Numerical Solutions to Partial Differential Equations: 2-d Diffusion
Вставка
- Опубліковано 16 жов 2024
- In this video, we will extend the concepts for a previous video on solving the 1d diffusion equation to two dimensions. Conceptually, this is similar to our previous work, but involves more bookkeeping to put things into a form our DAE solver can handle.
Previous Video: • Sparse Matrices to Spe...
Github: github.com/kpm...
Tip Jar: https//paypal.me/kpmooney
bro ur chanel thought me how to code in like 5 weeks, excellent content and explanation
Have you tried doing the sparse matrix method of this problem ? Couldn't find it on your channel
Not in the channel. There is a recent video on sparse matrices and Jacibians for the 1d case though.
It's been awhile since you've posted a new video. I'd love for you to continue your content. It's great. I tried to check for other socials to make the same comment but I didn't see any.
Hope you come back and provide more future content
Mainly no time these days. That, and I have already covered most of the low-hanging fruit that I can do with fairly minimal prep.
@@kpmooneyYou've done a good amount of IV. What about IV for the entire option chain? You can then show term structure. material prep from the Vix White Paper.
I love watching and sharing the videos as an engineer who is in finance now you bridge both my passions so well haha.
Thank you!
can you send link of the video in which you have explained 1 D diffusion problem?
ua-cam.com/video/qo-WzsVnXGE/v-deo.htmlsi=5zZu78-z_jVBLbjY
Awesome video! Thank you!
Excellent video !
Can you do a video on the numerical resolution of Ito's integral ?
Very nice!
I tried changing the boundary conditions and I don’t see anything changing in the output. Am I doing something wrong?
Where are you handling the boundary conditions. They should be set in the function equations.
Sir do you know how to calculate (number of trades) of option
I am not sure what you mean by number of trades here.
Please increase the zoom percentage of the notebooks next time to make it more readable.
The code is available on his Github page which is linked to in the notes above.