Reputation
4,956
Next tag badge:
27/100 score
11/20 answers
Badges
11 36
Impact
~93k people reached

Jun
30
answered Underlying Sample Space in Continuous Market Model
Jun
23
revised Covariance between two stocks in a two-factor model
added 5 characters in body
Jun
23
answered Covariance between two stocks in a two-factor model
Jun
23
comment Covariance between two stocks in a two-factor model
You write "the factor model is" and then two numbers. This is not a model. Do the 2 stocks "have" 2 different models? This is very unclear. Please format the question and insert the formulas that describe the models.
Jun
23
comment Options on Volatility Control Index
+1 beause I did not know that "Volatility Control Indices" exist. Who publishes them? Where? Thanks!
Jun
21
awarded  Yearling
Jun
19
comment The Distribution of Future Stock Price
It is difficult to say what is meant if they do not state it explicetly. But the word "instantaneous drift" could point to the GBM setting - thus lognormal prices ( i.e. log returns are normal).
Jun
19
revised How to break down an FX option P&L?
edited title
Jun
19
accepted Seasonal patterns in financial markets (weekday effects)
Jun
19
answered The Distribution of Future Stock Price
Jun
18
comment Seasonal patterns in financial markets (weekday effects)
I usually like looking at rather recent data just because I think that the world changes and that e.g. 2008-2014 is more relevant for today than periods before that. Thus looking at the link there seems to be quite a strong pattern showing reversal in the period 2006-2010. I would love to see more recent data too. But for this period the effect looks strong to me - although in general the article summarizes that the effect is not reliable. Maybe not at all times - maybe not in old days but today !? ;)
Jun
18
comment Seasonal patterns in financial markets (weekday effects)
Hi, thanks for the references. Do they also cover patters during the week?
Jun
18
asked Seasonal patterns in financial markets (weekday effects)
Jun
18
comment Extracting Signal from Noisy Data
Yes ... in modern markets you can not expect large sources of arbitrage (small $\beta$). But if $\beta$ is small then speaking the the terms of your model the error dominates and you are likely to lose money.
Jun
18
revised How to use calibrated Standard Stochastic Volatility?
added 34 characters in body
Jun
18
answered Extracting Signal from Noisy Data
Jun
16
awarded  Popular Question
Jun
16
comment Regression model syntax
$y$ in this case is $r_{t+1}+ \cdots +r_{t+H}$. In training the model you have to form sets of $y$ and corresponding $x$ (which are terms involving $D$). These will overlap if you increase $t$ by $1$ only - which should be ok as this usually happens in time-series regression.
Jun
15
comment Regression model syntax
The term $D_{t_i,k}$ are based on past returns before $t$. So one could say that they are independent and that $r_{t+1} + \cdots$ is "dependent". I would rather say that these are explanatory for the latter. Do you want to find out how that $D$ terms are calculated precisely?
Jun
15
comment Implied volatility interview question
This is really basic ... let one parameter go to infinity ...