Public company intelligence preview
JERASH HOLDINGS (US) INC
3 insider trades surfaced from the last year. This page shows only aggregate signals, not the underlying transactions, people, filings, filters, or AI workspace.
Snapshot
A narrow read on a much deeper workspace.
The preview gives search visitors enough signal to understand coverage. It does not expose transaction records, person-level profiles, filters, comparisons, or analyst workflows.
Insider compensation
Public aggregate: $414107.40 average total compensation across covered insiders.
Governance movement
Public aggregate: 0 governance events in the last year.
Institutional ownership
Public aggregate: 19 holders from the latest quarter.
Restricted sales and governance
Public counts, not the investigation layer.
The full product opens the underlying filings, insider context, historical holdings, comparison tools, and AI analysis.
Market context
Basic quote context for the preview.
Company note
Context before the data.
Company Overview
Jerash Holdings (US) Inc. is a consumer cyclical apparel manufacturing company that produces customized ready-made sportswear and outerwear, mainly from knitted fabrics, through its operations in Jordan and support functions in Hong Kong and China. Its products include jackets, polo shirts, t-shirts, pants, shorts, and PPE, and it supplies major global brands and retailers such as VF Corporation, New Balance, G-III, Hugo Boss, American Eagle, and Skechers. The business is highly customer-driven and operates with limited long-term contract protection, so order flow and volumes can change with brand sourcing decisions. Fiscal 2025 showed stronger shipments, improved gross margin, and a narrower net loss, but the company remains exposed to tariff changes, freight disruptions, and concentration in the U.S. market and VF Corporation.
Executive Compensation Practices
For a company in the Apparel Manufacturing industry, executive pay is likely tied to operational execution metrics such as revenue growth, gross margin, manufacturing efficiency, on-time delivery, and working capital management rather than only earnings per share. Jerash’s recent filings suggest those drivers are especially important because profitability improved mainly from higher volume, better scale, lower logistics costs, and tighter expense control, while share-based compensation also affected SG&A. That means compensation programs may reward management for improving utilization across its factories, managing export costs, expanding capacity, and maintaining liquidity in a capital-intensive manufacturing environment. Because tariffs, customer concentration, and supply-chain disruptions materially affect results, incentive plans for executives in this sector often include qualitative or adjusted performance measures that account for these external risks.
Insider Trading Considerations
Insider trading patterns at Jerash may be influenced by order visibility, customer concentration, and tariff-sensitive demand, since the company’s revenue can shift significantly based on a few large customers, especially VF Corporation. Management likely has substantial insight into shipment timing, customer replenishment trends, logistics costs, and tariff impacts before those factors are fully reflected in reported results, which can make insider transactions more informative around quarter-end or after major customer updates. The company’s exposure to Jordanian operations, freight disruptions, and financing needs may also create trading sensitivity when executives learn about production interruptions, margin pressure, or changes in bank borrowing and receivables collection. As a manufacturer in the Consumer Cyclical sector, Jerash insiders may also face heightened blackout restrictions around earnings because results can move materially with seasonal demand, customer orders, and shipping timing.
Unlock the full JRSH insider intelligence workspace.
Move from public aggregate counts into transaction-level detail, people, filings, compensation history, ownership shifts, export tools, and AI-assisted analysis.