RSI 2 and Other Oscillators

The 2 period RSI oscillator is a popular indicator of short-term over-bought and over-sold market prices. I was wondering if Synergy could be used to identify models that use a 2 period RSI. By default, the period of an RSI oscillator in Synergy can range from 2 to 50. Assuming the default range is not Read more about RSI 2 and Other Oscillators[…]

S&P 500 Index (SPX) Sentiment Data (StockTwits)

This article takes a quick look at the daily SPX Sentiment Data (StockTwits). The motivation is purely curiosity. There isn’t enough history yet for me to start using data of this nature for building production models. The data can be downloaded for free on this page: https://www.quandl.com/data/PS1/SPX_ST-S-P-500-Index-SPX-Sentiment-Data-StockTwits When you create a Quandl account you get Read more about S&P 500 Index (SPX) Sentiment Data (StockTwits)[…]

SP Rubric Pattern Predictor Using OHLC and Simple Moving Averages

The Rubric Pattern Predictor defines patterns by comparing the levels of input features, evaluates candidate patterns over a trailing modeling period and uses the patterns that have been historically successful walking-forward. The pattern building phase is repeated every n bars. Inspiration for the Rubric Pattern Predictor came from the Adaptrade Price Pattern Strategies and Price Read more about SP Rubric Pattern Predictor Using OHLC and Simple Moving Averages[…]

SP Trend Pullback Dakota 3 System

Trend pullback trading strategies are relatively simple and tend to work across different time frames and on a wide range of securities. We are going to build a Dakota 3 system for the SP futures contract that goes long when a short-term decline occurs in an uptrend and goes short when a short-term rally occurs Read more about SP Trend Pullback Dakota 3 System[…]

K-Step Ahead SVMPredictor Dakota 3 System

We are going to build a Dakota 3 market timing model that predicts the 5 period change in the natural log of the daily SP closing price using support vector machines for k-step ahead modeling. The K-Step Ahead SVMPredictors work like this: A support vector machine is trained to predict the input series 1 time Read more about K-Step Ahead SVMPredictor Dakota 3 System[…]