vanguard2k

655 reputation

bio	website
	location	Vienna, Austria
	age
visits	member for	10 months
	seen	May 17 at 13:29
stats	profile views	46

	655 reputation	bio	website		visits	member for	10 months
11 badges		location	Vienna, Austria		seen	May 17 at 13:29

summary answers questions tags badges favorites bounties reputation activity

31 Comments

suggestions reviews revisions comments badges posts accepts all

Jan 16	comment	Comparison of Brownian Motion Expected Drawdown and simulated results @ManInMoon I edited my post
Jan 7	comment	Yield of a risky bond @Freddy I edited my answer according to your suggestion and hope you can agree with me now. Still, in my opinion, yield-to-maturity is not directly risk related but yield spread is. Nevertheless, I think we are all talking about the same things here.
Jan 7	comment	Yield of a risky bond I am sorry but I disagree on the point where you say simple-to-calculate risk premia. For most corporate bonds for example you have to work hard to separate default risk from other risk factors. Further more, you don't arrive at a "probability measure" but rather at a yield spread as I stated in my answer. The probability of default still remains unclear. You still have to model the default probability for a given yield spread.
Jan 7	comment	Yield of a risky bond @Freddy thats precisely what I said in the second statement about the yield spread. There is no point we disagree on. The textbook way to calculate a yield just depends on the price and the coupons though. Of course the default risk has impact on the price, thus on the yield-to-maturity.
Dec 27	comment	How to detect regime change when estimating asset correlation from historical time series? @strimp099 Are there any resources in these search results you find particularly instructive and interesting? Introductions, surveys, papers, books?
Dec 27	comment	Most natural generalization of covariance/correlation to model dependence of extreme events @vonjd Its the definition of covariance: en.wikipedia.org/wiki/Covariance#Definition
Dec 27	comment	How to reactivate a risk mangement rule in an automated process I think the question was pointing into a different direction. The rules to close the positions are there but when to open them again? I guess this is a very general question (and old) question. To my mind, almost any rule will do - but you should have one. If one has a rule which tells when to close a position one should also have a rule which tells when to open one. Examples of the latter rules where the question here.
Dec 21	comment	Most natural generalization of covariance/correlation to model dependence of extreme events Strictly speaking, there are no assumptions of linearity or normality in the notions of covariance and correlation. The only assumptions needed are: two random variables with finite second moments.
Dec 20	comment	What are the best Journals & Conferences in Quantitative Finance? @montyhall is there a difference to arxiv.org?
Dec 19	comment	How to cluster ETFs to reduce cardinality for portfolio selection I wanted to add one thing here: Elimination of highly correlated assets reduces the condition number of the variance-covariance matrix thus giving you more stable results. At one point in the optimization procedure you have to invert this matrix somehow. So elimination of correlated products is also sensible from a numerical point of view
Dec 19	comment	How to cluster ETFs to reduce cardinality for portfolio selection I would definitely do a preselection by looking at bid-ask spreads, cost/tracking error, trading volume, NAV premium/discount, replication mode (not necessarily in this order but I would advise it). I think you will find that after this analysis your universe will be narrowed down...
Nov 29	comment	Recommendations for books to understand the math in quantitative finance papers? @Gravitas : I think most of the book recommendations below are marvellous books but they are merely primers. I doubt you will fully understand recent academical work after reading them. Its like driving a formula 1 car in your first driving lesson. It feels cool but it will not take you very far. Take these texts as a motivation to plunge into some more serious math and take the problems one step at a time. (and after many years things will still be a mystery I can assure you that :-) )
Nov 9	comment	Exposition of Growth in a Perpetuity Take the dividend discount model for example. In your example the dividend growth rate $g$ would be greater than the investors required return $r$. So the required return should definitely be larger than the dividend growth rate. Finally, you should end up with the price of the stock after all. :-)
Nov 8	comment	Is the binomial model wrong? Hm I am reading your reference right now and I have a suggestion. In the part where you say "It is safe to say the set of traders and risk managers that are able to comprehend this differs little form the empty set". I think you should restate this - it is rather a set of measure zero - but definietely not empty. ;-)
Oct 4	comment	How to show that this weak scheme is a cubature scheme? @TheBridge Is this question still of interest?
Oct 3	comment	Encyclopedia of Statistical Tests @DangerMouse I dont doubt that its a great book I just thought it would be great to read a book review before ordering it. (And I almost surely will) Just to see if it is too theoretical or too "shallow" material.
Oct 3	comment	Markowitz mean-variance optimization as “error maximization” @vonjd I am sorry but I am missing the point about the maximization of the error here. Sensitive to error, ok, but maximized? In what sense? Maybe it is not maximization in a mathematical but a more dubious sense (form people ciritcal about MV optimization) like: "The optimal portfolio not only maximizes your utility but also your error" (whatever that error means).
Oct 2	comment	When to use Monte Carlo simulation over analytical methods for options pricing? Further more you can estimate models without normality much easier. Just sample from the distribution. For many contingent claims on stochastic processes the PDE equivalent does not really exist in a classical form (PIDE for jump processes for example). I think this is the main strength of MC.
Oct 2	comment	Michaud's Resampled Efficient Frontier - Out of Sample Simulation Testing OK now I know what you mean (sorry about the misunderstanding). Intuitively, you would score the weights to get the objectively scored portfolios on the frontier. Then you would average all these frontiers. Look at the descriptions of the charts (also in the paper). They underline this: "The bottom solid curves in Exhibit 6.3 display the average of the true, out-of-sample, risks and returns of the optimized portfolios." and not the scored average weights.
Oct 2	comment	Michaud's Resampled Efficient Frontier - Out of Sample Simulation Testing @Harokitty Of course there is a difference between averaging the weights and the scoring results. (as you mentioned volatility depends on it in a nonlinear fashion) Look at page 10 and Step 4 in the Michaud^2 Paper you cited. It says to get the RE optimal portfolio you should average the weights. To generate the comparison chart above you should average the efficient frontiers (which, in the case of the REF - which consists of already scored averaged portfolio weights).