This is a summary of links featured on Quantocracy on Monday, 03/28/2016. To see our most recent links, visit the Quant Mashup. Read on readers!
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Machine Learning and Its Application in Forex Markets [Quant Insti]In the last post we covered Machine learning (ML) concept in brief. In this post we explain some more ML terms, and then frame rules for a forex strategy using the SVM algorithm in R. To use ML in trading, we start with historical data (stock price/forex data) and add indicators to build a model in R/Python/Java. We then select the right Machine learning algorithm to make the predictions. First,
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Glamour Can Distract Investors [Larry Swedroe]Theres very strong historical evidence to support the existence of a value premium in equity markets. While theres no dispute over the existence of the value premium (value stocks have provided an annual average return 5% higher than growth stocks over the long term), there is much debate over the cause of the difference in returns. In one camp are financial economists who argue that the
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The Internal Bar Strength Indicator [System Trader Success]The internal bar strength or (IBS) is an oscillating indicator which measures the relative position of the close price with respect to the low to high range for the same period. The calculation for Internal Bar Strength is as follows IBS = (Close Low) / (High Low) * 100; For example, on 13/01/2016 the QQQ etf had a high price of $106.23, a low price of $101.74 and a close price of