Return Movement Research Articles

The Magnet Effect of Price Limits: An Agent-Based Approach

ABSTRACT In this paper, we study the magnet effect within the context of circuit breaker events that transpired in global stock markets during March 2020. Our analysis encompasses nine such events across six countries. Employing a time-distanced quadratic function to model trading activities leading up to limit hits, we observe a substantial acceleration in return movement and the convergence of traders’ behavior preceding limit hits. Furthermore, most circuit breaker events manifest a distinct reduction in trading volume and amplified market stability during this crucial phase. To gain deeper insights into the magnet effect, we employ an agent-based model of the stock market that incorporates price limits. Our model replicates the stylized facts associated with limit hit events and the magnet effect. Importantly, our simulation results closely align with empirical observations. We also emphasize the importance of market environment changes and shifts in traders’ behavior in influencing limit hit events and the magnet effect.

Returning to fund refugeehood: dispersal and survival between Uganda and South Sudan

ABSTRACT Return movements of refugees, even when gradual or temporary, are typically understood as part of a process of full repatriation or as a ‘strategy’ for leveraging socio-economic opportunities across borders. However, for some refugees, return is neither a step towards repatriation nor an empowering strategy. Drawing on qualitative and quantitative data from Uganda and South Sudan, this article shows how, due to gradual reductions in aid and the lack of livelihood opportunities in Uganda, South Sudanese refugees travel back to their homeland in order to financially support their relatives who remain in exile. These return movements and the phenomenon of split households among South Sudanese are responses to severe hardship and, paradoxically, are deployed to sustain their life in Uganda. While cross-border migration enables refugees to access subsistence opportunities, this article argues that it underscores how refugees must now find their own means to ‘fund’ their refugeehood, given ongoing reductions in international assistance for protracted displacement.

Roots tourism experiences, identity construction, social equity and social justice: a mixed methods approach

ABSTRACT The incidence of African diaspora’s pilgrimage to their ancestral motherland in Africa has recently increased. Indeed, initiatives such as the Black Travel Movement and Year of Return have increased the desire for black diasporans to ‘go back home’. Evidence in the literature illustrates that this homecoming is a deliberate effort towards identity construction. Using a mixed-method research approach (and W.E.B Du Bois’s sociological; terror management, and substantive identity negotiation theories), this study examined root tourism’s effects on identity construction, social justice, and equity using data from the Cape Coast and Elmina Castles in Ghana. The study’s key outcome shows root tourism’s power to influence social justice and human rights equality. Furthermore, the study discovered that terror management and substantive identity negotiation theories are limited in their relevance to non-Western contexts. This study demonstrates how managers of tourism firms can rightly position root tourism as a distinct tool for identity construction, social justice and social equity. The study also discusses its implications, limitations and future studies.

“To dance like Solomon: imitation and martyrdom in a Qajar ghazal”

ABSTRACT Iran’s neoclassical Literary Return movement (Bāzgasht-i adabī) that reached its climax in the first half of the nineteenth century has, to date, been studied almost exclusively in relation to the Qajar royal court and the elite male poets who received imperial patronage. This article examines how one of the founding mothers of the violently persecuted and socially marginalized Babi-Baha’i religious community succeeded in producing a bold, emotionally charged response to a celebrated ghazal by one of the towering figures of the Persian poetic canon, Mawlana Jalal al-Din Rumi. Considering herself a worthy imitator and drawing on a transhistorical chain of responses to Rumi spanning the sixteenth to nineteenth centuries, this Babi-Baha’i poet refused to be excluded from the dominant literary currents of her day. Consequently, study of this unknown poet and those like her who, for far too long have been erased from modern Iran’s literary history, demands of us a broader definition of the community of Qajar poets, one that transcends social, doctrinal, and gendered lines.

Enhancing the accuracy of stock return movement prediction in Indonesia through recent fundamental value incorporation in multilayer perceptron

PurposeThe study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.Design/methodology/approachThe study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.FindingsIncorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.Research limitations/implicationsThe study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.Practical implicationsGovernments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.Originality/valueStudies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

The Effect of Macroeconomic Variables on Stock Returns of The Jakarta Islamic Index: A Panel Vector Error Correction Model Approach

Introduction: This study was conducted because there were differences in stock return trends in JII during 2016-2018, where stock return movements simultaneously decreased, but different conditions occurred in 2019-2022, where trend returns experienced different conditions between companies. This was caused by the domino effect of the Covid-19 Pandemic, which resulted in changes in Indonesia's BI Rate and Inflation. Thus, this study aims to analyze the long and short-term effects of BI Rate and Inflation on changes in the return of company shares in JII. Research Methods: This study uses the Panel Vector Error Correction Model (VECM) method, secondary data in the form of a Panel of Stock Return of 4 companies, BI Rate and Inflation during 2016-2022. Results: The long and short-term results in the previous two and three-quarters of the BI Rate were significantly positive for stock returns. While in the long and short term, inflation was significantly negative for stock returns. Conclusion: The research found that the BI Rate does not always negatively affect return. When the BI Rate increases, it gives investors confidence that the value of their investment is protected from depreciation. This can create a positive environment for the stock market so that it has an impact on rising stock prices.

PENGARUH SUKU BUNGA, KURS RUPIAH, DAN HARGA EMAS TERHADAP RETURN SAHAM PERUSAHAAN LQ 45 YANG TERDAFTAR DI BURSA EFEK INDONESIA

This research aims to analyze the significance of the influence of interest rates, rupiah exchange rates and gold prices on stock returns in LQ 45 companies listed on the Indonesia Stock Exchange. The population in this study was 60 LQ 45 companies listed on the Indonesia Stock Exchange from 2016 to 2020, while the sample in this study used a purposive sampling technique to obtain 30 companies. The analysis technique used is panel data regression analysis technique with the Eviews 9 program. The research results show that the rupiah exchange rate has a significant negative effect on stock returns while the gold price has a significant negative effect on stock returns. Meanwhile, interest rates do not have a significant effect on stock returns. The implication of this research is that investors must know and be able to predict the state of interest rates, the rupiah exchange rate and the price of gold before investing in shares. Suggestions for further research are to add other macro variables (inflation, world oil prices and other commodity prices) and internal company variables in the hope of being able to analyze more representative stock return movements. Keywords: Stock Return, Interest Rate, Rupiah Exchange, Gold Price

Interconnectedness of European insurers and cat shocks contagion effects

PurposeThe purpose of this paper is to examine the evolution of interconnectedness of European insurers among themselves, as well as with other non-financial firms, for the period 2000–2021 and to analyze the stock return movements around the costliest catastrophic events (hurricanes) in the past two decades.Design/methodology/approachThis paper follows the “simple” approach of Patro et al.(2013) and examines the daily stock return correlations of the largest 30 insurers and the largest 30 non-financial firms headquartered in Europe. In addition, the study uses event study methodology to examine stock return movements around the costliest hurricanes.FindingsWe find that the European insurance sector has become highly interconnected during the past two decades; however, its increasing connectedness with non-financial firms is limited to a few firms. In addition, we find weak evidence of the destabilizing effects of catastrophic events on European insurers and non-financial firms; however, the potential for cat risk contagion effects exists as the insurance industry becomes heavily interconnected.Originality/valueThe extant literature is largely concerned with the contribution of the insurance sector to the systemic risk of the financial sector. We focus on a specific region (Europe) and analyze the evolution of interconnectedness of the largest insurers within the insurance sector as well as with the largest non-financial firms encapsulating important crisis periods. In addition, we relate to the literature that examines the market reactions around catastrophic events to test the relevance of traditional insurance activities in instigating potential contagion shocks.

The impact of investor greed and fear on cryptocurrency returns: a Granger causality analysis of Bitcoin and Ethereum

PurposeThis study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.Design/methodology/approachThe authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.FindingsThe study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.Practical implicationsDespite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.Originality/valueThis study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.

Dynamics of Idxenergy Stock Returns: A Comprehensive Analysis of GDP, Exchange Rates, DJIA Index and Oil Prices

The movement of stock returns is a complex phenomenon that can be influenced by a number of factors, both macroeconomic and global factors. This study aims to explore the relationship and understand the extent to which these factors affect stock return movements, especially in the context of macroeconomic and global dynamics. The population of this study consists of companies listed in the IDXENERGY sector. Purposive sampling is used as a sample selection technique and 30 companies that meet the criteria are obtained. Panel data regression analysis with a significance level of 5% was conducted using Eviews 13. The research findings show that GDP has a negative impact on stock returns, while exchange rates, DJIA Index, and world oil prices have a positive impact on stock returns

A literacy of the relevance of Asian value sustainability reporting in Indonesia

An independent institution gives appreciation to companies in Indonesia that have published their sustainability reports by ranking their sustainability reports in the Asia Sustainability Reporting Rating. This institution plays a role in facilitating and encouraging companies, organizations and other entities in Indonesia to adopt good sustainability reporting practices. This ranking factor is predicted to influence the movement of abnormal returns so that it can influence value relevance through the earnings response coefficient. The aim of this study is to reveal the relevance of value in order to obtain empirical evidence regarding the influence of sustainability reports, sustainable report ratings and earnings persistence on the earnings response coefficient. The research sample was 130 companies in Indonesia that were included in the Asia Sustainability Reporting Ranking for the period 2019 to 2022. This paper uses a quantitative multiple linear regression method to test the hypothesis. The research results show that consistent profits can be predicted from the past and make a positive contribution to future earnings response. A company transparently discloses its performance in the sustainability aspect, thereby making the profit response more positive. Companies with high sustainability ratings tend to get a more positive profit response from the market and stakeholders. This study suggests that management and company owners in Indonesia are aware of the need to pay attention to long-term sustainability through the publication of sustainability reports to become a company’s commitment to implementing sustainability and minimizing risks arising from the company’s economic, social and environmental activities. AcknowledgmentsThe authors would like to thank the Directorate of Research, Community Service and Publications (DPPMP) of Stikubank University for supporting the funding of this research. Thanks also to fellow FEB lecturers who have helped provide the facilities needed for this research.

Uticaj berzanskih indeksa i cena sirovina na kretanje prinosa hartija od vrednosti kompanije Caterpillar

The goal of this paper is to examine the effect of selected stock market indices and the market prices of chosen raw materials on the movement of future daily returns of Caterpillar's shares. Historical data on stock returns and other relevant factors can be utilized to build statistical models for forecasting future market movements. Daily time-series data were collected from Yahoo finance for a five-year period. In this study, we use multiple linear regression to predict the returns of CAT shares. The model results can be analyzed to identify patterns, trends, and insights that may be useful for forecasting. The results show that the prediction accuracy of the proposed model, with four additional predictors, is 13.3% higher than the benchmark model, which only used the SPY market index (SPDR S&P 500 ETF) to explain the variability in CAT stock returns. The research confirmed that, in addition to the SPY market index, the performance of the PKB (Invesco Dynamic Building and Construction ETF) fund, as well as the prices of copper, steel, and aluminium have a statistically significant impact on the movement of CAT stock returns. The practical implication of this study is that investors, when deciding whether to invest in CAT shares, must consider not only systematic factors but also the performance of shares within its supply chain. The implication highlights the importance of analyzing Caterpillar's entire business system when making investment decisions. Such predictions contribute to a better understanding of the characteristics that enable optimal aggregation of information and efficient price determination. They also assist investors in selecting an investment strategy aligned with their objectives

The Market Efficiency of Socially Responsible Indices in India

Socially Responsible Indices allow investors to invest in those companies which are deemed to be socially responsible. These indices comprise those constituent companies screened and assessed for environmental, social and governance (ESG) criteria. This paper analyses the weak form of the Efficient Market Hypothesis (EMH) for socially responsible investment indices in India. The authors used the daily closing price of two indices, Carbonex and Greenex, from June 3, 2013, to December 31, 2022. This study conducted Augmented Dickey Fuller, normality, and autocorrelation tests to analyse the randomness of prices and test whether the future price can be predicted using the past price. The weak form theory of the efficient market hypothesis is violated if the returns are not random and dependent on past returns, thereby enabling investors to gain abnormal returns by extrapolating the past data. The research results suggest that the theory of weak form of efficient market hypothesis is valid for Carbonex and Greenex, which are the socially responsible indices of India. It implies that the future movement of returns for socially responsible investment indices in India cannot be predicted from past prices. Therefore, the opportunity to gain abnormal returns is not possible.

The Effect Of Economic Value Added (Eva), Market Value Added (MVA), Refined Economic Value Added (REVA) On Stock Prices And Stock Returns In Manufacturing Companies Listed In Indonesia Stock Exchange

The development of stock returns of manufacturing companies shows fluctuating movements from year to year. Return movements like this indicate that the condition of the manufacturing company is unstable so that it has an impact on the resulting stock returns. This uncertainty will certainly create its own concerns for investors who will invest in shares in manufacturing companies. With this, it is important for investors to analyze the company's condition first so that the investment made can provide returns. One aspect of the company that can be assessed by investors is the company's performance through financial statements. Helfert (2012: 98) grouped company performance measurements into three groups, namely (1) Earning Measures, (2) Cash Flow Measures, (3) Value Measures. Performance measurement based on value measures is economic value added (EVA), market value added (MVA), and refined economic value (REVA) This performance measurement holds the view that increasing value means also increasing long-term shareholder investment returns. Steward (2013: 115) states that value measures are considered to have capabilities that exceed Another performance measurement, because it takes into account all factors related to the creation (value) of the company that have an impact on the increasing prosperity of shareholders. The purpose of this study is to test EVA, MVA, and REVA against stock prices and stock returns. In this study using a research sample of 104 manufacturing companies taken through random sampling in the period 2014-2016. Data analysis and hypothesis testing in this study used the Partial Least Square Path Modeling (PLS-SEM) method. The results of this study show that EVA, MVA, and REVA have a significant positive relationship with stock price and stock return . By looking at the results of this study, it shows that performance appraisal using the EVA, MVA, and REVA methods has a strong influence on stock prices and stock returns . This shows that value-based valuation is important because every investment cannot escape the consequences of the incurring cost of capital as compensation for the funds used to finance the investment. The return on an investment will only mean that if the amount of return exceeds the cost of capital incurred to realize the investment, measurement certainly requires an accurate valuation method.

Silicon Valley Bank bankruptcy and Stablecoins stability

To what extent does the collapse of a commercial bank spread contagion across cryptocurrency markets? How do markets behave around bankruptcy if digital assets remain stuck within the bank and cannot be withdrawn? We use a BEKK model to examine contagion effects across major digital assets during the Silicon Valley Bank (SVB) collapse period in early March 2023. We find evidence of contagion across major stablecoins and Bitcoin. We also examine the price action when nearly all withdrawals at SVB were prohibited. We find substantial abnormal movements in stablecoin cumulative returns and traded volumes, indicating a “flight to safety” from less to more authoritative and trusted stablecoins. The implications for practitioners and policymakers are discussed.

Interconnectedness of Cryptocurrency Uncertainty Indices with Returns and Volatility in Financial Assets during COVID-19

This paper investigates the dynamic relationship between cryptocurrency uncertainty indices and the movements in returns and volatility across spectrum of financial assets, comprising cryptocurrencies, precious metals, green bonds, and soft commodities. It employs a Time-Varying Parameter Vector Autoregressive (TVP-VAR) connectedness approach; the analysis covers both the entire sample period spanning August 2015 to 31 December 2021 and the distinct phase of COVID-19 pandemic. The findings of the study reveal the interconnectedness of returns within these asset classes during the COVID-19 pandemic. In this context, cryptocurrency uncertainty indices emerge as influential transmitters of shocks to other financial asset categories and it significantly escalates throughout the crisis period. Additionally, the outcomes of the study imply that during times of heightened uncertainty, exemplified by events such as the COVID-19 pandemic, the feasibility of portfolio diversification for investors might be constrained. Consequently, the amplified linkages between financial assets through both forward and backward connections could potentially compromise financial stability. This research sheds light on the impact of cryptocurrency uncertainty on the broader financial market, particularly during periods of crisis. The findings have implications for investors and policymakers, emphasizing the need for a comprehensive understanding of the interconnectedness of financial assets and the potential risks associated with increased interdependence. By recognizing these dynamics, stakeholders can make informed decisions to enhance financial stability and manage portfolio risk effectively.

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the physicians' experience and the patient's characteristics. And the training should have high accuracy on the premise of safety. Therefore, trajectory customization, optimization, and tracking control algorithms are conducted based on a new upper limb rehabilitation robot. First, joint friction and initial load were identified and compensated. The admittance algorithm was used to realize the trajectory customization. Second, the improved butterfly optimization algorithm (BOA) was used to optimize the nonuniform rational B-spline fitting curve (NURBS). Then, a variable gain control strategy is designed, which enables the robot to track the trajectory well with small human-robot interaction (HRI) forces and to comply with a large HRI force to ensure safety. Regarding the return motion, an error subdivision method is designed to slow the return movement. The results showed that the customization force is less than 6 N. The trajectory tracking error is within 12 mm without a large HRI force. The control gain starts to decrease in 0.5 s periods while there is a large HRI force, thereby improving safety. With the decrease in HRI force, the real position can return to the desired trajectory slowly, which makes the patient feel comfortable.

Early and 1-year postsurgical stability and its factors in patients with complicated skeletal Class Ⅲ malocclusion treated by conventional and surgery-first approach: A prospective cohort study

This study aimed to compare postsurgical stability between conventional (CSA) and surgery-first (SFA) approaches and investigate its prognostic factors in patients with a skeletal Class Ⅲ extraction. Twenty and 19 patients treated with LeFort I osteotomy and bilateral sagittal split ramus osteotomy (BSSRO) with premolar extraction were enrolled in SFA and CSA groups, respectively. Serial cone-beam computed tomography images obtained before surgery, immediately after surgery (T1), 3 months after surgery, and 12 months after surgery were used for 3-dimensional quantitative analysis. The condyle was segmented for analyzing volumetric changes. Repeated measures analysis of variance, independent t test, and chi-square test were used to compare time-course and intergroup differences. Pearson and Kendall correlation and multivariate linear regression analyses were used to explore prognostic factors affecting skeletal stability. In both CSA and SFA, postsurgical relapse mainly occurred in the mandible sagittal and vertical dimensions and during the first 3 months after surgery. Stability in SFA was significantly less than that in CSA. Intraoperatively, inferolateral condylar displacement with proximal segment inwards, clockwise rotation, and return movements after surgery were observed regardless of the treatment approach. The condylar volume remained stable over time. Multivariate regression analysis showed that posterior vertical dimension (VD) at T1 (-1.63mm), surgical amount of mandibular setback (-10.33 mm), surgical condylar downwards displacement (-1.28 mm), and anterior overjet at T1 (6.43 mm) were the most important predictors of early mandibular relapse (r2= 0.593). The risk of early relapse could be reduced by controlling the anterior, middle, and posterior constraints provided by the prediction model.

Normality Test of NEPSE Sensitive Index

A return from the stock market is assumed to follow the random walk hypothesis. An investor is concerned about the risk and returns of the fund in which he or, she has invested. A risk-averse investor develops a portfolio with a secured return followed with a perfect prediction. Hence, a normality test for the market return is an easier way to diversify and eliminate risk. Thus, this paper tests the normality of the returns from the ‘blue-chip’ stocks in the context of NEPSE. A NEPSE Sensitive Index is an index calculated based on the trade of stocks for large, capital-based Nepalese listed companies with better earning histories and higher book values. The NEPSE sensitive index and NEPSE sensitive float index are tested for normality. The paper followed the data visualization technique, descriptive statistics, and test statistics to test the normality and find out the parameters of normal distribution. The paper found that the daily return from both indices best fit a normal distribution. Hence, two basic statistical parameters from the returns, i.e., the mean and standard deviation, are sufficient to estimate future trend for ‘blue-chip’ stock return in Nepal. The governing body should develop a new index that would better represent the market movement in the coming days that would be beneficial to predict the return movement from NEPSE.

The Impact of the COVID-19 Pandemic and the Russia-Ukraine War on Stock, Gold, and Bitcoin Markets: Examining Volatility Spillovers and Extreme Return Movements

We examine how the COVID-19 pandemic and Russia-Ukraine war affect volatility spillovers and extreme return movements in the stock, gold, and bitcoin markets. Our study uses the post-pandemic period of up to two and a half years in order to reflect the lingering effects of the pandemic as well as its initial impact. We find that volatility spillover has weakened in the post- versus pre-pandemic period. Additionally, our results suggest that the Russia-Ukraine war has had little impact on volatility spillovers. We subsequently test for extreme return movements separately and find substantial increases in the likelihood that two assets’ extreme returns move simultaneously post- versus pre-pandemic.