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In this paper we investigate the empirical performance of an alternative beta risk estimator, which is designed to be superior to its conventional counterparts in situations of extreme thin trading. The estimator used is based on the sample selectivity model. The study compares the resultant selectivity-corrected beta to the OLS beta and Dimson Betas. We demonstrate the empirical behaviour of the selectivity corrected beta estimator using a sample of stocks in seven countries from Latin America. The results indicate that the selectivity-corrected beta does correct the downward bias of the OLS estimates and is likely to better estimate stock risk.

This book is an attempt to reflect on what we have learned from financial policies and financial crises in Latin America. The 21 chapters in this volume capture the developments in various ways. They cover theoretical contributions, regional empirical studies, and specific inquiries on Argentina, Brazil, Chile, Colombia, Cuba, Ecuador, Mexico, Peru and Venezuela. The breadth of methodologies implemented suggests that researchers are looking at Latin American financial markets through a variety of lenses. The chapters are divided into 7 parts, including, in Part I, an initial overview. Part II examines the foreign exchange markets in Latin America and their interactions with other markets. Part III discusses dollarization issues in the region. Part IV then takes up the issue of banking in Latin America. Equity and bond markets are considered in Parts V and VI, respectively. Lastly, Part VII considers pension systems in Latin America. Taken as a whole, the 21 chapters seize the excitement of studying Latin America and provide lessons that are applicable around the world.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.