Latent View Analytics IPO allotment status available on Linkintime; Check GMP
Latent View Analytics IPO allotment status is available on the registrar Linkintime's website. Those who applied for Latent IPO can check their status by entering their PAN or Application number or DP client id.
Latent View Analytics IPO allotment has been finalised at Rs 197 per share. The Latent View Analytics IPO market lot size is 76 shares. The shares will be credited into the demat accounts of the successful bidders on Friday.
Latent View Analytics IPO listing on the BSE and NSE will likely take place on November 23.
The initial public offer of Latent View Analytics Limited had received an overwhelming response from all categories of investors and got subscribed a whopping 326.49 times on the last day of subscription. The Rs 600 crore-IPO received bids for 5,72,18,82,528 shares against 1,75,25,703 shares on offer, according to NSE data.
The category for non-institutional investors was subscribed a massive 850.66 times while the portion for Qualified Institutional Buyers (QIBs) received 145.48 times subscription and Retail Individual Investors (RIIs) 119.44 times.
The IPO aggregating up to Rs 600 crore has a fresh issue of up to Rs 474 crore and an offer for sale of up to Rs 126 crore. Price range for the offer was fixed at Rs 190-197 per share. Latent View Analytics raised Rs 267 crore from anchor investors.
The grey market premium of Latent View Analytics is very strong, indicating a bumper listing gain on debut. Latent View Analytics shares are trading at a premium of over Rs 330 apiece which is more than 150 per cent over the issue price.
Proceeds from the fresh issue will be used for funding inorganic growth initiatives, working capital requirements of the subsidiary Latent View Analytics Corporation, and investment in subsidiaries to augment their capital base for future growth and general corporate purposes.
The company provides services ranging from data and analytics consulting to business analytics and insights, advanced predictive analytics, data engineering, and digital solutions.
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