ABSTRACT In this paper a hybrid genetic algorithm–support vector regression (GA‐SVR) model in economic forecasting and macroeconomic variable selection is introduced. The proposed algorithm is applied to the task of forecasting US inflation and unemployment. GA‐SVR genetically optimizes...

This paper attempts to investigate if adopting accurate forecasts from Neural Network (NN) models can lead to statistical and economically significant benefits in portfolio management decisions. In order to achieve that, three NNs, namely the Multi-Layer Perceptron (MLP), Recurrent Neural...

We investigate the performance of more than 21,000 technical trading rules on 12 categorical and country-specific markets over the 2004-2015 study period. For this purpose, we apply a discrete false discovery rate approach in more than 240,000 hypotheses and examine the profitability,...

In this study, the profitability of technical analysis and Bayesian Statistics in trading the EUR/USD, GBP/USD, and USD/JPY exchange rates are examined. For this purpose, seven thousand eight hundred forty-six technical rules are generated and their profitability is assessed through a novel data...

The financial technology revolution is a reality, as the financial world is gradually transforming into a digital domain of high-volume information and high-speed data transformation and processing. The more this transformation takes place, the more consumer and investor behaviour shifts towards...

This paper uses five pairs trading strategies to conduct in-sample training and backtesting on 35 commodities in the major commodity markets from 1980 to 2018. The Distance Method (DM) and the Co-integration Approach (CA) are used for pairs formation. The Simple Thresholds (ST) strategy, Genetic...

Activating self-scheduling workers on on-demand platforms when services are most needed is challenging because of a lack of cooperation between workers. To align workers' interests with the platform's profit-driven goals, various ride-sharing and food delivery platforms have recently embraced...