Data-driven stock trading in financial markets: an adaptive control approach

Abbracciavento, Francesco; Formentin, Simone; Savaresi, Sergio M.

doi:10.1080/00207179.2020.1837395

Cited by 7 publications

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kyriakou et al (2020) examines how feedback trading tactics affect three simulated real estate portfolios to establish long-term market volatility. Consequently, it is possible to assert that neither volatility-based indicator is capable of producing results that are satisfactory for intraday or short-term trading (Abbracciavento et al, 2022).…”

mentioning

confidence: 99%

Quantifying the Volatility of Stock Price Changes in the Indian Market Using the Moving Average Envelope and Bollinger Bands

Chakrabarty,

Majumdar,

Chatterjee

2024

IJIE

View full text Add to dashboard Cite

A trading system in any stock market is built on long-term, intermediate-term, and short-term indicators. Some ‘lagging’ indicators, such as the simple and exponential moving averages, can be used to determine the direction of a medium- to long-term trend. Some ‘leading’ oscillators, on the other hand, can tell a trader whether or not a trend is losing momentum. This paper examines how well moving average envelopes and Bollinger Bands measure stock price volatility, and how useful these technical analysis tools are for short-term horizons. The paper then attempts to evaluate the speed of these indicators in order to explain the sensitivity and response time of data collected from a secondary survey in the Indian capital market. The article concludes that moving average envelopes outperform Bollinger Bands in real trading settings, since technical trading rules are generally designed for short-term investments. Bollinger Bands can detect abrupt price fluctuations, however they are not more effective than moving average envelopes to measure profitability.

show abstract

mentioning

confidence: 99%