Lam Research (LRCX) Intangibles (2010 - 2024)
Lam Research's Intangibles came in at $138.55 million for fiscal Q4 2024 (quarter ended Jun 30, 2024), down 17.8% from $168.45 million a year earlier and down 2.8% from the prior quarter.
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Analysis
Lam Research (LRCX) Intangibles (2010 - 2024) Analysis & Trends
Going back to fiscal Q4 2010, Lam Research's Intangibles data covers 56 quarters.
- Intangibles carries a five-year compound annual growth rate of -8.6% (FY2019 to FY2024).
- Going back by fiscal year, Intangibles was $168.45 million in FY2023 (+65.4%), $101.85 million in FY2022 (-23.1%), $132.37 million in FY2021 (-21.5%) and $168.53 million in FY2020 (-22.3%).
- The fiscal Q4 2024 figure represents the lowest quarterly Intangibles since fiscal Q1 2023.
- Year-over-year, Intangibles has declined for three consecutive quarters, with growth averaging 20.4% over the last eight quarters.
- The fastest year-over-year change in Intangibles over five years came in fiscal Q4 2023 (growth of 65.4%), and the weakest in fiscal Q2 2022 (a decline of 28.2%).
- Business Quant data shows LRCX's Intangibles at $142.48 million (Q3 2024), $151.08 million (Q2 2024) and $157.62 million (Q1 2024) in the three fiscal quarters before Q4 2024.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Intangibles (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,563.73 Bn | 5,337.89 Bn | 72.14 Bn | 3.00 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,381.64 Bn | 2,007.35 Bn | 27.22 Bn | 761.69 Mn |
| 3 | Broadcom | 1,640.54 Bn | 1,566.58 Bn | 20.46 Bn | 26.33 Bn |
| 4 | Micron Technology | 1,238.95 Bn | 1,177.72 Bn | 35.06 Bn | 473.00 Mn |
| 5 | Advanced Micro Devices | 1,004.87 Bn | 961.62 Bn | 6.20 Bn | 15.64 Bn |
| 6 | Asml Holding | 697.02 Bn | 652.86 Bn | 5.90 Bn | 628.70 Mn |
| 7 | Intel | 605.16 Bn | 489.89 Bn | 6.51 Bn | 2.55 Bn |
| 8 | Lam Research | 425.56 Bn | 402.36 Bn | 3.48 Bn | - |
| 9 | Applied Materials | 420.05 Bn | 385.49 Bn | 4.59 Bn | 315.00 Mn |
| 10 | Arm Holdings | 310.17 Bn | 295.88 Bn | 1.25 Bn | 217.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2024 | 138.55 Mn |
| Mar 31, 2024 | 142.48 Mn |
| Dec 24, 2023 | 151.08 Mn |
| Sep 24, 2023 | 157.62 Mn |
| Jun 25, 2023 | 168.45 Mn |
| Mar 26, 2023 | 179.65 Mn |
| Dec 25, 2022 | 184.78 Mn |
| Sep 25, 2022 | 110.39 Mn |
| Jun 26, 2022 | 101.85 Mn |
| Mar 27, 2022 | 113.31 Mn |
| Dec 26, 2021 | 112.08 Mn |
| Sep 26, 2021 | 125.01 Mn |
| Jun 27, 2021 | 132.37 Mn |
| Mar 28, 2021 | 143.26 Mn |
| Dec 27, 2020 | 156.09 Mn |
| Sep 27, 2020 | 161.71 Mn |
| Jun 28, 2020 | 168.53 Mn |
| Mar 29, 2020 | 182.68 Mn |
| Dec 29, 2019 | 193.12 Mn |
| Sep 29, 2019 | 206.26 Mn |
API Access
Lam Research Intangibles 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=intangibles&ticker=LRCX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "intangibles", "ticker": "LRCX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=intangibles&ticker=LRCX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();