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Metal stocks to buy ahead of Q2 results: Nuvama picks Coal India, Tata Steel; Jindal Steel an underperformer |Here’s why

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⚡ Instant Key Takeaways (TL;DR)
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Core Development: Metal stocks to buy ahead of Q2 results: Nuvama picks Coal India, Tata Steel; Jindal Steel an underperformer |Here’s why
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Market & Financial Impact: Metal stocks show mixed Q2 FY27 performance expectations. Coal India and Tata Steel are favored, while Jindal Steel may underperform. EBITDA per tonne for steel companies is projected to decline due to higher costs and lower realizations. Coal India expected to see 22% YoY EBITDA growth.
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Actionable Insight: 🔴 Bearish Risk: Regulatory scrutiny, profit decline, or sell-off risk may create near-term volatility.

Metal stocks are likely to deliver a mixed performance in the September quarter, with Coal India and Tata Steel emerging as Nuvama Institutional Equities’ preferred names, while Jindal Steel is expected to be the key underperformer.

In its Q2 FY27 preview, Nuvama expects most steel companies under its coverage to report a 10–13% sequential increase in EBITDA, supported by a recovery in volumes after maintenance shutdowns during Q1. However, lower realisations and higher costs are expected to weigh on profitability on a per-tonne basis.

The brokerage expects steel volumes to recover by 6–25% QoQ, helped by capacity ramp-ups. At the same time, average flat steel prices remained relatively firm, while long steel prices declined by around ₹3,500 per tonne sequentially. This is likely to result in lower blended realisations across most companies.

Higher coking coal costs are another margin headwind. Nuvama expects coking coal prices to rise by around $10–15 per tonne QoQ, although this could be partly offset by a decline of around ₹100 per tonne in iron ore costs.

As a result, EBITDA per tonne is expected to decline by around ₹600–2,200 per tonne across the steel companies under coverage.

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Official Publisher Attribution: This report is aggregated from LiveMint. ZeroLive provides live aggregation, automated sentiment synthesis, and exchange disclosure monitoring for retail market participants.
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