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You and that damned hospital! At least it's minor surgery I guess. Going back to the Joint High low distribution, the Cumulative distribution function of the joint High Low is nice and converges fairly quickly. The PDF on the other hand isn't as user friendly and Maximum Likelihood...

I can't see how the interpolation would be of any use because it's dependent upon the the knots that you use, so that's the actual important part. However, I can see a few situations where this might be useful: 1) having a functional from makes it easy for numerical methods. 2) diurnal patterns...

I don't think the answer given is correct, because when finding the numerator you need to know the probability of hitting the high: p(high |.80 range)*p(.8 range)+p(high|not .80 rane)*p(not .80 range). Since we don't know the probability of .80 range, we can't solve it without added info...

When I get time I'll look at it mathematically. It will be a good excecise.

No, because each company will behave according to maestro's numbers in the long run (this is our "given" info). Sample size won't matter because our domain is all the companies within the portfolio for which we have the relevant statistics for. (remember this is a hypothetical example). In...

"if any security is at 80% from it daily range." so are you saying that if the distance from the high and low is greater than 80%? "it has 90% chance of reaching it daily average high (or low)". Are you saying it has 90% chance of reaching one or the other?

The winding of a river is dependent not only on the flow of the water, but also the properties of the river banks as well. Also if there are runoffs and flood plains (dammed). This needs to be accounted for too.

I guess there's also a critical point in the thread where it becomes trashed as well. With regard to the chart Maestro posted, I don't know if I'm over reaching here, but perhaps these papers have something to do with his data plot...

Think about applause in a large crowd. At what point is it obvious that this event (applause) is happening? From a single persons perspective how so you know when to start and stop? How would you measure this mathematically? How does this relate to the markets? Have you ever been that jackass...

Thanks for the links! Other good stuff on subordination and SABR. I've done research on the changes of the distribution of returns for groups of equities and have found that when volatility increase the cross variance of returns is smaller than "nontrending" periods. I guess this is within the...

Ising model looks interesting in dealing with discrete global behavior.

It can be proven if P(a)*p(b)=P(A intersect B) I don't believe this is something you can conclude on face value. By the way if you've ever waited for the market to hit your bid and then keep chasing it to have only missed beautiful price run, you can at least imagine how his example would hold.

You're asking if it has any value. The better question is, what is the oppurtunity cost of watching charts. I would rather read the tape than the charts for certain markets. If u trade discretionary then a chart is useful for identifying stable character traits, and perhaps magnet areas etc...

Hi Mike, Thanks for the thought experiment. When I first glimpsed at this thread I thought you were going somewhere else with the experiment before I had a chance to look at the spreadsheet. Was the motivation for this experiment optimal stopping or was is bayes Monty Hall stuff? Have...

I took a look at that paper and I could be wrong in my analysis, but the results seem trivial. The E[X|x>.5]= .75 assuming a Continuous uniform dist. from 0 to 1. So if we are given a value of x, s.t. X>.5 or x<.5. Then our cond. expected values will be .75 and .25 respectively. So how often...

Markets do not always follow a random walk. There have been numerous studies that support this. There are other stylized facts that aren't supported by rw's. Even if markets followed a random walk, you could still make money from them. Look Andrew Lo's old papers and then use more appropriate...

you could hedge with other baskets. you can test when it's optimal to get out of the basket. you could model and assume price shocks as alternative subset play. you could hedge volatility. you could model longer or shorter plays to also hedge. you could also better select markets to trade...

sampling error and everything that follows. how do portfolio managers deal with that type of risk? there are a few ways

The price generation models tht you use will generally determine your paradigm. So you first make sure you have the stylized facts covered and then implement proper betting strategy. if you cover all possibilities of what the market does with different models, that's one way.

TS?.. marting... max. likelihood...