A test of futures market disequilibrium using twelve different technical trading systems

Returns from neural network enhanced technical analysis indicator: A study on crude oil futures

“…Even after taking into consideration the transaction costs, the returns for all the NNclose and NNeMA for FCLO, FCO and FCPO are much larger than the passive buy-and-hold control strategy as shown in Table 5. Similar findings by Lukac et al (1988), Brock et al (1992 and Park and Irwin (2009) support the results. To compare the five models, the base prices of $33.00 for FCLO, $27.76 for FSO and RM1766 for FCPO as of at 2/1/2004 are used.…”

“…The estimation techniques employed are as those used in Brock et al (1992), Lukac et al (1988), Gencay and Stengos (1998) and Yao et al (1999). The study tests if one or more of the technical trading rules could possibly be superior in producing greater returns than that of the passive buy-and-hold strategy.…”

“…The purpose of the moving averages tests used by Brock et al (1992), Lukac et al (1988) and Gencay and Stengos (1998) is to ascertain whether the application of fixed moving average trading rules is able to generate higher returns compared to the passive buy-and-hold strategy and, in particular, whether the Neural Network enhanced Moving Average (NNeMA) is able to outperform the most optimized moving average commonly used by Brock et al (1992), Lukac et al (1988) and the market practitioners and the neural network of close prices. The procedure is first, to find the most optimized moving averages for the three oil futures contracts; second, to generate forecast values using back propagation artificial neural network (ANN) from (i) input of close prices and (ii) inputs of close prices and their 20 days moving averages using Matlab; third, to generate appropriate trading signals using the forecasted output.…”

“…The trading techniques are chosen from the commonly used ones as benchmark in Brock et al (1992), Lukac et al (1988), Gencay and Stengos (1998) and Yao et al (1999). The purpose of the moving averages tests used by Brock et al (1992), Lukac et al (1988) and Gencay and Stengos (1998) is to ascertain whether the application of fixed moving average trading rules is able to generate higher returns compared to the passive buy-and-hold strategy and, in particular, whether the Neural Network enhanced Moving Average (NNeMA) is able to outperform the most optimized moving average commonly used by Brock et al (1992), Lukac et al (1988) and the market practitioners and the neural network of close prices.…”

Weak-Form Market Efficiency: Evidence from the Brazilian Stock Market

“…However, since the mid 1980s, there have been numerous empirical studies supporting the predictability and profitability of technical trading rules in stock markets. The origin of this new found interest was from a few influential academic articles by Sweeney (1986), Lukac, Brorsen & Irwin (1988), and Brock, Lakonishok & Lebaron (1992). After these three studies, many academicians have pursued their works and published a myriad of papers in opposition to the efficient market hypothesis by constructing technical trading rules to beat the market rather than using the random walk testing.…”