Big Lots (BIG, $24.67) posts narrower-than-expected loss

Big Lots  reported a fiscal-third-quarter loss narrower than anticipated, as the company continued to emphasize on cost-cutting and restructuring.

For the three months ended November 2, the retail company incurred an adjusted loss of -18 cents a share, compared to the -20 cents loss expected by analysts polled by FactSet. In the year-ago quarter, the loss was -12 cents a share.

The results include an after-tax gain of $136.6 million, or $3.49 a share, from the sale of the company's distribution center in Rancho Cucamonga, Calif., as well as after-tax expense of $2.6 million, or 7 cents a share, associated with the company's strategic business revamp.

Big Lots’ sales for the quarter increased +1.6% to $1.17 billion, in line with the $1.2 billion expected by analysts.

Same-store sales decreased -0.1%, compared to the company’s guidance of flattish growth. 

For the fourth-quarter, Big Lots has projected earnings of $2.40 to $2.55 a share, and expects a slight increase in comparable-store sales. Analysts polled by FactSet are expecting $2.55 a share in earnings.

CEO Bruce Thorn said that the company expects to return to EBIT and EPS growth in 2020, including substantial boost in normalized free cash flow. This is expected  after a year of restructuring in 2019.

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Sergey Savastiouk|Expert

Sergey Savastiouk, Ph.D. has a degree in Applied Mathematics from Moscow University and has extensive experience as an entrepreneur, investor, manager, and mathematician. His professional expertise is in applied mathematics, mathematical modeling, system and pattern analysis, and software and hardware system integration. He has served as the CEO of several hi-tech start-up companies and nonprofit organizations, which has given him proven capabilities in business strategy for high-tech start-up companies, market assessment, company formation, team building, product development, marketing, and sales. He has published numerous articles in journals and magazines on related fields. As a retail investor, he spent 15 years developing his proprietary trading and quantitative algorithms (now Tickeron’s A.I.), which brought him significant returns in trading the stock market. His current work and goal in founding Tickeron is to bring professional, sophisticated stock market analysis capabilities to retail investors via an easy-to-use interface.