Financial volatility trading using a self-organising neural-fuzzy semantic network and option straddle-based approach

By Whye Loon Tung, Hiok Chai Quek. 2010

50 citations recorded by the source corpus.

Research highlights ► A straddle trading framework based on eFSM neural-fuzzy model and MACD principle. ► eFSM dynamically models and forecasts the volatility trends of the Hang Seng Index. ► MACD generates timely trading signals using projected volatility trends from eFSM. ► Straddles are bought and sold based on the MACD signals. ► Trading framework achieves significantly higher return than time deposit account.

Subfields: Economics and Econometrics, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Sercan Karaoglu
2. Ugur Arpaci
3. Serkan Ayvaz
4. Omer Berat Sezer
5. A. Ozbayoglu
6. M. Ugur Gudelek

In Management Science and Operations Research

1. Sercan Karaoglu
2. Ugur Arpaci
3. Serkan Ayvaz
4. M. Ugur Gudelek
5. Omer Berat Sezer
6. A. Ozbayoglu

Citations in the corpus

• A Deep Learning Approach for Optimization of Systematic Signal Detection in Financial Trading Systems with Big Data (2017, background): “Recently, there have been many studies investigating Artificial Neural Network (ANN) techniques in various context to improve the accuracy of trading decision support systems [1]–[5].”