Q1 Same-Property Cash NOI increased 15.6% to $9.9 million in 2Q26 on a constant-currency basis, "primarily due to higher rental rates and increased occupancy".

6/17 16:30

Logistic Properties of the Americas Forms Strategic Alliance with FIBRA Prime for $145 Million

Logistic Properties of the Americas "announced a strategic alliance with FIBRA Prime, a preeminent diversified Real Estate Investment Trust in Peru, through the divestment of Parque Logistico Lima Sur, a premier logistics park located in the Lurin submarket of Lima. Subject to customary regulatory approvals and closing conditions, FIBRA Prime will acquire 100% of PLS for a total consideration of US$145.0 million, substantiating the carrying value of LPA's real estate portfolio and its resulting book value of approximately $8.00 per ordinary share. The sale will generate US$85.0 million in net proceeds for LPA after debt repayment and before taxes, bolstering the Company's financial flexibility to drive its expansion plans. PLS generated US$10.3 million in net operating income (cash NOI) for the last twelve months ended March 31, 2026, with the potential for further growth, underscoring the institutional quality and stabilized cash flow profile of the asset. The Company expects to redeploy proceeds of the sale into its actionable investment pipeline in Mexico, where mid- and long-term demand fundamentals, strong domestic consumption, nearshoring and ecommerce tailwinds, as well as a robust acquisition and development opportunity set all offer compelling risk-adjusted returns. This capital is expected to be fully invested in stabilized, high-quality properties over the course of the next 12 to 18 months as LPA evaluates select opportunities across key submarkets of the country."

5/21 08:50

Logistic Properties of the Americas Expands Lease with Scharff by 38,438 Square Feet

Logistic Properties of the Americas announced the expansion of its existing lease agreement with Scharff Logistica Integrada at Building 100 within Parque Logistico Callao. Under the agreement, Scharf, an existing tenant at Parque Logistico Callao, will lease an additional 38,438 square feet at Building 100, further expanding its operational footprint within the park. The expanded lease is scheduled to commence on June 1, 2026 and underscores LPA's continued ability to capture demand and drive occupancy growth, aligned with the Company's asset-optimization strategy, in one of Peru's most supply-constrained logistics submarkets.

11/3 16:43

Logistic Properties of the Americas Secures New Long-Term Lease in Colombia

Logistic Properties of Americas "announced the signing of a new long-term lease with a premier U.S.-based membership warehouse club operator. This agreement strengthens LPA's regional relationship with the client, which initially partnered with the Company in Costa Rica and is now expanding its operations in Colombia. The 15-year lease encompasses approximately 97,250 square feet in Building 300 at Parque Logistico Calle 80, located in Bogota's most strategic and modern logistics corridor. With this lease, the flagship park will achieve 100% occupancy, solidifying LPA's position as top-tier logistics real estate provider in Colombia's capital city, serving a market with over 11 million people. The lease reflects current market rates, supported by favorable market fundamentals such as minimal new supply over the past two years, a resilient consumer sector, improving market sentiment, and the platform's capacity to seamlessly serve multinational clients across multiple countries."

6/30 08:05

Logistic Properties of the Americas joins Russell 3000, Russell Microcap Indexes

Logistic Properties of the Americas announced that it has been added to the Russell 3000 and Russell Microcap Indexes, effective after U.S. market close on June 27, as part of the annual reconstitution of the US Russell indexes. The Russell 3000 also serves as the U.S. component of the Russell Global Index.

Ver más eventos

Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.