Kun Peng International (KPEA) Non Operating Interest Expenses (2013 - 2017)
Kun Peng International's Non Operating Interest Expenses was $3,025 in fiscal Q1 2018 (quarter ended Dec 31, 2017), down 72.8% from $11,125 a year earlier but up 1.2% from the prior quarter.
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Analysis
Kun Peng International (KPEA) Non Operating Interest Expenses (2013 - 2017) Analysis & Trends
On a trailing twelve-month basis, Kun Peng International's Non Operating Interest Expenses was $26,921 through Dec 31, 2017, down 12.8% year-over-year; for FY2017 (ended Sep 30, 2017), it was $35,021, up 64.4% from FY2016.
- Non Operating Interest Expenses shows a four-year compound annual growth rate of 41.3% (FY2013 to FY2017).
- In earlier fiscal years, Non Operating Interest Expenses was $21,307 in FY2016 (+262.6%), $5,876 in FY2015 (-56.7%), $13,575 in FY2014 (+54.6%) and $8,778 in FY2013.
- Quarterly Non Operating Interest Expenses has moved between -$4,099 (fiscal Q4 2015) and $18,539 (fiscal Q2 2017) over five years.
- Compared with a year earlier, Non Operating Interest Expenses has declined for three straight quarters, with growth averaging 75.5% over the last six quarters.
- The best year-over-year quarter for Non Operating Interest Expenses over five years was fiscal Q1 2017 (growth of 609.1%); the worst was fiscal Q4 2017 (a decline of 73.4%).
- Per Business Quant data, KPEA's Non Operating Interest Expenses in the three fiscal quarters before Q1 2018 was $2,990 (Q4 2017), $2,367 (Q3 2017) and $18,539 (Q2 2017).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non Operating Interest Expenses (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,686.58 Bn | 2,203.28 Bn | 104.83 Bn | 1.31 Bn |
| 2 | Home Depot | 283.87 Bn | 277.11 Bn | 16.12 Bn | 583.00 Mn |
| 3 | Tjx Companies | 145.82 Bn | 123.36 Bn | 5.07 Bn | - |
| 4 | Lowes Companies | 103.43 Bn | 96.39 Bn | 8.58 Bn | - |
| 5 | Ross Stores | 74.61 Bn | 57.54 Bn | 2.12 Bn | - |
| 6 | Target | 71.16 Bn | 65.74 Bn | 8.94 Bn | 98.00 Mn |
| 7 | O Reilly Automotive | 69.71 Bn | 68.80 Bn | 2.52 Bn | 69.87 Mn |
| 8 | Carvana | 68.78 Bn | 60.38 Bn | 1.38 Bn | 101.00 Mn |
| 9 | Autozone | 46.23 Bn | 45.13 Bn | 2.52 Bn | - |
| 10 | Kun Peng International | 13.20 Mn | 13.12 Mn | -5,644.00 | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Dec 31, 2017 | 3,025.00 |
| Sep 30, 2017 | 2,990.00 |
| Jun 30, 2017 | 2,367.00 |
| Mar 31, 2017 | 18,539.00 |
| Dec 31, 2016 | 11,125.00 |
| Sep 30, 2016 | 11,225.00 |
| Jun 30, 2016 | 6,944.00 |
| Mar 31, 2016 | 1,569.00 |
| Dec 31, 2015 | 1,569.00 |
| Sep 30, 2015 | -4,099.00 |
| Jun 30, 2015 | 3,325.00 |
| Mar 31, 2015 | 3,325.00 |
| Dec 31, 2014 | 3,325.00 |
| Sep 30, 2014 | 3,325.00 |
| Jun 30, 2014 | 3,325.00 |
| Mar 31, 2014 | 3,110.00 |
| Dec 31, 2013 | 3,814.00 |
API Access
Kun Peng International Non Operating Interest 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=non-operating-interest-expenses&ticker=KPEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-operating-interest-expenses", "ticker": "KPEA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=non-operating-interest-expenses&ticker=KPEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();