Binomial Option Pricing Model || Theory & Implementation in Python

[@nielsenhari]

Thank you so much I get it now. You explained everything in 30min very clear, and there is our teacher taking weeks and I got nothing. Good job!!!

[@frederikwoite3916]

You are beyond skilled in both teaching and QF!

[@king199324]

Great idea using the numpy arrays! thanks for sharing!

[@mphikelelimbongiseni6277]

Useful amongst many, Thank you👏

[@aniruddhvasishta8334]

At 32:49 -- won't you get a recombining tree even if ud is not 1 since if the stock price goes up then down the price will be udS_0 whereas if it goes down then up you'll get duS_0 which are the same thing? In these cases it's just not true that S_2 = S_0 but I don't see why that's an issue.

[@georgekollias3442]

great video, simplicity at its best :)

[@5GWGuerillaFighter]

@ 11:19 what is this "Lore of One Price" you speak of?

[@homodeus-k9f]

Hey I think it's great work here and now that I've started my financial engineering masters I can finally understand this. Just one thing tho - in the risk-neutral probabilities coding part, I think it should be u = np.exp(sigma * np.sqrt(T / N)), d = 1 / u, qu = (R - d) / (u - d)... I think there was a mixup somewhere

[@gatsbyliu1084]

I am on my way study financial engineering master too :), so good to see another person in manadarin name

[@teroliikala]

Brilliant channel. Keep it up!

[@benardkiplimo3508]

Well done! Thank you for the video

[@topticktom]

Didn"t understand any of it, but I did enjoy the 49 minutes anyways

[@daves1413]

In 15:36 you say "bank account (Su-Sd)". I think it should be "stock units" not "bank account units" for your beta, no?

[@KazekageKidd]

Fantastic lesson mate., really like this approach.

[@Picklpickls]

It is an amazing video!

[@PJokerLP]

Hey, thanks for your video. But shouldn't type 2 arbitrage (3:36) be defined as P(V_T>=V_0) = 1, since your definition allows for losing money by having V_0 > 0. Greetings and stay healthy Marcel

[@samuraijgt]

Why does the bank account not decrease in value when going to the down state

[@joshuakendrick3528]

How does the coding change for American options?

[@chykeinvesting9429]

hey this was so great, I actually am using this to help me secure a quant position at a trading desk... I am just confused on one part, can i schedule a one on one?

[@benardkiplimo3508]

Did you get the job?

[@chykeinvesting9429]

@@benardkiplimo3508 nah, I wasn’t advanced enlugh

[@SamManink23]

I have one question why we are taking bank account units.

[@gutefrage9425]

I understand it but what is it good for? How to apply it?

[@jayjayf9699]

If you have a 4 step time tree the number of nodes does not equal N+1

[@wqw9475]

Hi very nice video but I think you have forgotten to take the max between the expectation and the payoff for each node.

[@jonathonemerick2084]

That’s the pricing formula for American style options not European style

[@wqw9475]

@@jonathonemerick2084 For European you never need to take the max. I mean exactly for the US kind the author forgot to take the max for each node.

[@QuantPy]

This video was for European pricing only. No max required for each node? Please check another video for American style option pricing kzbin.info/www/bejne/gWOsqmuYeNKLoM0

[@wqw9475]

@@jonathonemerick2084 ok I got it because that's for European pricing. I thought it's for American kind. Thanks for your response.

[@wqw9475]

@@QuantPy Yes I get it now since I was working on American side so I thought this example too. Thanks for the response.

[@annog6673]

You flipped the meaning of alpha and beta right on the middle and got a little bit confused there, didn't you? Or is there a meaning behind using beta for the weighting of stock and calling it bank account weighting?

[@QuantPy]

The alpha and beta terms are just constants. In the video I've assigned Beta as the number of Shares and Alpha as the number of bank account units. Feel free to use your own constants and go through the math 👍