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Twitter Trading – Downloading Tweets Using Python (Part 2 of 2) | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2012/05/19/twitter-trading-downloading-tweets-using-python-part-2-of-2
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Twitter Trading Downloading Tweets Using Python (Part 2 of 2). May 19, 2012. Previously in Part 1. Code was produced to use tweetstream and download tweets in real time, this part of the series will look at how to store these tweets for future analysis. The tweets will be saved into SqliteDB ( http:/ www.sqlite.org/download.html. 1 twitter...
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February | 2015 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2015/02
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Monthly Archives: February 2015. Hidden Markov Models – Trend Following – Part 4 of 4. February 1, 2015. Part 3 of this series demonstrated how to train a HMM on a toy model, this post will focus on how to actually go about modelling real life data. A trend following strategy will be developed for trading the S&P 500. One of the excellent ...
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Hidden Markov Models – Forward & Viterbi Algorithm Part 2 of 4 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2014/05/26/hidden-markov-models-forward-viterbi-algorithm-part-2-of-4
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Hidden Markov Models Forward & Viterbi Algorithm Part 2 of 4. May 26, 2014. In the previous post the Hidden Markov Model. The forward algorithm calculates the likelihood of the data given the model over all possible. The Viterbi algorithm calculates the likelihood of the data given the model over the single most likely. It is defined as:.
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Hidden Markov Models – Examples In R – Part 3 of 4 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2014/09/07/hidden-markov-models-examples-in-r-part-3-of-4
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Hidden Markov Models Examples In R – Part 3 of 4. September 7, 2014. Method One – Single HMM Each State is a Regime. The credit for this section must go to the fantastic Systematic Investor blog http:/ systematicinvestor.wordpress.com/2012/11/01/regime-detection/. Code for method 1:. BullMarketOne, bearMarket, bullMarketTwo ). Y, nStates =.
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Python Code | Gekko Quant – Quantitative Trading
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Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Category Archives: Python Code. Twitter Trading Downloading Tweets Using Python (Part 2 of 2). May 19, 2012. Previously in Part 1. Code was produced to use tweetstream and download tweets in real time, this part of the series will look at how to store these tweets for future analysis. And Python ( Sqlite Python Docs. 1 twitter sqlite CREAT...
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Trading Papers | Gekko Quant – Quantitative Trading
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Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Category Archives: Trading Papers. Trading Strategies To Exploit Blog, News & Twitter Sentiment (Paper). May 15, 2012. Trading Strategies To Exploit Blog and News Sentiment (Paper). The method has four Parameters:. Sentiment Analysis Period – How many days of previous sentiment data to use? What i like most about the paper is that the asse...
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Hidden Markov Models – Model Description Part 1 of 4 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2014/05/18/hidden-markov-models-model-description-part-1-of-4
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Hidden Markov Models – Model Description Part 1 of 4. May 18, 2014. General Pattern Recognition Framework. A set of features. Are derived from data set. Identified by finding the most likely class given the data. Is unknown, so Bayes’ rule must be used. Since the maximisation does not depend upon. We can ignore it. The terms. Is a vector d...
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Hidden Markov Models – Trend Following – Part 4 of 4 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2015/02/01/hidden-markov-models-trend-following-sharpe-ratio-3-1-part-4-of-4
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Hidden Markov Models – Trend Following – Part 4 of 4. February 1, 2015. Part 3 of this series demonstrated how to train a HMM on a toy model, this post will focus on how to actually go about modelling real life data. A trend following strategy will be developed for trading the S&P 500. One of the excellent properties of HMM is that they al...
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January | 2014 | Gekko Quant – Quantitative Trading
http://gekkoquant.com/2014/01
Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Monthly Archives: January 2014. K-Nearest Neighbour Algo – Find Closest Period in History. January 26, 2014. This post is going to continue on from my last post on the K-nearest algo http:/ gekkoquant.com/2013/12/02/k-nearest-neighbour-algo-fail/. Sharpe ratio: -0.537182. Sharpe ratio: -0.591864. The fast signal lookback used to calculate ...
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Trading Strategy | Gekko Quant – Quantitative Trading
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Gekko Quant Quantitative Trading. Quantitative Trading, Statistical Arbitrage, Machine Learning and Binary Options. Skip to primary content. Skip to secondary content. Category Archives: Trading Strategy. High Probability Credit Spreads – Using Linear Regression Curves. September 29, 2013. Video 1 presents a technique called “linear regression curves” about 10mins in. Linear regression curves aim to solve the problem of the moving average being slow to track the price. See how tightly the blue linear reg...