Rekor Systems (REKR) Accumulated Expenses (2016 - 2019)
Rekor Systems (REKR) posted Accumulated Expenses of $3.03 million for Q1 2019, down 14.0% from $3.52 million a year earlier but up 14.7% from the prior quarter.
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Analysis
Rekor Systems (REKR) Accumulated Expenses (2016 - 2019) Analysis & Trends
At the end of FY2018, Rekor Systems' Accumulated Expenses came in at $2.64 million, down 13.6% from FY2017.
- In prior years, Rekor Systems' Accumulated Expenses was $3.06 million in FY2017 (+432.1%) and $575,203 in FY2016.
- Quarterly Accumulated Expenses has run from a low of $575,203 in Q4 2016 to a high of $3.52 million in Q1 2018 over five years.
- On a year-over-year basis, Accumulated Expenses increased in two of the last four quarters, with growth averaging 118.0%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $2.64 million (Q4 2018), $3.19 million (Q3 2018) and $3.02 million (Q2 2018).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 328.64 Bn | 313.71 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 276.50 Bn | 256.94 Bn | 1.10 Bn |
| 3 | Fortinet | 132.74 Bn | 118.67 Bn | 1.64 Bn |
| 4 | Snowflake | 120.19 Bn | 107.50 Bn | 1.04 Bn |
| 5 | Datadog | 99.51 Bn | 81.15 Bn | 881.34 Mn |
| 6 | Okta | 35.35 Bn | 25.44 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 33.58 Bn | 28.10 Bn | 546.45 Mn |
| 8 | Zscaler | 32.06 Bn | 18.18 Bn | - |
| 9 | MongoDB | 28.84 Bn | 19.30 Bn | 569.77 Mn |
| 10 | Rekor Systems | 50.93 Mn | 9.26 Mn | 7.11 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | 3.03 Mn |
| Dec 31, 2018 | 2.64 Mn |
| Sep 30, 2018 | 3.19 Mn |
| Jun 30, 2018 | 3.02 Mn |
| Mar 31, 2018 | 3.52 Mn |
| Dec 31, 2017 | 3.06 Mn |
| Sep 30, 2017 | 1.90 Mn |
| Dec 31, 2016 | 575,203.00 |
API Access
Rekor Systems Accumulated Expenses 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=accumulated-expenses&ticker=REKR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "REKR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=REKR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();