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Vedanta shares drop 4% as govt reportedly doubles down against demerger plan
Metal major Vedanta's shares fell nearly 4% on Wednesday to hit the day's low of Rs 471 after its demerger plans received another setback. The government reportedly doubled down its objection, accusing the proposed demerger scheme of being a tactic to hinder the recovery of its dues.The objections were placed before the National Company Law Tribunal (NCLT) where the government claimed that the demerged entity of Malco Energy will likely go into liquidation. The government also flagged financial risks that may arise following the demerger exercise, CNBC-TV18 reported today.Continuing on its August 20 arguments, the government alleged that Vedanta has misrepresented its hydrocarbon assets. The government has raised “serious objections” over alleged concealment and non-disclosure of key details in the rejig exercise.According to a CNBC-TV18 report, the Ministry of Petroleum and Natural Gas flagged concerns that the proposed demerger could compromise the government’s ability to recover dues. The ministry alleged instances of revenue inflation and under-reporting of liabilities on Vedanta’s books.Meanwhile, the Securities and Exchange Board of India (Sebi) has also earlier issued a warning letter to Vedanta after it altered the demerger scheme despite having secured prior approvals from stock exchanges and the regulator — a move that was termed a serious breach.Last month, the company faced another setback where the Supreme Court dismissed a plea by the Vedanta Group seeking additional compensation for its Punjab-based Talwandi Sabo Power project. The company had approached the apex court challenging the withdrawal of ‘deemed export’ benefits and sought higher compensation.The apex upheld the Appellate Tribunal for Electricity’s (APTEL) order, ruling that Talwandi Sabo was never legitimately entitled to such benefits, a Mint report said, adding that this effectively closes the door on any additional financial relief from the project.The mining major had posted an 11.7% year-on-year (YoY) decline in its consolidated net profit in Q1 to Rs 3,185 crore. However, the company’s revenue from operations rose by 5.75% YoY to Rs 37,824 crore, up from Rs 35,764 crore reported a year ago.The net profit is comparable to Rs 3,606 crore posted in the same quarter of the previous financial year. The net profit is attributable to the owners of the company.Sequentially, the company’s profit attributable to the owners declined by 8.5%, down from Rs 3,483 crore reported in the previous quarter.(Disclaimer: Recommendations, suggestions, views and opinions given by the experts are their own. These do not represent the views of Economic Times)
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Chris Wood of Jefferies has a warning for investors chasing AI stocks
The Wall Street's record run, built on the promise of artificial intelligence, risks ending in “a massive overinvestment bust” if investors ignore the lessons of recent developments in the sector, as capital spending by US technology giants accelerates at an unsustainable pace, Christopher Wood, global head of equity strategy at Jefferies, has cautioned.Wood, speaking to ET Now, said the U.S. equity market’s momentum has little to do with trade tensions or tariffs, and is instead being driven by what he described as the “AI capex arms race”. Since early 2023, he noted, four US hyperscalers, along with Nvidia, have accounted for “nearly 50% of the gains in the S&P 500.”The AI euphoria“All the evidence right now today is that the AI capex is accelerating,” Wood said, pointing to forecasts that the four largest hyperscalers will spend about $350 billion this year on AI-related infrastructure. Investors, Wood argued, have brushed aside warnings from the launch of DeepSeek earlier this year, which showed that large language models could become “commodities.”“The market has completely forgotten the lessons of DeepSeek, and is celebrating the fact that the four hyperscalers are guiding to spend 350 billion US dollars this year on AI-related capex, and everybody is celebrating the data centre construction. But in my view, this will end up in a massive overinvestment bust,” Wood said.Retail-driven rallyThe global head of equity strategy at Jefferies described the current momentum as a retail-driven phenomenon: “The market thinks AI is the next big thematic and probably many retail investors are buying stocks because the AI models are telling them to buy the stocks, which leads to a reflexive feedback loop.”Valuations, he stressed, are stretched. “On a valuation basis, the U.S. market is trading at an all-time high price to sales,” Wood said, adding that reported earnings are often “artificially exaggerated” due to non-GAAP adjustments.Beyond tariffs and tradeWhile much attention has focused on U.S. President Donald Trump’s tariff regime, Wood argued that the equity surge has little to do with trade policy. “The U.S. markets are not running on the tariff story; the U.S. market is running on the AI theme,” he said.He contrasted the hyperscalers’ current business model with their earlier “asset light” approach. “These hyperscalers are moving from asset-light business models to asset-heavy ones,” he said, pointing out that even though they generate about $100 billion annually in profits, “$360 billion is a huge amount of money to be investing in capex.”Also read | Ola Electric vs Ather Energy shares: Which EV bet looks stronger for your portfolio right now?Risks of reversalWood maintained his long-held view that the U.S. market had already peaked as a share of global market capitalisation late last year. “When that theme unwinds, there will be a big correction,” he said, while emphasising that sentiment shifts would be the trigger to watch.Also read | With gold prices at record highs, are gold loan lenders a better bet for your portfolio than jewellery makers?For now, the rally remains supported by expectations of Federal Reserve rate cuts and by technical provisions in U.S. tax law that have delayed the accounting impact of the capital spending boom. But Wood’s warning was clear: “If the message of DeepSeek is correct, as these large language models are commodities and we have to remember DeepSeek is open-sourced, then it is clearly a risk that a lot of this spending will be wasted.”
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