790 karma · joined November 7, 2014
However, no-one really believes that the Standard Model is the ultimate theory. There must be other stuff out there that we have found yet. What people are looking for now are deviations from the standard model.
Concepts are nice for some things, but as Alexandrescu argues convincingly in the talk omaranto linked, they become quickly become very unwieldy if you need to consider multiple orthogonal concepts at once in the same place. You get a combinatorial explosion of things you need to name. static_if needs to much nicer and smaller code.
The wait paper you link raises some valid concerns, but if it is something you can implement just as a library (as the lightning talk shows) most of them are moot. Note that this library-only version is a somewhat restricted version of static_if, the code in the branches that are not taken is still required to parse, it just is never instantiated.
EDIT: looking again at the whitepaper, they were arguing against a specific proposal for static_if. I think this library-only version does not have the same issues.
Nice discussion here: http://open-std.org/jtc1/sc22/wg21/docs/papers/2015/p0128r0....
Also, cool to see that they are considering adding a version to the language in C++17. Thought they'd ruled it out. Andrei Alexandrescu has a very nice talk on how static_if is superior to concepts, this is definitely very nice to have.
Scott Adams has a great post on the Trump tactics, highly recommended http://blog.dilbert.com/post/126589300371/clown-genius.
It's all string, more specifically a docstring (see https://en.wikipedia.org/wiki/Docstring ). They are also used in other languages, including Python.
(Incidentally, there is such a thing as Lebesgue-Stieltjes integral, the kind of issues Riemann-Stieltjes solve are orthogonal to the issues that motivate Lebesgue integration.)
As for the foundations of probability theory I am skeptical. I agree the theorems are nicer if you base probability theory on the Lebesgue integral, but I very much doubt if there is a realistic physical question that could not be answered by probability theory based on the Riemann integral.
And for what it is worth, a lot of modern physics (i.e., all of quantum field theory and modern statistical physics) is based on a type of integral (the path integral) that does not yet have rigorous mathematical foundations.
However in mathematics, it did change how people think about integration. "Integral" now usually means "Lebesgue integral" outside of specialized applications. One of its advantages is that a lot of theorems involving integration become simpler to state, since with the Riemann integral you need to add more conditions to make sure it is defined.
Actually, if you think about it, the only plausible way you could have something in space with zero jerk and non-zero acceleration would be an interstellar ship maintaining constant acceleration, so the suggested rule is almost exactly wrong.
Not sure what someone could possibly mean by that. Pretty much every celestial body has non-zero jerk. For instance, earth's acceleration is (to pretty good approximation) a constant times the $-e_r/r^2$, and the time derivative of that is definitely not zero.
'A novice was trying to fix a broken Lisp machine by turning the power off and on.
Knight, seeing what the student was doing, spoke sternly: “You cannot fix a machine by just power-cycling it with no understanding of what is going wrong.”
Knight turned the machine off and on.
The machine worked.'
See the rest at http://www.catb.org/jargon/html/koans.html
What is actually going on is simply that HFT firms tend to make a lot of small uncorrelated bets on the market, each of which has a pretty unimpressive winning percentage. If you make money on 51% of trades, and make one trade per day you'll have a losing day roughly every other day. If you make 100 trades per day it will be much rarer that you have a losing day, and if you make 1000000 trades it will almost never happen.
This is simply the law of large numbers, as you increase the number of samples the realized return will converge to the expected return (which is positive), far from statistically impossible.
Firstly, not sure what you think the distinction is between HFTs as opposed and "algorithimic market makers". I think most people would equate them, for instance most would agree that firms like Virtu Financial and Knight Capital Group are both HFT firms and market makers (for instance, they are Designated Market Makers on many NYSE securities, the closest thing we have to an "official" market maker these days).
Second, HFTs definitely make more money in moderate to high vol (the current period of prolonged low vol in the markets has been pretty hard for the sector), and during those periods it seems even you agree that they are providing liquidity - and I would argue, adding value.
During extreme vol events, yes HFTs will pull out of the market, but so does everybody else. If they can manage it, they will liquidate positions, but their books are small relative to other players, I am skeptical that this is an important factor in further increasing vol, will stand corrected if you can point to me evidence it is.
If HFT is really making vol worse, then why are we not seeing higher vol since it became prevalent? Certainly, we have had periods of great macro uncertainty in the last half a dozen years, but there was no apocalypse in the market.
Finally, my point in bringing up the NASDAQ broker example, is that HFTs perform an important function as market makers. If you want to get rid of HFT and do not propose who's going to take their place, I have to assume we would go back to the old system of human market makers. I think pointing out their flaws is entirely fair.
It's easy to demonize HFTs, but nobody forces you to trade with them. It would be relatively easy to setup a darkpool that does not allow HFTs to trade there. Some people have tried this (or at least to market the notion that they tried), but inevitably they decide they need HFT liquidity and end up courting them instead.
First of all, HFTs have certainly taken over market making functions in today's markets, almost entirely in equities, to a lesser extent in some other asset classes.
Yes, it is true that some HFTs will stop trading during extreme volatility events (but they are not consuming volatility either, merely not providing it any more). But the same was true of human market makers of the past (there is a famous story of NASDAQ brokers simply stopping to answer their phones during crashes in the '80s, even though they were required to always make markets by regulation) - so who are you comparing them too?
The flip side is that HFTs (as any market maker) make more money when the volatility is high, so they have strong incentives to get back in there providing liquidity.
Market makers are people that take no long term view on price movements, just try to provide liquidity in the short run, collecting the spread and trying not to to accumulate positions that are too large either way. Without market makers, prices would be much more volatile (they would just move a round lot because of short term fluctuations of supply and demand with no long term predictive power).
Basically you can think that market makers charge you a small (very small in case of HFTs) fee in exchange for the risk they run for holding inventory for a little bit and in the process reduce volatility.
Before HFTs, market makers were people that had seats at exchanges, which had much more of an information advantage over normal market participants and who certainly charged much larger fees and ripped off people more. The current system, with HFTs playing that role, is by any measure better for both retail and institutional investors.
(disclaimer, am an HFT trader)
And sometimes a stock might be entering an index but leaving another (e.g., moving from Russell 2000 to Russell 1000), so the net result might be opposite to what you'd naively expect.
So yes, it is possible to make money doing this, but it's not a sure thing.
I've tried to use ipython (with the '!' magic) as a bash notebook, but it doesn't handle bash variables in a nice way, and it requires escaping $s and some other characters. Too much friction for me.
The author hints at future Bokeh support, that would be icing on the cake!
It is a pretty great book.
They are matching buyers and sellers of ads across different exchanges, how are buyers and sellers hurt by this?
Yes, the traders pocket a spread for their trouble, but they also save you the hassle of checking all the different exchanges. And if you really care about that spread, you still have the option of looking at all the different exchanges.
If these arbitrageurs are keeping all the prices in different exchanges in line, it means that your average ad seller/buyer does not need to spend time and money on researching which exchange has best liquidity (although they probably still want to know which one chargers lower comissions).
Of course, there will be an effective fee that the arbitrageurs collect, but competition amongst them will drive that feed down (in principle, to less than what the average person would have spent on research).
If the traders are arbitrating prices between different ad exchanges, their net price will be zero and they make the ad market more efficient. Who exactly is hurt?