Forecasting directional changes in the FX markets

Most of existing studies sample markets' prices as time series when developing models to predict market's trend. Directional Changes (DC) is an approach to summarize market prices other than time series. DC marks the market as downtrend or uptrend based on the magnitude of prices changes. In this paper we address the problem of forecasting trend's direction in the foreign exchange (FX) market under the DC framework. In particularly we aim to answer the question of whether the current trend will continue for a specific percentage before the trend ends. We propose one single independent variable to make the forecast. We assess the accuracy of our approach using three currency pairs in the FX market; namely EUR/CHF, GBP/CHF, and USD/JPY. The experimental results show that the accuracy of the proposed forecasting model is very good; in some cases, forecasting accuracy was over 80%. However, under particular settings the accuracy may not outperform dummy prediction. The results confirm that directional changes are predictable, and the identified independent variable is useful for forecasting under the DC framework

TSFDC: A Trading strategy based on forecasting directional change

Directional Change (DC) is a technique to summarize price movements in a financial market. According to the DC concept, data is sampled only when the magnitude of price change is significant according to the investor. In this paper, we develop a contrarian trading strategy named TSFDC. TSFDC is based on a forecasting model which aims to predict the change of the direction of market’s trend under the DC context. We examine the profitability, risk and risk-adjusted return of TSFDC in the FX market using eight currency pairs. We argue that TSFDC outperforms another DC-based trading strategy

Intelligent Dynamic Backlash Agent: A Trading Strategy Based on the Directional Change Framework

The Directional Changes (DC) framework is an approach to summarize price movement in financial time series. Some studies have tried to develop trading strategies based on the DC framework. Dynamic Backlash Agent (DBA) is a trading strategy that has been developed based on the DC framework. Despite the promising results of DBA, DBA employed neither an order size management nor risk management components. In this paper, we present an improved version of DBA named Intelligent DBA (IDBA). IDBA overcomes the weaknesses of DBA as it embraces an original order size management and risk management modules. We examine the performance of IDBA in the forex market. The results suggest that IDBA can provide significantly greater returns than DBA. The results also show that the IDBA outperforms another DC-based trading strategy and that it can generate annualized returns of about 30% after deducting the bid and ask spread (but not the transaction costs

Developing trading strategies under the Directional Changes framework, with application in the FX Market

Directional Changes (DC) is a framework for studying price movements. Many studies have reported that the DC framework is useful in analysing financial markets. Other studies have suggested that, theoretically, a trading strategy that exploits the full promise of the DC framework could be astonishingly profitable. However, such a strategy is yet to be discovered. In this thesis, we explore, and consequently provide proof of, the usefulness of the DC framework as the basis of a profitable trading strategy. Existing trading strategies can be categorised into two groups: the first comprising those that rely on forecasting models; the second comprising all other strategies. In line with existing research, this thesis develops two trading strategies: the first relies on forecasting Directional Changes in order to decide when to trade; whereas the second strategy, whilst based on the DC framework, uses no forecasting models at all. This thesis comprises three original research elements: 1. We formalize the problem of forecasting the change of a trend’s direction under the DC framework. We propose a solution for the defined forecasting problem. Our solution includes discovering a novel indicator, which is based on the DC framework. 2. We develop the first trading strategy that relies on the forecasting approach established above (Point 1) to decide when to trade. 3. We develop a second trading strategy which does not rely on any forecasting model. This is trading strategy employs a DC-based procedure to examine historical prices in order to discover profitable trading rules. We examine the performance of these two trading strategies in the foreign exchange market. The results indicate that both can be profitable and that both outperform other DC-based trading strategies. The results additionally suggest that none of these two trading strategies outperforms the other in terms of profitability and risk simultaneously