# Tag Info

22

I've worked at a hedge fund that allowed GA-derived strategies. For safety, it required that all models be submitted long before production to make sure that they still worked in the backtests. So there could be a delay of up to several months before a model would be allowed to run. It's also helpful to separate the sample universe; use a random half of the ...

19

I can help you beat random walk 'in the way you want', i.e. the expected value $E[\$]$will always be positive even assuming no drift. However, I have to warn people that$E[\$] > 0$ is NOT really an adequate condition for 'beating' in reality (at least to myself). Let's define some mathematical notations for derivation, and rephrase (simplify) vonjd's ...

19

Consider the standard error, and in particular the distance between the upper and lower limits: $$\Delta = (\bar{x} + SE \cdot \alpha) - (\bar{x} - SE \cdot \alpha) = 2 \cdot SE \cdot \alpha$$ Using the formula for standard error, we can solve for sample size: n = \left(\frac{2 \cdot s \cdot ...

18

I know that I have seen things like this in the past. Wasn't there something recently that used Twitter? Here are a few recent papers as examples, although I will be brutally honest that I don't know if they speak to your decent quality requirement: "Trading Strategies to Exploit Blog and News Sentiment" (Zhang, Skiena 2010) "The Predictive Power of ...

17

By "cryptography" you mean information theory. Information theory is useful for portfolio optimization and for optimally allocating capital between trading strategies (a problem which is not well addressed by other theoretical frameworks.) See: J. L. Kelly, Jr., "A New Interpretation of Information Rate," Bell System Technical Journal, Vol. 35, July ...

16

I think the biggest problem that genetic algorithms have are overfitting, data snooping bias and that they are black boxes (not so much like Neural Networks but still - it depends on the way they are implemented). I think they are not used very much. I guess there are a few hedge funds out there that use it but all in all they were hyped and then busted. ...

14

I would say in the context of trading in general (for HFT see my comment above) further developments of recurrent neural networks (RNN), e.g. so called historical consistent neural networks (HCNN) together with forecasting ensembles, are state of the art. I published an article on that which will be published this month by Springer Verlag (Zimmermann, ...

14

I unfortunately can't point you to a great book on the exact subject that you're describing. The closest thing for beginners is "Quantitative Trading". It's a reasonable introduction, but I really wouldn't recommend it as a primary source. The author is at best incomplete (if not misleading) on a number of issues. My favorite book at the moment is ...

14

There are few things to consider. Trading moves the price, to minimize market impact and maximize return it is generally optimal to split an order in several child orders. See the Kyle model. Splitting optimally dependents on specific assumptions that you make. The simplest (and first) approach is that of Berstsimas and Lo (Optimal Control of Execution ...

13

I made the switch years ago, and it has been great. I even switched the class I teach from Matlab to Python. Here are some things to consider Others can run your Python code when you share it with them. Matlab has compilers and the like, but they are an extra step you must take since most people do not have Matlab on their desk. Python and its ...

12

I've applied GA to all sorts of things. I had some success in the deterministic world where a pattern actually existed and I knew that some physical structure existed (seismic analysis, vibration analysis, inventory calcs, etc). After I found a GA model that behaved, the real work started....figuring out why it behaved. I also generated a lot of GA ...

11

In a very, very general sense, what Renaissance Technologies does well [and others try to do, many do less well] is understand where the "true" signal is (i.e. where prices should be) and what is noise (i.e. over-/under-reactions by others in the market) in the total signal of market prices. Generally, trading profits are made by taking the opposing ...

11

For "maximum pessimism" you should calculate thus: for longs - enter at the bar high and exit at the bar low on bar following signal bar for shorts - enter at the bar low and exit at the bar high on bar following signal bar I had previously heard this approach to back testing called the "torture test."

11

There are a large range of products that are now being offered as "alternative beta". These try to provide consistent returns in a known systematic bias or strategy, as defined by an index tracking that strategy. ETF's can be a very good source of information on transparent quantitative strategies that have a published track record. See, for example, ...

11

To respond to your questions in order: The formula looks deceptively simple. Does it actually work? That depends on what you mean by "work". Chan spends the rest of the chapter discussing the pitfalls of investing at "full Kelly". Do professionals use it at all? Professionals may maximize geometric growth, but I don't know anyone who does so with ...

10

Just FYI the Reuters product is called NewsScope. The selling point is that they provide a sentiment reading per news item so the user doesn't have to do any NLP. If you have a Reuters sales rep or contact them then they can get you several research/white papers that are interesting. Here are the ones I have been able to find online (my sales rep has ...

10

Rich, you might find this cheatsheet useful on your journey. I was advocating Python over Matlab to a co-worker just minutes ago. I should start by saying that Matlab is a fine piece of software - its documentation is amazing, as are the pdfs that accompany the various toolboxes (as I'm sure you know). However, regarding Python, Brian B brings up many ...

10

HFT seems to be the big money making mystery machine these days. That's not correct. By its very nature, HFT can only produce a limited amount of revenue. The big money makers are still the large hedge funds that charge 2-and-20 on their \$10B worth of assets. There are not too many players there at the moment so markets are not completely ... 10 First of all a very warm welcome to Quantitative Finance Stack Exchange :-) Concerning your question there are some basic points that seem to be unclear. In general "Quantitative Trading" by Ernie Chan is a good starting point for learning about quantitative trading strategies. The problem is of course that in this small book there are many concepts whose ... 10 The only way to find out is to try it! It shouldn't take very long to write some simple code to simulate the computations you plan to do, and run it in a loop. With current versions of Visual Basic (VB.net), performance should be comparable to Java in most cases because the basic technology (compiling to intermediate code and then running a just-in-time ... 10 All .NET languages are perfectly able to compete with the speed of C and even FORTRAN. It all depends on if they are used the correct way. 1) Both Java and .NET have considerable longer startup times than most native app. Therefore, you will have to have the application running and not starting it over and over on request. 2) Memory management is crucial ... 10 An interesting starting point is The Cost of Latency by Moallemi and Saglam. After setting up a simple order execution problem --- in which a trader must chose between a market order and a limit order and guarantee execution over a fixed interval$[0,T]\$, they proceed to derive a (complex) close form solution for the optimal strategy and evaluate the impact ...

9

There's a lot of people here talking about how GAs are empirical, don't have theoretical foundations, are black-boxes, and the like. I beg to differ! There's a whole branch of economics devoted to looking at markets in terms of evolutionary metaphors: Evolutionary Economics! I highly recommend the Dopfer book, The Evolutionary Foundations of Economics, ...

9

Assuming you avoid data-snooping bias and all the potential pitfalls of using the past to predict the future, trusting genetic algorithms to find the "right" solution pretty much boils down to the same bet you make when you actively manage a portfolio, whether quantitatively or discretionary. If you believe in market efficiency then increasing your ...

9

I honestly think that most people who could be able to answer to this question simply won't either because they actually work for Renaissance, or because they work in a top quant hedge fund and they'll keep it a secret. I discussed this topic once during an interview and the guy said "we'll discuss this further if you get the job" lol. About papers, I'm ...

9

One might probably mention Yale's Endowment under David Swensen which generated returns of 13% per annum over the past two decades (as compared to the 8 or 9% average return of college and university endowments). Now, I would not label Swensen's approach to portfolio management with a pure absolute return strategy tag but he definitely uses some insights ...

9

I did some digging and found the following papers - most of them offering quite a distinct perspective compared to classical option pricing theory! Stock Options as Lotteries by Brian H. Boyer et al. (2011) The Efficiency of the Buy-Write Strategy: Evidence from Australia by Tafadzwa Mugwagwa et al. (2010) The following is my favorite: You could do some ...

9

I'll not say how most people do it, but rather how I think most people should do it. You should compare the actual strategy with a number of goes of randomly trading through the time period using the same constraints as the strategy. Basically this is a way of not mixing species of fruit and seeing what the distribution of luck is for the particular fruit ...

8

That's a tough question to answer. The "quant business" is a business. Some quants sell low-grade/low-volatility results, some sell fast-moving/unpredictable results, some sell industry targeted results, etc. It depends on what the buyer wants to buy. There's a market for everything. Haven't we all met people that think they're going to win the ...

8

This is an evergreen. I've been discussing this with many people - without any clear-cut conclusion. The answer and the preferred solution depend on your trading style (e.g. frequency), your skills, the size of the team, and many other factors. For simplicity, I call "Research" the Matlab/R/etc. environments, whereas "Live" refers to the re-programmed ...

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