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Sep
10
answered How do Return.portfolio and Return.rebalancing work in Performance Analytics in R?
Jul
28
revised Non-Negativity of up-factor and down-factor in Binomial No-Arbitrage Pricing Model
added 686 characters in body
Jul
28
answered Non-Negativity of up-factor and down-factor in Binomial No-Arbitrage Pricing Model
Jul
25
awarded  Yearling
Jul
23
comment reference question about portfolio optimization
Although I voted to close this question: You are recommending the Pfaff book. I havent read it yet, is it good? Just a small comment though: #4 is also weritten by Bernd Sherer and those are commercial software packages. #3 Is basically a cookbook for the corresponding R package and treats rather advanced optimization problems (compared to classical MVO).
Jul
21
answered Risk Parity portfolio construction
Jul
17
revised Handling Missing values in stocks returns when estimating the co variance matrix
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Jul
17
comment Handling Missing values in stocks returns when estimating the co variance matrix
@user3481555 Well if you delete the stock you simply reduce your investment universe. My intuition says that this induces at least some bias because the stocks with shorter history had a reason to enter the index later on. On the other hand, If you throw away the all the data where at least one stock has a missing value you might run into dimension problems (if you estimate a covariance matrix for hundrets of assets you want to search for "dimension reduction" or "shrinkage" or "robust" in quant.SEs search function). I will see if I can come up with the paper I mentioned...
Jul
17
answered Handling Missing values in stocks returns when estimating the co variance matrix
Jul
16
revised ETFs have lower tracking error than Futures?
added tags
Jul
16
suggested suggested edit on ETFs have lower tracking error than Futures?
Jul
2
awarded  Curious
Jul
2
comment Implementing A 50/50 Prediction Model Strategy
@emcor The 50% rate is only the percentage of right classifications. Just imagine an algorithm that gets the lottery numbers right 50% of the time. See also the comment by Joshua Ulrich
Jul
1
answered Implementing A 50/50 Prediction Model Strategy
Jun
26
comment economic facts that causes the financial time series to be heavy tailed
For EVT, the more puzzling fact is that the "real" heavy tails do not scale with time...
Jun
23
comment What Is A Good Success Rate Using Machine Learning For A Beginner?
I think this question is definitely appropriate here. I am no expert on this topic, but I think if you use models like that you aim for a success rate that is well above $50\%$ with the amount depending on the cost of implementing the trading signal so that you place bets with an expected value >0. Further more, you would want to add some additional margin (for estimation and modelling error or changing environment for example). It definitely depends on the cost of getting in and out of the position. Thats why there can't be a single target number.
Jun
11
comment PDF Calculation by Fourier Inversion of Characteristic Function for Affine Intensity Process in Matlab
Have you tried the matlab-function ifft? It seems to make more sense than doing the quadrature explicitly. Depending on the implementation, you might have to normalize your vector afterwards though.
Jun
11
revised calculate gamma value using finite difference method
added 5 characters in body
Jun
10
answered calculate gamma value using finite difference method
Apr
25
comment derive black scholes greeks
I suppose $q$ is a continuous yield dividend and $r$ the risk-free rate. But be careful, $N^\prime$ is most likely not the differential operator here! It is the probability density function of the standard normal.