Sequential smoothing for turning point detection with application to financial decisions

Grillenzoni, Carlo

doi:10.1002/asmb.1945

Cited by 4 publications

(3 citation statements)

References 24 publications

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“…Yet, an exponential moving average (EMA)-based trading system is considered more adaptive because EMA puts more weight on recent prices while putting fewer weights on earlier days (Huang et al , 2009; Kayal, 2010; Zhu and Wang, 2010). In this regard, Grillenzoni (2014) evaluated the ability of sequential smoothing methods to detect TPs in the financial time series. His novel idea was to evaluate the effectiveness of smoothing and alarm coefficients on the profitability of the detected trading strategy.…”

Section: Turning Points (Tps) Detection Methodsmentioning

confidence: 99%

A binary integer programming (BIP) model for optimal financial turning points detection

Yazdani

Khashei

Hejazi

2022

JM2

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Purpose This paper aims to detect the most profitable, i.e. optimal turning points (TPs), from the history of time series using a binary integer programming (BIP) model. TPs prediction problem is one of the most popular yet challenging topics in financial planning. Predicting profitable TPs results in earning profit by offering the opportunity to buy at low and selling at high. TPs detected from the history of time series will be used as the prediction model’s input. According to the literature, the predicted TPs’ profitability depends on the detected TPs’ profitability. Therefore, research for improving the profitability of detection methods has been never given up. Nevertheless, to the best of our knowledge, none of the existing methods can detect the optimal TPs. Design/methodology/approach The objective function of our model maximizes the profit of adopting all the trading strategies. The decision variables represent whether or not to detect the breakpoints as TPs. The assumptions of the model are as follows. Short-selling is possible. The time value for the money is not considered. Detection of consecutive buying (selling) TPs is not possible. Findings Empirical results with 20 data sets from Shanghai Stock Exchange indicate that the model detects the optimal TPs. Originality/value The proposed model, in contrast to the other methods, can detect the optimal TPs. Additionally, the proposed model, in contrast to the other methods, requires transaction cost as its only input parameter. This advantage reduces the process’ calculations.

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Section: Turning Points (Tps) Detection Methodsmentioning

confidence: 99%

A binary integer programming (BIP) model for optimal financial turning points detection

Yazdani

Khashei

Hejazi

2022

JM2

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“…are natural tools for nonparametric turning point identification since they filter out the random elements of the series and allow the trend component to be monitored (see also ref. for a review). Among the many alternatives, the most common method used by financial analysts, because of its simplicity and flexibility, is known as the MAC.…”

Section: A Review Of Turning Point Detection Methodsmentioning

confidence: 99%

Online detection of financial time series peaks and troughs: A probability‐based approach*

Bramante

Facchinetti

Zappa

2019

Statistical Analysis

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The problem related to the identification of a change in time series trajectories plays a crucial role in many contexts. In this paper, we propose a flexible and computationally efficient procedure for turning point identification based on hypothesis testing applied to the difference between two consecutive slopes in a rolling regression framework. Along with the description of the methodology, to measure the performance of the method we have applied it to the S&P 500 Stock Index and its subsector indices. By using an in‐sample/out‐of‐sample approach we compare results with the profit/losses we could obtain by using the moving average crossover strategy. Results show that the operating signals obtained by our proposal may better enable financial analysts to make profitable decisions. Finally we present an extensive simulation study to show the weaknesses and strengths of the proposal under different expected returns and volatility scenarios.

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“…Turning point analysis has been widely employed in economics to identify statistically meaningful changes in time series data. There are numerous approaches to turning point analysis, which can be grouped into smoothing, regression, and statistical approaches (17). In traffic safety fields, a couple of recent studies used a turning point analysis to evaluate safety data.…”

Section: Evaluating Safety Performance Of Climbing Lane Configurations On South Korean Expresswaysmentioning

confidence: 99%

Evaluating Safety Performance of Climbing Lane Configurations on South Korean Expressways

Shim

Jang

Park

et al. 2016

Transportation Research Record: Journal of the Transportation R

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This study evaluated the safety performance of two types of climbing lane configurations—pocket and overtaking—that are implemented on South Korean expressways. For the evaluation, empirical Bayes (EB) and turning point analyses were sequentially applied to compare crash occurrences before and after the configuration change from pocket to overtaking types on 30 climbing lanes. First, the EB analysis with a meta-analysis indicated that the overall safety performance was not significantly degraded after the configuration conversion. However, because some sites were associated with substantial increases in crash occurrences, 11 sites were identified with crashes above the upper bound of a confidence interval estimated from the meta-analysis. A turning point analysis was applied to those sites to validate whether the increase in crash occurrences and the configuration conversions were consistent in the temporal trend. The results show that changes in crash occurrence at three study sites did not coincide with the configuration change, suggesting no evidence for causality. This implies that in a comparative analysis, evaluation of time series of crash occurrences is important, in addition to a comparison of crash frequencies before and after the implementation of roadway facilities. This study suggests that the developed method can be used to evaluate the safety performance of implementing a roadway facility and for selecting sites where the facility degraded the safety performance and required further evaluation by field engineers.

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Sequential smoothing for turning point detection with application to financial decisions

Cited by 4 publications

References 24 publications

A binary integer programming (BIP) model for optimal financial turning points detection

A binary integer programming (BIP) model for optimal financial turning points detection

Online detection of financial time series peaks and troughs: A probability‐based approach*

Evaluating Safety Performance of Climbing Lane Configurations on South Korean Expressways

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