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2

If you have a vector of weights $w=(w_1,\ldots,w_n)^T$ then $(1,\ldots,1)* w = \sum_{i=1}^n w_i$ thus a sum condtion can be formulated by multiplication with a row of ones. A $\le$ can be put into an $\ge$ by multiplying with $(-1)$ and if you have to put all your constraints into on $A$ then you usually stack all the row vectors together. In your case the ...


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I agree with the previous statement that this is more stats related than anything else (it's not quant finance). But it's still a great question! This sounds awfully similar to linear regression testing with multiple predictor variables; you're basically doing it in a "monte carlo" fashion :) Depending on how your data is formatted, you could enter it into ...


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Such an approach is done by the systemic investor blogger in his blog Time Series Matching with Dynamic Time Warping.


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Others may have different views, but I've tried applying Kelly formula/fractional Kelly strategies to capital allocation, and find it rather unpractical and risky. I would honestly suggest a three-tier optimization framework that I am myself adopting: Assuming you have $M$ number of models covering multiple instruments and strategies. Your goal is to pick ...


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Bayesian Odds Ratios can be used to compare models and allocate wealth to various models based on the relative probability that each particular model is "best." You could begin to look into it more on the wiki site.


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Choose the most robust (or insensitive) strategy. You are right that the best strategy might be overfit. So look at your parameter space and focus on the area where profitability, for example, changes least when you change the parameter value. Here is a 1D example: The most profitable strategy is that single point that unfortunately leaves no room for ...


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Have a look at my paper http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2259133 I checked Kelly formula and found the answer from it is exactly as Markowitz's theory. >Thus, most issues on mean-variance theory (e.g. noise of estimation for mean and >variance) applies here. Kelly is not exactly as Markowitz's theory but they are indeed closely ...


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The formula looks deceptively simple. Does it actually work? The formula is a correct approximation if the asset in question is not too volatile. It works good if a) you exactly know the parameters mu and sigma b) if you can commit a lot of trade In practice the parameters are often very roughly estimated. The rule of thumb is to reduce mu and ...


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Bootstrap is a very interesting method to obtain the variance of any estimator. This means you can rely on it to obtain de variance of your Sharpe ratio (SR), but what you try to do is to deduce something (the probability to be positive) from the distribution of it. From a methodological viewpoint, if you boostrap your SR a "standard" way (i.e. ...


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Problematic is already the use of the words "conservative" and "minimum". There is no absolute minimum, worst case (in continuous models, i.e. reality), as things can always get worse than they have ever been before and than anybody anticipated. Depending on where one defines the minimum, there can always be an even more conservative investor in the market. ...


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this is just theory, don't take it as serious, theory it's just take on approximation of reality and in this case not good one, people trade to check that strategy is profitable or trade because they think it will profitable, besides that you have many other spaces on what people compete with each other in this game


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The formation of asset price bubbles, such as the recent US housing market bubble, is perhaps the clearest indication that markets are not efficient. Hundreds of bubbles have been documented for all kinds of traded assets; see the tulip mania for an extreme case. Many practitioners also routinely use trading strategies such as momentum or reversion to the ...


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It's unclear what type of trading you are referring to (day trading sort of?). Also I'm not familiar with the aforementioned paradox. However, I think it's weird to say that you can't make money from trading, the semi-strong (strong) from of the EMH only states that the current share price incorporates all publicly (and non-publicly) available information. ...


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Making money is not the only reasonable objective to trading. Another common reason is to manage/reallocate risk. For example, this is exactly the objective of liability-driven-investors, such as pension funds. They're specifically trying to match durations of their liabilities. It doesn't matter if pension fund managers believe there are no inefficiencies ...


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There is a general principle that the answer to "Would this extremely simple strategy make money?" is "No". This is the "no free lunch" or "no arbitrage" rule. It isn't exactly a physical law, but it is a pretty decent approximation of reality. (A more nuanced version is, maybe it can make some money, but only in proportion to the difficulty, risk, and ...


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I just checked for S&P 500 from Yahoo Finance. From Jan 3rd, 2005 to April 14th, 2014 (2336 trading days), for 2014 days High is greater than Open and 322 days they are equal. Assume no friction. Suppose you are an almighty person to catch Highs on your trade, then in one day you will make %0.00675 on average. That is your ceiling. Now add friction ...


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The open is also almost never the low, so you could aswell short the asset. But in both cases, you have only marginal profit with potentially unbounded losses if it does not cross tick+spread. E.g. see this change in EUR/USD exchange rate: http://www.ariva.de/euro-dollar-kurs/chart?layout=neu&boerse_id=36&t=week This event would have created a ...


4

Like Good Guy Mike says in his answer, you have to account for transaction costs. But change "one tick" to "transaction costs + 1 tick" and you still have a question. One issue is that while the open may not usually be the day's high, you'll have a few catastrophic losers that you hold all day, and they may be enough to wipe out your small steady gains. If ...


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Because you have to take transaction costs into account.



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