Does frequency matter for intraday technical trading?

Frömmel, Michael; Lampaert, Kevin

doi:10.1016/j.frl.2016.04.014

Cited by 14 publications

(10 citation statements)

References 34 publications

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“…Also, Kirilenko and Lo (2013) point out that the majority of trades by volume on U.S. exchanges across all financial markets are high-frequency transactions and so high-frequency technical trading must be a popular tool for investors. The literature on high-frequency technical trading generally suggests that there is little profitability from technical trading at high frequency (for instance Neely and Weller 2003;Marshall et al 2008;Frömmel and Lampaert 2016), although Narayan et al (2015) do show significant profits from trading Brazilian, Indian and South African exchange rates on 5 minute frequency data.…”

Section: Introductionmentioning

confidence: 99%

Sampling frequency and the performance of different types of technical trading rules

Hudson

McGroarty

Urquhart

2017

Finance Research Letters

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The predictive ability of technical trading rules has been studied in great detail however many papers group all technical trading rules together into one basket. We argue that there are two main types of technical trading rules, namely rules based on trend-following and mean reversion. Utilising high-frequency commodity ETF data, we show that mean-reversion based rules perform increasingly better as sampling frequencies increase and that conversely the performance of trend-following rules deteriorate at higher-frequencies. These findings are possibly related to noise created by high-frequency traders.

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Section: Introductionmentioning

confidence: 99%

Sampling frequency and the performance of different types of technical trading rules

Hudson

McGroarty

Urquhart

2017

Finance Research Letters

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“…Low positive returns are certainly no reason to get out of the market. Unless a trading strategy is described in detail and applied to real data, any claim of profitability remains unsubstantiated (Frömmel & Lampaert, 2016;Smales, 2016). Fourth, the performance of a very sophisticated procedure that depends on a large number of tuning parameters can only be assessed when it is applied to different datasets.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of current research on stock return predictability

Reschenhofer

Mangat

Zwatz

et al. 2019

Journal of Forecasting

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The results of recent replication studies suggest that false positive findings are a big problem in empirical finance. We contribute to this debate by reviewing a sample of articles dealing with the short-term directional forecasting of the prices of stocks, commodities, and currencies. Screening all relevant articles published in 2016 by one of the 96 journals covered by the Social Sciences Citation Index in the category "Business, Finance," we select only those studies that use easily accessible data of daily or higher frequency. We examine each study in detail, from the selection of the dataset to the interpretation of the results. We also include empirical analyses to illustrate the shortcomings of certain approaches. There are three main findings from our review. First, the number of selected papers is very low, which is surprising even when the strict selection criteria are taken into account. Second, there are hardly any relevant studies that use high-frequency data-despite the hype about financial big data and machine learning. Third, the economic significance of the findings-for example, their usefulness for trading purposes-is questionable. In general, apparently good forecasting performance does not translate into profitability once realistic transaction costs and the effect of data snooping are taken into account. Other typical problems include unsuitable benchmarks, short evaluation periods, and nonoperational trading strategies.

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“…The Japanese candle appears in two colour variants depending on the rising or falling tendency of the price [5]. The trends are further divided into short-term and long-term ones [8][9]. It may occur that the limited trend is bearish but the long-term trend is bullish and the other way around.…”

Section: Literature Researchmentioning

confidence: 99%

“…For the long position, the signal is created when the MA with a shorter period intersects the MA with the longer period from the bottom. For a short position, the signal is generated when an MA with a shorter period intersects an MA with a larger period from above [9].…”

Section: Literature Researchmentioning

confidence: 99%

A Basic Technical Analysis of Shares on the Example of a Specific Company

Horák

Sulek

2021

SHS Web Conf.

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This paper deals with the technical analysis of The Coca-Cola Company (KO) shares. The first signal for the stock price movement was created on the basis of the intersections of moving averages, namely after intersecting the shorter average through the longer average. This signal signifies a drop in the share price. The same signal was generated after comparing the trend of the share price and the trend of the trading volumes. It is these particular trends that have a different direction. Consequently, this is an indicator for a decline in the share price. The last signal created a graphical pattern called symmetric bear triangle which also predicts a drop in the stock price. Only one indicator did not generate a signal for price increase or decrease, namely the RSI with a 14-day period. The examined data collection contains data from 2.1.2015 to 29.4.2020. At the same time, all presented results and predictions are based on the date of April 29, 2020. Finally, the use of the given indicators for different titles, assets or for different types of trade with different lengths is evaluated and proposed. The paper provides suggestions of measures for investors and speculators which should be applied before the start of the analysis.

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Does frequency matter for intraday technical trading?

Cited by 14 publications

References 34 publications

Sampling frequency and the performance of different types of technical trading rules

Sampling frequency and the performance of different types of technical trading rules

Evaluation of current research on stock return predictability

A Basic Technical Analysis of Shares on the Example of a Specific Company

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