The economics of stock touting during Internet‐based pump and dump campaigns

Siering, Michael

doi:10.1111/isj.12216

Cited by 18 publications

(12 citation statements)

References 65 publications

(105 reference statements)

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“…Consequently, because investors' judgement is influenced by the forward-looking disclosure (Allee and DeAngelis, 2015;Hales et al, 2011;Huang et al, 2013;Siering, 2019), the manipulation of MD&A tone has the potential to mislead the analysts and to provide a distorted view of the company to investors.…”

Section: Introductionmentioning

confidence: 99%

Management discussion and analysis: a tone analysis on US financial listed companies

Caserio

Panaro²,

Trucco

2019

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Purpose The purpose of this paper is to investigate whether financial companies of the USA are inclined to manipulate the management discussion and analysis (MD&A) tone and thus to follow impression management behaviours. Also, the paper proposes a tone analysis of MD&As conducted by comparing the tone of MD&As of one year with financial conditions of the same year and the next. Design/methodology/approach The tone analysis is conducted on two sub-samples of US-listed financial companies, unhealthy firms and healthy firms, which experienced different financial conditions between 2002 and 2011. Findings With regard to healthy firms, MD&A tone is useful to explain the current year’s performance and helps to predict next year performance, whereas, with reference to unhealthy companies, managers use the tone to pursue impression management strategies, by using more positive words and more future-oriented words than healthy companies. Research limitations/implications This study analyses the correlation between MD&A tone at time t and financial performance at time t and t+1, it does not investigate other time spans. The empirical results of this study cannot be generalized to other countries. Practical implications Main implications are addressed to regulators and policy makers, which may contrast impression management through a more effective regulation. Another implication regards investors, who cannot fully rely on MD&As of unhealthy companies. Originality/value This study analyses financial companies, rather neglected by the literature on MD&A tone. Results suggest that financial firms are also inclined to engage in impression management. This research would be useful for investors who base their decisions on qualitative analysis, interested in understanding to what extent the MD&A narratives are reliable.

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Section: Introductionmentioning

confidence: 99%

Management discussion and analysis: a tone analysis on US financial listed companies

Caserio

Panaro²,

Trucco

2019

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“…In a specific post

, we assume that there are

words in the positive list and

words in the negative list. Following Siering [ 20 ], we compute the sentiment score of the post as show in Equation ( 5 ).

…”

Section: Proposed Modelmentioning

confidence: 99%

“…Groß‐Klußmann et al [ 9 ] proposed an unsupervised learning method based on the positive and negative word lists from emotion dictionaries to build sentiment scores of microblog messages. Siering [ 20 ] applied a dictionary‐based method that computes the textual sentiment by the number of positive and negative words.…”

Section: Introductionmentioning

confidence: 99%

A study of the impact of COVID‐19 on the Chinese stock market based on a new textual multiple ARMA model

et al. 2022

Statistical Analysis

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Coronavirus 2019 (COVID‐19) has caused violent fluctuation in stock markets, and led to heated discussion in stock forums. The rise and fall of any specific stock is influenced by many other stocks and emotions expressed in forum discussions. Considering the transmission effect of emotions, we propose a new Textual Multiple Auto Regressive Moving Average (TM‐ARMA) model to study the impact of COVID‐19 on the Chinese stock market. The TM‐ARMA model contains a new cross‐textual term and a new cross‐auto regressive (AR) term that measure the cross impacts of textual emotions and price fluctuations, respectively, and the adjacent matrix which measures the relationships among stocks is updated dynamically. We compute the textual sentiment scores by an emotion dictionary‐based method, and estimate the parameter matrices by a maximum likelihood method. Our dataset includes the textual posts from the Eastmoney Stock Forum and the price data for the constituent stocks of the FTSE China A50 Index. We conduct a sliding‐window online forecast approach to simulate the real‐trading situations. The results show that TM‐ARMA performs very well even after the attack of COVID‐19.

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“…Email spam filters are also constantly being improved by Internet services such as Google and Symantec. In research conducted in [25], a total of 1,299 suspicious stock recommendation emails was obtained. It involved 221 stocks recommended in 252 advertising campaigns.…”

Section: Pump and Dump And Share Price Based Fdbsmentioning

confidence: 99%

Novel Methods for Resolving False Positives during the Detection of Fraudulent Activities on Stock Market Financial Discussion Boards

Lee¹,

Owda²,

Crockett³

2018

ijacsa

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Abstract-Financial discussion boards (FDBs) have been widely used for a variety of financial knowledge exchange activities through the posting of comments. Popular public FDBs are prone to being used as a medium to spread false financial information due to larger audience groups. Although online forums are usually integrated with anti-spam tools, such as Akismet, moderation of posted content heavily relies on manual tasks. Unfortunately, the daily comments volume received on popular FDBs realistically prevents human moderators to watch closely and moderate possibly fraudulent content, not to mention moderators are not usually assigned with such task. Due to the absence of useful tools, it is extremely time consuming and expensive to manually read and determine whether each comment is potentially fraudulent. This paper presents novel forward and backward analysis methodologies implemented in an Information Extraction (IE) prototype system named FDBs Miner (FDBM). The methodologies aim to detect potentially illegal Pump and Dump comments on FDBs with the integration of per-minute share prices in the detection process. This can possibly reduce false positives during the detection as it categorises the potentially illegal comments into different risk levels for investigation purposes. The proposed system extracts company's ticker symbols (i.e. unique symbol that represents and identifies each listed company on stock market), comments and share prices from FDBs based in the UK. The forward analysis methodology flags the potentially Pump and Dump comments using a predefined keywords template and labels the flagged comments with price hike thresholds. Subsequently, the backward analysis methodology employs a moving average technique to determine price abnormalities and backward analyse the flagged comments. The first detection stage in forward analysis found 9.82% of potentially illegal comments. It is unrealistic and unaffordable for human moderators or financial surveillance authorities to read these comments on a daily basis. Hence, by integrating share prices to perform backward analysis can categorise the flagged comments into different risk levels. It helps relevant authorities to prioritise and investigate into the higher risk flagged comments, which could potentially indicate a real Pump and Dump crime happening on FDBs when the system is being used in real time.

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The economics of stock touting during Internet‐based pump and dump campaigns

Cited by 18 publications

References 65 publications

Management discussion and analysis: a tone analysis on US financial listed companies

Management discussion and analysis: a tone analysis on US financial listed companies

A study of the impact of COVID‐19 on the Chinese stock market based on a new textual multiple ARMA model

Novel Methods for Resolving False Positives during the Detection of Fraudulent Activities on Stock Market Financial Discussion Boards

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