Price Clustering Research Articles

Exploring the Nordic numbers: an analysis of price clustering in Scandinavian stocks

PurposeThis paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland.Design/methodology/approachThis paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering.FindingsUnivariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Results reveal pervasive clustering, strengthening with higher prices and turnover but weakening with larger trade volumes, firm size, and smaller tick sizes. These empirical findings support the theoretical expectations of price negotiation and resolution hypotheses.Practical implicationsThe observed clustering presents an opportunity for investors to potentially capitalize on this market anomaly and achieve supra-normal returns.Originality/valuePrice clustering, the phenomenon where certain price levels are traded more frequently, challenges the efficient market hypothesis and has been extensively studied in financial markets. However, the Scandinavian stock markets, particularly those in the Nasdaq Nordic Exchange, remain unexplored in this context.

Another look at the price clustering behavior: evidence from the Muscat stock exchange

PurposeThe price clustering behavior is becoming a core part of the market efficiency theory especially with the development of trading strategies and the occurrence of major and unprecedented shocks which have led to severe inquiry regarding asset price dynamics and their distribution. However, research on emerging stock market is scant. The study contributes to the literature on price clustering by investigating an active emerging stock market, the Muscat stock market one of the Arabian Gulf Markets.Design/methodology/approachThis research adopts the artificial intelligence technique and other statistical estimation procedure in understanding the price clustering patterns in Muscat stock market and their main determinants.FindingsThe findings reveal that stock prices are marked by clustering behavior as commonly highlighted in the previous studies. However, we found strong evidence of price preferences to cluster on numbers closer to zero than to one. We also show that the nature of firm’s activity matters for price clustering behavior. In addition, firms with traded bonds in Oman market experienced a substantial less stock price clustering than other firms. Clustered stock prices are more likely to have higher prices and higher volatility of price. Finally, clustering raised when the market became highly uncertain during the Covid-19 crisis especially for the financial firms.Originality/valueThis study provides novel results on price clustering literature especially for an active emerging market and during the Covid-19 pandemic crisis.

Market structure and price clustering: Maker‐taker versus taker‐maker

AbstractWe examine whether the different fee structures on equity exchanges, maker‐taker or taker‐maker, affects the frequency with which security prices cluster on round increments. We find higher price clustering on traditional maker‐taker venues relative to inverted taker‐maker venues. These results generally hold at the individual exchange level and across transaction‐ and quotation‐level clustering measures. Furthermore, we document that quoted depth, both inside and outside the best prices, is significantly greater on maker‐taker venues than on taker‐maker venues. We show that liquidity supply is the main economic driver behind the difference in price clustering between market structures. Our findings indicate that fees and rebates alter order‐routing strategies, which affect the precision of asset prices.

Price clustering and the panic trading hypothesis: evidence from an African coup d'état

Price clustering and the panic trading hypothesis: evidence from an African coup d'état

Price clustering and the panic trading hypothesis: evidence from an African coup d'état

Price clustering and the panic trading hypothesis: evidence from an African coup d'état

Clustering and Financial Performance Analysis of Indonesian Coal Mining Industry Stock Prices

In the comprehensive study of the Indonesian coal mining industry, a rigorous exploration and clustering approach was applied to historical stock price data and financial metrics from coal companies listed for over a decade. Data sourced from Yahoo Finance underwent an automated download process, ensuring consistency and efficiency. The research utilized robust clustering techniques, including K-means, Hierarchical, and Correlation Clustering, to discern the stock price movements during the dynamic market conditions of 2022 and 2023. Financial performance analysis, focusing on key metrics such as ROA, NPM, and EPS, highlighted the unique financial dynamics of companies like PTIS, IATA, and AIMS. The study's results provide a multifaceted understanding of the coal industry's financial trends, emphasizing varied company responses to market conditions and revealing significant financial performance divergences among key players. This research not only offers invaluable insights into the coal industry's financial landscape but also presents an innovative methodology poised to transform financial analytics in the sector.

PRICE CLUSTERING BEHAVIOR IN VIRTUAL REAL ESTATE MARKETS

We analyze 21,209 intraday transactions in the virtual real estate market and document significant price clustering at round numbers 0, 00, and 000 as ending digits, consistent with the negotiation hypothesis. The clustering increases with price level and pricing uncertainty proxied by the number of buyers and sellers in the NFT market. Moreover, market venue influences price clustering dynamics. Digits 9, 99, and 999 as ending prices are overrepresented in the sample, consistent with the left digit effects. However, we do not find support for the psychologically feeling right hypothesis or the strategic trading hypothesis.

Dynamics of price clustering in the Pakistan stock exchange

PurposeIn this paper, the authors study the phenomenon of price clustering in the Pakistan Stock Exchange (PSX), a market viewed as one of the best-performing stock markets in the world during 2014–2017. The authors study the effect of stock-level variables on price clustering and analyze the determinants of the cross-sectional patterns of price clustering in the PSX, in particular the causal link between price clustering and political instability.Design/methodology/approachThe authors' dataset comprises daily observations on 100 PSX stocks spanning from January 1, 2009 to June 30, 2019. The authors use multivariate regression and spectral analysis to shed light on the dynamics of stock price clustering in PSX.FindingsThe authors document abnormally high levels of stock price clustering, particularly on integer increments, in PSX. The nature of stock price clustering in PSX is consistent with the negotiation hypothesis of Harris (1991). The levels of stock price clustering on PSX are persistent and contain a cyclical component. Furthermore, the authors find that political uncertainty in Pakistan is a significant contributor to the high levels of price clustering on PSX. The authors' conclusions are robust to alternative econometric specifications and different measures of price clustering and political uncertainty.Practical implicationsThe authors' findings are of interest to investors and policymakers. Since price clustering decreases market quality and degrades the information content of stock prices, the authors' study shows that price efficiency in PSX has not improved despite major reforms over the last decade. One practical implication of the authors' results is that investors should be cautious while rebalancing portfolios around political events such as general elections because stock price clustering increases in the PSX during these periods. As a result, stock prices are likely to deviate from their intrinsic values.Originality/valueResearch on price clustering is limited to developed markets, and emerging/frontier markets have been largely overlooked. The phenomenon of price clustering in the PSX has yet to be studied, despite the relevance of the PSX for emerging/frontier market investors.

Efficiency and price clustering in the Baltic stock exchanges: evidence from a micro-level analysis

ABSTRACT In this article, we examine for the first time a set of securities traded in the Baltic stock exchanges for indication of price clustering. This study adds to the literature about the efficiency of the Baltic stock markets, as well as to knowledge about the clustering of financial prices. Our main conclusion is that clustering is pervasive at the firm level, with traders having a striking preference for closing prices ending in zero. Price clustering tends to increase with price level, turnover, and relative spread and to decrease with tick size. Overall, our results are consistent with the idea that the lower the cost of rounding prices and the greater the uncertainty about the proper value of the securities, the higher the propensity of prices to cluster at round numbers. Therefore, the evidence provides some support for the negotiation/resolution hypotheses.

Penerapan Algoritma K-Means Untuk Clustering Harga Rumah Di Bandung

The need for shelter is one of the fundamental aspects of daily life for humans. A house serves not only as a place to seek protection and rest but also as a venue for socializing with family. One of the factors influencing the decision in choosing a house is its price. House prices vary in each region, depending on factors such as location and other attributes. In major cities like Bandung, house prices differ based on their categories. However, many people still find it challenging to determine the value and discern whether a house is classified as affordable or expensive. Hence, there is a need for a clustering process of house prices in Bandung to aid in comprehending and categorizing house prices based on attributes such as the house price, total building area, and total land area. To understand and analyze the patterns of house prices in Bandung, this study utilizes the K-Means method to cluster the house price data into several groups based on their similarity in attributes. Additionally, the research aims to determine the optimal number of clusters through the cluster validation process using the silhouette index. The findings show that when using n_cluster=2, a silhouette score of 0.8870 is obtained, and with n_cluster=3, the silhouette score is 0.8009. These results indicate that clustering with n_cluster=2 and n_cluster=3 both exhibit strong interpretative structures. Thus, the clustering of house prices in Bandung can be effectively grouped into 2 clusters, as evidenced by the higher silhouette score obtained with n_cluster=2, approaching 1 compared to n_cluster=3.

Herding behavior in exploring the predictability of price clustering in cryptocurrency market

We propose the K-means approach and the Hidden Markov Model (HMM), to predict the phenomenon of price clustering of the cryptocurrency market. This approach aims to understand the relationship of price clustering with herding behavior, volatility, price, and economic policy uncertainty (EPU). Our results indicate that the (HMM) with four states has the best one-step-ahead forecasting performance. The results gave new insights into the financial analysis of cryptocurrency market about the dynamic relationship between price clustering regimes and different states of the explanatory variable. Our finding proves the efficiency of (HMM) for our sample and provides a good predictability.

Round offer prices in M&A transactions: costly negotiation and psychological preference

PurposeThe authors of this study aim to investigate possible explanations of the prevalence of price clustering in the final offer prices of mergers and acquisitions (M&A).Design/methodology/approachThe authors use final offer price in M&A deals to investigate the price clustering phenomena. The authors used regressions and logistic regressions to examine potential factors that might affect pricing strategy by looking into one-time acquirers and experienced serial acquirers.FindingsPrice clustering increases with negotiation uncertainties characterized as competitive bidding, number of bidders, challenged deals and duration. Moreover, the authors find persistent price clustering in experienced serial acquirers that are more experienced and better equipped with handling uncertainties, suggesting a preference of using round numbers regardless of levels of uncertainties. The authors' evidence shows that price clustering results from a combination of Harris' (1991) costly negotiation hypothesis where round prices may be used to lower search costs and psychological bias and preference.Originality/valueThe authors appear to be the first to investigate alternative theories that support M&A offer price clustering behavior, finding that both the costly negotiation and psychological bias and preference theories apply to M&A final price formation. Thus, the authors' major contribution, specific to the M&A process, is a clarification of physical and psychological factors associated with bidding and negotiation behavior. The authors are confident that the authors' study impacts conventional knowledge regarding M&A deal negotiation strategies, including bidding behavior, contract negotiation, financial analysis, management practices and risk management.

Quantum prices

Many retailers practice an extreme form of discrete pricing defined as quantum prices: differentiated products are priced using few and sparse price buckets. To show this, online data was collected for 350,000 products from over 65 fashion retailers in the U.S. and the U.K. This pricing strategy is observed within categories and across categories (i.e., similar or even disparately distinct products like jeans and bags have an identical price), as well as in product introductions, where new products come in at previous price buckets. Normalized indices indicate substantial price clustering after controlling for popular prices, convenient prices, assortment size, or digit endings. Quantum prices have implications for price adjustments through product shares, markdown prices, and for the law-of-one-price. A behavioral model of price salience and recall is discussed.

Efficiency and price clustering in Islamic stocks: evidence from three Asian countries

PurposeThis paper aims to examine the extent of price clustering in a selection of Islamic stocks listed in Indonesia, Malaysia and Pakistan and also investigates the determinants of the phenomenon at the firm level.Design/methodology/approachThe author test the uniformity of price distribution in the selected securities. Then, the determinants of price clustering were investigated through multivariate analysis based on a binary logistic regression model. Following the arguments of Narayan et al. (2011), who emphasize the importance of considering firm heterogeneity when studying the phenomenon, the author conducts the empirical study at the firm level.FindingsThe evidence indicates that Islamic stocks show a mild level of price clustering. Only half of the stocks under analysis rejected the uniformity test in the distribution of prices. In these cases, investors exhibited a preference for prices ending at zero and five. The evidence does not confirm the cultural clustering theories. Price clustering is found to be positively associated with price level and relative bid-ask spread. Overall, the negotiation hypothesis, which predicts that investors prefer round prices to minimize the costs associated with negotiations, best explains most of our results.Research limitations/implicationsThe existence of price clustering is difficult to reconcile with the prediction of the efficient market hypothesis that prices should follow a random walk. Moreover, the evidence indicates that Muslim investors share a preference for round prices in some settings, under the assumption that Islamic stocks are mostly traded by Muslim investors.Originality/valueTo the author’s best knowledge, this is the first study to address the subject of price clustering in Islamic stocks.

Understanding Accra’s housing market: an exploratory study using user-generated data

ABSTRACT Access to housing data in Ghana has been a challenge for researchers due to the lack of comprehensive data sources. However, the recent availability of big data sources has presented opportunities to bridge this data access gap. Using Greater Accra as a case, this study uses web scraping techniques to acquire publicly available housing data from two major E-commerce websites in Ghana and explores the Greater Accra Metropolitan Area’s (GAMA) prevailing housing market. Spatial autocorrelation statistics show clustering of high median prices in known high-class neighborhoods. Median prices in high-class neighborhoods were three to five times higher than median prices in the entire metropolis, highlighting high housing costs in high-class neighborhoods. This research highlights the high housing cost in GAMA, making it impossible for the average resident to afford to buy a house. Hence, a more inclusive housing strategy is needed to provide affordable housing options for all.

Ex-post facto analysis of cryptocurrency literature over a decade using bibliometric technique

Heaping praise on cryptocurrency network due to its transparency, portability, divisibility, and resistance to inflation, the crypto market has gained huge support from investors and traders worldwide. Given its rising popularity, most of the central banks today plan to launch their own cryptocurrencies. Such phenomenal growth trend has undoubtedly impacted academic research with hundreds of publications filling the academic space. This study provides a comprehensive overview of the academic trends and thematic dimensions of cryptocurrency research. Applying bibliometrics, we track ten thematic clusters identified as: cryptocurrency as a tool for risk management; decentralization of crypto transactions using blockchain and fintech; regulatory and digital framework of cryptocurrencies; market efficiency of cryptocurrencies; pricing efficiency of cryptocurrencies; price clustering and liquidity in crypto transactions; cryptocurrency as an investment asset; portfolio diversification using cryptocurrency; trading volume, return and volatility of cryptocurrencies; and role of information in the volatility of crypt prices. Along with an analysis of each of the thematic clusters, we provide directions for future research.

Price Clustering on Cryptocurrency Order Books

Price Clustering on Cryptocurrency Order Books

Price clusters and stock price stability

Understanding the factors affecting stock return volatility, for analysts, investors and company executives, it is critical. In this study, using a traditional approach, we identify the factors influencing volatility and how price friction is formed on stock price stability, and in particular, examining the clustering test for price increases. This study was carried out by examining the price clusters and stock price stability in the stock market and the OTC market between 2009 -2010. Econometric software was used to investigate the research variables. In this study, we tried to study stock price volatility in proportion to stock price clusters. Research findings showed; there is no significant relationship between stock price volatility and price clusters in the OTC market and the stock market.

Spatial-Temporal Change Trend Analysis of Second-Hand House Price in Hefei Based on Spatial Network.

Spatial Markov chain can effectively explore the spatial evolution trend of housing price under the influence of lag factor. This paper uses spatial autocorrelation and spatial Markov to study 353 second-hand houses in Hefei. The results show that (1) the housing price of Hefei urban area presents a situation of “two points and one side,” the high housing price is concentrated in the south and southwest of the urban area, and the price level gradually weakens from south to north, and the housing development shows a north-south differentiation. (2) There is a significant spatial autocorrelation between second-hand housing prices in Hefei. The “high-high” residential price clusters are mainly distributed in Shushan District and Binhu New Area, while the “low-low” residential price clusters are mostly in Yaohai district and its surrounding areas. The number of “low-high” agglomeration and “high-low” agglomeration is small, and the degree of change is not big. (3) Under the influence of different neighborhood environments, the housing prices in urban Area of Hefei show club convergence overall. At the same time, under the short-term influence of the policy, the housing prices of low level and middle and low level are promoted in the same neighborhood environment, while the housing prices of high level and middle and high level are negatively affected.

Trade price clustering in the corporate bond market

PurposeIn this paper, the authors document the existence of price clustering in the US corporate bond market.Design/methodology/approachUsing a sample of 8,422,593 corporate bond trades in 2014, the authors find that over 18% (1,522,284 trades) of all bond trades end in a clustered price, defined as a price ending in 00, 25, 50, or 75.FindingsOverall, the authors find that both bond rating category and risk, as measured by standard deviation of prices, play a role in price clustering; speculative grade bonds account for the majority of clustered prices. Clustered prices are more likely to have higher coupon rates, higher prices, and higher standard deviations of price than bonds with non-clustered prices. Regardless of size, both buy and sell dealer trades with customers (relative to interdealer trading) lead to an increase in price clustering. Dealers appear to use clustered prices when purchasing from and selling to institutions and, therefore, may use a clustered price to insulate themselves from the risk of asymmetric information. Additionally, the prevalence of clustered prices for retail-sized dealer sell trades suggests that dealers exercise dealer power over retail-sized traders.Originality/valueThis paper contributes to the literature on price clustering by examining trade price clustering of corporate bonds. It is different from previous papers on price clustering in equities. Given that bonds tend to be priced off of yield, it is unusual that trade prices cluster. It also demonstrates what kind of bonds cluster and with which customers dealers trade at clustered prices. It parallels other research in demonstrating dealer power over retail-sized traders.