476 reputation
39
bio website Nope
location Paris, France
age 26
visits member for 3 years, 9 months
seen Dec 4 at 11:44

Graduated from the Msc. El Karoui of probabilities and finance and from the Msc. Laure Elie (promo 2011).

Looking for a full-time job opportunity in NY or London.

My Linkedin


Dec
8
comment Innovative ways of visualizing financial data
Do you accept to extend your question also to "audio visualization"?
Dec
6
comment What is the precision of standard deviation estimates with small samples?
Sorry @SRKX I have not responded to your question I thought you were interested by the rate of convergence of the CLT estimate. To be clear, you are interested by the standard error of your standard deviation..?
Dec
5
comment Are there “live” uses of the Generalized Method of Moments or are they all academic?
One of the most popular GMM method is the Maximum Likelihood methodology. For many models (ARCH/ GARCH/ ..) it leads to a closed-form function maximization while for the vast majority models (stochastic volatility models, ..) the maximized function is not computable analytically and need to be approached with filters. This approach - originated from robotic - was introduced recently by practitioners in the banking area. A good reference (but difficult) on this matter is the book 'Inference in Hidden Markov Models' of Cappé, Moulines and Rydén.
Dec
4
comment How to reduce variance in a Cox-Ingersoll-Ross Monte Carlo simulation?
Could u give more details on the considered payoff/& models ?
Nov
15
comment What programming languages are most commonly used in quantitative finance?
The C# numerical library of reference is NAG nag.com it's well expensive but you pay for a solution you can rely on. I have also experimented NMATHS which I found not fitted for Quants. Last but not least, the free MATHS.NET library, professionaly developped, suited to cope with large data, very promising but today incomplete and not mature for large deployments.
Oct
4
comment How to build a regime-switching model which knows its own limits?
The regime switching issue can be tackled by considering otherwise historic based estimator (that includes the last stock observations) : $ E(v_{t+1}|S_t,\dots,S_0)$. These estimates has proven very reactive to the market movement.
Oct
4
comment Can VIX be interpreted as a proxy for instantaneous volatility?
VIX index (or V2X for the Eurostoxx50) cannot be used to estimate the instantaneous volatility. It is rather used for long-period comparison purpose. For example let's consider an article of 2003 of Polson and Stroud. A forecast for the Heston instant volatility is built from stock historic data. Then turning to real data, they compare VIX and the historic instant vol estimator on a 10Y period. The two curves have almost the same behavior. However, on a 1Y comparison one observes an excessive smoothness of the VIX and the lack of interactivity of this index compared to the instant estimator..
Sep
8
comment What tradeoff is there to using an accurate estimate with a large confidence interval?
Thank you very much sheegaon for your helpful answer. Actually, there is no error on the above graph, the confidence bounds are built with the aid of a CLT for weakly dependent processess so the convergence is very very slow
Aug
15
comment Is there a quantitative finance ranking system for universities?
I agree with @Gortaur, it would be useful and also very interesting to share our thoughts on this topic.
Aug
5
comment Switching from C++ to R - limitations/applications
I have spent some time during the last weeks to infer parameters (calibrate) of a vol-sto model (hence using the classical Baysian inference theory). I used C# interfaced with R, no memory problem, even with a parallelized implementation..
Aug
5
comment Switching from C++ to R - limitations/applications
Anyone to defend C#??
Aug
5
comment Switching from C++ to R - limitations/applications
@Karol Piczac since i have migrated to R-Evolution i have no more problem with big data file, have a look at this (revolutionanalytics.com/products/revolution-enterprise.php)
Jul
17
comment Obtaining characteristics of stochastic model solution
you wrote $\langle S\rangle_t=\sigma^2t$ instead of $\langle S_t\rangle=\sigma^2S_t^2t$. (RockScience obtained the right sde)
Jul
15
comment Obtaining characteristics of stochastic model solution
For me MC methods are often the fastest way to get rapid & painless solutions, useful to test your results.
Jul
15
comment Obtaining characteristics of stochastic model solution
pdf = probability density function. To get numerically an empiricall estimate of your density function: 1 -- draft sample of $X_t$, 2 -- trace the empirical cdf (cumulative distribution function) of this sample 3 -- then compute (numerically) the differentiated function which is nothing but the empirical density ;)
Jul
15
comment Obtaining characteristics of stochastic model solution
Why not considering the empirical way (MC) to get the pdf?
Jul
15
comment Obtaining characteristics of stochastic model solution
can you put some details on your filtration $F_t$?
Jun
28
comment What is Ito's lemma used for in quantitative finance?
Itô's lemma is also applicable if $f$ is a $C^1$ function in time and space and also $C^2$ in space everywhere except in a countable set of points