meta user
network profile
| bio | website | |
|---|---|---|
| location | ||
| age | ||
| visits | member for | 3 months |
| seen | 9 mins ago | |
| stats | profile views | 20 |
|
May 15 |
comment |
Profiting from price discrepancies between stock exchanges I'm not sure if I understood the 4h paragraph about the HFTs "jamming". But you are basically saying that what they are doing is providing liquidity? |
|
May 14 |
revised |
Profiting from price discrepancies between stock exchanges added 20 characters in body |
|
May 14 |
asked | Profiting from price discrepancies between stock exchanges |
|
Apr 30 |
comment |
t-statistics for the mean return, using Newey-West standard errors When I use X is ones I get the warning that one of the matrices is singular and it returns NaN. |
|
Apr 30 |
comment |
t-statistics for the mean return, using Newey-West standard errors For the model residuals? I find it hard to understand what X corresponds to in the regression model. And why does it return a 2x1 vector? |
|
Apr 29 |
comment |
t-statistics for the mean return, using Newey-West standard errors Still a bit confused about the program. What is X resp. e If I don't have a regression model (I just want to compute the NW s.e. for a random variable, no coefficients). |
|
Apr 28 |
comment |
Volatility of a rolling window strategy Ok. What I thought was that when rolling forward the same profits will be included several time (at least similar profits generated by the same stock movement or whatever the underlying asset is, also dependent on how the strategy is implemented). As the returns are also similar this doesnt affect the mean. However the s.d. gets heavily reduced. Isn't this a bit misleading? The shorter the rolling window is the more similar the profits get and the more the s.d. is reduced. |
|
Apr 28 |
comment |
Volatility of a rolling window strategy Mainly at the risk profile of the strategy, by looking at the standard deviation of the returns |
|
Apr 27 |
asked | Volatility of a rolling window strategy |
|
Apr 17 |
comment |
Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) let us continue this discussion in chat (if you don't mind) |
|
Apr 17 |
comment |
Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) I'm sorry if I'm a bit slow. But I don't understand. First you say: no market neutrality in cointegration by definition, cointegration in definition has nothing related to "Market Neutrality". Then you say: yes it is: because errors e=y-bx are stationary (at least in a weak sense). The latter I understand but the first is a bit confusing to me. <br/> Also I don't understand how you get that $r_X-br_Y=0$ for $b=\frac{Cov(r_X,r_m)}{(Var(r_X)}$. I know it's the regression coefficient though, so it makes sense that it should solve the equation. |
|
Apr 17 |
comment |
Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) Hmm, don't understand this last comment. What do you mean by "all cointegration tells us is that errors will be nice, which is also what we are interested in when searching for neutrality"? If cointegration doesn't imply market neutrality (by definition, as you say). Isn't a long/short strategy that uses the concept of cointegration, such as pairs trading, always market neutral? |
|
Apr 17 |
comment |
Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) Of course this does not hold in practice since these are just models. Also, I find that from $\beta_X - b\beta_Y = 0$ you get that $b = \frac{\beta_X}{\beta_Y} = \frac{Cov(r_X,r_m)}{Cov(r_Y,r_m)} \neq$ what you said? Although if this is indeed true this means that the market neutrality from the cointegration is consistent with CAPM? If CAPM says that b needs to be what you said, and that is indeed the the regression coefficient you get from the cointegration. But of course, these are just models and in practice this falls apart for several reasons. |
|
Apr 17 |
comment |
Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) I am not sure if I completely follow you. Are you talking about 'in practice'? In one of your previous comments (another question): "great. "a" is not important, if you want to be "market neutral" you go 1 stock of X long/short and 2 stocks of Y in the opposite dir. you can choose any other size ofcourse assuring that relation X/Y will be 1/2 – cf16". I'm only concerned about the theory here. I think it seems kind of intuitive that it would be indeed market netural if you invest according to this relationship. However, I wanted to see if this is consistent with CAPM. |
|
Apr 16 |
asked | Using cointegration to prove that a long-short strategy is market neutral (in CAPM sense) |
|
Apr 15 |
comment |
t-statistics for the mean return, using Newey-West standard errors Thank you very much! |
|
Apr 15 |
comment |
t-statistics for the mean return, using Newey-West standard errors Ok, thank you! Maybe you just gave the article a quick glance so you can't answer this. But do you know if the choice of the lag (6) is arbitrary or is it because the strategy is tested over a 6 month period, but just pushed forward 1 month every time (when backtesting it). In other words each month is traded 6 times. |
|
Apr 15 |
comment |
t-statistics for the mean return, using Newey-West standard errors Ok I think I understand the purpose of using the Newey-West s.e. now. Since they evaluate the performance over a 6 month period and then only rolls forward 1 month, the returns will be correlated, hence this has to be adjusted for. The lag 6 is because the return "today" is correlated with those 6 (shouldnt it be 5?) month backwards. Is this correct? However, I am still confused about the input in the matlab code. I would really appreciate if someone could explain it (the questions in my previous comment) to me! |
|
Apr 13 |
comment |
t-statistics for the mean return, using Newey-West standard errors Thanks, this is a lot more then I hoped for! I'm still a bit confused about the error terms. Since our hypothesis is that the returns are zero, would that imply that the error terms (they are equivalent with the model residuals, isn't it?) are simply the returns? If I use the article as an example, the result would be a T x n vetor of the returns from altering the strategy n times/ways. Should e (as def in your code) be the T x n vector, or should the s.e. be evaluated separately for each vector of return. Also, what would X be? |
|
Apr 12 |
asked | t-statistics for the mean return, using Newey-West standard errors |
