Don't miss your chance to take the Fabric Data Engineer (DP-600) exam for FREE! Find out how by watching the DP-600 session on-demand now through April 28th.
Learn moreJoin the FabCon + SQLCon recap series. Up next: Power BI, Real-Time Intelligence, IQ and AI, and Data Factory take center stage. All sessions are available on-demand after the live show. Register now
Hi @ssstaud ,
Could you please provide the calculation logic of weighted time to maturity(Y axis)? As checked the data of transactions table, it only have start_date. So how can we get the weighted time to maturity? It will display as the specific date, and equal to start_date plus the number of days for xxx?
Best Regards
erer
Hi @ssstaud ,
According to the revised history of your post, I updated your sample pbix file(see attachment). Please check whether that is what you want.
If the above one is not your expected result, please provide more details(calculation logic and specific examples) for your expected result. Thank you.
Best Regards
Hello @Anonymous,
Thank you so much for helping me and sorry for deleting it, thought that nobody would care about this.
Sadly it is not the solution I was looking for.
I will try to depict my problem better this time. I have updated the pbix and and excel files on the link: https://mega.nz/folder/vlo0RCJS#Kxh79nbxIEPh05wX-h1hhw
What are the important values here:
mature_at: the time when our company has to pay the money back to the client
amount: how much money we have to pay back (i.e. the weight)
The calculation logic is better described by this:
How it works: Lets say that in may 2016 a person bought a bond that matures in 5 yrs for the amount of $100. So WAM is for may 5 yrs. For June 2016 it is 4 yrs 11 months.
In July sb. bought a bond of the same value of $100 that also matures in 5 yrs. So for July 2016 the WAM is 4 yrs 11 months, because:
And the graph should look like this (eventually ending in a zero, because all the bonds matured i.e. the money was given back to the client)
Thank you once again for helping me!
Check out the April 2026 Power BI update to learn about new features.
If you have recently started exploring Fabric, we'd love to hear how it's going. Your feedback can help with product improvements.
A new Power BI DataViz World Championship is coming this June! Don't miss out on submitting your entry.
| User | Count |
|---|---|
| 41 | |
| 37 | |
| 34 | |
| 21 | |
| 16 |
| User | Count |
|---|---|
| 65 | |
| 62 | |
| 31 | |
| 26 | |
| 25 |