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Stage one of determining the sample. Specifying the ticker symbols listed on the TSE for 13 consecutive years
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Following the recent efforts made to achieve a predictable capital market, this study attempted to explore the interlocking relationships between the stock returns of companies listed on Tehran stock exchange (TSE). For that purpose, data concerning 36 industry classes between 2000 and 2013 were examined through clustering and association rule. Pre...
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Citations
... Analiz sonuçları, FP-Growth algoritmasıyla elde edilen birliktelik kurallarının Apriori algoritmasına göre daha olumlu sonuçlar verdiğini göstermektedir. Masum (2019) Hernández vd. (2021) çalışmalarında kripto paraların birlikte hareketlerini veri madenciliği yöntemi ile analiz etmişlerdir. ...
Emtia piyasaları küresel ekonomide kilit bir rol oynamaktadır. Emtialar hem gelişmiş hem de gelişmekte olan ekonomilerin endüstriyel süreçleri için vazgeçilmez varlıklardır. Emtia piyasalarının finansallaşması ile birlikte, emtia endekslerine yapılan yatırımlar hızla artmış ve sundukları çeşitlendirme fırsatları nedeniyle küresel yatırımcıların ilgisini çekmeye başlamıştır. Dolayısıyla emtialar, yatırımları çeşitlendirmek ve enflasyona karşı korunmak için alternatif bir yol olarak görülmüştür. Bu nedenle yatırımcıların bir borsanın düşüşü veya yükselişi sonrasında diğer borsaların veya finansal varlıkların hangi yöne doğru hareket edeceğini öngörmesi, hızlı ve etkili kararlar almasında kritik öneme sahiptir. Bu çalışmada 20 emtianın 01.01.2010-01.08.2023 tarihleri arasında 3216 işlem günündeki hareketleri veri madenciliği yöntemlerinden birliktelik kuralı ile analiz edilmiştir. Çalışmada birliktelik kuralı analizleri, Apriori ve FP-Growth algoritmaları kullanılarak gerçekleştirilmiştir. Hem Apriori hem de FP-Growth algoritmaları ile üretilen birliktelik kurallarının tümünde Brent petrolün diğer emtialara eşlik ettiği gözlemlenmiştir. Bu sonuç, Brent petrol fiyatlarının yukarı veya aşağı yönde hareketinin, Brent petrol fiyatlarını yakından takip eden yatırımcılara, karar vericilere ve politika yapıcılara, diğer emtiaların hareketi ile ilgili yol gösterici olabileceğini göstermektedir. Petrolün ekonomik sistemi etkileyen stratejik bir enerji kaynağı olduğu gerçeği göz önüne alındığında, bu sonuç şaşırtıcı değildir.
... These have applications in the marketing, finance, and retail sectors and are beneficial for figuring out associations between attributes. Applications of association rules include prediction of stock market using financial news (Umbarkar and Nandgaonkar 2015), stock market prediction (Lu et al. 1998), Co-Movement prediction of company's stock prices (Arafah and Mukhlash 2015), prediction of association between stock returns of companies (Masum 2019), stock market trend prediction (Argiddi and Apte 2012), forecasting changes in stock price index (Hoon and Sohn 2011) and prediction of relationship between different global stock indices (Kartal et al. 2022). A study by Liao et al. 2008 also implemented aprioribased association rule to examine the stock market investment issues in the Taiwan stock market. ...
Present study explores the efficacy/performance of association rules for prediction of global stock indices. Global stock indices data for the last 12 years are used to develop the prediction models. The data consists of several technical indicators. Technical indicators were converted to categorical variables and rules were extracted using association rules. The performance of mined rules was tested for global stock indices considered in this study. Based on the findings of the study, it can be concluded that association rules have potential to provide profitable returns with a fair degree of model parsimony. The outcome of the study indicate that Stochastic Oscillator %K%D, relative strength index (RSI), Disparity 5 Days and Disparity 10 Days are the common market signal sources across all stock indices. Along with these, investors can make decisions using additional indications from rate of change (ROC), commodity channel index (CCI) and Momentum. Association rules can be used for profitable decision making with limited number of technical indicators. Limited number of technical indicators are easy to handle even for smaller retail investors. Trading decisions made on the basis of mined association rule were able to comprehensively beat buy-and-hold return for the selected indices included in the study.
... As a result of the analysis, they established rules at a minimum support level of 0.1, 0.07 and 0.06 and found that the increase in certain stocks caused increases and decreases over other stocks. Masum (2019) has examined the co-movement of the stocks of 36 companies listed on the Tehran stock market index. In total, 249,061 records are tested by association analysis. ...
Abstract
Purpose: This study aims to provide preliminary information to the investor by determining which indices co-movement, with the data mining method.
Design/methodology/approach: In this context, datasets containing daily opening and closing prices between 2001-2019 have been created for 11 stock market indexes in the world. The association rule algorithm, one of the data mining techniques, is used in the analysis of the data.
Findings: It is observed that the US stock market indices take part in the highest confidence levels between association rules. XU100 stock index co-movement with both the European stock market indices and the US stock indexes. In addition, the HSI stock index (Hong Kong) takes part in the association rules of all stock market indices.
Originality: The important issue for datasets is that the opening /closing values of the same day or the previous day are taken into account according to the open or closed status of other stock market indices by taking the opening time of the stock exchange index to be created. Therefore, data sets are arranged for each stock market index, separately. As a result of this data set arranging process, it is possible to found out co-movements of the stock market indexes. It is proof that the world stock indices have co-movement and this continues as a cycle.
... Processing big data presents a challenge to existing computation software and hardware (Yang and Fong 2015). Thus, this paper proposes a model to explore big data for discovering association rules using association rule mining (ARM) which is a kind of data mining (Masum 2019). ARM (Tai and Chiu 2009) is a well-researched field based on relationship mining that helps to uncover hidden or previously unknown connection (Wassan 2015). ...
... ARM is a well-researched field based on relationship mining that helps to uncover hidden or previously unknown connection. A rule in the form of A ) B denotes an implication of element A by an element B, i.e., how two items (A and B) are co-related with each other (Wassan 2015;Masum 2019). ...
Data mining has become a hot research topic, and how to mine valuable knowledge from such huge volumes of data remains an open problem.
Processing huge volumes of data presents a challenge to existing computation software and hardware. This study proposes a model using association rule mining (ARM) which is a kind of data-mining technique for discovering association rules of chronic diseases from the enormous data that are collected continuously through health examination and medical treatment. This study makes three critical contributions: (1) It suggests a systematical model of exploring huge volumes of data using ARM, (2) it shows that helpful implicit rules are discovered through data-mining techniques, and (3) the results proved that the proposed model can act as an expert system for discovering useful knowledge from huge volumes of data for the references of doctors and patients to the specific chronic diseases prognosis and treatments.
