)

-44.2% (2023-12 peak to 2024-04 low, recovered 2024-11)

What is the price implying?

~58%annual earnings growth implied by the price

At a P/E of 460.1x, the price would imply about 57.7%/yr earnings growth for 10 years under the same assumptions, but it is not ranked.

Earnings figures have not updated recently, so the company is left out of the lists.

“Implied growth” is what the current price would require under our stated assumptions, not what we expect.

The market-wide Expectations lists

Key figures

Share Priceclose 9 Nov
₹230.06
P/E
460.1x
Market Cap
₹207 cr
Revenue (TTM)
₹1 cr
P/S
248.9x
Promoter Holding
74.9%
12M Momentum
-13.2%

52-week range

₹210.00₹332.55
16% of the way from its 52-week low to its high

Price risk

1Y volatility
44.3%

Who has been buying and selling?

  • Over 2 years, FIIs added 2.1 pts.
  • The number of shareholders fell from 21,099 to 19,838 (-6%) between Dec 2023 and Jun 2026.

Holdings, Jun '26

How each group changed

GroupDec '23Jun '26Change
Promoters74.9%74.9%0.0 pts
FIIs0.0%2.1%+2.1 pts
DIIs0.1%0.1%0.0 pts
Public and others25.0%22.9%-2.1 pts

Number of shareholders

19,838shareholders-6% since Dec '23
20k20k21k21k Dec '23Jun '24Dec '24Jun '25Dec '25Jun '26
Dec '23: 21,099
Mar '24: 20,624
Jun '24: 20,725
Sep '24: 20,598
Dec '24: 20,848
Mar '25: 20,425
Jun '25: 20,317
Sep '25: 20,141
Dec '25: 20,024
Mar '26: 19,867
Jun '26: 19,838
20k20k21k21k Dec '23Dec '24Dec '25Jun '26
Dec '23: 21,099
Mar '24: 20,624
Jun '24: 20,725
Sep '24: 20,598
Dec '24: 20,848
Mar '25: 20,425
Jun '25: 20,317
Sep '25: 20,141
Dec '25: 20,024
Mar '26: 19,867
Jun '26: 19,838

Quarterly shareholding as reported, labelled by the quarter it covers (it becomes visible about two months later).
Shareholder counts are only available for recent quarters.

This quarter's smart-money board

What happened next to similar setups

Not enough comparable history to show analogs for this company yet.

Methodology

How historical analogs are built

Data as of 2026-11-09. Outcome pool: Jan 2020 to Oct 2025.

For every company we look at the situation it is in today (valuation, return on capital, margins, debt, growth, 12-month price momentum, drawdown, size and volatility) and find past company-months that looked most like it. We then show what happened to those past situations over the following 12 months, measured against the ApnaFunda All index and against the base rate. It describes history. It does not predict anything.

What is compared

FeatureWeightNon-financialFinancial
P/E1yesyes
P/S1yes—
P/B1—yes
ROCE1yes—
operating margin1yes—
ROE1—yes
debt/equity0.75yes—
interest cover0.5yes—
revenue growth0.75yesyes
12-month momentum1yesyes
drawdown from 12-month high0.75yesyes
size0.75yesyes
volatility0.5yesyes

Weights were set by judgement before any outcome was looked at and are never tuned on results. Loss-making companies (negative P/E or net profit) are only matched with other loss-making companies. Banks, NBFCs and insurers are compared only with each other and use a different feature set. Every feature is converted, month by month, to its rank among companies in the same pool in that month, so a P/E of 30 in a hot market and a P/E of 22 in a cold one can match if both were equally expensive for their time. Only that month's data is used.

How closeness and the sample are defined

Distance is the weighted root-mean-square gap between the standardised features both companies have. A match needs at least 70% of the query's feature weight, a distance of at most 0.9, and 30 matches at minimum to be shown. We keep up to 50 matches with these exclusions: never the company itself, one match per company (its closest month), and at most 7 from any one calendar month so a single market episode cannot dominate.

Base rate

The base rate is the distribution of 12-month returns, relative to the market, of every eligible company-month in the same pool, with each month weighted to match the months the analogs came from. It answers: how did a random company do in these same months? Because matches from nearby months share the same market conditions, we also report the number of distinct 12-month windows behind a result, and a bootstrap that resamples months decides whether the analog median differs from the base rate at all. "Not meaningfully different" is the usual outcome and the page copy is written for it.

Limits you should know

  • One market period. The outcome pool covers 2020–2025 only (70 months), including the 2020 crash and the 2020–21 rally.
  • Survivorship. Only companies listed today are included. Delisted and bankrupt companies are missing, which flatters past outcomes, particularly for distressed-looking setups.
  • Price return only. Dividends are excluded, and the benchmark is an ApnaFunda market-cap-weighted index of the same listed companies, not an official index.
  • Reporting lag. Fundamentals are matched on an assumed 60-day lag after the quarter end, not on real announcement dates.
  • Pools: non-financial: 98,395 company-months from 2019 companies; financial: 5,659 company-months from 108 companies. 2349 companies currently have a result; the rest are suppressed because too few comparable situations exist.

Does it work? A walk-forward check

The walk-forward check has not been run for this build, so skill is shown as not yet measured.

Disclaimer

This is history, not a forecast. These are past situations where other companies had broadly similar reported numbers and price trends. What happened to them does not tell you what will happen to any company shown. The comparison covers only 2020–2025, a single market period, and only companies still listed today. Companies that were delisted or went bankrupt are missing, which makes past outcomes look better than they were. Returns exclude dividends and are measured against an ApnaFunda-built index, not an official benchmark. Fundamentals are matched on a 60-day assumed reporting lag, not actual announcement dates. Its historical skill has not yet been measured. Past patterns may not repeat.

What changed?

13 events since Mar '20

  1. JulPriceFell 31% from the Dec 2025 peak to the Jul 2026 low.
  2. NovPriceRegained the 2023-12 peak, 7 months after the low.
  3. AprPriceFell 44% from the Dec 2023 peak to the Apr 2024 low.
  4. DecPriceRegained the 2022-02 peak, 18 months after the low.
  5. JunPriceFell 58% from the Feb 2022 peak to the Jun 2022 low.
  6. FebPriceRegained the 2021-10 peak, 2 months after the low.
  7. DecPriceFell 37% from the Oct 2021 peak to the Dec 2021 low.
  8. OctPriceRegained the 2021-06 peak, 0 months after the low.
Show 5 earlier events
  1. OctPriceFell 31% from the Jun 2021 peak to the Oct 2021 low.
  2. JunPriceRegained the 2021-04 peak, 1 month after the low.
  3. MayPriceFell 25% from the Apr 2021 peak to the May 2021 low.
  4. AprPriceRegained the 2019-03 peak, 13 months after the low.
  5. MarPriceFell 66% from the Mar 2019 peak to the Mar 2020 low.

Events are generated from the data by fixed rules.
The month shown is when the change became visible in the reported figures, assuming a 60-day lag after each quarter end; it is not an announcement date.

Where price and fundamentals disagree, market-wide Rewind the whole market to any month

Monthly history95 months · 2019-01 to 2026-11
MonthP/ERevenue (TTM)
2026-11460.1x₹1 cr
2026-10469.8x₹1 cr
2026-09470.0x₹1 cr
2026-08484.1x₹1 cr
2026-07430.6x₹1 cr
2026-06478.5x₹1 cr
2026-05503.1x₹1 cr
2026-04520.2x₹1 cr
2026-03493.7x₹1 cr
2026-02527.8x₹1 cr
2026-01504.2x₹1 cr
2025-12580.7x₹1 cr
2025-11530.0x₹1 cr
2025-10520.0x₹1 cr
2025-09514.5x₹1 cr
2025-08552.0x₹1 cr
2025-07502.2x₹1 cr
2025-06348.4x₹1 cr
2025-05342.7x₹1 cr
2025-04350.3x₹1 cr
2025-03324.0x₹1 cr
2025-02333.9x₹1 cr
2025-01358.6x₹1 cr
2024-12322.3x₹1 cr
2024-11291.7x₹1 cr
2024-10280.7x₹1 cr
2024-09267.2x₹1 cr
2024-08260.2x₹1 cr
2024-07259.6x₹1 cr
2024-06268.7x₹1 cr
2024-05221.4x₹1 cr
2024-04175.5x₹1 cr
2024-03180.0x₹1 cr
2024-02222.1x₹1 cr
2024-01230.0x₹1 cr
2023-12269.6x₹1 cr
2023-11148.2x₹1 cr
2023-10142.0x₹1 cr
2023-09142.5x₹1 cr
2023-08128.6x₹1 cr
2023-07111.9x₹1 cr
2023-06114.1x₹1 cr
2023-05108.0x₹1 cr
2023-04112.9x₹1 cr
2023-0398.1x₹1 cr
2023-0291.3x₹1 cr
2023-0198.5x₹1 cr
2022-12107.7x₹1 cr
2022-11113.9x₹1 cr
2022-10102.0x₹1 cr
2022-09100.0x₹1 cr
2022-08104.5x₹1 cr
2022-0791.9x₹1 cr
2022-0681.7x₹1 cr
2022-0597.4x₹1 cr
2022-04107.5x₹1 cr
2022-03110.4x₹1 cr
2022-02135.6x₹1 cr
2022-01109.2x₹1 cr
2021-1289.6x₹1 cr
2021-1190.5x₹1 cr
2021-1087.3x₹1 cr
2021-0984.2x₹1 cr
2021-0889.8x₹1 cr
2021-07108.6x₹1 cr
2021-06105.6x₹1 cr
2021-0597.9x₹1 cr
2021-04102.0x₹1 cr
2021-0347.2x₹1 cr
2021-0252.8x₹1 cr
2021-0148.4x₹1 cr
2020-1255.1x₹1 cr
2020-1157.7x₹1 cr
2020-1045.3x₹1 cr
2020-0944.8x₹1 cr
2020-0848.7x₹1 cr
2020-0741.5x₹1 cr
2020-0647.4x₹1 cr
2020-0538.8x₹1 cr
2020-0436.4x₹1 cr
2020-0328.0x₹1 cr
2020-0253.0x₹1 cr
2020-0160.3x₹1 cr
2019-1261.2x₹1 cr
2019-1157.0x₹1 cr
2019-1071.0x₹1 cr
2019-0970.5x₹1 cr
2019-0862.2x₹1 cr
2019-0769.6x₹1 cr
2019-0671.1x₹1 cr
2019-0570.1x₹1 cr
2019-0463.0x₹1 cr
2019-0365.2x₹1 cr
2019-0261.7x₹1 cr
2019-0161.8x₹1 cr

Methodology and data notes

Methodology

Methodology and data notes

All figures come from public exchange prices and screener.in financial statements. Quarterly and annual results are shown from 60 days after the period end, so a month never uses a result before it would plausibly have been published. Statements are the latest versions, which may include later restatements.

Sector medians, percentiles and indices use today's listed companies in the sector (survivorship bias). Prices are adjusted for splits and bonus issues; around a corporate action the fundamentals may lag the price by up to a month, and affected sections are hidden.

The return decomposition uses price = P/E × net profit ÷ share count. The reverse DCF uses a fixed 12% cost of equity, a 10-year horizon and a 15x terminal P/E, and is an illustration only. Events, flags and twins follow fixed rules and thresholds described next to each section.

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