Thin Trading Research Articles

Forecasting migration movements using prediction markets

Migration forecasts are crucial for proactive immigration and integration management. While the demand for accurate migration forecasts continues to grow, the current state of migration forecasting is still unsatisfactory, because they tend to lack precision. We introduce an alternative method to forecast migration movements: prediction markets. While prediction markets are mainly unknown in migration studies, they are established in the political economy of forecasting election outcomes. For its application to a complex phenomenon in a more constrained information environment such as migration movements, we argue that prediction markets allow to balance complementarities of current qualitative and quantitative approaches if they provide solutions to avoid thin trading and integrate expert knowledge into the market. We apply the prediction market to forecast immigration in four West European countries in 2020 and find encouraging results. We discuss the strengths and limitations of prediction markets to migration forecasting, including ethical considerations, and guide its future application.

Does market microstructure affect time-varying efficiency? Evidence from emerging markets

This study advances beyond the conventional singular factor analysis and considers multiple market microstructure components to investigate time varying informational efficiency. This holistic approach deepens the comprehension of the intricate interplay among diverse microstructure facets. This study employs the System Generalized Method of Moments (SGMM) model to mitigate potential endogeneity pitfalls. The dataset comprises firm-level data from five emerging markets, for the period 2001–2020. After controlling for a battery of macroeconomic factors and idiosyncratic risk, this study finds that liquidity, volatility, thin trading, and trading cost are the key determinants of time varying efficiency. In comparison anonymous trading, tick size, and automation are not found to have a significant influence. The results are robust for an alternative choice of sample periods and alternative estimation methods. Individual and institutional investors should consider market microstructure components while designing asset allocation strategies.

Sustainability reporting, board diversity, earnings management and financial statements readability: evidence from an emerging economy

PurposeThis paper aims to investigate the moderating effect of sustainability reporting on the relationship between the independent variables of board diversity, and earnings management and the dependent variable of readability of financial statements.Design/methodology/approachThe study panel data regression analysis involved 36 Kenyan-listed companies from 2016 to 2020.FindingsKey findings were that increased board diversity was found to significantly improve the readability of financial statements. Discretionary earnings management was found to significantly reduce the readability of financial statements. Sustainability reporting was found to significantly increase the readability of financial statements, and it moderated the relationship between board diversity, earnings management and financial statements readability in Kenya.Research limitations/implicationsThe study sample of 36 non-financial listed in the Nairobi Securities Exchange was very small and was affected by the problem of thin trading; hence, caution should be adopted when interpreting the findings.Practical implicationsThe Capital Markets Authorities (CMA) as a policymaker should enforce sustainability reporting by Kenyan listed firms as there is evidence that the reporting enhances the readability of financial statements. The Institute of Certified Public Accountants as a policymaker should closely monitor the published financial statements of firms for earnings management and punish the perpetrators, as there is empirical evidence that the practice reduces the readability of financial statements.Social implicationsSustainability reporting is successful as a moderating variable between readability of financial statements and determinants of readability of financial statements.Originality/valueThis study contributes to knowledge by studying sustainability reporting as a moderating variable between the independent variables of board diversity and earnings management and the dependent variable of readability of financial statements and measured sustainability reporting using a dummy variable for the period before and after the enactment and release of CMA code of 2016 on corporate governance that required sustainability reporting by Kenyan listed companies.

Value relevance of audit opinions in an emerging market: evidence from Morocco

Purpose This paper aims to determine whether audit opinions in Morocco, an emerging market, are value relevant to the stock market, through the investigation of the market reaction to the issuance of modified audit opinions (MAOs). Design/methodology/approach The event study approach is used. The data are derived from the financial reports of listed companies on the Casablanca Stock Exchange over a period of 10 years from 2010 to 2019. Findings This paper does not find evidence that the market reacts to the issuance of MAOs when grouped together. When partitioning the sample by types, there is an evidence of a stock market reaction to qualified audit opinions and the qualified audit opinions with observation paragraph when they are combined with a negative variation of earnings per share. Examination of the impact of different natures of qualifications shows no consistent results and that the market does not distinguish between natures of qualifications. Research limitations/implications These results may be due to the fact that some investors have information about the audit opinion long before it is made public, due to privileged access to audit opinions, or that investors underestimate audit opinions relative to other financial indicators. Originality/value This study contributes to the existing literature by investigating an emerging market, not previously tested, after the introduction of several regulatory reforms in Moroccan market aimed at enhancing transparency in financial reporting. It refines the market reaction models used in previous studies by using both ordinary least squares and the Scholes–Williams techniques that correct for the effect of thin trading on the market index. In addition, special attention is given to studying the market reaction to each type of MAOs and to each natures of qualifications.

A Procedure to Set Prices and Select Inventory in Thinly Traded Markets Using Data from eBay

Prices respond to equate supply and demand. However, price-setting in low-volume or “thin” markets is a challenge as is determining which items to carry. We present an algorithm that takes into account a store’s fixed costs, the cost of goods sold, prices, and listing duration to determine the portfolio of items to maximize profits. Prices can then be assigned as a mark-up over cost. The usefulness of this approach is demonstrated by applying it to a store on eBay in which the seller needs to meet a profit threshold. The findings identify how sellers of unusual items can effectively determine which items to list and how to set price to reach profit goals.

The Impact Of Thin Trading Adjustments On Exchange Rate Exposure

This study investigates the multiple exchange rate exposure of large non-financial firms in Asia and emerging countries using the unadjusted and adjusted two-factor exchange rate exposure model. The autoregressive-distributed lag (ARDL) method was applied to investigate the existence of exchange rate exposure. The Dimson-Fowler-Rorke (DFR) adjustment method was applied to adjust the ordinary least squares (OLS) market risk estimator for the thin trading phenomenon. The study’s findings indicate that exchange rate exposure does affect firm value. Incorporating the DFR market beta in the exchange rate exposure model indicates two important findings. Firstly, there is a significant increase in the number of firms exposed to exchange rate movements, especially in Indonesia, Thailand, Sri Lanka, and Vietnam. Secondly, there are more firms that will be exposed to multi bilateral exchange rate exposure across the sample countries. The findings imply that market characteristics such as thin trading could be an alternative explanation of the exchange rate exposure puzzle. Furthermore, future research should include asymmetric analysis as an alternative explanation for exchange rate exposure.

Homebuyer Purchase Decisions: Are They Anchoring to Appraisal Values or Market Prices?

Price discovery is an important research topic in real estate due to the heterogeneous nature of housing attributes and relatively thin trading activities compared to other assets. In Commonwealth countries, including New Zealand, governments usually conduct periodic appraisals for the purpose of collecting rates and levies. Such official appraisal values of properties, also known as capital values (CVs), are considered a price anchor for market participants in their negotiation processes. Real estate agents often use these appraisal values to advertise their listings and negotiate transaction prices. In this study, we aim to make an initial attempt to study the influence of CV on market prices using Granger causality tests and a hedonic pricing model. To test the lead-lag relationships, three million housing transactions from 1990 to 2020 in New Zealand are used to construct the capital values (CVs) and transacted prices (TPs) indices in both primary and secondary housing markets. The Granger causality test suggests that the indices of TPs and CVs have a bi-directional lead-lag relationship in the secondary housing market, whereas the relationship does not follow in the primary market where the information on CVs is unavailable. The results imply the existence of a CV anchoring effect. Such anchoring effects are also contingent on the timeliness of price anchors, which is consistent with the availability heuristic from behavioural economics.

Assessing Proxies for Market Prices of Thinly Traded Assets with Scheduled Cash Flows

Assessing Proxies for Market Prices of Thinly Traded Assets with Scheduled Cash Flows

Event studies with daily stock returns in Stata: Which command to use?

In this article, I provide an overview of existing community-contributed commands for executing event studies. I assess which command could have been used to conduct event studies that have appeared in the past 10 years in 3 leading accounting, finance, and management journals. The older command eventstudy provides a comfortable graphical user interface and good functionality for event studies that do not require hypotheses testing. The command estudy, described in Pacicco, Vena, and Venegoni (2018, Stata Journal 18: 461–476; 2021, Stata Journal 21: 141–151), provides a set of commonly applied test statistics and useful exporting routines to spreadsheet software and LATEX for event studies with a limited number of events. The most complete command in terms of available test statistics and benchmark models as well as its ability to handle events with insufficient data, thin trading, and large samples is eventstudy2.

Effect of Market Capitalization on Economic Growth of East African Community

Stock markets in developing nations are faced with various constraints such as thin trading, liquidity issues and lack of developed investor base. Most stock markets in Africa are dominated by a single Industry as the backbone of the economy. Therefore, the main aim of this study was to establish effect of market capitalization on economic growth of east African community. The study was guided by Financial Intermediary theory. This study adopted causal research design. Data were obtained from: capital markets, Stock Exchanges (USE NSE, RSE and DSE) of the EAC member countries, annual Statistical report from the EAC website and World Bank as well. Analysis of the data was done using descriptive and inferential statistics. This study adopted a Panel Vector Autoregressive (Panel VAR) model. The results of this study indicated that stock market performance variables have a long run positive effect on the economic growth in the EAC and a bi-directional causality between market capitalization. Therefore, this research is beneficial to East Africa Securities Regulatory Authority (EASRA) in designing of policies that creates favorable business environment for stock markets to flourish. The study recommends that the EAC member governments should pursue policies that can contribute to increased liquidity as this would in turn lead to a higher stock turnover rate. Keywords: Capitalization, Market, Economic Growth, East Africa Community. DOI: 10.7176/JESD/12-10-05 Publication date: May 31 st 2021

Peer Group Beta Reliability under Thin Trading Conditions: Results from a Simulated Environment in the Standard, Mean-Reversion and, Bayesian Framework.

Finance literature has proposed numerous techniques in order to eradicate the effects of thin trading, ranging from (il-)liquidity indicators indicating distortions in beta estimates to beta correction procedures directly correcting them in the traditional market model. This study exam-ines the superiority of comprehensive sets of 16 popular (il-)liquidity indicators and 10 popular beta correction procedures among themselves as well as against each other according to bias (effi-ciency) and accuracy (predictive ability) in the standard framework. Furthermore, the analysis is duplicated for the mean-reversion and the Bayesian framework, thus relaxing the assumption of beta stationarity. The results indicate (i) the (il-)liquidity indicators to generally outperform the beta correction procedures in small as well as in large stock markets, across different levels of thin trad-ing, across different levels of risk (beta magnitudes) and, across all three market model frame-works, (ii) the Illiquidity (Amihud-Hasbrouck) Indicator and the Return-to-Turnover Indicator as well as the Trade-to-Trade Method to dominate in the standard and the mean-reversion frame-work, (iii) the Turnover Indicator as well as the Error Correction Model to dominate in the Bayesian framework and, (iv) the (il-)liquidity indicators to generate absolutely best indications on beta dis-tortions in the Bayesian framework as well as the beta correction procedures to generate absolute-ly best beta estimates in the standard framework.

An Agent Based Model of a Thinly Traded Land Market in an Urbanizing Region

An Agent Based Model of a Thinly Traded Land Market in an Urbanizing Region

The The development of financial markets in Africa: trends, challenges and prospects

This paper explores trends and challenges in the development of African financial markets over the past two decades. Access to capital is essential for government to finance its budget and the performance of government policies is in part evaluated through how financial asset prices respond to the policy choices. Erratic security issuance, thin trading, low turnover ratios and lack of market depth has characterised African financial markets as inefficient. Applying a descriptive research model on key data from international think tanks to observe the behaviour of financial markets data in African countries, the study finds that African financial markets still face the traditional challenge of lack of market depth relative to other regions in other continents due to their limit size and very low market capitalisation. This is a key factor holding back the ability of investors to exploit expansion opportunities. This paper recommends that, part of the solution to challenges faced by African financial markets is for governments to assist in set-up electronic trading platforms, improve trading and settlement infrastructure.

Revisiting Index Methodology for Thinly Traded Stock Market. Case: Helsinki Stock Exchange

Stock market indices play a central role in portfolio management and academic research. This paper reviews and discusses the main issues in index construction, especially on thinly traded stock markets and in a historical setting with deficiency of information. The main methods to deal with missing price observations are studied. As a case in point, a newly collected historical database for the Finnish stock market that covers the period from the establishment of the Helsinki Stock Exchange (HSE) in October 1912 forward is used. The HSE suffered from severe thin trading with only approximately 20% of the stocks having a daily transaction in the early part of the sample. Overall, the results show that index construction methodology have a major impact on the index as well as its statistical properties. The results also highlight the impact of corporate actions, the hardest information to obtain, on the market index performance.

Event Studies with Daily Stock Returns in Stata: Which Command to Use?

This article provides an overview of existing community-contributed commands for executing event studies. I assess which command(s) could have been used to conduct event studies that have appeared in the past ten years in three leading accounting, finance and management journals. The older command eventstudy provides a comfortable graphical user interface and good functionality for event studies that do not require hypotheses testing. The command estudy described in Pacicco et al. (2018, Stata Journal 18(2), pp. 416–476; 2020, Stata Journal, forthcoming) provides a set of commonly applied test statistics, useful exporting routines to spreadsheet software and LATEX for event studies with a limited number of events. The most complete command in terms of available test statistics and benchmark models as well as its ability to handle events with insufficient data, thin trading and large samples is eventstudy2.

Analysing the effect of trading characteristics on liquidity measures – a combined approach to liquidity: evidences from Tehran Stock Exchange

Liquidity estimation has always been of conspicuous importance to all investors as well as risk and return. The purpose of this study is to examine the impact of trading characteristics (price, trading volume, variability, return volatility, absolute stock return, and Beedles thin trading measure) on liquidity measures (Amihud illiquidity ratio, return reversal measure, stock turnover, zero return, turnover-volatility ratio and proportional bid-ask spread) in Tehran Stock Exchange. We extend previous studies by combining different liquidity measures using TOPSIS technique and by employing a multidimensional variable, namely TOPSIS output. Results reveal both of the liquidity measures are strongly related to trading characteristics including stock turnover and zero return. Also, stock price, trading volume, and Beedles thin trading measures are the most significant factors in estimating liquidity. Different effects of different liquidity measures indicate that liquidity is a multidimensional and complex concept, and each measure reflects only one aspect of liquidity. The results of examining the influence of trading characteristics on the combined (multidimensional) liquidity measure indicate that trading characteristics are the main determinants of liquidity.

Market reaction to the announcement of an information technology investment: Evidence from Indonesia

This study examines the market’s reaction around and subsequent to the announcement of an Information Technology Investment (ITI). The Scholes-Williams’ and Dimson’s betas, a more accurate, and longer time-window are employed to capture market reactions in an environment of thin trading on the Indonesian capital market from 2001 to 2016. The results show that Indonesian investors need time to recognise the signals of either an increase or decrease in value from an ITI. This study also finds that greater market reactions are characterised by firms in the banking industry, smaller sized firms, lower competitive position firms, first-time IT adopter firms, and enterprise resource planning investment firms.

Housing price dispersion in the presale market

Sale before completion (i.e. presale) is a common practice that real estate developers use to sell residential units. Since presale buyers are unable to inspect uncompleted units, developers may take advantage of asymmetric information and release information about quality to the market selectively. The search theory also suggests that incomplete pricing information, especially for new products, will induce a less competitive market that is characterised by dispersed presale prices. Would price dispersion be reduced if developers were required to provide more quality and pricing information? In this study, we argue that this is not necessarily the case. We conduct a natural experiment using a new information disclosure ordinance governing first-hand residential sales in the Hong Kong SAR, China. We find that the ordinance reduced the price dispersion of presale units with asymmetric information about property quality, but increased their price dispersion when limited pricing information (e.g. thin trading volume) was available in the neighbourhood. As a critical test, we further show that the ordinance increased price dispersion even more after the units were completed. This suggests that the ordinance has indeed made presale pricing more difficult because developers are no longer allowed to use different strategies to test market demand.

Characteristics of New Zealand dividend omissions and resumptions

PurposeFor firms listed on the New Zealand Stock Exchange, which is a relatively thinly traded market, the purpose of this paper is to examine the nature of stock returns associated with a dividend omission announcement when computations specifically address thin trading, and whether specific firm characteristics affect the likelihood and nature of a dividend omission.Design/methodology/approachFirst, event study analysis is used to check if dividend omissions actually do impact share prices in terms of short-term abnormal returns and longer-term cumulative abnormal returns (CARs) in a thinly traded market. Second, binomial logistic regression analysis is used to determine what, if any, company characteristics are associated with the decision to omit a dividend. Third, multinomial logistic regression analysis is employed to determine what firm characteristics are associated with continuing (or ending) a phase of no dividends before a dividend resumption.FindingsDividend omissions generate immediate negative abnormal returns, and there is a longer-term persistence of negative CARs. The size and duration of these abnormal returns are smaller, but still significant, when thin-market-specific methodology is employed. With respect to firm characteristic, smaller firms, firms with decreased earnings, a higher level of extraordinary charges, greater leverage and firms with a higher book-to-market value are associated with a greater likelihood of making an omission. With respect to the length of time between an omission and resumption of dividend payments, earnings decreases, a higher book-to-market value, a higher level of extraordinary charges and a decrease in firm debt level become significant.Originality/valueThis paper adds value in two dimensions. First, it considers dividend omissions in three different, but inter-connected ways. Second, the use of multinomial logistic regression to examine an aspect of the non-payment hiatus breaks new ground.

How Valuable Is Market-and Firm-Specific Information for Calculating Bond Spreads in an Emerging Market?

ABSTRACT The determinants of corporate bond credit spreads are investigated in Chile as an example of an emerging market with relatively few actors and thin trading. Both market-level and firm-level factors are considered. Three models previously used to analyze the highly developed US market are applied to Chilean inflation-indexed bond trade data, and the results for the two markets are compared. The determinants found to be significant for Chile form the basis for the design of a new multifactor regression model that is used to explain Chilean bond spreads. The results are evaluated with an out-of-sample test, and the root-mean-square error is calculated to compare the model’s results with those obtained by the method commonly applied in illiquid markets by repeating the last recorded transaction for days on which no data are available. The proposed formulation is found to reduce the degree of error.