J.Law & Dakota Johnson Just Wore the Anti-Trend Autumn Buy That’s All Over H&M

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J.Law & Dakota Johnson Just Wore the Anti-Trend Autumn Buy That's All Over H&M

The first day of autumn isn’t technically for another week or so, but ever since the temperatures went from the 30s to barely reaching the 20s in recent days, the celebrity set hasn’t wasted any time trading in their linen trousers and cotton dresses for cosy knits designed for the season ahead. Case in point: Dakota Johnson and Jennifer Lawrence, who, despite living on opposite coasts—Johnson’s in L.A. while Lawrence is in NYC—were spotted this week wearing near-identical knits that, together, unofficially kick-started sweater season.

Lawrence was seen strolling through the city alongside her husband, Cooke Maroney, wearing a beige turtleneck with flowy The Row trousers, slipper slides, and the XL version of Loewe‘s iconic Flamenco bag. Meanwhile, Johnson went grocery shopping in Malibu in a similarly relaxed jumper, matching lounge pants, and a pair of now sold-out sage-green Sambas. Both outfits would’ve looked out of place a week ago. But after the recent temperature drop, they each appear perfectly autumnal.

Follow their leads and shop the classic autumn knit from H&M below. 

On Jennifer Lawrence: The Row shoes and Gala Crepe Wide-Leg Pants ($1090); Loewe Large Flamenco Knot Leather Clutch ($2990)

On Dakota Johnson: Adidas Samba OG Sneakers ($139)

This zip-top knit sells out year after year.

This also comes in black, cream and grey.

An easy sweater that will look so good with white denim and boots.

I love a collar detail.

SO chic!

Cosy, affordable and versatile. What more could you want?

Styling a rollneck under a jumper? Genius.

I really rate H&M’s cashmere.

A chunkier style I’ve got my eye on.

Looks how polished this is with tailored trousers in a similar hue.

Stunning.

Beige knits look great with silky slip skirts.

This story originally appeared on Who What Wear US. 

Next Up: The Autumn/Winter 2023 Fashion Trends That Really Matter

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