Good Afternoon All,
I have current data, along with the history for credit card balances. I have grouped these by month and delinquency buckets(1 cycle = 30 days past due, 2 cycle = 60 days past due etc.)
There is an old process that I've inherited to forecast delinquencies, it is an markov chain that I don't like how it's written so I'm going to try to do it over using IML. I'm also going to do a moving average.
Why I'm reaching out to the group is to find out if someone has experience with an exercise like this, if they have a certain model or procedure that they thought fit this kind of data best.
Thank You,
Mark
I cannot speak to "the exercise" personally, but it sounds similar to some SGF papers that Gongwei Chen wrote. If you decide to rewrite the analysis in IML, there are a few articles about Markov chains and moving averages in IML that you might find helpful for writing efficient code:
I cannot speak to "the exercise" personally, but it sounds similar to some SGF papers that Gongwei Chen wrote. If you decide to rewrite the analysis in IML, there are a few articles about Markov chains and moving averages in IML that you might find helpful for writing efficient code:
That's great, thanks Rick!
No idea of the accuracy compared to a Markov model, but 2 stage regression are models are what I've seen. First stage calculates the probability of default and the second calculates the amount of the default assuming they're going to default.
SAS Innovate 2025 is scheduled for May 6-9 in Orlando, FL. Sign up to be first to learn about the agenda and registration!
ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
Find more tutorials on the SAS Users YouTube channel.