<t>Hi,I am currently doing a PhD in financial econometrics at a European university. I am going to finish next August and I am planning to apply for jobs in systemic trading, so I would like to ask for a profile evaluation. My research interest lies in nonlinear and non-Gaussian state space models a...

Hi neuroguy,Can you mention some of these interesting data science issues relating to market 'tick' data? I would really appreciate it, because it is hard filter out some useful information from the internet (most of the material is either superficial or IT oriented).Thanks in advance!

<r>Hi Alan,I don't know the answer to your questions but let me through in some relevant thoughts:- There are reduce form credit risk models which take into account additional information. These models usually look like [$]\lambda_{it}=exp(\beta c_{it} )[$] where [$]\lambda[$] is the default intensi...

nice follow up on the paper VPIN and the Flash Crash

You should carry out a likelihood ratio test to check your hypothesis.

check this paper

Thank you for the suggestions!It seems a quadratic specification would indeed help.

check this package and the related paper

<t>I have the following two OU processesandwhere W_1 and W_2 are independent Brownian motions.LetI am interested in the following expectationI derived the dynamics of f but (of course) the drift is a non-linear function of X_1 and X_2 so I can not use standard affine arguments to get a closed form e...

<t>This is how I understand what they are doing:1, they pick starting parameters2, given the parameters they calculate \lambda_t and \gamma_t for all the 31 observations by minimizing the root mean squared errors at every observation date.3, they calculate the root-mean-squared error between the est...

Here are some academic papers:Frailty Correlated Default Multiperiod Corporate Default Prediction Latent Factor Intensity Model

Hi!Recently I have read some papers about the effect of parameter uncertainty on pricing. For exmaple.I was wondering if this has any practical relevance or this is again some academic dead end.Any idea?

The procedure in the Kim et al paper is fast and efficient I would say. You can also check their follow up paper.However I think the sequential Monte Carlo methods are more interesting eg this paper.

<t>I have a practical question regarding value at risk calculation. I would like to calculate the VaR as a quantile of the historical return series.1. If I have daily data that is no problem, and I found that in the industry they calculcate e.g. 10-day VaR by using the 1-day VaR multiplied by sqrt(1...

<t>Hi, I am reading "Multilevel Monte Carlo path simulation" by Mike Giles, and I don't get why this method helps in calculating non path dependent option prices (for example european call in one of the applications in the paper). He uses the following estimatorwhere \hat{P_l} is the f(S(T)) payoff ...