The Influence of Cognitive Biases and Financial Factors on Forecast Accuracy of Analysts

The objective of this study was to jointly analyze the importance of cognitive and financial factors in the accuracy of profit forecasting by analysts. Data from publicly traded Brazilian companies in 2019 were obtained. We used text analysis to assess the cognitive biases from the qualitative reports of analysts. Further, we analyzed the data using statistical regression learning methods and statistical classification learning methods, such as Multiple Linear Regression (MRL), k-dependence Bayesian (k-DB), and Random Forest (RF). The Bayesian inference and classification methods allow an expansion of the research line, especially in the area of machine learning, which can benefit from the examples of factors addressed in this research. The results indicated that, among cognitive biases, optimism had a negative relationship with forecasting accuracy while anchoring bias had a positive relationship. Commonality, to a lesser extent, also had a positive relationship with the analyst’s accuracy. Among financial factors, the most important aspects in the accuracy of analysts were volatility, indebtedness, and profitability. Age of the company, fair value, American Depositary Receipts (ADRs), performance, and loss were still important but on a smaller scale. The results of the RF models showed a greater explanatory power. This research sheds light on the cognitive as well as financial aspects that influence the analyst’s accuracy, jointly using text analysis and machine learning methods, capable of improving the explanatory power of predictive models, together with the use of training models followed by testing.

Is Bitcoin Price Driven by Macro-financial Factors and Liquidity? A Global Consumer Survey Empirical Study

This research aims to utilize macro-financial and liquidity elements as the factors that may affect the price of Bitcoin as the largest cryptocurrency in terms of market capitalization. The macro-financial factors analyzed in this study were foreign exchange, stock market index, interest rates, and gold, while liquidity ratio is the internal factor. This study applied a fixed-effect model (FEM) and Generalized Method of Moments (GMM) on gathered weekly data from 1 January 2017 to 29 December 2019 from 18 countries with the total of 2,826 observations. The analysis revealed that US Dollar amplifies Bitcoin trading; an increase in interest rate will decrease investors’ intention to invest in Bitcoin as a speculative asset, and gold could replace Bitcoin as a substitute asset. Moreover, Bitcoin was found to be highly liquid, which attracts many investors, while the stock market index proved to be insignificant.

Why People Emigrate to Work in Elder Care?

Emigration is one of the sorest problems in Lithuania. Emigrants from Lithuania most often fill the sector of unskilled labour in the target countries, one of which is elder care. Financial factors are considered the main motivation for emigration; however, migration is a complex phenomenon and requires a more nuanced investigation. The aim of this article is to analyse subjectively identified reasons of emigration from Lithuania to work in the elder care sector and motivation in choosing a particular country. The thematic data analysis of 13 semi-structured interviews revealed that emigration is motivated by an entirety of reasons: beside financial factors other „push“ (family, health) and „pull“ (knowledge about the country, family formation) factors are important. The move also is facilitated by the chain migration factors. The importance of the economic reasons for migration is revealed in cases of financial insecurity (loss of employment, threat of company bankruptcy, financial difficulties in the parents’ family etc.). Economic considerations become significant again, when comparing the job options and working conditions available to migrants. Work in the care sector for older people is seen as relatively easy, accessible and well paid. Other “push” factors were related to an unsatisfactory life situation, including stressful employment, and unsatisfying family relationships. The desire to get to know a foreign country, the opportunity to start a family or establish oneself there can work as „pull“ factors. The decision to emigrate was supported by the chain migration factors – encouragement, help and support of previously established immigrants. In some cases, it emerged as an independent factor of migration people emigrated, invited by relatives or acquaintances from abroad even though they did not initially plan to migrate. With the rapidly growing share of older people in Lithuania and the underdeveloped care services, the opportunity to retain potential emigrants by creating attractive working conditions for them in Lithuania, remains untapped. Policies should aim to improve the working conditions and opportunities in the care sector in Lithuania in order to encourage Lithuanians to stay in the country. In addition, regulations to better absorb (returning) migrants should be in place, given the ongoing movement between countries.

Evaluating the causative factors that lead to rejection of hearing aids among young adults having moderate to severe degree sensorineural hearing loss

Background: Hearing loss in young adulthood causes real stigma and a state of denial. The crucial clinical management to sustain the hearing loss is hearing aid fitting, but most adult people reject it or do not use it. Many factors, including social, personal, and device problems, lessen the usage of hearing aid. The objective of this study was to evaluate the causative factors which can lead to the rejection of hearing aids. Patients and methods: This was a cross-sectional survey carried out in 9 cities of Punjab, Pakistan, using a convenient sampling technique during summer 2018. A total of 171 participants were included who were young adults ranging from 19-40 years. A questionnaire with 11 factors and a further 35 sub-reasons was given to the participants. Questions were close-ended in yes or no. Data were analyzed through frequency and percentages tabulation with SPSS software. Results: Results showed that hearing aid value/speech clarity was the most problematic reason for patients to reject hearing aid. The given factor had four sub-reasons ('noisy situation,' 'poor benefit,' 'poor sound quality, and 'not suitable for the type of hearing loss). A total number n=154 (90.05%) marked yes for facing poor sound quality followed by poor benefit n=141 (82.45%), not suitable for the type of hearing loss n=121 (70.76%) and noisy situation n=118 (69.00%), thus making hearing aid value the leading cause of rejection. The second leading cause was financial factors followed by situational factors, appearance, fit and comfort, device factors, psychosocial factors, ear infections, care and maintenance, attitude, and family pressure to use a hearing aid. Conclusion: Most prevalent cause of not taking up a hearing aid is the hearing aid value followed by financial factors, situational factors, appearance, fit, and comfort.

Employee Motivation: An Indian Perspective

Motivation is the driving force which stimulates an individual to take action and sustains that behaviour. In the initial stage, only money was considered as a factor of motivation but there are many other factors also which motivates the individuals. The importance of these factors of motivation varies from person to person. Some people prefer financial factors while some people prefer non-financial factor. Present research aimed at identifying preference of factors affecting motivation of employees working in various Indian Enterprises and impact of demographic factors on the factors of motivation. Study was conducted with the help of questionnaire for this research. The questionnaire consisted of two parts: Part (A) and Part (B). The questionnaire was prepared on the basis of ten factors of motivation, Participants were asked to give the ranking to the factors of motivation on the basis of their importance. Relationship between motivational factors and demographic variables were established with the help of T test and ANOVA. The motivating factors were taken with the help of literature review. This research is supposed to provide useful directions to managers and other policy makers in developing employee motivation policies.

FINANCIAL FACTORS AFFECTING PRODUCTION EFFICIENCY OF SMALL SCALE COFFEE FARMS IN BURUNDI

Purpose: The study sought to evaluate financial factors affecting the production efficiency of small-scale coffee farms in Burundi. Methodology: The research design used during the study was descriptive. The research targeted a population of 300 small-scale coffee farmers. The study had a sample population of 121 smallholder coffee farmers. The study conducted the research for a 6-year period between 2015-2020. The data was collected using a secondary data collection sheet. Secondary data was obtained from Coffee federations' annual reports, cooperatives reports, and coffee farmers’ records. Analysis of the data was done using the Eviews student 11 version. The analyzed data was presented in form of tabulations, mean and standard deviation. Findings: The study findings showed that the correlation analysis showed that the selling prices per kilogram of coffee beans had a negative and significant correlation to the production efficiency by R = 0.98. Production efficiency had a negative and significant correlation to capital availability by R = 0.260. Lastly, production efficiency had a positive and significant correlation to production costs at R = 0.500. The findings of the research obtained that selling prices per kilogram of coffee beans had a not significant negative effect on production efficiency, while capital availability and production costs had a positive effect on the production efficiency. A unique contribution to theory, practice, and policy: The study recommended that government should review the policies relating to the selling prices per kilogram of coffee beans to improve small-scale coffee farmers’ incomes. Government should also facilitate access to credit to small-scale coffee farmers. The study incorporated the Cobweb theory of price fluctuation, the theory of credit rationing also called adverse selection theory, and the high payoff inputs model.