awesome mate!! Thanks for this :) Would you make a video about RAROC indicator that uses value at risk as parameter? Or a deep dive into value at risk and different distributions? I have lots of doubts about which distribution model should I use for my models.
Greats vids mate. Very informative. I work at Lacima with Les and Chris in Sydney and fyi Les' surname is pronounced as "Clue - low". Low as in not so high ;-) Keep up the great content 🙂
Thank you. I am clear about the option pricing using this MC technique. Now the question is how do you obtain or calculate the delta based on this method. WOuld be happy to receive your answer.
Thanks for this great video.. I have one query regarding this line of code: sigma = np.sqrt( np.sum( (CT[-1] - C0)**2) / (M-1) ) I think here C0 is in present value terms whereas CT[-1] array is in Future value terms. Shouldn't we discount CT[-1] array back to presnt value to calculate the sigma? Or am i missing anythg? Thanks in advance..
Amazing video as always! May i suggest a video on Monte Carlo Simulations for risk management? (By simulating an equity curve besed on win rate and reward to risk ratio)
I appreciate the detail here. It's waaaay over my head though. I was just wanting to learn; my main question is what is the simulation generating? Are you randomly generating portfolios, price data, or both?
What's the best /cheapest way to get historical options data? Or is it preferable to grab snapshot data and keep your own history via pipelines? Love your channel! Wish I found it sooner.
Cheapest, definitely to download data everyday from your broker. Obviously there are clauses on brokerage website in the T&Cs that say you can't use data for any purposes other than personal use. Best - I'd like to review some of the cheapest API options currently available. Hopefully we can come up with some good options that have depth in terms of markets/products, as well as granulity. It seems impossible to find Trade Tick Level information without paying an arm and a leg for it.
Is speed of PRNG and possiblity of generating many independent streams important in Monte Carlo Option Pricing? How much time simulations in real buisness can take? Is PRNG efficiency bottleneck of such simulations?
Dear QuantPy, would it also be possible to simulate S/K, i.e. the moneyness of an option? As far as I know the max() function is linear homogenous of degree 1, so you could write max(S/K-1, 0/K,) don't you?
Yes this is often better completed in binomial/trinomial trees. I currently have one video on this. Will soon drift back into path dependent options, early exercise contracts ect.
@@QuantPy A deep dive into the Least Squares Monte Carlo Method proposed by Longstaff and Schwartz in 2001, would be great. I am currently working on a python code to apply it for real option analysis.
