Adaptive use of technical indicators for the prediction of intra-day stock prices

Tanaka‐Yamawaki, Mieko; Tokuoka, Seiji

doi:10.1016/j.physa.2007.04.126

Cited by 63 publications

(27 citation statements)

References 2 publications

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“…Allen and Karjalainen [3] also conclude that technical trading rules do not generate abnormal profits over the buy-and-hold strategy, especially after deducting transaction fees. More recently, Tanaka-Yamawaki and Tokuoka [4] also report that frequently used technical indicators, such as Moving Average Convergence-Divergence (MACD) and Relative Strength Index (RSI), are not effective in forecasting various selected intra-day US stock prices.…”

Section: Introductionmentioning

confidence: 99%

Revisiting the Performance of MACD and RSI Oscillators

Chong

Liew

2014

JRFM

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Chong and Ng (2008) find that the Moving Average Convergence-Divergence (MACD) and Relative Strength Index (RSI) rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD (12,26,0) and RSI(21,50) rules consistently generate significant abnormal returns in the Milan Comit General and the S&P/TSX Composite Index. In addition, the RSI(14,30/70) rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors' belief in these two technical indicators in different developed markets.

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Section: Introductionmentioning

confidence: 99%

Revisiting the Performance of MACD and RSI Oscillators

Chong

Liew

2014

JRFM

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“…The assumption behind its utilisation in the investment industry is that above-average risk-adjusted returns are possible when using past time series of stock information, and Clarke et al [15] show that this practice is wide-spread in the investment industry. A meta-analysis by [20] also demonstrates that the majority of studies on the topic of technical analysis report a profitability that undercuts the arguments of the efficient market hypothesis [21]. Apart from moving average methods, perceived patterns are among the other, less investigated methods that are used by technical analysts, for example the so-called "head-and-shoulders pattern".…”

Section: Predicting Stock Returnsmentioning

confidence: 99%

Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning

Moews

Ibikunle

2020

Physica A: Statistical Mechanics and its Applications

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Standard methods and theories in finance can be ill-equipped to capture highly non-linear interactions in financial prediction problems based on large-scale datasets, with deep learning offering a way to gain insights into correlations in markets as complex systems. In this paper, we apply deep learning to econometrically constructed gradients to learn and exploit lagged correlations among S&P 500 stocks to compare model behaviour in stable and volatile market environments, and under the exclusion of target stock information for predictions. In order to measure the effect of time horizons, we predict intraday and daily stock price movements in varying interval lengths and gauge the complexity of the problem at hand with a modification of our model architecture. Our findings show that accuracies, while remaining significant and demonstrating the exploitability of lagged correlations in stock markets, decrease with shorter prediction horizons. We discuss implications for modern finance theory and our work's applicability as an investigative tool for portfolio managers. Lastly, we show that our model's performance is consistent in volatile markets by exposing it to the environment of the recent financial crisis of 2007/2008.

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“…MACD; Divergências; Ações; Investimentos; Análise Técnica. TOKUOKA, 2007). A partir disso, por repetir padrões passados, pode ser desenvolvida uma familiaridade com o movimento e o comportamento dos preços, reconhecendo situações que possam ocorrer no futuro (LO;MAMAYSKY;WANG, 2000).…”

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Uma Estratégia de Investimento Baseada na Divergência do Indicador MACD

Martins

Rodrigues

2018

RACEF

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This paper presents an investment strategy using the divergence pattern of the Moving Average Convergence -Divergence (MACD) Technical Analysis indicator. This pattern indicates trend reversals, signaling buying and selling times. A strategy based on the MACD indicator has been developed and applied to several historical US stock price series. In addition, the strategy was applied in a stock portfolio composed of the companies with the highest trading volume. These tests considered the period from 2003 to 2013. In most cases, positive and superior returns were obtained in comparison with the main stock market indices from the USA. It can be concluded, therefore, that the divergence pattern of the MACD indicator was efficient in considering reversals of stock price trends in the period considered.

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Adaptive use of technical indicators for the prediction of intra-day stock prices

Cited by 63 publications

References 2 publications

Revisiting the Performance of MACD and RSI Oscillators

Revisiting the Performance of MACD and RSI Oscillators

Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning

Uma Estratégia de Investimento Baseada na Divergência do Indicador MACD

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