Netlist (NLST) Price to Book (2009 - 2026)
Netlist's (NLST) Price to Book stood at 13.36 in Q3 2026, down 67.8% from the prior quarter.
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Analysis
Netlist (NLST) Price to Book (2009 - 2026) Analysis & Trends
For FY2023, Netlist's Price to Book came in at 20.07, up 104.4% from FY2022.
- Across earlier years, Price to Book came in at 9.82 in FY2022 (-64.2%) and 27.46 in FY2021.
- The Q3 2026 figure is the lowest quarterly Price to Book since Q4 2022.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Apple | 5,177.41 Bn | 4,922.87 Bn | 54.82 Bn |
| 2 | Cisco Systems | 377.40 Bn | 377.40 Bn | 11.79 Bn |
| 3 | Arista Networks | 249.38 Bn | 198.58 Bn | 2.33 Bn |
| 4 | Dell Technologies | 220.34 Bn | 176.10 Bn | 9.83 Bn |
| 5 | Sony | 166.48 Bn | 103.89 Bn | 7.96 Bn |
| 6 | Sandisk | 127.44 Bn | 112.27 Bn | 9.38 Bn |
| 7 | Seagate Technology Holdings | 121.35 Bn | 116.20 Bn | 2.43 Bn |
| 8 | Western Digital | 110.67 Bn | 100.50 Bn | 2.53 Bn |
| 9 | Hewlett Packard Enterprise | 64.15 Bn | 42.09 Bn | 4.93 Bn |
| 10 | Netlist | 1.92 Bn | 1.53 Bn | 68.86 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 26, 2026 | 13.36 |
| Jun 27, 2026 | 41.48 |
| Mar 28, 2026 | 53.27 |
| Mar 30, 2024 | 40.00 |
| Dec 30, 2023 | 20.07 |
| Sep 30, 2023 | 15.32 |
| Jul 1, 2023 | 39.79 |
| Apr 1, 2023 | 37.94 |
| Dec 31, 2022 | 9.82 |
| Oct 1, 2022 | 15.60 |
| Jul 2, 2022 | 15.89 |
| Apr 2, 2022 | 24.96 |
| Jan 1, 2022 | 27.46 |
| Oct 2, 2021 | 27.54 |
| Jul 3, 2021 | 28.77 |
| Apr 3, 2021 | 50.26 |
| Oct 1, 2016 | 25.42 |
| Sep 26, 2015 | 46.38 |
| Jun 27, 2015 | 5.15 |
| Mar 28, 2015 | 3.45 |
API Access
Netlist Price to Book API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=price-to-book&ticker=NLST&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-book", "ticker": "NLST", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=price-to-book&ticker=NLST&period=max&api_key=YOUR_API_KEY");
const data = await res.json();