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seen Apr 10 at 6:59

May
19
comment When the Inverse Correlation between the SPX and VIX breaks down
@jessica, a long straddle is long iVol, and my implication was that many PMs on the buy side do not look to sell or be net-short implied vol products. So when a cash market trades higher, cash equity returns correlate less negatively with changes in implied volatility. But my overall point is that you are most likely wasting your time by trying to model future investor behavior on realized vol or realized correlation data points. To answer your last question: you are looking at relationships that existed in the past and that you observe changed.
May
19
comment When the Inverse Correlation between the SPX and VIX breaks down
@jessica, re your first comment, no, its not a warning sign of anything, maybe one time yes, the other 99 times not. There is no repeated pattern that would give you an edge that can be exploited. You most often cannot take advantage of realized vs implied vol differentials, such differentials can widen out another couple orders of magnitude or can stay out for months/years. All that this correlation breakdown tells you is that traders do not sell as much implied vol as a rising cash market suggests, nothing else. Many buy side PMs have an allergy against being short wings.
May
19
comment When the Inverse Correlation between the SPX and VIX breaks down
@Andrew, having traded for many years various volatility products I can advise to be very careful when drawing conclusions from all such observations ("such", as in investors delta hedge to take advantage of realized vs implied vol differentials [which in itself is hard to impossible to do profitably over the long-term], or your observation of the skew vs correlation relationships). Such observations are anything but stable and thus a very bad recipe for building trading strategies around.
May
19
comment When the Inverse Correlation between the SPX and VIX breaks down
like all observations of "realized" metrics, realized correlation tells you something about data points that lie in the past not what the market implies about the future. Thus, trying to draw conclusions from a breakdown in realized correlations about future investor behavior looks to be a futile endeavor.
May
16
comment Market Exposure and Hedging
You should then change your question. What you actually like to ask is hardly explained in the above
May
16
comment Add transaction costs to prediction
@siamii, you are asking a question that is impossible to answer without a host of other information which you did not provide.
May
16
comment Market Exposure and Hedging
I do not see how they are not good short term instruments. Many are traded with tight enough spreads and with deep enough liquidity to rival large cap stocks.
May
16
comment Market Exposure and Hedging
you should look at sector ETFs, which should solve your problem.
May
14
comment Why C is still in use especially in area of numerical optimization (instead of C++)?
@Downvoter, care to comment? I find it disrespectful to down-vote others' work without providing the slightest reasoning behind it.
May
10
comment How does the CME set margin requirements on commodity Futures
Not at all. Most exchanges set their margins according to their risk models but please keep in mind those can be overridden at their own discretion at any time. If exchange X decides to hike the margin on a contract Y then they are at total liberty to do so and you may not be able to capture that in your models.
May
10
comment How does the CME set margin requirements on commodity Futures
Well you asked how CME sets margins. And the answer is they use SPAN. By the way span is available to clients there are three separate products that are based on span. The information is available on their website.
May
10
comment Best way to store hourly/daily options data for research purposes
@sashkello, well I find it incredibly hard to put time series data into sql tables and to efficiently query them later. Why? Because each time you want to retrieve just one metric you have to load the whole row for each time stamp. What if you want to expand? You need to re-write all schemata and table structures. And most sql solutions are orders of magnitude slower than most any nosql solution, regarding time series data. But if sql works for you then go for it. The above is just my opinion not any hard rule.
May
9
comment How does the CME set margin requirements on commodity Futures
@John, could it be you meant to point to this link? cmegroup.com/clearing/risk-management/span-overview.html
May
9
comment Best way to store hourly/daily options data for research purposes
It seems very fast but I admit I only ran some quick code through the nuget library targeting .net. I like their concept much better than most columnar db solutions.
May
9
comment Best way to store hourly/daily options data for research purposes
I like Teafiles, just it's that the use base is (still) very small. I thought I read somewhere that an R library exists to load and query Teafiles but I may be mistaken. My own binary file database is structured actually very similarly.
May
9
comment Best way to store hourly/daily options data for research purposes
@olaker, with all due respect to your function as moderator , may I point to the fact that I have not initiated any debate nor accused anyone. I was recommended by other moderators to flag unconstructive and accusing posts which I have done. I would appreciate if those who actually initiate false accusations to be called out and not those who take the time to help other users. I think I have done my best to tone down rhetoric. The other user has been very confrontational in similar ways before and I reserve the right to defend against false accusations.
May
9
comment Best way to store hourly/daily options data for research purposes
@kristine, I pointed out I cited nobody. I derive my conclusions and recommendation from lots of implementations I have seen and that were presented to me as well as I have worked with. Do a simple Google search and if you still believe professionals store any sort of time series data, whether it be options chain data, tick data, or other time compressed data in SQL tables then all the power to you. I would never recommend anyone touching SQL to tackle time series data. I respect your answer (though I disagree) and hope you could also pay respect to others who put in time to help others.
May
9
comment Best way to store hourly/daily options data for research purposes
@sashkello, I recommend you to think only about your requirements first. Do not get confused by someone who is ecstatic about Redis or SQL or what have you. You want to store data (speed is not so important), you want to query data fast and flexibly, you probably want to query it in R as well because you mentioned you want to profile and analyze said data. You want to look for a solution that can grow dynamically and which is extensible. Read up what people use to store time series. After that decide whether any SQL solution actually makes sense here or other solutions solve the problem better
May
8
comment Best way to store hourly/daily options data for research purposes
@sashkello, I added some content based on your requirements.
May
7
comment Relationship between European, American options volatility
define "monotone in volatility" please. Do you mean volatility being deterministic?