This is a summary of links featured on Quantocracy on Monday, 09/26/2016. To see our most recent links, visit the Quant Mashup. Read on readers!
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Kalman Filter-Based Pairs Trading Strategy In QSTrader [Quant Start]Previously on QuantStart we have considered the mathematical underpinnings of State Space Models and Kalman Filters, as well as the application of the pykalman library to a pair of ETFs to dynamically adjust a hedge ratio as a basis for a mean reverting trading strategy. In this article we will discuss a trading strategy originally due to Ernest Chan (2012)[1] and tested by Aidan O'Mahony
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Alternate Trading Days: An Important Analytical Tool [Allocate Smartly]Many of the tactical asset allocation strategies that we track are designed to only trade at the end of the month. When tracking these strategies for members however, we show the results of trading on other days of the month as well. We dont do this to show off our backtesting prowess; its an important analytical tool for understanding more about a strategy and for sniffing out potential
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Step One In Building An Intraday Trading System [System Trader Success]If you have been reading System Trader Success for a while youre probably familiar with how I develop trading systems. The very first step is to come up with a simple idea to act as the seed or core of your trading system. I call this your key concept. This key concept is a simple observation of market behavior. This observation does not need to be complex at all. In fact, they are often very
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Is the Value Premium Disappearing (h/t @AbnormalReturns)? [A Wealth of Common Sense]The value premium has been talked about in investment circles going all the way back to the 1934 release of Benjamin Grahams Security Analysis. At its core value investing relies on buying undervalued securities, something every investor can or should be able to intuitively understand. You buy stocks for less than their fundamental value, wait until that value is recognized by the market,
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High Yield Bond ETFs: Liquidity Time Bombs? [Flirting with Models]Many articles expounding upon the risks of ETFs that invest in illiquid assets (high yield bonds, bank loans, emerging markets, etc.) have been published in recent years. While there are additional risks inherent to these ETFs, the ETF structure provides an additional layer of liquidity that is not available when trading directly in the underlying securities. With the majority of trades in an ETF,
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Better Model Selection for Evolving Models [Quintuitive]For quite some time now I have been using Rs caret package to choose the model for forecasting time series data. The approach is satisfactory as long as the model is not an evolving model (i.e. is not re-trained), or if it evolves rarely. If the model is re-trained often the approach has significant computational overhead. Interestingly enough, an alternative, more efficient approach allows
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Webinar: Contemporary Portfolio Optimization Modeling with R [Interactive Brokers]In the first part of this webinar, we will review the most common ways to conduct the task of portfolio optimization with R. After this introduction, we will address some remarks on the modeling of portfolio problems. In the second part, we will demonstrate a revolutionary way to model and solve portfolio optimization problems using R. The basic idea of conceptualizing a new way to model portfolio