Investment performance and emotions: an international study

2019 ◽  
Vol 36 (1) ◽  
pp. 32-50
Author(s):  
Guy Kaplanski ◽  
Haim Levy

Purpose The purpose of this paper is to expand the peer effect analysis to investments in the stock market, where neither direct competition nor interaction with other investors exists. Design/methodology/approach A total of 772 subjects dwelling in six countries completed a questionnaire about their satisfaction with the performance of their hypothetical investment in the stock market. They were informed about the performance of the local stock market and the performance of their peer group, referred to in the questionnaire as their “friends.” Findings Only 5 per cent of subjects are indifferent to their friends’ investment performance, as advocates by expected utility paradigm. Most subjects are happier when their friends earn lower rather than higher returns. On average, subjects are better off losing rather than gaining money as long as their friends lose more money, which violates the univariate monotonicity axiom. A negligible number of subjects exhibit a consistent favorable response, which is a necessary condition for pure economic altruism. Hostility is greater in less-wealthy countries. No link is found with regard to economic inequality. Originality/value This paper shows that when a conflict between absolute wealth and relative wealth arises, the latter dominates, even when the comparison is not with an opponent or a colleague but with the subject’s friends. The astonishing result is that subjects prefer having less wealth as long as their friends lose more, despite no direct competition between subjects as in ultimatum games and despite the performance being equal to market performance.

2017 ◽  
Vol 8 (2) ◽  
pp. 143-160 ◽  
Author(s):  
Devi Lusyana ◽  
Mohamed Sherif

Purpose The purpose of this paper is to investigate the impact of the Indonesia Shariah-compliant Stock Index (ISSI) on the performance of included shares. In essence, the authors ask whether the establishment of the ISSI provides abnormal returns for the firms that are not included in the Jakarta Index. Design/methodology/approach The authors use an event study methodology to estimate cumulative abnormal returns in the days surrounding the event to examine the relationship between Shariah-compliant investments and stock returns. The estimation window of 90 trading days prior to the event (−30) to day 60 after (+60) is adopted. They also use a range of investment performance measures to provide new evidence on whether faith-based ethical investments generate superior performance compared to their unscreened benchmarks. Findings Using daily returns, the Indonesia ISSI and panel data model, the findings show that the inclusion of the ISSI has a positive impact on the financial performance of the included shares during the 41-day event window. The evidence also suggests that the ethical investment has a significant influence on the performance of stock market returns. Research limitations/implications This study offers insights to policymakers, investors and fund managers interested in the indices’ performance. A key conclusion that could be derived by bodies that regulate Islamic products and services is that investors are not only concerned about what is profitable but also what makes their investments ethical. Originality/value Although the global growth of the Islamic capital market products and services has been tremendous in recent years, very few studies focus on the Indonesian market and indeed, none of them devote sufficient attention to Shariah-compliant investments and stock returns.


2018 ◽  
Vol 31 (3) ◽  
pp. 869-885 ◽  
Author(s):  
Sara Fernández-López ◽  
Lucía Rey-Ares ◽  
Milagros Vivel-Búa

Purpose The purpose of this paper is to adopt a behavioural approach to explain how the internet use influences stock market participation (SMP) decisions. Design/methodology/approach Drawing on the literature on sociability and SMP, this paper analyses whether virtual sociability affects SMP decision in a sample of 34,715 individuals in 14 European countries. Findings The results show that internet users are more likely to be stockowners. However, the obtained evidence does not support either an informational effect or a social multiplier effect of the virtual sociability. After controlling by the country’s SMP rates, a positive effect of internet usage on SMP decision remains, suggesting that contextual factors matter rather than internet usage per se. Thus, in countries where individuals are “used” to being stockholders, the habit of using internet increases SMP, but the “breeding ground” is a necessary condition. Originality/value The massive use of the internet provides a valuable opportunity to find evidence of the frictional costs which would act as inhibitors of the SMP, as economic theory hypothesised. After some promising results, the differences in the evolution of both the SMP and internet usage rates have not confirmed the initial enthusiasm. In addition, the question of why the SMP rates systematically differ across countries still remains open.


2017 ◽  
Vol 21 (3) ◽  
pp. 623-639 ◽  
Author(s):  
Tingting Zhang ◽  
William Yu Chung Wang ◽  
David J. Pauleen

Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along. Research limitations/implications This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets. Originality/value Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.


2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.


2019 ◽  
Vol 12 (4) ◽  
pp. 463-475
Author(s):  
Selma Izadi ◽  
Abdullah Noman

Purpose The existence of the weekend effect has been reported from the 1950s to 1970s in the US stock markets. Recently, Robins and Smith (2016, Critical Finance Review, 5: 417-424) have argued that the weekend effect has disappeared after 1975. Using data on the market portfolio, they document existence of structural break before 1975 and absence of any weekend effects after that date. The purpose of this study is to contribute some new empirical evidences on the weekend effect for the industry-style portfolios in the US stock market using data over 90 years. Design/methodology/approach The authors re-examine persistence or reversal of the weekend effect in the industry portfolios consisting of The New York Stock Exchange (NYSE), The American Stock Exchange (AMEX) and The National Association of Securities Dealers Automated Quotations exchange (NASDAQ) stocks using daily returns from 1926 to 2017. Our results confirm varying dates for structural breaks across industrial portfolios. Findings As for the existence of weekend effects, the authors get mixed results for different portfolios. However, the overall findings provide broad support for the absence of weekend effects in most of the industrial portfolios as reported in Robins and Smith (2016). In addition, structural breaks for other weekdays and days of the week effects for other days have also been documented in the paper. Originality/value As far as the authors are aware, this paper is the first research that analyzes weekend effect for the industry-style portfolios in the US stock market using data over 90 years.


2019 ◽  
Vol 13 (3) ◽  
pp. 574-602 ◽  
Author(s):  
Yixi Ning ◽  
Gubo Xu ◽  
Ziwu Long

Purpose This study aims to examine the venture capital (VC) industry in China. It has demonstrated a history of high growth with significant variations over time. The authors have examined the trends and determinants of VC investments in China over a 20-year period from 1995 to 2014. They find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. initial public offerings (IPOs), interest rate, price-to-earnings ratio, etc.). They also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk levels by allocating more capital to later-stage investments and securing more deals with later-round financings. However, after the 2008 global financial crisis, the China’s venture industry has recovered faster compared to the US counterpart response. Design/methodology/approach The authors first perform trend analysis of VC investments at an aggregate level, by stages of development, and across industry from 1995 to 2014.To test H1 and H2, the authors use multiple regression models with lagged explanatory variables. To test H3, the authors use univariate tests to compare the measures of VC investments at an aggregate level, stage funds ratios, stage deals ratios and financing series ratios during both a five-year and seven-year time windows around the 2007 A-Share stock market crash and the subsequent financial crisis. Findings The development of the VC industry in China has demonstrated a history of high growth with significant variation over time. The authors find that the aggregate amount of VC investments, the total number of venture deals and the average amount of venture investments per deal in China are all significantly impacted by macroeconomic conditions (i.e. GDP, export, money supply), technology innovations and financial market indicators (i.e. IPOs, interest rate, price-to-earnings ratio, etc.). The authors also find that the 2007 China A-Share stock market crash and the subsequent global financial crisis have motivated VCists in China to adjust their investment strategies and risk by allocating more capital to later-stage investments and securing more deals with later-round financings. However, the China VC industry has recovered faster compared to the USA just after the 2008 global financial crisis. Research limitations/implications There are also limitations in the study. The VC data in China in the earlier 1990s might not be very reliable due to the quality of statistics. Therefore, the trend analysis and discussions mainly focus on the time after 2000. Also, the authors cannot find VC financing sequence data for the analysis. Second, there is no doubt that the policy impact from Chinese transforming economic system and government policies on its VC industry is substantial (Su and Wang, 2013). However, they cannot find an appropriate variable to be included in the empirical models to consider this effect. Further study on this area would provide meaningful information. Third, although the authors have done comparison study between the VC industry in China in this study and the VC industry in the US documented in Ning et al. (2015) and discussed some interesting findings, more in-depth research in this area will be very useful. Practical implications The findings have meaningful implications for VCists and start-up companies seeking equity financings in China. VCists should closely monitor macroeconomic and market conditions to make appropriate adjustments to their risk and investment strategies. Entrepreneurs seeking equity financings for their business could also monitor the identified macroeconomic and market indicators, which can help them with their timing and to negotiate a better equity financing deal. VC financing is more likely to succeed when key macroeconomic and market indicators become favorable. Originality/value This paper contributes to the literature by testing the supply and demand theory on the VC market proposed by Poterba (1989) and Gompers and Lerner (1998) from the macroeconomic perspective using 20 years’ VC data from China. The authors also examine how the 2007 A-Share stock market crash and the subsequent financial crisis affected VCists to adjust their risk levels and investment strategies. It provides useful information for international academia and policymakers to understand the quick rise of China VC industry. The authors also find that the macroeconomic drivers of VC industry are somewhat different under different economic systems.


2017 ◽  
Vol 44 (6) ◽  
pp. 715-731 ◽  
Author(s):  
Ivy Drafor

Purpose The purpose of this paper is to analyse the spatial disparity between rural and urban areas in Ghana using the Ghana Living Standards Survey’s (GLSS) rounds 5 and 6 data to advance the assertion that an endowed rural sector is necessary to promote agricultural development in Ghana. This analysis helps us to know the factors that contribute to the depravity of the rural sectors to inform policy towards development targeting. Design/methodology/approach A multivariate principal component analysis (PCA) and hierarchical cluster analysis were applied to data from the GLSS-5 and GLSS-6 to determine the characteristics of the rural-urban divide in Ghana. Findings The findings reveal that the rural poor also spend 60.3 per cent of their income on food, while the urban dwellers spend 49 per cent, which is an indication of food production capacity. They have low access to information technology facilities, have larger household sizes and lower levels of education. Rural areas depend a lot on firewood for cooking and use solar/dry cell energies and kerosene for lighting which have implications for conserving the environment. Practical implications Developing the rural areas to strengthen agricultural growth and productivity is a necessary condition for eliminating spatial disparities and promoting overall economic development in Ghana. Addressing rural deprivation is important for conserving the environment due to its increased use of fuelwood for cooking. Absence of alternatives to the use of fuelwood weakens the efforts to reduce deforestation. Originality/value The application of PCA to show the factors that contribute to spatial inequality in Ghana using the GLSS-5 and GLSS-6 data is unique. The study provides insights into redefining the framework for national poverty reduction efforts.


2016 ◽  
Vol 9 (2) ◽  
pp. 123-146 ◽  
Author(s):  
Kim Hiang Liow

Purpose This research aims to investigate whether and to what extent the co-movements of cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles are linked across G7 from February 1990 to June 2014. Design/methodology/approach The empirical approaches include correlation analysis on Hodrick–Prescott (HP) cycles, HP cycle return spillovers effects using Diebold and Yilmaz’s (2012) spillover index methodology, as well as Croux et al.’s (2001) dynamic correlation and cohesion methodology. Findings There are fairly strong cycle-return spillover effects between the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles. The interactions among the cross-country business cycles, cross-country stock market cycles and cross-country real estate market cycles in G7 are less positively pronounced or exhibit counter-cyclical behavior at the traditional business cycle (medium-term) frequency band when “pure” stock market cycles are considered. Research limitations/implications The research is subject to the usual limitations concerning empirical research. Practical implications This study finds that real estate is an important factor in influencing the degree and behavior of the relationship between cross-country business cycles and cross-country stock market cycles in G7. It provides important empirical insights for portfolio investors to understand and forecast the differential benefits and pitfalls of portfolio diversification in the long-, medium- and short-cycle horizons, as well as for research studying the linkages between the real economy and financial sectors. Originality/value In adding to the existing body of knowledge concerning economic globalization and financial market interdependence, this study evaluates the linkages between business cycles, stock market cycles and public real estate market cycles cross G7 and adds to the academic real estate literature. Because public real estate market is a subset of stock market, our approach is to use an original stock market index, as well as a “pure” stock market index (with the influence of real estate market removed) to offer additional empirical insights from two key complementary perspectives.


2016 ◽  
Vol 6 (3) ◽  
pp. 264-283 ◽  
Author(s):  
Mingyuan Guo ◽  
Xu Wang

Purpose – The purpose of this paper is to analyse the dependence structure in volatility between Shanghai and Shenzhen stock market in China based on high-frequency data. Design/methodology/approach – Using a multiplicative error model (hereinafter MEM) to describe the margins in volatility of China’s Shanghai and Shenzhen stock market, this study adopts static and time-varying copulas, respectively, estimated by maximum likelihood estimation method to describe the dependence structure in volatility between Shanghai and Shenzhen stock market in China. Findings – This paper has identified the asymmetrical dependence structure in financial market volatility more precisely. Gumbel copula could best fit the empirical distribution as it can capture the relatively high dependence degree in the upper tail part corresponding to the period of volatile price fluctuation in both static and dynamic view. Originality/value – Previous scholars mostly use GARCH model to describe the margins for price volatility. As MEM can efficiently characterize the volatility estimators, this paper uses MEM to model the margins for the market volatility directly based on high-frequency data, and proposes a proper distribution for the innovation in the marginal models. Then we could use copula-MEM other than copula-GARCH model to study on the dependence structure in volatility between Shanghai and Shenzhen stock market in China from a microstructural perspective.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ha Min Son ◽  
Dong Gyu Lee ◽  
Yoo-Sook Joung ◽  
Ji Woo Lee ◽  
Eun Ju Seok ◽  
...  

Purpose The current golden standard for attention deficit hyperactivity disorder (ADHD) diagnosis is clinical diagnosis based on psychiatric interviews and psychological examinations. This is suboptimal, as clinicians are unable to view potential patients in multiple natural settings – a necessary condition for objective diagnosis. The purpose of this paper is to improve the objective diagnosis of ADHD by analyzing a quantified representation of the actions of potential patients in multiple natural environments. Design/methodology/approach The authors use both virtual reality (VR) and artificial intelligence (AI) to create an objective ADHD diagnostic test. Diagnostic and statistical manual of mental disorders, 5th Edition (DSM-5) and ADHD Rating Scale are used to create a rule-based system of quantifiable VR-observable actions. As a potential patient completes tasks within multiple VR scenes, certain actions trigger an increase in the severity measure of the corresponding ADHD symptom. The resulting severity measures are input to an AI model, which classifies the potential patient as having ADHD in the form inattention, hyperactivity-impulsivity, combined or neither. Findings The result of this study shows that VR-observed actions can be extracted as quantified data, and classification of this quantified data achieves near-perfect sensitivity and specificity with a 98.3% accuracy rate on a convolutional neural network model. Originality/value To the best of the authors’ knowledge, this is the first study to incorporate VR and AI into an objective DSM-5-based ADHD diagnostic test. By including stimulation to the visual, auditory and equilibrium senses and tracking movement and recording voice, we present a method to further the research of objective ADHD diagnosis.


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