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seen Dec 9 at 11:52

Python and R


Sep
1
comment How do I eliminate developed currency funding cross rate risk in an EMFX position?
Thanks - it's what I suspected. I'll look at Stock & Watson. I think the multiple regression route that I suspected is the way to go. I am going to have to look at the multicolinearity aspects though if I include a lot of other EMFX in there. Perhaps a PCA first?
Sep
1
comment How do I eliminate developed currency funding cross rate risk in an EMFX position?
Yep - not looking at the rates - could use IRS too of course. or fund bonds in FX forwards or repo. Looking for the pureplay on ZAR so your last para kind of answers the question.
Aug
22
comment How do I eliminate developed currency funding cross rate risk in an EMFX position?
That is wrong for the following reason. If I have a view on the South African rand, for whatever reason, I do not want to trade EURUSD. Yet there is a high correlation between USDZAR and EURUSD. Thus even though I am benchmarked in USD, trading USDZAR gives me EURUSD risk. Indeed USDZAR contains a whole bunch of other risks too, including SPX, bonds, BRICS etc etc. What I want to do is isolate out the ZAR specific risk, so that I can trade a pureplay on South African fundamentals or technicals. I am seeking a generalised technique to isolate a pureplay on a currency (or indeed on any series)
Aug
19
comment How do I eliminate developed currency funding cross rate risk in an EMFX position?
nothing wrong. Bloomberg has a correlation weighted set of indices (BCWI <go>} but they average the weights on each optimal basket - which to me doesn't make a huge amount of sense - takes away from the pureplay of each currency as we deviate from its optimal weights. I was just wondering at the time if there was something more interesting being done out there. I have gone with PCA bloomberg-style, without weight averaging.
Aug
16
comment How to derive the implied probability distribution from B-S volatilities?
Thank you very much. Now off to program it......
Aug
12
comment How to derive the implied probability distribution from B-S volatilities?
I am indeed looking for the implied distribution as from there it's simple enough to do the qqplot. My first priority is an empirical approach, as the target audience of this visualization will want to use it to get and idea of which parts of the surface are cheap/dear, by visual comparison to historical performance of the pair. This will not (yet) be for a trading model. Of course I would like to be able to show this in an intuitive fashion (with all the usual caveats about historical v future returns, and low-probability event risk). Thank you for your interesting starting points.
Aug
9
comment What is the role of Credit Valuation Adjustment (CVA) desks in investment banks?
I'll add one final point, and that's about culture. The "culture" of the front office is taking risk, wherease the culture of the CVA desk is inherently to reduce risk. If you're asking this question in relation to career choice, you need to keep this in mind, as the training you will receive and the instincts you may develop on markets, will obviously be affected.
Aug
9
comment What is the role of Credit Valuation Adjustment (CVA) desks in investment banks?
Put it this way. The term "front office" of a bank inherently involves selling. Traders, Researchers, and Salespeople are engaged with providing services to their clients, in various ways. That is not the case for CVA - they are there to help create the conditions for those services to be offered by the front office, by optimizing one aspect of risk. Indeed, it is important that CVA does NOT report to front office, as this would be a conflict of interest. Keep this in mind though: CVA people have all the skills and training to become excellent prop traders or portfolio managers.
Aug
9
comment What is the role of Credit Valuation Adjustment (CVA) desks in investment banks?
yes indeed, they are fully active in the external market, but then they're market takers, not makers. In other words, they're the client. Perhaps my characterization of "middle office" is misleading, now that I think of it. Rather, they're part of the risk control function, which some banks breakout separately into counterparty risk.
Jun
20
comment How do I compare implied and historic volatility?
@vonjd I have found the following two papers to be interesting wrt to this question as well: bcb.gov.br/ingles/estabilidade/2002_nov/ref200201c62i.pdf and rbnz.govt.nz/research/discusspapers/dp02_04.pdf
Jun
17
comment How do I compare implied and historic volatility?
thanks for the links to the paper and the book. So there is no point in trying to compare the skew and kurtosis of the historic distribution, to the risk reversal pricing and smile of the curve, analagous to how macro traders will compare historic with implied ATM vol? That's what I was wondering basically. Second, what do you mean by overlapping data? I am using bloomberg "last price" closing prices, so there should be no overlap? For completeness I take log returns of that series and multiply by sqrt(262) to get the annualized vol. What would you do differently?
Jun
6
comment How do I compare implied and historic volatility?
@vonjd no with Excel. I am shamed to say that I while I am an experienced trader and programmer, I am not a quant, and am only beginning to learn R. So the data comes from Bloomberg, which gives the ATM, RR, and flys for each tenor and delta and I have backed out the outright vols for each point.
Jun
4
comment Monthly data for popular indices (constituents).
@Terco I have a spreadsheet that will do this if you like. It only does a few months, you'd have to fill out the other months by copying and pasting the formulae. You'll need access to the Bberg terminal though, with Excel and the add-in. Email me at lagunafinance at me dot com if you're interested.
Jun
4
comment How do I eliminate developed currency funding cross rate risk in an EMFX position?
@moderator: How can I start a bounty on this question? It doesn't seem to be letting me do so.
Jun
4
comment What concepts are the most dangerous ones in quantitative finance work?
Actually, we can turn this argument on its head. We can profit from the fact that correlation vanishes during a crisis, by selling correlation to the street. Fact is because many retail investors don't want to choose specific assets in an asset class, they tend to buy baskets. Since they also want capital protection, they tend to buy options on those baskets. Writing these options takes the street short the correlation of the basket elements, and they're happy to pay up to buy it back at (usually expensive) levels, which is what many Hedge Fund traders do through dual binaries and such like.