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Dec
1
comment Which measure to determine Risk?
The reason why one gets away pricing derivatives in the risk-neutral probability space (given certain conditions are met) is because the drift is already accounted for through the underlying and because of the hedge argument. This, however, is not the case when you take a straight exposure to cash equity. Of course you can always setup an equity pricing model where you end up with a stochastic differential in which the drift term "vaporized" but I question its usefulness. For pricing its perfectly fine as long as everyone agrees on the same way (such as B-S) but risk?
Nov
30
comment open-source implementation of orderbook from FAST?
@javapowered, with all due respect but it sounds like you are missing some crucial basics here. You can't derive your best bid/offer without building and maintaining the book and that is precisely what Louis has already told you
Nov
30
comment Which measure to determine Risk?
I am not a believer in Value at Risk (VaR) and when I think about true exposure to firm-specific risk then you are in effect at the mercy of the specific equity return and hence risk. The classic theoretical model of assuming a BM driven process with specific drift is anyway a flawed concept no matter how you turn it. For equity linked or direct equity exposure other models, such as those that incorporate jumps, are way superior vs the traditional Ornstein–Uhlenbeck process, for example. My point is that you deliberately chose to expose yourself to the equity drift -> use it.
Nov
28
comment Is price gaping the major risk that market maker has?
@pteetor, maybe someone else can chime in but I would identify gap risk as the major risk in providing liquidity in general, unless we are talking about highly illiquid stocks and/or stocks that trade at 2-3 levels throughout the whole trading session. Properly managing inventory to high frequency trading is like the necessity for humans to walk in order to go to work. Not being able to intelligently manage inventory should by default disqualify one to even participate in this advanced trading environment.
Nov
26
comment What is the industry standard Quant Finance modeling library for F#
@Nikos, but let me ask you a question as well if I may: Several months have passed, can you say with confidence that F# has solved sufficiently many problems for you at fair trade-offs and acceptable compromises that C# or other .Net products would not have? Please keep in mind that all .Net get compiled into the same CLR. If problem expression appears to be better served in F# then I reckon the real problem lies in the user's ability to transfer concrete problems into the next "abstraction layer".
Nov
26
comment What is the industry standard Quant Finance modeling library for F#
...looking for a language that offers support on the quant side through analytics libraries? Most likely not. I just think the quant industry is currently very well served on all ends, Matlab and Mathematica on the raw Math side, R/SPSS/... on the stats side, C++ and .Net (and Java for frontend apps) on the programming/implementation side. And I believe Big Data will catch a lot more attention by the quant community, but I just do not see the benefit of broad support for functional languages, sure they solve individual problems but it costs tons to change languages in large dev environments.
Nov
26
comment What is the industry standard Quant Finance modeling library for F#
Yes and here is why: If your requirements are raw performance such as throughput and latency then go with C or C++, if you need libraries that support quant analytics then for modeling purposes go with Matlab or R, else C++ or C#. If you have programmed for any length of time you will value the importance of broad support and vast amounts of open source solutions and libraries. For today's average quant's job requirements I do not see where a functional language is supposed to kick in. I am sure there are people that still swear by Cobol or Fortran but would I recommend such to someone...
Nov
24
comment Is price gaping the major risk that market maker has?
@pteetor, sounds to me you are describing the "chicken or egg problem". Sure most all risks in this space can be traced back to improper inventory management. But I think what smyoo describes is yet a risk that truly has little to do with inventory management. In his example there is nothing you can do or could have done better other than not having provided liquidity in the market in the first place which is easy to say in hindsight. Inventory management in this example is really not the issue imho.
Nov
21
comment Can I trade the volume of a security or index?
You can express views on volume indirectly through VWAP order types. You can pay 10-15 pips for a guaranteed vwap price and look to beat that through a hedge of your own if you believe you have a superior view on price levels and where volume trades. But this is more an expression of trading intraday volume.
Nov
21
comment Black-Scholes: Why the focus on volatility?
I addressed many of your comments and questions and you all debunked them. I also added references for you to read up on. What else do you need? There are different IVs across moneyness and the reason is explained in detail in many answers on this board. Please search for one of my past answers to this particular question as I am a little short of time right now.
Nov
21
comment Black-Scholes: Why the focus on volatility?
@AndrewDabrowski, I stand by my explanation. Implied volatility is never a "fudge factor" but rather an actively traded "asset class". Maybe you want to write up an answer to your own question if you think all other answers are incorrect, which of course begs the question why you would have asked in the first place.
Nov
13
comment Risk and Reward in practice
Absolutely, agree fully. And then I also know several of the momentum based funds' owners personally, some of which manage just double digit millions, some triple digits, not huge by any of today's standards. But many have been in existence for several decades and if you follow momentum based fund performances you will see there were years where such funds horribly underperformed. Yet, investors stuck with those funds for various reasons, among others of course long-term performance, but also honesty, trust, and integrity in its management.
Nov
12
comment Risk and Reward in practice
@Richard, sorry I did not mean to address you directly, my comments are more geared towards most of the buy-side fund industry. Regarding your last sentence, I believe if one handles money responsibly while generating alpha, over a long period of time then clients will stick with such PM even if he underperforms others at a certain point in time.
Nov
12
comment Risk and Reward in practice
Just to not be misunderstood, my point is that it does not make a difference whether I am a trader or PM as long as I call the shots on risk. If I set myself a risk limit or stop and adhere to it and indeed sometimes get kicked out of trades then I am of course aware that the market may right after reverse and that I would have been in good shape if I had not squared my position. But that is a completely flawed way of thinking. If I am scared to underperform others and because of that cannot properly fulfill my fiduciary duty then I should never manage others' funds. Simple as that.
Nov
12
comment Risk and Reward in practice
Well, then I need to ask the PM why he/she is in this business in the first place: If one cannot make reliable predictions (for which I would not fault anyone because neither can I) but also does not find a momentum approach nor fundamental approach appealing then I think that person does not belong in the driving seat of a couple hundred million dollars or more. I find it almost a criminal act to not be in cash just because nobody else is, despite believing that investments will lose more money. Its peoples' significant investments those mor... are gambling with.
Nov
12
comment Risk and Reward in practice
I would again disagree in that loss limits are subtle. Loss limits are there for a reason. After all, you are (your firm is) risking clients' funds, sometimes the funds of the fund owners. The only people or whole industry group that does not seem to understand the meaning of fiduciary duty is the buy-side mutual fund industry. For most of them it seems to be ok to beat the benchmark index but still lose 30 or 40 percent. This concept will never get into my head. A great long-only fund PM is supposed to be all in cash when the global economy starts to falter.
Nov
12
comment Risk and Reward in practice
That last sentence scares me (and is probably the reason I have never entrusted a single dollar to buy-side funds in my life) ;-)
Nov
11
comment the law of comparative advantage and exchange rate
The author is half right, half wrong. Right in that PPP does not cause currencies to adjust for different purchasing power when currencies are pegged. Wrong, in that comparative advantage does not disappear just because currencies are pegged. Look at China and the US. A large driver of the persistent trade imbalance is the artificially weak yuan. It presents a persistent comparative manufacturing advantage to China.
Nov
8
comment Is the risk-reward ratio considered in Quantitative Finance?
My whole point is that quants should do what they do best, test out theories, develop models and by all means, work closely with traders and other risk takers to fully understand the repercussions when models eventually blow up or correlations break down. Strictly speaking an algorithmic trading strategy should not concern itself at all with risk-reward in the portfolio sense but it should generate trading signals based on the model intrinsic risk-reward characteristics. Whether signals are taken, how orders are sized, how pre-trade risk correlates with open positions should be left to traders
Nov
8
comment Is the risk-reward ratio considered in Quantitative Finance?
@sets, no question, I holeheartedly agree. But when you leave real risk and rewards in the hands of those with very little to no risk taking and managing experience due to an over-reliance on academic theories you end up with something like all current global central banks = blown out of any feasible proportion balance sheets and a gamble-like experiment that nobody understands nor risks to estimate the outcome of. Same stories goes with uncountable "quant desks" that blew up because of lack of risk management experience and over-reliance on models.Model risk is the most underpriced risk today