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Feb
1
comment Is it possible to deal with non-normal distribution in Black-Litterman model?
@SimoneBortolato The output of the BL method is a vector of means. If you want to optimize based on that means, you have to either assume something about the investor or about the market. Usually, its quadratic utility (only first two moments are relevant) or normality of the market. You say that your market is not normal and you care about it so you probably have to change these assumptions. You could incorporate higher moments into your function or do a full-scale optimization for example.
Feb
1
comment Is it possible to deal with non-normal distribution in Black-Litterman model?
@John I suppose so. But I guess this is one of the main points of the BL method. What was your problem with the lognormal version? For multi asset portfolios I dont even have an idea how to get the market cap (e.g. for commodities) even if there are no derivatvies though one could argue there are some sources.
Jul
20
comment Why do stocks fall so quickly? Technical explanations
Great! You could cite a seminal paper youve read and explain why it backs your answer. This would improve your answer a great deal because the OP (and me, too) could check it himself. Dont get me wrong: Almost anyone will have heard of this effect but hardly noone has taken time to verify it for himself (especially for Chinese stocks I would say).
Jul
17
comment Why do stocks fall so quickly? Technical explanations
Can you back that up somehow or is this just your assumption/interpretation?
Jul
15
comment Performance analysis for a changing portfolio
To get a meaningful answer to your question, could you state precisely what you mean by performance analysis?
Jul
7
comment Getting ETF data from google finance
Hi @Richard ! My 2 cents: Maybe it is more practical to do the following - Get data on the actual tracking error and, most importantly, tracking difference from trackinsight.com (i took a fresh look today it seems you have to register now), which is the most CLEANED data provider on etfs out there. Then you could take the historical index and subtract the tracking difference. You can use the tracking error to model a random factor. If you use historical data (fewer etfs!) you have both a shorter history and a less efficient ETF market than today.
Jun
23
comment ISM PMI data - sector trend through ranking and seasonal decomposition
But to deal with your question: What framework do you have? In the programming language R for example, you can use the command order() to rank the sectors, for seasonal decomposition you can do all kinds of stuff. As a first step I would use a moving average or the decompose() function of the stat package. As far as scaling is concerned, you will divide by the number of sectors at some point - but you can do it in different ways. The question is: do you want to preserve the information that the sector has a PMI that indicates growth or do you just want to see the ranking.
Jun
23
comment ISM PMI data - sector trend through ranking and seasonal decomposition
Just a small comment from my side. This chart does not say anything AT ALL - and this is the most friendly way for me to put it. I don't see what people get of posts like "It might be clear, it might not be!" - this is a no-brainer. I would recommend anyone to be very careful with this "macro" charts with left and right scales and different origins (especially comparing leading and lagging numbers and not shifting).
Jun
16
comment How to properly assess the costs of replicating an index via futures contracts?
The CME article is great!
Apr
30
comment Expectation of maximum draw down in the Brownian motion case
@Richard Maybe it appears to be a MC simulation because of the default value for $t$, which is $1000$, but to me the code .maxddStats looks like a numerical quadrature with precomputed values which are hard-coded into the function. I didn't look into it in more detail though.
Apr
29
comment New ways of communicating risk
could you provide any references as to why var should be the scapegoat of the financial crisis?
Apr
8
comment What is the legal difference between ETFs, ETNs and ETCs
Its not mumbo-jumbo! As a portfolio manager, it is important to know what your are buying!
Mar
31
comment Best written quantitative finance papers
could you esplain WHY you chose these authors?
Mar
30
comment Best written quantitative finance papers
Hi, i am not quite sure if the question is on topic here but I like it a lot and I think we should give it a chance! As for the question: Could you specify what audience you are writing for? In the academic literature, there is a quite standardized procedure about how to write things, at least structurally. If you write for a broader audience without experience in the field I suppose it is a lot trickier.
Mar
10
comment Book on market microstructure
Strange indeed as your answer is more in depth (as far as the first four references are concerned and you are an author of the book suggested. :-)
Mar
5
comment How to assess stock price movement from implied volatility?
@Victor123 The calculation is correct. For me, the problem with this calculation is that the volatility is a point on the volatility surface and the result not only depends on the moneyness (which you specified) but also on the term of the option. For a stock, you would typically give ONE volatility number OR concentrate on the investment horizon (here, you should probably take an appropriate value for "time to maturity" on the volatility surface). Maybe its better to calculate the stock's volatility directly if possible.
Mar
4
comment What to use as portfolio diversification measure?
@Richard I can fix you up in the meantime: papers.ssrn.com/sol3/papers.cfm?abstract_id=2276632
Feb
10
comment Why do we usually model returns and not prices?
I dont have time to formulate an answer right now but I recommend the "Quest for Invariance" article by Meucci. The basic principle is: You need to look for an iid distributed "invariant". This obviously cant be the prices. Most people consider stock returns as more or less iid, thats why we use them. They are the invariants. Others use time series models to explain the distribution in more detail. Here, its the innovations $\epsilon$ who are the invariants (iid). For options for example, returns are of little use. We use the implied vol surface to get one of the invariants.
Feb
5
comment Portfolio choice problem of a CARA investor with n risky assets
Hi! Could you post the reference to your book? Firstly, the derivative is wrong. It should be : $\mu + \frac{\alpha}{2}\Sigma \phi = 0$ (a vector equation: in your version, $1^\prime \mu$ is a salar, $\Sigma\phi$ is a vector). Secondly, you didnt incorporate the budget constraint. My guess is that it comes into the utility function via a Lagrange method.
Feb
4
comment Covariance matrix and Cholesky decomposition
@crunch Yes, definitely. Also, $LL^T$ does not have to be SPD for this definition. Thats probably a reason to define it this way: Its defines a broader class of distributions (because $\Sigma$ does NOT have to be SPD).