Stock market trading rule discovery using technical charting heuristics

Abstract

In this case study in knowledge engineering and data mining, we implement a recognizer for two variations of the`bull¯ag' technical charting heuristic and use this recognizer to discover trading rules on the NYSE Composite Index. Out-of-sample results indicate that these rules are effective. q

Stock market trading rule based on pattern recognition and technical analysis: Forecasting the DJIA index with intraday data

“…To the best of our knowledge, the works by Leigh, Modani et al (2002), Leigh, Paz et al (2002) and are the first ones to deal with the graphical recognition of this kind of pattern and to introduce a trading rule linked to it. In order to identify the pattern, we use a 10x10 grid of weights, like the one that figure 1 shows, which allows to recognize the bull flag pattern .…”

“…While Leigh, Modani et al (2002), Leigh, Paz et al (2002), y Chan (2007, 2009) use the consolidation and breakout version, we explore the breakout and consolidation approach. The second difference lies in the range of weights considered and in the distribution of the weights around the matrix: the weights configuration is a key point in our proposal.…”

“…Most of the literature considers a holding period of candlesticks. The value will change according to different authors: = 6 in Lee and Jo (1999), = 20 in and = 100 in Leigh, Modani et al (2002). In order to increase the solidity of the results and mitigate the data snooping effect some authors propose to consider a group of values for instead of an only one:…”

Rethinking construction expertise with posthumanism

“…Initiated by the seminal work of Edward Feigenbaum, 'expert systems' have been developed: rule-based computer programmes designed to solve problems more effectively and efficiently than humans (Feigenbaum, 1992). Expert systems have been proposed across all manner of domains, from medicine (Adler et al 2014) to finance (Leigh et al 2002), and construction (Alkass et al 1996;Okoroh and Torrance, 1999). However, as the philosophers Dreyfus and Dreyfus (2005) explain, 'although computers are faster and more accurate than people in applying rules, master-level performance has remained out of reach' (p781).…”

CAST: Using neural networks to improve trading systems based on technical analysis by means of the RSI financial indicator

“…One of the tools for this financial practice is technical analysis, also known as ''charting''. According to Leigh, Modani, Purvis, and Roberts (2002), Charles Dow developed the original Dow Theory for technical analysis in 1884 revisited by Edwards and Magee (1997) more than a century earlier. Technical analysis studies historical data surrounding price and volume movements of the stock by using charts as the primary tool to fore cast future price movements (Murphy, 1999).…”