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There is no defensible single “Lakshmi Mills target price” unless the forecast identifies the exact security, date, earnings base, valuation method and downside case. Lakshmi Mills Company Limited trades under NSE symbol LAKSHMIMIL and BSE code 502958. Before treating any published number as a buy signal, rebuild the company’s earnings from its latest filings, value textiles and rental services separately, and test bear, base and bull assumptions. The latest disclosures show why that work matters: textiles were loss-making in the nine months ended 31 December 2025 while rental services generated a large segment profit, and a large deferred-tax charge turned a pre-tax profit before exceptional items into a reported post-tax loss.
What a Lakshmi Mills target price actually tells you
A target price is an output of a model, not a fact about what the share must be worth. An analyst normally forecasts revenue, margins, taxes and cash flows, then applies a valuation method such as a price-to-earnings multiple, enterprise-value-to-operating-profit multiple, discounted cash flow or net asset value. A different forecast horizon, tax treatment or multiple can produce a very different price from the same set of filings.
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For Lakshmi Mills, a consolidated model can be particularly misleading because the company reports two businesses with different economics. Textiles are exposed to yarn prices, cotton, power, labour, utilization and domestic and export demand. Rental services depend more on occupancy, lease renewals, rent escalations and property values. A target that does not show how it handles those segments is difficult to audit.
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Use a published target as a scenario to investigate. Do not rely on it as a promise, and do not compare two numbers until their dates, horizons and assumptions are aligned.
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1. Verify the security, exchange and forecast date
Confirm that the forecast is for the right company
Start with Lakshmi Mills Company Limited, NSE symbol LAKSHMIMIL and BSE code 502958. Check the legal name and ticker in the source itself; similarly named textile companies can produce an apparently plausible but irrelevant target.
Record the “as-of” date and horizon
Write down the date on which the forecast was published and what it means. A “12-month target” is not interchangeable with a value expected at the end of a financial year, a near-term technical level or a multi-year projection. A target without a date becomes stale as new results, cotton prices, interest rates and market valuations change.
Check the information set
Identify the latest annual report and interim result available to the analyst. Lakshmi Mills maintains annual-report and financial-results archives on its investor site. The model should not describe older results as current when a later filing has changed the earnings base.
2. Rebuild the earnings base from the filings
Before accepting an earnings forecast, reconcile the headline numbers to the company’s reported statements. The FY2025-26 directors’ report gives the following comparison, in ₹ lakh:
| Measure | FY2025-26 | FY2024-25 | How to use it |
|---|---|---|---|
| Revenue from operations | ₹24,183.48 lakh | ₹26,316.27 lakh | Check the forecast’s growth rate and whether it separates textile and rental revenue. |
| Profit before tax and exceptional items | ₹753.75 lakh | ₹740.45 lakh loss | Test whether the model explains the operational improvement rather than simply extrapolating it. |
| Profit after tax | ₹1,554.94 lakh loss | Not stated in the cited comparison | Reconcile tax, deferred tax and exceptional items before using EPS. |
| Deferred-tax charge | ₹2,119.53 lakh | Not stated in the cited comparison | Determine whether the forecast treats this as recurring, reversing or a separate valuation adjustment. |
Revenue fell year over year even though profit before tax and exceptional items moved from a loss to a profit. That combination can result from mix changes, cost reductions, lower finance costs or one-off operating effects. A target model should identify the driver. Simply applying a higher earnings multiple to the improved pre-tax figure can overstate sustainable earnings.
Bridge pre-tax profit to post-tax profit
For FY2025-26, ₹753.75 lakh of profit before tax and exceptional items became a ₹1,554.94 lakh post-tax loss after a ₹2,119.53 lakh deferred-tax charge. This is a reconciliation issue, not a detail to hide in an EPS footnote. Ask the forecast author to show:
- current tax and deferred tax separately;
- the reason for the deferred-tax charge;
- whether any deferred-tax asset or liability is expected to reverse;
- the treatment of exceptional items; and
- the share count used to convert the resulting profit or loss into EPS.
If an analyst values Lakshmi Mills on normalized earnings, the normalization must be explained and supported by the filing. If the model uses reported EPS, the deferred-tax impact should remain visible. A target based on pre-tax profit is not directly comparable with one based on post-tax EPS.
Reconcile the forecast line by line
Build a worksheet with the latest reported revenue, operating profit, finance cost, tax, exceptional items and shares outstanding. Add the forecast beside each line and calculate the implied year-over-year change. A large unexplained jump in margin, a sudden disappearance of finance cost or a share-count change that is not disclosed is a reason to lower confidence in the target.
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3. Separate textiles from rental services
The interim financial-results filing approved on 12 February 2026 states that the company is structured into two reportable business segments: “Textiles” and “Rental Services.” The nine months ended 31 December 2025 illustrate why each needs its own forecast:
| Segment (nine months ended 31 December 2025) | Revenue | Segment result before interest and tax | What to investigate |
|---|---|---|---|
| Textiles | ₹15,675.56 lakh | ₹586.40 lakh loss | Yarn prices, cotton and power costs, volumes, spindle utilization, wages, export demand and domestic demand. |
| Rental Services | ₹1,945.48 lakh | ₹1,499.74 lakh profit | Occupancy, lease renewals, rent escalation, tenant concentration, property values and one-off income. |
Model the textile business operationally
For textiles, forecast physical and price drivers before applying a margin. At minimum, document yarn selling prices, volume, cotton input cost, energy cost, labour cost, other conversion costs and spindle utilization. The directors’ report attributes weaker yarn production and turnover to adverse domestic and export markets and fluctuations in labour availability. Those are operating assumptions that should appear in the model, not just in a risk paragraph.
Installed capacity remained 1.44 lakh spindles throughout 2025-26. Capacity is not the same as production: utilization, downtime, product mix and labour availability determine how much of that capacity earns revenue. A bull case that assumes a full recovery should state the utilization level and the time needed to reach it.
Value rental services on their own evidence
Rental-services profit can provide stability, but it is not automatically recurring at the latest nine-month run rate. Check lease expiry dates, renewal terms, escalation clauses, vacancies, maintenance obligations and any unusually large tenant or property transaction. If a target applies a textile-company earnings multiple to rental profit, ask why. A sum-of-the-parts approach or a separate property-based cross-check may be more informative, provided the model explains its property assumptions.
Watch for consolidated-multiple distortion
A high-margin rental segment can make consolidated operating margins look better while the textile segment remains under pressure. Conversely, a weak textile year can obscure the value of a durable rental stream. Require the forecast to show segment revenue, segment profit, corporate costs and the bridge to consolidated profit.
4. Stress-test the assumptions that move value
Construct at least three cases rather than one precise outcome. The cases should change the operating variables that matter to Lakshmi Mills, not merely apply arbitrary percentages to the final target.
Bear case
- Yarn prices remain weak while cotton, power or labour costs rise.
- Domestic and export demand stay soft, reducing volumes and spindle utilization.
- Labour-availability fluctuations delay production recovery.
- Rental occupancy falls or renewals occur without the expected escalation.
- The deferred-tax charge does not reverse when the model expects it to.
- The market applies a lower multiple to cyclical textile earnings.
Base case
- Textile prices and volumes recover gradually rather than immediately.
- Utilization improves from the current operating level without assuming new spindle capacity.
- Input-cost pressure normalizes at a documented pace.
- Rental income continues under existing leases, with only contractually supportable escalations.
- Taxes and deferred tax are modeled from the filing evidence and then updated as audited statements arrive.
Bull case
- Yarn demand and pricing improve in both domestic and export markets.
- Labour availability supports higher utilization of the 1.44 lakh spindles.
- Energy and cotton costs are favorable relative to selling prices.
- Rental occupancy and renewals exceed the base case.
- The deferred-tax effect reverses as assumed and does not recur.
- The valuation multiple expands, with a stated reason such as higher confidence in normalized earnings.
For each case, calculate revenue, segment profit, corporate costs, finance cost, tax, EPS or free cash flow and the implied value. Then identify which two or three assumptions account for most of the price range. A scenario table is more informative than a target printed to the nearest rupee.
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|---|---|---|---|
| Yarn selling price | What if prices remain below the level needed to cover conversion costs? | What gradual recovery is supported by recent results? | What evidence supports a faster price and mix recovery? |
| Cotton and power cost | Can the company pass through higher input costs? | What cost level is consistent with the latest margin? | What durable cost advantage justifies higher margins? |
| Spindle utilization | How much idle capacity persists? | What utilization is achievable with current labour availability? | What timing and demand support near-full utilization? |
| Rental income | What vacancy or renewal risk reduces profit? | Which leases support the current run rate? | What signed or highly visible escalation supports upside? |
| Tax and deferred tax | What if the charge recurs? | What portion is normalized, and why? | What evidence supports reversal? |
| Valuation multiple | What multiple fits cyclical, loss-making textiles? | What blended or segment-specific multiple is justified? | What changed enough to justify expansion? |
5. Match the valuation method to the business mix
Price-to-earnings
P/E is usable only when the earnings denominator is representative. Reported FY2025-26 post-tax loss makes a simple trailing P/E unusable or economically meaningless. A forward P/E can be used if the forecast explains how it normalizes deferred tax and cyclical textile earnings. Compare the multiple with companies that have similar textile exposure, leverage and rental contribution; do not use an undisclosed peer set.
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Enterprise value to operating profit
An enterprise-value-to-operating-profit method can avoid some tax distortions, but it still depends on a sustainable operating profit. Show debt, cash, lease liabilities where relevant and corporate costs. A multiple applied to consolidated profit may hide the difference between a textile loss and rental profit.
Discounted cash flow
A DCF requires explicit assumptions for revenue, margins, capital expenditure, working capital, taxes, terminal growth and discount rate. Textile cash flows should reflect working-capital swings and maintenance capital expenditure; rental cash flows should reflect property maintenance and vacancy. Small changes to terminal growth or discount rate can dominate the result, so publish a sensitivity range rather than one output.
Sum-of-the-parts or net asset cross-check
A sum-of-the-parts model can value textiles and rentals using different methods, then subtract corporate costs and net debt. A property or net-asset cross-check can be useful for rental services, but an estimated property value is not the same as cash that can be realized without taxes, transaction costs and time. Explain whether the model uses book value, an independent valuation or a market-based estimate.
6. Compare forecasts on the same axes
When two or more target prices exist, place them in one table and normalize the definitions before comparing them.
| Comparison item | What to record | Why it changes the conclusion |
|---|---|---|
| Forecast horizon and as-of date | Publication date and whether the target is 12 months, fiscal-year end or another period | A newer or longer-horizon target may not be directly higher-confidence merely because it is higher. |
| Revenue and segment assumptions | Textile volume, pricing, utilization and rental revenue | Shows whether the target depends on a textile recovery or rental contribution. |
| Profit measure | EBIT, EBITDA, profit before tax, EPS or free cash flow | Prevents comparison of a pre-tax target with a post-tax target. |
| Valuation method | P/E, EV/operating profit, DCF, sum-of-the-parts or NAV | Different methods embed different treatment of tax, debt and property. |
| Multiple and peer set | Applied multiple, comparable companies and rationale | A high multiple can be the main source of upside rather than better earnings. |
| Deferred tax and exceptional items | Included, normalized, deferred or excluded | The ₹2,119.53 lakh deferred-tax charge materially changes FY2025-26 reported earnings. |
| Downside and sensitivity | Bear case, price range and key sensitivities | Shows whether the published number is a range-based conclusion or a point estimate. |
| Analyst identity and count | Named analyst, publisher and number of contributing analysts | A consensus with one undisclosed source is not the same as a broad, transparent estimate. |
| Revision history | Older target, revision date and subsequent results | Reveals whether the analyst updates assumptions when evidence changes. |
7. Judge forecast quality, not just the headline number
Demand a transparent publication record
For every external target, capture the publisher, analyst identity, publication date, target horizon, earnings or cash-flow estimates, valuation method, applied multiple and prior-target revisions. If the source omits its date or methodology, label the target low-confidence rather than filling the gap with assumptions.
Assess track record correctly
Compare earlier targets with the prices and financial results that followed, but do not infer skill from one successful call. Use several dated forecasts, distinguish a market-wide move from company-specific accuracy, and check whether targets were revised after the fact. A forecast that changes without a documented earnings or multiple change is difficult to evaluate.
Separate consensus from an unsupported number
A consensus target should disclose how many analysts contributed and the date on which their estimates were collected. If no current, independently verifiable consensus table with a transparent analyst count and methodology is available, do not present a single internet number as “the” market target. The absence of a verifiable consensus is itself information about confidence and coverage.
8. Account for the quality and timing of the evidence
The December 2025 interim results were approved on 12 February 2026 and were limited-reviewed. The review report states that a review is substantially less in scope than an audit and does not provide an audit opinion. Use those figures for trend analysis, but update the model when audited annual statements become available.
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A limited review does not mean the figures are unusable; it means the level of assurance is lower than an audit. Mark each input in your worksheet as audited, limited-reviewed, management-reported or an analyst assumption. Cross-check copied figures against the official Lakshmi Mills filing archive, and retain the filing date beside each number.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.9. A practical pre-investment workflow
- Identify the security. Confirm Lakshmi Mills Company Limited, NSE LAKSHMIMIL and BSE 502958.
- Timestamp the forecast. Record publication date, target date and horizon.
- Collect primary filings. Use the latest annual report, directors’ report and interim results, noting whether each is audited or limited-reviewed.
- Rebuild the base year. Enter revenue, operating profit, finance cost, tax, deferred tax, exceptional items and share count in ₹ lakh or another consistent unit.
- Split the segments. Model textiles and rental services separately, then reconcile them to consolidated results.
- Test operating drivers. Vary yarn prices, cotton, power, labour, utilization, export demand, rental occupancy and lease escalations.
- Choose an appropriate valuation. Explain why P/E, EV/operating profit, DCF, sum-of-the-parts or a property cross-check fits the evidence.
- Build bear, base and bull outputs. Show the implied value range and the assumptions responsible for the spread.
- Audit the forecast source. Record analyst count, methodology, peer set, downside case and revision history.
- Set an update trigger. Revisit the model after audited annual results, a material segment change, a major input-cost move or a new filing that changes tax or debt assumptions.
10. Common mistakes and how to correct them
Repeating an undated target
Problem: A search result presents a precise price without a publication date or horizon.
Correction: Treat it as unverified until the source identifies the date, security, methodology and forecast period.
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Using reported loss with a P/E multiple
Problem: FY2025-26 post-tax loss produces a meaningless trailing P/E.
Correction: Use a documented normalized or forward earnings measure, or switch to a cash-flow, operating-profit or segment-based method.
Ignoring deferred tax
Problem: The model uses ₹753.75 lakh pre-tax profit as though it were post-tax earnings, or treats the ₹2,119.53 lakh deferred-tax charge as permanently recurring without analysis.
Correction: Show the bridge to the ₹1,554.94 lakh post-tax loss and explain the expected reversal or recurrence.
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Problem: Strong rental profit masks a textile segment loss.
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Correction: Forecast each segment, value them with methods suited to their economics and reconcile corporate costs.
Confusing capacity with output
Problem: The unchanged 1.44 lakh spindle capacity is treated as proof of higher production.
Correction: Forecast utilization, downtime, labour availability, product mix and demand before converting capacity into revenue.
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Problem: Interim numbers are presented with the assurance of audited annual statements.
Correction: Label the December 2025 results as limited-reviewed and refresh the model when audited figures arrive.
Confusing precision with accuracy
Problem: A target quoted to a precise rupee appears more reliable than a range.
Correction: Publish the assumptions, sensitivities and downside case; the useful output may be a range, not a point estimate.
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After building the scenarios, compare the current market price with the modeled range only after checking the date of that price and the date of the filings. Ask whether the potential upside compensates for the bear-case loss, the uncertainty around textile recovery and the possibility that rental income is less durable than assumed.
Set explicit conditions for changing your view. Examples include a sustained improvement in textile utilization, evidence that yarn prices cover cotton, energy and labour costs, renewal of major leases on expected terms, or audited confirmation that deferred tax is reversing. Negative triggers could include another period of textile losses, worsening labour availability, falling occupancy or a new tax charge that invalidates normalized EPS.
Position size should reflect uncertainty. A wide bear-to-bull range, limited analyst disclosure and limited-reviewed evidence call for more conservative exposure than a narrow range supported by audited results and transparent assumptions. This is a risk-management conclusion, not a prediction of the share price.
Bottom line
Evaluate any Lakshmi Mills target price by tracing it back to LAKSHMIMIL/502958, dating the forecast, rebuilding the FY2025-26 earnings bridge, separating textiles from rental services and testing bear, base and bull cases. The company’s ₹24,183.48 lakh FY2025-26 revenue, ₹753.75 lakh pre-tax profit before exceptional items, ₹2,119.53 lakh deferred-tax charge and ₹1,554.94 lakh post-tax loss show why a headline target can mislead. A target becomes decision-useful only when its assumptions, evidence quality and downside are visible.
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