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I am not sure Dark Pools (DP) have been created to avoid "market manipulation". They have been created by firms because they found an advantage to create them (see Market Microstructure in Practice, L and Laruelle Eds.). The main reasons have been: spare market fees, for DP created by brokers (like UBS MTF); spare market impact, for block pools (like ...


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A public order book gives traders information not only on the current price of a security, but also the volume and structure of the entire supply and demand schedule. Such information can be used for arbitrage and market manipulation strategies in various ways: Spoofing: Inserting a large limit order as an apparent buy or sell signal which is canceled any ...


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Your source is not particularly clear about why what they're doing is a Z-score. To give some background, what they're doing is calculating $$\frac{R-\mu_{R}}{\sigma_{R}}$$ where R is the number of runs and the mean and standard deviation are of the number of runs. It's really more of a test statistic than a Z-score per se. The denominator in their formula ...


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Firstly, I suggest you to use more recognized source to study and compute quantitative finance model or indicators; in such case, for instance, you could take as example the following paper as reference. Precisely there, the authors describe some common errors that one can do in computing the Sortino ratio; although surely you did not do any of them, ...


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I don't know if there is a standard way of solving the problem, but I solve it thus: Strategy A bought for $C_a$ dollars and sold for $S_a$ dollars for a result of $R_a = S_a - C_a$ over $T_a$ days. Strategy B bought for $C_b$ dollars and sold for $S_b$ dollars for a result of $R_b = S_b - C_b$ over $T_b$ days. Where $C_a$ and $C_b$ is the total sum of ...


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In trading you need to make a lot of simple computation of a very large flow of data. FPGA are perfect that for. It is typically FPGA that will host marketfeed handler (see NOVASPARKS website, or ACCELLIZE) ; analytics computations ; risk computation (see ULLINK solution for instance). For more, this generic article is not that bad: Introducing ...


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FPGA's are used to run the latency sensitive HFT strategies. They can also be used solely for parsing whatever protocol is in use (FIX, ITCH, etc..) and routing the decoded objects to a CPU for number crunching. They can of course be used for anything else but these two uses are what is most common now.


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I think the problem is not that you optimize a wrong criterion, but the trading strategy itself. Compare this to testing a hypothesis: if you reject at p-value of 1% then the proportion of true discoveries among all discoveries is, say, 70% (high "expectancy"). If you reject at 10% then the true discovery proportion is 40% (lower "expectancy"), but you make ...


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Use your total wealth allocated to the trades as denominator. Total wealth allocated would include all collateral. In this way you (or your broker) make sure that the denominator is always positive. Presumably this would also reflect what you really want to track. The only problem that remains is what amount of your wealth needs to be allocated. But this is ...


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I think the best choice for technical analysis with node is node-talib, a wrapper around TA-Lib. We're using it for some projects and it works ok so far. Here's a list of the indicators you get out of the box: AD Chaikin A/D Line ADOSC Chaikin A/D Oscillator ADX Average Directional Movement Index ADXR ...


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I am using NodeJS for a similar project. There's not a ton of packages on NPM for finance and stocks, so I wrote my own, that might help you get started: Fetching historical stock data, including intraday: https://www.npmjs.org/package/node-activetick Charting, analysing, forecasting the data: https://www.npmjs.org/package/timeseries-analysis You can ...


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Cloud9Trader uses Node.js on the back end and JavaScript across its technology stack, including for writing the trading algorithms themselves. https://www.cloud9trader.com



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