Security Prices Research Articles

Securities Prices are Set by Those at the Market's Margins

Securities Prices are Set by Those at the Market's Margins

IMPACT OF THE QUALITY OF FINANCIAL REPORTING INFORMATION ON THE SECURITIES LIQUIDITY OF LISTED COMPANIES ON THE STOCK MARKET IN VIETNAM

Research on the relationship between financial statement information quality and securities liquidity, making recommendations to improve the liquidity of listed companies. The purpose of this paper is to assess the impact of quality of financial reporting on the liquidity of securities of companies on the stock market in Vietnam. Using a mixed method to measure Financial statement information quality, securities liquidity. Using a regression model to evaluate the influence of financial statement information quality on securities liquidity of 149 companies listed on HOSE and HNS in 2022. The information quality characteristics of the financial statements are: Appropriate, Honest, Understandable, Comparative, Timely, Verifiable. To measure the liquidity of securities, the author uses the price and trading volume of securities of listed companies at the beginning of the year, the end of the first quarter, the second quarter, the third quarter, and the fourth quarter of 2022. The analysis results show that six characteristics Financial reporting information quality has a positive impact on the liquidity of securities in companies listed on the Vietnamese stock market. Among them, the most influential characteristic is honesty. The study offers suggestions based on the aforementioned findings to improve the quality of financial report information in order to promote liquidity. At the same time, to make the recommendations feasible in practice, the study also proposes recommendations to create a legal corridor and practical support for relevant factors. The author recommends that businesses need to have independent auditing companies audit annually, and those companies need to be reputable in the professional world.

Arbitrage problems with reflected geometric Brownian motion

Contrary to the claims made by several authors, a financial market model in which the price of a risky security follows a reflected geometric Brownian motion is not arbitrage-free. In fact, such models violate even the weakest no-arbitrage condition considered in the literature. Consequently, they do not admit numéraire portfolios or equivalent risk-neutral probability measures, which makes them unsuitable for contingent claim valuation. Unsurprisingly, the published option pricing formulae for such models violate classical no-arbitrage bounds.

A micro-foundation of a simple financial model with finite-time singularity bubble and its agent-based simulation

This paper proposes a mathematical model of financial security prices in continuous time with bubbles in which prices may diverge and crash in finite time. Just before the bubbles burst, prices increase super-exponentially. In addition, a discrete-time excess demand model is proposed to provide a micro-foundation for the continuous-time model. The derived discrete-time security price model has the same characteristics as the continuous-time price model and expresses the finite-time singularity. Furthermore, based on the excess demand model, an agent-based simulation is performed to check the price behavior. As expected, we can confirm that prices can diverge in finite time and increase super-exponentially.

The impact of news about COVID-19 on the dynamics of the Russian stock market

Subject. The article addresses the Russian stock market during the COVID-19 pandemic. Objectives. The study aims at empirical substantiation of the influence of tonality of news about COVID-19 published in official sources and social networks, on the Russian stock market. Methods. We employ a set of methods and procedures to assess the sentiment of downloaded news texts and tweets and to model the dynamics of general and sectoral stock indices (bag-of-words method, Markov-switching GARCH models, evaluation of text tonality using EcSentiThemeLex dictionary). Results. The paper reveals the influence of the tone of coverage of events related to COVID-19 pandemic in news sources and social networks on changes in stock prices of Russian companies. We substantiated the existence of industry specifics in terms of the degree of influence of the tone of news and tweets on stock price dynamics. The findings can be used by investors and issuers to model and predict changes in securities prices, and complement the theory, by underpinning the significance of the tonality of messages in the news and social networks for the dynamics of the Russian stock market. Conclusions. Changes in the emotional tonality of news and social media posts about COVID-19 impacted the stock market of the Russian Federation. The models enabled to prove that in a volatile economy, not only the information published about the coronavirus is significant for the stock market, but also the dynamics of the number of cases.

A Comparative Study on Stock Price Forecasting after the COVID-19 Pandemic

Nowadays, stock price forecasting is still a difficult problem plaguing people, due to the uncertainty of the market. We contrast the effectiveness of three models in this research.: ARIMA, SVM, and BPNN model. To get the outperformed model in predicting after the COVID-19 pandemic, the data set is the stock price of Citic Securities (600030) on the Shanghai Stock Exchange from 2022.4.1 to 2022.12.30. Experiment results show that all three models predict outcomes with very little error from the actual values. And BPNN model has the best accuracy because of its great ability to portray the non-linear characteristic of our data.

MFF-CNER: A Multi-feature Fusion Model for Chinese Named Entity Recognition in Finance Securities

The objective of Chinese financial securities named entity recognition is to extract relevant entities from unstructured Chinese text, such as news, announcements, and research reports, that impact security prices. Recognizing entities in this field is challenging due to the abundance of specialized terms, diverse expressions, and the limited feature extraction capabilities of traditional models. To address this, we propose MFF-CNER, a multi-feature fusion model, to improve the effectiveness of Chinese financial securities named entity recognition. MFF-CNER encompasses several key steps. Firstly, it leverages a BERT pre-training model to capture semantic features at the character level. Secondly, a BiLSTM network is utilized to capture contextual features specific to financial securities text. Additionally, we introduce an Iterated Dilated Convolutional Neural Network (IDCNN) to blend, and extract local features, incorporating an Attention mechanism for weighted feature integration. Finally, the predicted sequences are optimized, and decoded using the Conditional Random Field (CRF). To validate the state-of-the-art performance of MFF-CNER in this domain, we compare it with five popular methods on a Chinese financial securities dataset annotated with the BIO labeling scheme. Notably, MFF-CNER demonstrates superior performance while maintaining compatibility among its components. Furthermore, we evaluate the applicability of MFF-CNER in the Chinese financial securities domain by utilizing public datasets from diverse domains, including social media (WEIBO), and news (MSRA). This research holds practical significance for downstream applications, such as constructing financial securities knowledge graphs, and analyzing factors that influence security prices.

Exploring the Existence of Efficiency in the Financial Markets

Since the market efficiency hypothesis theory was introduced by Fama in 1970, many investors and researchers argued about the efficiency form of the real financial market. In the real financial market, there are solid pieces of evidence that the price of securities could reflect related public information. However, as real human beings, the investors in the financial market are not always rational and act according to the assumptions stated in the market efficiency theory, which results in a reduction in the efficiency of the real financial market. In this paper, our group tends to use two different views (investors and companies) to prove that all of the market efficiency hypothesis theory assumptions are violated in the real financial market, and the current market efficiency is weak. From an investors view, our group tends to analyze the effect of psychological factors from investors on market efficiency. Furthermore, from the companies side, our group tends to use case analysis to provide solid evidence for the market efficiency analysis.

Deviation from the Target Capital Structure and Acquisition Choices

This paper aims to discuss how managers consider capital structure variations when deciding which purchases to make. Compared to their debt ratio, highly leveraged companies are less likely to decide to buy cash. These companies purchase unimportant goals at a bargain. The capital structures of over-leveraged companies are changed by their managers in anticipation of a merger or acquisition. The methodology entails the approach to the research, and the right debt-to-capital ratio was found by using Compustat and the Center for Research on Security Prices (CRSP). These data will be used in assessing the estimation model and various regression and correlation analyses. Finally, they look for acquisitions that will add the most value. This research examines the relationship between capital structure and investment choices in the context of financial frictions, highlighting the importance of capital structure in investment choices.

SOLIDITY AND IMMUTABILITY OF BEHAVIOURAL FINANCE THEORY IN CAPITAL MARKET INVESTMENT: A GLOBAL PERSPECTIVE

This study evaluated the argument that the capital market is efficient such that all information from both the past, present, and unpublished have already been reflected in the market price of security as a guide for investors in the market and that the behavior of the same investors could affect the performance of the market. To address the above concern, the researcher employed various suitable final metric tools such as the Normality/Random Walk test, Variance ratio test, EGARCH models, etc., to analyze the daily historical data from prominent capital markets, each from all the continents around the world. From the results of these tools employed, none of the markets under study follow the random walk theory within the scope of the study. The results of EGARCH and volatility clustering tests also revealed that all the countries under study exhibited the property of stock returns distribution called volatility clustering or volatility pooling, a kind of heteroscedasticity, suggesting the nonconformity of the random walk theory. The failure of the various results to corroborate the random walk theory shows that investors are rational and unpredictable. These results have rightly positioned the behavioral finance theory as a veritable tool that can guide economic agents on capital market investment decisions. That means the behavior of investors makes share prices deviate from the economic fundamentals or assumptions. Considering the above findings, the researcher boldly advocates for a paradigm shift to behavioral finance theory, where emotions and psychology or mindsets of investors influence the investment decision-making process and financial markets, hence a veritable guide for decisions on stock market investments. Therefore, the researcher suggested that emotional and psychological checks be carried out on all stock market investors, mainly when an innovation or new policy is promulgated.

An MA-MRR model for transaction-level analysis of high-frequency trading processes

The transaction-level analysis of security price changes by Madhavan, Richardson, and Roomans (1997, hereafter MRR) is a useful framework for financial analysis. The first-order Markov property of trading indicator variables is a critical assumption in the MRR model, which contradicts the information lag empirically demonstrated in high-frequency trading processes. In this study, a nonparametric test is employed, which shows that the Markov property of the trading indicator variables is rejected on most trading days. Based on the spread decomposed structure, an MA-MRR model was proposed with a moving average structure adopted to absorb the information lag as an extension. The empirical results show that the information lag plays an important role in measuring the adverse selection risk parameter and that the difference in this parameter between the original and the extension is significant. Furthermore, our analysis suggests that the information lag parameter is a useful measure of the average speed at which information is incorporated into prices.

Business strategy and the cost of equity: the mediating role of accounting information quality

PurposeThe study examines the mediating role of accounting information quality (AQ), a proxy for firms' information risk, in firms' business strategy and the cost of equity (COE) nexus to highlight how AQ provides a mechanism through which a company's business strategy affects its COE.Design/methodology/approachThe research study utilises data from 12,100 firm-year observations of United States (US) non-financial firms from 2001 to 2017, drawn from multiple databases, and employs the bootstrapping method of mediation analysis to test the indirect effect of AQ on the business strategy–COE relationship. The authors rely on Miles and Snow's two pure business strategy typologies, prospectors and defenders and use innate accrual quality and implied COE models to measure AQ and COE, respectively.FindingsThe results suggest that AQ partially mediates the relationship between business strategy and COE. The authors document that while innovative-oriented prospector firms have a lower AQ and a higher implied COE, efficiency-oriented defenders are associated with a higher AQ and lower COE. The higher (lower) COE of prospector (defender) firms is observed to be partly due to their lower (higher) AQ. The results indicate that while the idiosyncratic risk implied in firms' strategic orientation can directly influence their COE, the business strategy implications on firms' COE can be indirect through their AQ, a source of information risk.Research limitations/implicationsDue to data limitation, it was not possible to measure all possible methods of measuring implied COE.Practical implicationsThe paper highlights the role of firm's business strategy in pricing decisions by investors.Originality/valueThe paper contributes to the existing literature by providing evidence that AQ, a proxy for information risk, is a mechanism through which business strategy affects firms' COE. The authors thus complement extant literature to empirically test the information risk effect inherent in strategic orientation on security pricing.

A LINEAR-PROGRAMMING PORTFOLIO OPTIMIZER TO MEAN–VARIANCE OPTIMIZATION

In the Markowitz mean–variance portfolio optimization problem, the estimation of the inverse covariance matrix is not trivial and can even be intractable, especially when the dimension is very high. In this paper, we propose a linear-programming portfolio optimizer (LPO) to solve the Markowitz optimization problem in both low-dimensional and high-dimensional settings. Instead of directly estimating the inverse covariance matrix [Formula: see text], the LPO method estimates the portfolio weights [Formula: see text] through solving an [Formula: see text]-constrained optimization problem. Moreover, we further prove that the LPO estimator asymptotically yields the maximum expected return while preserving the risk constraint. To offer a practical insight into the LPO approach, we provide a comprehensive implementation procedure of estimating portfolio weights via the Dantzig selector with sequential optimization (DASSO) algorithm and selecting the sparsity parameter through cross-validation. Simulations on both synthetic data and empirical data from Fama–French and the Center for Research in Security Prices (CRSP) databases validate the performance of the proposed method in comparison with other existing proposals.

Bank solvency stress tests with fire sales

We present a new framework combining current methods of bank solvency stress tests with a model of fire sales. We apply the framework to the stress tests conducted by the European Banking Authority. Fire sales are described by an equilibrium model balancing leverage improvements and drops in security prices. Additional bank losses caused by fire sales are significant and go beyond the trivial fact that with fire sales we will get bigger losses. Ignoring potential fire sales effects may lead to a false sense of resilience by assuming that institutions, which are in fact fragile, are resilient.

Herding behavior and government policy responses: Evidence from COVID-19 effect

The purpose of this study is to investigate the impact of a sudden shock from the COVID-19 epidemic on the behavioral bias of investors in the stock market of Iran as a developing country. The study also examines whether the government response to the COVID-19 pandemic can reduce investor herding behavior. We have used the Cross-sectional absolute deviation (CSAD) to measure securities dispersion from market returns. The studied period includes the cross-sectional data of the top 50 companies listed on the stock exchange during 2381 working days of the market (from March 1, 2012, to March 1, 2022). Furthermore, we use the semi-parametric estimator of the quantile regression for the data on the Iranian government response during the COVID-19 epidemic taken from the Oxford COVID-19 Government Response Tracker (OxCGRT). The main findings are in order. First, results show that the COVID-19 pandemic caused the formation of herding behavior aggravated by market volatility. Second, we document that the government response stringency index is unsuccessful in reducing investor herding behavior in the Iranian stock market. Finally, given the evidence that herding behavior, as a form of behavioral distortion, can drive security prices away from equilibrium values supported by fundamentals and cause price bubbles, our findings have important implications for policymakers and investors to mitigate herding effects and mis valuations.

Herding Behavior in Security Market and Portfolio Management

This study will examine the herding behavior in security market and its impact on the security pricing and overall market return as well as individual returns. Herding is known as an excessive irrational tendency of investors ignoring the fundamental information presented to them that act together in the markets (Gębka & Wohar 2013). Herding can directly lead to the security market distress and to the increase in trading volatility. In this study, we will examine how the security market under this irrational tendency would directly affect the prices of securities, and returns on individual’s portfolios.

Pricing, issuance volume, and design of innovative securities: The role of investor information

This study investigates the role of asymmetric information for the pricing, issuance volume, and design of innovative securities. By analyzing the information that structured product issuers provide to the investors of those products, we can identify specific sources of asymmetric information between the issuers and investors in this market. We show that issuers exploit this information friction to offer products to investors that appear more profitable for the issuer. In addition, we find that the friction induces issuers to design products with higher information asymmetry. Our results suggest that product issuers’ behavior increases information frictions in the financial system.

Banks as Liquidity Multipliers

Abstract We characterize the interaction between banks’ liquid assets purchases and deposit issuance decisions. Using global games, we derive a liquidity multiplier: the amount of deposits a bank can create when endowed with one additional unit of liquid asset to maintain a given level of liquidity risk. In our central theorem, we prove it is larger than unity. This entails that banks have a special role in enhancing liquidity provision, “multiplying” liquid assets into a larger quantity of deposits. Our theory has implications for banks’ balance sheet choices, the pricing of liquid securities, and the role of public liquidity provision.

M&A and technological expansion

AbstractWe examine how public firms listed in North American stock exchanges acquire technology companies during 2010–2020. Combining data from Standard and Poor's (S&P), Refinitiv, Compustat, and Center for Research in Security Prices, and utilizing a unique S&P taxonomy that classifies tech mergers and acquisitions (M&As) by tech categories and business verticals, we show that 13.1% of public firms engage in any tech M&A in the S&P data, while only 6.75% of public firms make any (tech or nontech) M&A in Refinitiv. In both data sets, the acquisitions are widespread across sectors of the economy, but tech acquirers in the S&P data are on average younger, more investment efficient, and more likely to engage in international acquisitions than general acquirers in Refinitiv. Within the S&P data, deals in each M&A‐active tech category tend to be led by acquirers from a specific sector; the majority of target companies in tech M&As fall outside the acquirer's core area of business; and firms are, in part, driven to acquire tech companies because they face increased competition in their core areas.

Pengaruh Fasilitas dan Kualitas Layanan Pelabuhan Terhadap Kepuasan Pelanggan

This literature study aims to review the literature relating to the effect of port facilities and service quality on customer satisfaction. The literature review was carried out by searching for articles published in leading and accredited journals. The results of the literature study show that port facilities and service quality have a significant influence on customer satisfaction. Complete and adequate facilities, such as parking areas, toilets and waiting areas, can increase customer satisfaction because they provide comfort and convenience for customers. In addition, good port service quality, such as service speed, staff friendliness, and punctuality, also contribute positively to customer satisfaction. Previous research has also shown that investment in port facilities and service quality can increase customer satisfaction. Customers who are satisfied with the services provided tend to return to using port services and recommend the port to others. However, there are several other factors that also affect customer satisfaction, such as the price of port services, port security, and ease of access. Therefore, it is important for ports to pay attention to these various factors in increasing customer satisfaction. In conclusion, this literature study shows that port facilities and service quality have a positive effect on customer satisfaction. Ports must pay attention to these factors to increase customer satisfaction and obtain long-term benefits for their business.