Deriving wisdom from virtual investing communities: an alternative strategy to stock recommendations

Kumar, Rahul; Mukherjee, Shubhadeep; Kumar, Bipul; Bala, Pradip Kumar

doi:10.1108/jm2-09-2019-0229

Cited by 5 publications

(4 citation statements)

References 43 publications

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“…In such a way, the considered periods are compared with each other seasonally, annually, etc. The efficiency achieved in fewer time intervals is the best (Kumar et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Credit Scoring Active Telegram Channels Offering Stock Signals

Sohrabi

Jafarabad

Orfi

2022

IJFIFSA

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The impact of personal judgment on the assessment of an individual's financial situation has been drastically reduced through the development of credit scoring. The systems are capable of deciding based on an applicant's total score which is a combination of several factors and indicators. Over the past few decades, credit scoring has been considered an essential tool for evaluation in various institutions and has also been able to transform the industry as aThe methodology used is "CRISP-DM," which consists of six steps. The main variables include social and financial variables that are examined for six months. In the research, we seek to identify, analyze and categorize active telegram channels in stock signals using the data mining model and the RFM method. The k-means algorithm is selected for this category. Then, in each cluster, the importance of social variables and the performance of the channels are extracted by the EXTRATREECLASSIFIER algorithm, and channel performance is measured by considering the changes in the total index.

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“…In such a way, the considered periods are compared with each other seasonally, annually, etc. The efficiency achieved in fewer time intervals is the best (Kumar et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Credit Scoring Active Telegram Channels Offering Stock Signals

Sohrabi

Jafarabad

Orfi

2022

IJFIFSA

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“…The aim of Kumar et al , (2020) is to expand such work by using different criteria to identify and weight such experts. Accuracy is deemed as the first important factor.…”

Section: Identifying Experts and Strategy Implementationmentioning

confidence: 99%

Towards better informed stock investment decisions

2020

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Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings Growing doubts about the reliability of professional analysts is making many investors hesitant to use the conventional approach to stock market investment. They are instead becoming increasingly attracted to an alternative strategy based on recommendations offered from members of virtual communities. Objective criteria are used to identify experts within such domains who have the potential to generate results comparable with major global indices. Originality/value The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

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“…Sharing opinions and votes on social networks manifests the wisdom of the crowds, which can be a key to profitable investment (Hill & Ready-Campbell, 2011). Based on the wisdom of the crowd assumption, a large crowd can outperform smaller groups or few individuals (Surowiecki, 2005) (Kumar et al, 2020). The most important feature of social media is wisdom and collective awareness (Rahjerdi et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Tehran Stock Exchange, Stocks Price Prediction, Using Wisdom of Crowd

Sohrabi,

Rouhani,

Yazdani

et al. 2023

IJFIFSA

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Two predominant methods for analyzing financial markets have been technical and fundamental analysis. However, the emergence of the Internet has altered the trading landscape. The availability of Internet and social media access plays a moderating role in information asymmetry, resulting in investors making informed decisions. Social media has turned into a source of information for investors. Through diverse communication channels on social media, investors articulate their perspectives on whether to buy or sell a stock. According to Surowiecki, the collective opinions gathered through social media frequently offer better predictions than individual opinions, a phenomenon referred to as the Wisdom of the Crowd. The wisdom of the crowd stands as an essential measure within social networks, with its potential to reduce errors and lessen information-gathering costs. In this study, we tried to evaluate the wisdom of the crowd's potential to improve stock price prediction accuracy. So, we developed a prediction model by Long Short-Term Memory based on the wisdom of the crowd. Users' opinions in Persian about the Tehran Stock Exchange (TSE) stocks were collected from SAHMETO for eight months. The Support Vector Machine classified them into buy, sell, and neutral classes. During the research period, people mentioned 823 stocks, and 52 stocks with over 100 signals were chosen. The results of the study show that although the model presented has achieved an acceptable level of accuracy, correlations between the actual and predicted values exceeded 90%. The accuracy metrics of the proposed model compared to the base model were not improved.

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Deriving wisdom from virtual investing communities: an alternative strategy to stock recommendations

Cited by 5 publications

References 43 publications

Credit Scoring Active Telegram Channels Offering Stock Signals

Credit Scoring Active Telegram Channels Offering Stock Signals

Towards better informed stock investment decisions

Tehran Stock Exchange, Stocks Price Prediction, Using Wisdom of Crowd

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