<t>QuoteOriginally posted by: outrunThat not the forefront really. :DThe most basic approach is to price an option with MC and then price it again with MC but then do it for S+h and S-h to get the delta/gamma. That's what my 5 year old son would do.Doing that you'll see that there is a lot of sample...
<r>I'm a newb. One step at a time. I just found it amazing that you can calculate an option price very easily using MC, as soon as you ask the next question "What about the greeks?" then you reach the forefront of quant finance knowledge so quickly. In physics it took me a year before I realised wha...
I looked through the contents of the book and what I could see in preview and I couldn't find any discussion of computing sensitivities, do you have a page number?
<t>So it seems the method you have mentioned above is the "Liklihood Ratio" method. As per Glasserman and what outrun says, it doesn't matter that the payoff is not differentiable at S=K since the probability is zero. I really find it amazing that nobody has written a simple accessible introductory ...
As a general aside, does anyone have any numbers on how long it takes in their pet language to generate e.g. 1 million such walks? In my python code it takes around 1 minute for a million.
<t>There's an obvious answer to fix that though, and basically all of the problems in the book. You need to get rid of moral hazard. The people taking the risks must bear the costs of failure. To put it into Taleb's words, "skin in the game". I think as soon as you fixed that people would be more wi...
<r>Anyone read this? Basically just confirms that all the problems that existed in the city pre-2008 are still alive and kicking. He interviewed 200 people for the book, however, the bit that caught my eye was his talk with a "cold fish headhunter". Some of the quotes sounded suspiciously like our o...
<t>QuoteOriginally posted by: AlanAnother way to do the MC delta (after switching to X = log S as bearish suggested) is to simply treat it as another option value with its own payoff.This avoids the complication of trying to do a numerical differentiation within a MC.Bit confused by this, can you el...
Yep I already found it but code without context is pretty meaningless Either way, I assume they have assimilated this knowledge from other books or papers to put into their book. What is the name of the method?
<t>QuoteOriginally posted by: bearishThere are three issues here. First, I understand that you may want to do time stepping for some other purpose, but it adds noise in the way that you are doing it. You should simulate the log stock price process (and then exponentiate it). This way there is no dis...
<t>QuoteOriginally posted by: CuchulainnFor the MC, your naïve approach won't work. Kienitz and Wetterau book discuss how to it. The ds factor is crucial based on Jaeckel 2005 "more likely than not" article.However, your fd would better using lattice The Euler method is awful in general, so fd (awfu...
<t>I have written the following python code to price a european call option. I get reasonable agreement with an online option calculator for the price, but the delta is quite a bit off. As far as I understand, I simulate a random walk, calculate the pay-off, present value the payoff, and then do lot...
<t>If we assume a risk-neutral random walk for an underlying [$] S [$] to be [$]dS = rS dt + \sigma S dX[$] then an obvious discretised monte-carlo algorithm for simulating this is:[$] S(t+\Delta t) = r S(t) \Delta t + \sigma S(t) \sqrt{\Delta t} \phi [$] where [$]\phi[$] is drawn from a normal dist...
<t>The question:Given a newbie has a finite number of hours to invest in learning before applying for jobs, where should they focus their attention in the current market? Of course I am interested in finance and want to know about this stuff anyway, but perhaps having an overview is sufficient rathe...