This document summarizes a research paper that proposes and tests determinants of the implied equity risk premium (ERP) in Brazil. The paper calculates the ERP using current stock prices rather than historical returns. It finds several market fundamentals are significantly related to changes in the ERP, including changes in interest rates, debt risk spreads, US market liquidity, and the S&P 500 index level. The paper also compares using implied ERP versus historical averages and finds implied ERP varies with market events while historical averages do not.
Cost of equity estimation for the Brazilian market: a test of the Goldman Sac...FGV Brazil
As an approach to determining the degree of integration of the Brazilian economy, this paper seeks to test the explanatory power of the Goldman Sachs Model for the expected returns by a foreign investor in the Brazilian market during the past eleven years (2004-2014). Using data for the stocks of 57 of the most actively traded firms at the BM&FBovespa, it begins by testing directly the degree of integration of the Brazilian economy during this period, in an attempt to better understand the context in which the model has been used. In sequence, in an indirect test of the Goldman Sachs model, the risk factor betas (market risk and country risk) of the sample stocks were estimated and a panel regression of expected stock returns on these betas was performed. It was found that country risk is not a statistically significant explanation of expected returns, indicating that it is being added in an ad hoc fashion by market practitioners to their cost of equity calculations. Thus, although there is evidence of a positive and significant relationship between systematic risk and return, the results for country risk demonstrate that the Goldman Sachs Model was not a satisfactory explanation of expected returns in the Brazilian market in the past eleven years, leading us to question the validity of its application in practice. By adding a size premium factor to the model, there is evidence of a negative and significant relationship between companies’ size and return, although country risk remains not satisfactory to explain stock expected returns.
Date: 2017-03
Authors:
Guanais, Luiz Felipe Poli
Sanvicente, Antonio Zoratto
Sheng, Hsia Hua
The CBS Television surprise hit “Undercover Boss” has aired for six consecutive seasons and
features publicly traded firms, closely-held corporations, and in some instances not-for-profit institutions. While
there has been much analysis on the ethical dilemmas faced by the undercover CEO or other executive, no
practical analysis of a firm‟s profitability has been conducted on any of the firms featured on the show.
Conventional wisdom would suggest that financial performance of a featured firm would improve after the initial
airing date, as the show typically ends on a „feel good‟ note and most often places the executive, as well as the
firm, in a positive light. This paper analyzes the stock market price after the initial air date as well revenue and net
income for all publicly traded firms that have appears on the show through the end of the sixth season.
Cost of equity estimation for the Brazilian market: a test of the Goldman Sac...FGV Brazil
As an approach to determining the degree of integration of the Brazilian economy, this paper seeks to test the explanatory power of the Goldman Sachs Model for the expected returns by a foreign investor in the Brazilian market during the past eleven years (2004-2014). Using data for the stocks of 57 of the most actively traded firms at the BM&FBovespa, it begins by testing directly the degree of integration of the Brazilian economy during this period, in an attempt to better understand the context in which the model has been used. In sequence, in an indirect test of the Goldman Sachs model, the risk factor betas (market risk and country risk) of the sample stocks were estimated and a panel regression of expected stock returns on these betas was performed. It was found that country risk is not a statistically significant explanation of expected returns, indicating that it is being added in an ad hoc fashion by market practitioners to their cost of equity calculations. Thus, although there is evidence of a positive and significant relationship between systematic risk and return, the results for country risk demonstrate that the Goldman Sachs Model was not a satisfactory explanation of expected returns in the Brazilian market in the past eleven years, leading us to question the validity of its application in practice. By adding a size premium factor to the model, there is evidence of a negative and significant relationship between companies’ size and return, although country risk remains not satisfactory to explain stock expected returns.
Date: 2017-03
Authors:
Guanais, Luiz Felipe Poli
Sanvicente, Antonio Zoratto
Sheng, Hsia Hua
The CBS Television surprise hit “Undercover Boss” has aired for six consecutive seasons and
features publicly traded firms, closely-held corporations, and in some instances not-for-profit institutions. While
there has been much analysis on the ethical dilemmas faced by the undercover CEO or other executive, no
practical analysis of a firm‟s profitability has been conducted on any of the firms featured on the show.
Conventional wisdom would suggest that financial performance of a featured firm would improve after the initial
airing date, as the show typically ends on a „feel good‟ note and most often places the executive, as well as the
firm, in a positive light. This paper analyzes the stock market price after the initial air date as well revenue and net
income for all publicly traded firms that have appears on the show through the end of the sixth season.
Lodging REIT Analysis - Keynote Presentation for Research Committee by Brad K...Brad Kuskin
Although numerous studies examine REIT performance over extended periods of time, many online and data-driven investment tools do not adequately provide existing and prospective investors with the tools necessary to extract business management risk out of lodging REIT returns. Given investors' current reliance on technology and graphic-oriented return analysis, it is critical that lodging REIT shareholders understand that not all equity REITs are equal. Typically, investors govern by a combination of return on capital and diversification. However, lodging REITs are inherently misleading due to their "equity REIT" classification.
As lodging REITs expand to encompass a vast portion of the hospitality industry, particularly marquis lodging assets in primary metropolitan markets, an accurate comprehension of inherent risks is critical for any investor considering deploying capital into a lodging REIT.
Hedge Fund Predictability Under the Magnifying Glass:The Economic Value of Fo...Ryan Renicker CFA
The recent financial crisis has highlighted the need to search for suitable models forecasting hedge fund performance.
This paper develops and applies a framework in which to assess return predictability on a fund-by-fund basis.
Using a comprehensive sample of hedge funds during the 994-2008 period, we identify the fraction of funds in each style that are truly predictable, positively or negatively, by macro variables.
Out-of-sample, exploiting predictability can be di¢ cult as estimation risk and model uncertainty lead to imprecise fund forecast.
Moreover, in our multi-fund setting, investors face a trade-o¤ between unconditional and predictable performance, as strongly predictable funds may exhibit low unconditional mean.
Nevertheless, a strategy that combines forecasts across predictors circumvents all these challenges and delivers superior performance.
We highlight the statistical and economic drivers of this performance, especially in periods when predictor values strongly depart from their long run means.
Finally, we use one such period, the 2008 crisis, as a natural out-of-sample experiment to validate the robustness of our findings.
The Risk and Return of the Buy Write Strategy On The Russell 2000 IndexRYAN RENICKER
Actionable trade ideas for stock market investors and traders seeking alpha by overlaying their portfolios with options, other derivatives, ETFs, and disciplined and applied Game Theory for hedge fund managers and other active fund managers worldwide. Ryan Renicker, CFA
MODELING THE AUTOREGRESSIVE CAPITAL ASSET PRICING MODEL FOR TOP 10 SELECTED...IAEME Publication
Systematic risk is the uncertainty inherent to the entire market or entire market segment and Unsystematic risk is the type of uncertainty that comes with the company or industry we invest. It can be reduced through diversification. The study generalized for selecting of non -linear capital asset pricing model for top securities in BSE and made an attempt to identify the marketable and non-marketable risk of investors of top companies. The analysis was conducted at different stages. They are Vector auto regression of systematic and unsystematic risk.
An Empirical Assessment of Capital Asset Pricing Model with Reference to Nati...ijtsrd
"This study concentrates on empirical assessment of Capital Asset Pricing Model CAPM on the National Stock Exchange NSE . CAPM assists to determine a well diversified portfolio. The main objective of this research paper is to check the applicability of Nobel laureate’s model in Indian equity market by testing the relationship between risk and return, whether there is any direct proportionality in the expected rate of return and its systematic risk. It relates its results by using the beta systematic risk as a measuring factor. The study was being conducted for a period of 260 weeks from 7 April 2013 to 25 March 2018. 45 companies from NSE were picked as a proxy for the market portfolio. This research was done by using regression analysis on stocks and portfolio to find out the final results. Research of this study nullifies that this model is applicable to the Indian market and also contradicts its expected return and systematic risk which are linearly related to each other. Miss. Yashashri Shinde | Miss. Teja Mane ""An Empirical Assessment of Capital Asset Pricing Model with Reference to National Stock Exchange"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management , March 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23105.pdf
Paper URL: https://www.ijtsrd.com/management/public-sector-management/23105/an-empirical-assessment-of-capital-asset-pricing-model-with-reference-to-national-stock-exchange/miss-yashashri-shinde"
Lodging REIT Analysis - Keynote Presentation for Research Committee by Brad K...Brad Kuskin
Although numerous studies examine REIT performance over extended periods of time, many online and data-driven investment tools do not adequately provide existing and prospective investors with the tools necessary to extract business management risk out of lodging REIT returns. Given investors' current reliance on technology and graphic-oriented return analysis, it is critical that lodging REIT shareholders understand that not all equity REITs are equal. Typically, investors govern by a combination of return on capital and diversification. However, lodging REITs are inherently misleading due to their "equity REIT" classification.
As lodging REITs expand to encompass a vast portion of the hospitality industry, particularly marquis lodging assets in primary metropolitan markets, an accurate comprehension of inherent risks is critical for any investor considering deploying capital into a lodging REIT.
Hedge Fund Predictability Under the Magnifying Glass:The Economic Value of Fo...Ryan Renicker CFA
The recent financial crisis has highlighted the need to search for suitable models forecasting hedge fund performance.
This paper develops and applies a framework in which to assess return predictability on a fund-by-fund basis.
Using a comprehensive sample of hedge funds during the 994-2008 period, we identify the fraction of funds in each style that are truly predictable, positively or negatively, by macro variables.
Out-of-sample, exploiting predictability can be di¢ cult as estimation risk and model uncertainty lead to imprecise fund forecast.
Moreover, in our multi-fund setting, investors face a trade-o¤ between unconditional and predictable performance, as strongly predictable funds may exhibit low unconditional mean.
Nevertheless, a strategy that combines forecasts across predictors circumvents all these challenges and delivers superior performance.
We highlight the statistical and economic drivers of this performance, especially in periods when predictor values strongly depart from their long run means.
Finally, we use one such period, the 2008 crisis, as a natural out-of-sample experiment to validate the robustness of our findings.
The Risk and Return of the Buy Write Strategy On The Russell 2000 IndexRYAN RENICKER
Actionable trade ideas for stock market investors and traders seeking alpha by overlaying their portfolios with options, other derivatives, ETFs, and disciplined and applied Game Theory for hedge fund managers and other active fund managers worldwide. Ryan Renicker, CFA
MODELING THE AUTOREGRESSIVE CAPITAL ASSET PRICING MODEL FOR TOP 10 SELECTED...IAEME Publication
Systematic risk is the uncertainty inherent to the entire market or entire market segment and Unsystematic risk is the type of uncertainty that comes with the company or industry we invest. It can be reduced through diversification. The study generalized for selecting of non -linear capital asset pricing model for top securities in BSE and made an attempt to identify the marketable and non-marketable risk of investors of top companies. The analysis was conducted at different stages. They are Vector auto regression of systematic and unsystematic risk.
An Empirical Assessment of Capital Asset Pricing Model with Reference to Nati...ijtsrd
"This study concentrates on empirical assessment of Capital Asset Pricing Model CAPM on the National Stock Exchange NSE . CAPM assists to determine a well diversified portfolio. The main objective of this research paper is to check the applicability of Nobel laureate’s model in Indian equity market by testing the relationship between risk and return, whether there is any direct proportionality in the expected rate of return and its systematic risk. It relates its results by using the beta systematic risk as a measuring factor. The study was being conducted for a period of 260 weeks from 7 April 2013 to 25 March 2018. 45 companies from NSE were picked as a proxy for the market portfolio. This research was done by using regression analysis on stocks and portfolio to find out the final results. Research of this study nullifies that this model is applicable to the Indian market and also contradicts its expected return and systematic risk which are linearly related to each other. Miss. Yashashri Shinde | Miss. Teja Mane ""An Empirical Assessment of Capital Asset Pricing Model with Reference to National Stock Exchange"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Fostering Innovation, Integration and Inclusion Through Interdisciplinary Practices in Management , March 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23105.pdf
Paper URL: https://www.ijtsrd.com/management/public-sector-management/23105/an-empirical-assessment-of-capital-asset-pricing-model-with-reference-to-national-stock-exchange/miss-yashashri-shinde"
Testing and extending the capital asset pricing modelGabriel Koh
This paper attempts to prove whether the conventional Capital Asset Pricing Model (CAPM) holds with respect to a set of asset returns. Starting with the Fama-Macbeth cross-sectional regression, we prove through the significance of pricing errors that the CAPM does not hold. Hence, we expand the original CAPM by including risk factors and factor-mimicking portfolios built on firm-specific characteristics and test for their significance in the model. Ultimately, by adding significant factors, we find that the model helps to better explain asset returns, but does still not entirely capture pricing errors.
Returns on financial assets in the stock markets are affected daily by different types of risk, both
internal (systematic) and external (idiosyncratic), to anticipate the possible risks, investors look for tools that
allow them to know the behavior of the market and at the same time identify the risks in which they are
immersed in order to maintain a profitability in the portfolios of investment; t
Not only are many factors becoming really expensive due to their popularity, the realized historical returns were only half as good as they looked on paper. Since smart beta is all the rage RAFI is doing important work.
International Journal of Business and Management Invention (IJBMI)inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
Similar to Determinants of the implied equity risk premium in Brazil (20)
What are the chances of your country winning the 2018 World Cup?
FGV's mathematical model predicts that Brazil has the greatest chances of winning.
http://fgv.br/emap/copa-2018
Interval observer for uncertain time-varying SIR-SI model of vector-borne dis...FGV Brazil
The issue of state estimation is considered for an SIR-SI model describing a vector-borne disease such as dengue fever, with seasonal variations and uncertainties in the transmission rates. Assuming continuous measurement of the number of new infectives in the host population per unit time, a class of interval observers with estimate-dependent gain is constructed, and asymptotic error bounds are provided. The synthesis method is based on the search for a common linear Lyapunov function for monotone systems representing the evolution of the estimation errors.
Date: 2017
Authors:
Soledad Aronna, Maria
Bliman, Pierre-Alexandre
Ensuring successful introduction of Wolbachia in natural populations of Aedes...FGV Brazil
The control of the spread of dengue fever by introduction of the intracellular parasitic bacterium Wolbachia in populations of the vector Aedes aegypti, is presently one of the most promising tools for eliminating dengue, in the absence of an efficient vaccine. The success of this operation requires locally careful planning to determine the adequate number of individuals carrying the wolbachia parasite that need to be introduced into the natural population. The introduced mosquitoes are expected to eventually replace the Wolbachia-free population and guarantee permanent protection against the transmission of dengue to human. In this study, we propose and analyze a model describing the fundamental aspects of the competition between mosquitoes carrying Wolbachia and mosquitoes free of the parasite. We then use feedback control techniques to devise an introduction protocol which is proved to guarantee that the population converges to a stable equilibrium where the totality of mosquitoes carry Wolbachia.
Date: 2015-03-19
Authors:
Bliman, Pierre-Alexandre
Soledad Aronna, Maria
Coelho, Flávio Codeço
Silva, Moacyr da
The resource curse reloaded: revisiting the Dutch disease with economic compl...FGV Brazil
This paper shows that the Dutch disease can be more formally characterised as low economic complexity using ECI-type indicators; there is a solid and robust inverse relationship between exports concentrating on natural resources and economic complexity as measured by complexity indicators for a database of 122 countries from 1963 to 2013. In a large majority of cases, oil answers for shares in excess of 50% of exports. In addition to empirical panel analysis, we address case studies concerned with Indonesia and Nigeria and introduce a brief review of the theoretical literature on the topic. Indonesia is considered in the literature as a good example in avoiding the negative effects of the Dutch disease, whereas Nigeria is taken as a bad example in terms of institutions and policies adopted during the seventies and eighties. The empirical results show that complexity analysis and Big Data may offer significant contributions to the still-current debate surrounding the Dutch disease.
Date: 2017-03
Authors:
Camargo, Jhean Steffan Martines de
Gala, Paulo
The Economic Commission for Latin America (ECLA) was right: scale-free comple...FGV Brazil
The main purpose of this paper is to apply big-data and scale-free complex network techniques to the study of world trade, with a specific focus on the investigation of ECLA and structuralist ideas. A secondary objective is to illustrate the potentialities of the use of the new science of complex networks in economics, in what has been recently referred to as an econophysics research agenda. We work with a trade network of 101 countries and 762 products (SITC-4) which generated 1,756,224 trade links in 2013. The empirical results based on network analysis and computational methods reported here point in the direction of what ECLA economists used to argue; countries with higher income per capita concentrate in producing and exporting manufactured and complex goods at the center of the trade network; countries with lower income per capita specialize in producing and exporting non-complex commodities at the network’s periphery.
Date: 2017-03
Authors:
Gala, Paulo
Camargo, Jhean Steffan Martines de
Freitas, Elton
A dynamic Nelson-Siegel model with forward-looking indicators for the yield c...FGV Brazil
This paper proposes a Factor-Augmented Dynamic Nelson-Siegel (FADNS) model to predict the yield curve in the US that relies on a large data set of weekly financial and macroeconomic variables. The FADNS model significantly improves interest rate forecasts relative to the extant models in the literature. For longer horizons, it beats autoregressive alternatives, with a reduction in mean absolute error of up to 40%. For shorter horizons, it offers a good challenge to autoregressive forecasting models, outperforming them for the 7- and 10-year yields. The out-of-sample analysis shows that the good performance comes mostly from the forward-looking nature of the variables we employ. Including them reduces the mean absolute error in 5 basis points on average with respect to models that reflect only past macroeconomic events.
Date: 2017-03
Authors:
Vieira, Fausto José Araújo
Chague, Fernando Daniel
Fernandes, Marcelo
Improving on daily measures of price discoveryFGV Brazil
We formulate a continuous-time price discovery model in which the price discovery measure varies (stochastically) at daily frequency. We estimate daily measures of price discovery using a kernel-based OLS estimator instead of running separate daily VECM regressions as standard in the literature. We show that our estimator is not only consistent, but also outperforms the standard daily VECM in finite samples. We illustrate our theoretical findings by studying the price discovery process of 10 actively traded stocks in the U.S. from 2007 to 2013.
Date: 2017-03
Authors:
Dias, Gustavo Fruet
Fernandes, Marcelo
Scherrer, Cristina Mabel
Disentangling the effect of private and public cash flows on firm valueFGV Brazil
This paper presents a simple model for dual-class stock shares, in which common shareholders receive both public and private cash flows (i.e. dividends and any private benefit of holding voting rights) and preferred shareholders only receive public cash flows (i.e. dividends). The dual-class premium is driven not only by the firm's ability to generate cash flows, but also by voting rights. We isolate these two effects in order to identify the role of voting rights on equity-holders' wealth. In particular, we employ a cointegrated VAR model to retrieve the impact of the voting rights value on cash flow rights. We finnd a negative relation between the value of the voting right and the preferred shareholders' wealth for Brazilian cross- listed firms. In addition, we examine the connection between the voting right value and market and firm specific risks.
Date: 2017-03
Authors:
Autor
Scherrer, Cristina Mabel
Fernandes, Marcelo
Mandatory IFRS adoption in Brazil and firm valueFGV Brazil
Using diff-in-diff approaches and the propensity-score matching, this study focuses on firm-level Tobin´s q and Market-to-book outcomes for Brazilian firms who in 2008 were required by Law 11.638/07 to adopt the full International Financial Reporting Standards (IFRS) by 2010. Brazil’s tier-system of corporate governance standards for publicly-traded firms, its uniquely wholesale adoption of the IFRS, and the previously considerable gap between its national GAAP and IFRS readily lend the scenario to research, which thus far finds small or inconsistent results when focused on IFRS adoption-related outcomes in Europe and China. However, while these features recommend the transitioned Brazilian equity market to analysis, additional unique features, such as its small population size and its limited historical data -- of varied quality – increase the challenge in selecting a suitable empirical methodology. Using quarterly data from 2006-2011, control firms in the Nivel II and Novo Mercado tiers of Bovespa which already complied with higher quality accounting standards are matched to treatment firms in the Regular and Nivel I tiers with similar averaged values of size and sector. Our results suggest that there is a positive impact on Tobin´s q and Market-to-book for firms who are forced to adopt IFRS in Brazil. We can observe the same results when we consider all variables winsorized at 5% level. We also find a positive relation between the firm value (measured by Tobin´s q and Market-to-book) and net income. Firms with higher net income are more likely to have higher Tobin´s q and Market-tobook. In an opposite way, we find a negative relation among firm value, size, Ebit-to-sales, sales growth and PPE-to-sales. All results are statistically significant at 1% level. '
Date: 2017-03
Authors:
Sampaio, Joelson Oliveira
Gallucci Netto, Humberto
Silva, Vinícius Augusto Brunassi
Dotcom bubble and underpricing: conjectures and evidenceFGV Brazil
We provide conjectures for what caused the price spiral and the high underpricing of the dotcom bubble of 1999–2000. We raise two conjectures for the price spiral. First, given the uncertainty about the growth opportunities generated by the new technologies and their spillover effects across technology industries, investors saw the inflow of a large number of high-growth firms as a sign of high growth rates for the market as a whole. Second, investors interpreted the wave of highly underpriced IPOs as an opportunity to obtain gains by investing in newly public companies. The underpricing resulted from the emergence a large cohort of firms racing for market leadership. Fundamentals pricing at the IPO was part of their strategy. We provide evidence for our conjectures. We show that returns on NASDAQ composite index are explained by the flow of high-growth (or highly underpriced) IPOs; the high underpricing can be fully explained by firms’ characteristics and strategic goals. We also show that, contrary to alternatives explanations, underpricing was not associated with top underwriting, there was no deterioration of issuers’ quality, and top underwriters and analysts became more selective.
Date: 2017-03
Authors:
Autor
Carvalho, Antonio Gledson de
Pinheiro, Roberto Benjamin
Sampaio, Joelson Oliveira
Contingent judicial deference: theory and application to usury lawsFGV Brazil
Legislation that seems unreasonable to courts is less likely to be followed. Building on this premise, we propose a model and obtain two main results. First, the enactment of legislation prohibiting something raises the probability that courts will allow related things not expressly forbidden. In particular, the imposition of an interest rate ceiling can make it more likely that courts will validate contracts with interest rates below the legislated cap. Second, legal uncertainty is greater with legislation that commands little deference from courts than with legislation that commands none. We discuss examples of effects of legislated prohibitions (and, in particular, usury laws) that are consistent with the model.
Date: 2017-03
Authors:
Guimarães, Bernardo
Salama, Bruno Meyerhof
Education quality and returns to schooling: evidence from migrants in BrazilFGV Brazil
We provide a new education quality index for states within a developing country using 2010 Brazilian data. This measure is constructed based on the notion that the financial returns obtained from an additional year of schooling can be
seen as being derived from the value that market forces assign to this education. We use migrant data to estimate returns to schooling of individuals who studied in different states but who work in the same labor market. We find very heterogeneous educational qualities across states: the poorest Brazilian region presents education quality levels that are approximately equal to one-third of the average of all other regions, a gap three times larger than the one suggested by standardized test scores. We compare our index with standardized test scores, educational outcome variables, and public expenditure per schooling stage at the state level, producing new evidence related to education in a large developing country. We conduct an education quality-adjusted development accounting exercise for Brazilian states and find that human capital accounts for 26%-31% of output per worker differences. Adjusting for quality increases human capital’s explanatory power by 60%.
Date: 2017-02
Authors:
Brotherhood, Luiz Mário
Ferreira, Pedro Cavalcanti
Santos, Cézar Augusto Ramos
On October 31st and November 1st, 2016, the Center for Regulation and Infrastructure from Fundação Getulio Vargas (FGV CERI) organized a two-day workshop discussion in collaboration with the World Bank and ABRACE. The event gathered regulators, government representatives, academics, operators, financial institutions and investors. The debate focused on the main challenges faced by the current restructuring process of the Brazilian gas industry. This document presents the main points discussed during the debates.
Date: 2017-01
Authors:
Vazquez, Miguel
Amorim, Lívia
Dutra, Joísa Campanher
The impact of government equity investment on internationalization: the case ...FGV Brazil
We examine the impact of government equity ownership on the degree of internationalization of emerging market firms. Our analysis of 173 Brazilian publicly traded firms from 2002 to 2011 shows that the higher the equity held by the state through the state investment bank and the pension funds of SOEs and privatized SOEs, the higher the firm’s degree of internationalization. Firms in which the government shared control with families, and with both families and foreigners, had a higher degree of internationalization. Our findings underline the importance of the institutional context in explaining the internationalization of Brazilian firms.
Date: 2016
Author:
Sheng, Hsia Hua
Techno-government networks: Actor-Network Theory in electronic government res...FGV Brazil
The Actor-Network Theory (ANT) is a theoretical approach for the study of controversies associated with scientific discoveries and technological innovations through the networks of actors involved in such actions. This approach has generated studies in Information Systems (IS) since 1990, however few studies have examined the use of this approach in the e-government area. Thus, this paper aims to broaden the theoretical approaches on e-government, by presenting ANT as a theoretical framework for e-government studies via published empirical work. For this reason, the historical background of ANT is described, duly listing its theoretical and methodological premises. In addition to this, one presented ANT-based e-government works, in order to illustrate how ANT can be applied in empirical studies in this knowledge area.
Date: 2016
Authors:
Fornazin, Marcelo
Joia, Luiz Antonio
Condemning corruption while condoning inefficiency: an experimental investiga...FGV Brazil
This article reports results from an economic experiment that investigates to what extent voters punish corruption and waste in elections. While both are responsible for a loss of welfare for voters, they are not necessarily perceived as equally immoral. The empirical literature in political agency has not yet dealt with these two dimensions that determine voters’ choices. Our results suggest that morality and norms are indeed crucial for a superior voting equilibrium in systems with heterogeneous politicians: while corruption is always punished, self-interest alone – in the absence of norms – leads to the acceptance and perpetuation of waste and social losses.
Date: 2016
Authors:
Arvate, Paulo Roberto
Souza, Sergio Mittlaender Leme de
Coalition management under divided/unified governmentFGV Brazil
"If the opposite of pro is con, then the opposite of progress must be the Congress”, says a popular joke about the divided government in the US two-party presidential regime. Divided government occurs when different political parties control different branches of government. By this arithmetic definition, however, divided government almost always takes place in multiparty presidential regimes, given that the party of the president rarely obtains solely the majority of seats in Congress. In order to govern and pass legislation, a minority president has to build and sustain post-electoral coalitions in multiparty settings. The received wisdom on multiparty presidential regime is that constitutional and agenda-setting powers and presidential preferences would be the key determinants for a successful minority government. In addition to those aspects, however, this paper claims that the degree of congruence between the preference of the presidential coalition and the preference of the floor of the Congress is the crucial ingredient. That is, regardless of presidential preferences or characteristics, the higher the preference incongruence between the president’s coalition and the floor, the more difficult would be the coalition management and the higher the probability that the Congress would work as the opposite of progress. It is, in fact, the equivalent functional of divided government in multiparty presidential settings. This paper explores conceptually and empirically the effect of the distance of preferences between the coalition and the floor in the multiparty presidential regimes in Latin America.
Date: 2016
Authors:
Pereira, Carlos
Melo, Marcus André B. C. de
Bertholini, Frederico
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
What website can I sell pi coins securely.DOT TECH
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the telegram contact of my personal pi merchant to trade with.
Tele-gram.
@Pi_vendor_247
Even tho Pi network is not listed on any exchange yet.
Buying/Selling or investing in pi network coins is highly possible through the help of vendors. You can buy from vendors[ buy directly from the pi network miners and resell it]. I will leave the telegram contact of my personal vendor.
@Pi_vendor_247
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
NO1 Uk Divorce problem uk all amil baba in karachi,lahore,pakistan talaq ka m...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
when will pi network coin be available on crypto exchange.DOT TECH
There is no set date for when Pi coins will enter the market.
However, the developers are working hard to get them released as soon as possible.
Once they are available, users will be able to exchange other cryptocurrencies for Pi coins on designated exchanges.
But for now the only way to sell your pi coins is through verified pi vendor.
Here is the telegram contact of my personal pi vendor
@Pi_vendor_247
Latino Buying Power - May 2024 Presentation for Latino CaucusDanay Escanaverino
Unlock the potential of Latino Buying Power with this in-depth SlideShare presentation. Explore how the Latino consumer market is transforming the American economy, driven by their significant buying power, entrepreneurial contributions, and growing influence across various sectors.
**Key Sections Covered:**
1. **Economic Impact:** Understand the profound economic impact of Latino consumers on the U.S. economy. Discover how their increasing purchasing power is fueling growth in key industries and contributing to national economic prosperity.
2. **Buying Power:** Dive into detailed analyses of Latino buying power, including its growth trends, key drivers, and projections for the future. Learn how this influential group’s spending habits are shaping market dynamics and creating opportunities for businesses.
3. **Entrepreneurial Contributions:** Explore the entrepreneurial spirit within the Latino community. Examine how Latino-owned businesses are thriving and contributing to job creation, innovation, and economic diversification.
4. **Workforce Statistics:** Gain insights into the role of Latino workers in the American labor market. Review statistics on employment rates, occupational distribution, and the economic contributions of Latino professionals across various industries.
5. **Media Consumption:** Understand the media consumption habits of Latino audiences. Discover their preferences for digital platforms, television, radio, and social media. Learn how these consumption patterns are influencing advertising strategies and media content.
6. **Education:** Examine the educational achievements and challenges within the Latino community. Review statistics on enrollment, graduation rates, and fields of study. Understand the implications of education on economic mobility and workforce readiness.
7. **Home Ownership:** Explore trends in Latino home ownership. Understand the factors driving home buying decisions, the challenges faced by Latino homeowners, and the impact of home ownership on community stability and economic growth.
This SlideShare provides valuable insights for marketers, business owners, policymakers, and anyone interested in the economic influence of the Latino community. By understanding the various facets of Latino buying power, you can effectively engage with this dynamic and growing market segment.
Equip yourself with the knowledge to leverage Latino buying power, tap into their entrepreneurial spirit, and connect with their unique cultural and consumer preferences. Drive your business success by embracing the economic potential of Latino consumers.
**Keywords:** Latino buying power, economic impact, entrepreneurial contributions, workforce statistics, media consumption, education, home ownership, Latino market, Hispanic buying power, Latino purchasing power.
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
how to sell pi coins on Bitmart crypto exchangeDOT TECH
Yes. Pi network coins can be exchanged but not on bitmart exchange. Because pi network is still in the enclosed mainnet. The only way pioneers are able to trade pi coins is by reselling the pi coins to pi verified merchants.
A verified merchant is someone who buys pi network coins and resell it to exchanges looking forward to hold till mainnet launch.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
2. TEXTO PARA DISCUSSÃO 430 • SETEMBRO DE 2016 • 1
Os artigos dos Textos para Discussão da Escola de Economia de São Paulo da Fundação Getulio
Vargas são de inteira responsabilidade dos autores e não refletem necessariamente a opinião da
FGV-EESP. É permitida a reprodução total ou parcial dos artigos, desde que creditada a fonte.
Escola de Economia de São Paulo da Fundação Getulio Vargas FGV-EESP
www.eesp.fgv.br
3. 1
Determinants of the Implied Equity Risk Premium in Brazil
Antonio Zoratto Sanvicente, Escola de Economia de São Paulo, Fundação Getúlio
Vargas
Mauricio Rocha Carvalho, Insper, Instituto de Ensino e Pesquisa
April 2016
Abstract
This paper proposes and tests market determinants of the equity risk premium (ERP) in
Brazil. We use implied ERP, based on the Elton (1999) critique. The ultimate goal of
this exercise is to demonstrate that the calculation of implied, as opposed to historical
ERP makes sense, because it varies, in the expected direction, with changes in
fundamental market indicators. The ERP for Brazil is calculated as a mean of large
samples of individual stock prices in each month in the January, 1995 to September,
2015 period, using the “implied risk premium” approach. As determinants of changes in
the ERP we obtain, as significant, and in the expected direction: changes in the CDI
rate, in the country debt risk spread, in the US market liquidity premium and in the level
of the S&P500. The influence of the proposed determining factors is tested with the use
of time series regression analysis. The possibility of a change in that relationship with
the 2008 crisis was also tested, and the results indicate that the global financial crisis
had no significant impact on the nature of the relationship between the ERP and its
determining factors. For comparison purposes, we also consider the same variables as
determinants of the ERP calculated with average historical returns, as is common in
professional practice. First, the constructed series does not exhibit any relationship to
known market-events. Second, the variables found to be significantly associated with
historical ERP do not exhibit any intuitive relationship with compensation for market
risk.
Keywords: Equity risk premium; Discounted dividend model; Capital asset pricing
model.
4. 2
1. Introduction
Any stock’s market risk premium, or “equity risk premium” (ERP), is given by the
difference between the expected return on the market portfolio and the rate of return on
the market’s risk-free asset. From one stock to another, the actual risk premium varies
with the particular stock’s beta, or sensitivity to returns on the market portfolio.
In many important applications, estimates of the expected return on the market portfolio
are made using averages of historical differences between returns on a stock market
index, such as the Standard & Poor’s 500 (S&P500) and a return on a riskless asset,
such as U.S. Treasury notes or bonds.
In Brazil, those important applications include: (a) the determination of discount rates in
order to value stocks of firms in acquisition and/or going private offers (OPAs); (b) the
setting of so-called “regulatory internal rates of return” for companies in regulated
sectors, such as electric power generation and distribution, highways, natural gas
distribution, among others. Internally, firms may need to calculate their cost of equity
capital as part of variable compensation schemes, or in the computation of their
weighted-average cost of capital when valuing new investment opportunities. This is
done because the Sharpe (1964), Lintner (1965), and Mossin (1966) version of the
capital asset pricing model (CAPM) is used in the construction of the relevant security
market line for estimating the appropriate opportunity cost of equity.
Two main issues stand out: (a) the already-mentioned use of historical return averages,
as opposed to current levels of the market portfolio’s expected return, in stark conflict
with the concept of an opportunity cost – for an individual or a firm that needs to make
an investment decision, the relevant cost should be that prevailing at the moment the
decision must be made, and not an average of what occurred in the past;1
(b) because
the available history for the Brazilian stock market is “short”, when compared to that of
the U.S. market, for example, one should use a U.S. market index as a proxy for the
market portfolio, and not Brazilian stock prices and returns, even when calculating an
equity risk premium for the Brazilian market.
In the present paper, we explain how to get around using historical averages as a basis
of estimating expected returns on the market portfolio, by describing a straightforward
procedure for obtaining the required expectation from current stock market prices. This
is known as an “implied” equity risk premium. We then present the resulting series for
the January 1995-September 2015 period, pointing out special situations, or “crises” in
which the expected market portfolio return spiked, as would be natural, as
compensation for sharp increases in the general level of risk perceived in the market.
1
In previous discussions, the authors have met with the contention that, if one uses historical averages of
very long periods of time, such as those available for the U.S. stock market, then the resulting estimate
would be “representative”. To this contention we simply offer the argument that, putting weak market
efficient considerations aside, this would be equivalent to saying that the distribution of rates of return is
stable throughout the historical period used, and that the “law of large numbers” applies, which simply
does not make sense in the case of financial asset prices and returns. It is much more plausible to admit
that the distribution of rates of return changes frequently and that one would do better by using an
approach that does not rely on assuming that the law of large numbers applies. Obviously, an historical
average does not change very frequently, but only with the slow addition of new observations as time
passes by.
5. 3
We also test the significance and direction of the relationship between easily observed
market fundamentals and our estimate for the market portfolio’s return, and show that
the results are significant for certain fundamentals, and in the appropriate direction.
An alternative manner in which one can point out to problems with the use of historical
returns in the computation of equity risk premiums is to mention that the approach is
based on the assumption that information surprises involving business firms tend to
cancel each other over time, so that past behavior would become an unbiased estimator
of future behavior. Elton (1999) questions this fact, demonstrating that, in practice, this
has not occurred. Damodaran (2011) points out that this methodology puts us at a
crossroad: if we use a very long historical period in order to have a representative
sample (such as Ibbotson (2010), whose series starts in 1926), we would have to assume
that investors’ risk profiles and market fundamentals remained constant throughout that
period. On the other hand, if we reduce the period to the last 40 or 20 years, say, high
return volatility would produce unacceptably high standard errors. If that is the case for
a mature and liquid market such as the United States, that effect would certainly be
amplified in emerging markets such as Brazil. In addition, there is survivorship bias.
Market histories are studied with the use of stock indices, and clear evidence for this
bias in successful stock markets are presented and discussed in Brown et al. (1995).
The use of an implied premium is predicated on the idea that valuation and analysis
exercises must look forward in time and incorporate market expectations. Gebhardt et
al. (1999) use residual income models to estimate the implied cost of equity as the
internal rate of return produced by forecasted earnings, and implicit in current stock
prices. Claus and Thomas (1999) use the same idea in the aggregate. Damodaran (2011)
calculates the implied premium for the American and Brazilian markets.
The fact that implied risk premium and cost of equity calculations are gaining relevance
at the expense of the historical return approach is emphasized by Nekrasov and Ogneva
(2011), who enumerate some of the following applications: shedding light on the equity
premium puzzle (Claus and Thomas, 2001; Easton et al., 2002); the market’s perception
of equity risk (Gebhardt et al., 2001); risk associated with accounting restatements
(Hribar and Jenkins, 2004); legal institutions and regulatory regimes (Hail and Leuz,
2006); tests of the inter-temporal CAPM (Pastor et al., 2008), among others.
More recently, the cost of equity estimated with implied risk premium has been used as
dependent variable in corporate finance research, such as, for example, in Javakhadze et
al. (2016), in which the influence of managerial social capital, that is, the capital
constructed with the development of managers’ networks, benefits a firm through a
reduction in its cost of equity. The cost of equity was estimated with the use of the
dividend discount model, with data for 729 firms in all continents. Lima and Sanvicente
(2013) present evidence that better governance leads to reductions in the cost of equity
in the Brazilian market.
Hsing et al. (2011) applied the EGARCH model to the Brazilian stock index during
1997 until 2010 and find correlations with a few aggregate economic variables. The
market seems to be positively affected by industrial production, the ratio of M2 money
supply to GDP and the US stock market index. They also found a negative impact of the
lending rate, currency depreciation and domestic inflation.
6. 4
Camacho and Lemme (2004) compared a set of 22 Brazilian companies with
investments abroad using two models: a Global CAPM and a Local CAPM to
investigate whether the cost of equity capital of Brazilian companies employed on
international investments should be greater than that used on national projects,
assuming an integrated market. They concluded that it is not correct to add any risk
premiums to the cost of domestic equity capital.
Ferreira (2011) observed the correlations between Brazilian macroeconomic variables
and the implied risk premium calculated using monthly data on stocks traded on the
Bovespa from January 2005 until December 2010. The results showed that the equity
risk premium demanded by investors is positively affected by the unexpected inflation
rate, the growth in money supply, the real interest rate, the output gap and it is
negatively affected by GDP growth.
A methodology for estimating the implied equity risk premium for the Brazilian market
is suggested in Minardi et alii. (2007). The proposal is to use business firm
fundamentals such as return on equity and payout ratio as inputs to the Gordon formula.
This is how the ERP for the Brazilian market is measured in the present paper.
The paper is organized as follows: section 2 reviews the literature, including previous
uses and tests of determinants of the ERP; section 3 describes the methodology for the
calculation of the ERP as implied by current stock prices; section 4 presents the
methodology for the analysis of risk premium determinants, including both the model
specification and the data used; the results are provided in section 5, and section 6
concludes and discusses both limitations and possible extensions.
2. Review of literature: implied equity risk premium and cost of equity
Claus and Thomas (1999) proposed a new approach to estimating the equity risk
premium for the U.S. market. This involved aggregating individual firm data and
determining the equity risk premium implied in current stock prices for a number of
firms, ranging from 1,559 in 1985 to 3,673 in 1998. Hence, they estimated a so-called
“implied market risk premium”. The implied equity risk premium was obtained as the
internal rate of return (k), in the following equation:
3 5 51 2 4
0 0 2 3 4 5 5
(1 '')
(1)
(1 ) (1 ) (1 ) (1 ) (1 ) ( '')(1 )
ae ae ae gae ae ae
p bv
k k k k k k g k
Where, for the end of each year (t = 0,…,5):
p0 = current stock market price;
bv0 = book value of the firm’s equity, as disclosed in its financial statements;
aet = abnormal earnings, equal to reported earnings minus a charge for the cost of
equity, i.e., the product of beginning book value of equity and the implied rate of return;
this means that projected earnings for year t are given by et = bvt-1 + 0.5 x et-1, where the
et are analysts’ earnings forecasts; this is the so-called “clean surplus” approach, with
the added assumption of a common 50% payout ratio for all firms;
g’’
= the assumed constant growth rate in earnings in perpetuity, fixed at the real risk
free rate, that is, the then current 10-year T-bond rate minus 3% p. a. This growth rate is
applied to all earnings projected for t > 5, so that the last term in the equation above
7. 5
represents what is usually referred to as the equity’s terminal value. In the calculation of
abnormal earnings for t = 1 to 5, the authors directly used analysts’ forecasts for years 1
and 2. For the remaining years (t = 3 to 5), they used g’, the implied growth rate in
analysts’ forecast for long-term earnings, that is, the forecasted 5-year growth rate.
This approach produced estimates of the equity risk premium of approximately 3% p.
a., with a low of 2.51% in 1997 and a high of 3.97% in 1995. This corresponds to
around half of the usually obtained premium on the basis of historical returns, that
apparently high level being the source of the so-called “equity premium puzzle” (Mehra
and Prescott, 1985).
In the calculation of the risk premium, the authors use the end-of-year 10-year Treasury
bond yield. They also discuss why this is an appropriate benchmark rate:
“There is some debate as to which maturity is appropriate when selecting the risk-free
rate. The risk premium literature has used both shorter (30-day or 1-year) and longer
(30-year) maturities for the risk-free rate. On the one hand, longer maturities exceed
the true risk-free rate because they incorporate the uncertainty associated with
intermediate variation in risk-free rates. On the other hand, short-term rates are likely
to be below the true risk-free rate, since some portion of the observed upward sloping
term structure could reflect increases in expected future short-term rates. Since the
flows (dividends or abnormal earnings) being discounted extend beyond one year, it
would not be appropriate to use the current short-term rate to discount flows that
have been forecast based on rising interest rates.” (Claus and Thomas, 1999, p. 16-
17)
In the appendix to their working paper, Claus and Thomas (1999) demonstrated that this
“accounting-based valuation model” is equivalent to the dividend growth approach used
in the present paper.
Claus and Thomas (1999) argue that, since earnings can be replaced by the
corresponding dividends in the equation above, one might think that there would be no
benefit in the use of earnings instead of dividends. Their contention, however, is: “the
main problem with using the dividend growth model resides in the arbitrary choice of
the assumed rate at which dividends grow in perpetuity” (Claus and Thomas, 1999, p.
9). This seems to be a strange argument, however, given their own need to propose a
value and a rationale for their g’’ rate.
Their working paper also makes an interesting and relevant comment on the relationship
between market efficiency and their approach to estimating an implied equity risk
premium (and any other approach based on current market prices, for that matter):
“Like other ex ante approaches, our approach assumes that the stock market
efficiently incorporates analyst forecasts into prices, and that analysts make unbiased
forecasts. There is however, a large body of research that has documented instances
of mispricing relating to information available in analyst forecasts, and also evidence
of various biases exhibited by analysts. Fortunately, the extent of mispricing
documented is relatively small. Also, the evidence on mispricing suggests that some
firms are underpriced and others are overpriced. Therefore, some of that mispricing
should cancel out at the market level, and be of less concern for our market-level
8. 6
study”. (Claus and Thomas, 1999, pp. 10-11) [Emphasis added, since this applies fully
to our own approach in this paper.]
In several instances, Claus and Thomas (1999) refer to biases in analysts’ forecasts.
This is a problem avoided in our approach, as described in section 3, since the only
forecast we are required to make is the growth rate in perpetuity, from time t = 0 on,
given our assumed earnings and dividends growth process. In addition, the existing
coverage and availability of earnings forecasts by analysts for Brazilian firms is much
more limited:
“Turning to the issue of analysts making efficient forecasts, although some of the
biases exhibited by analysts would similarly cancel out in the aggregate, there is
evidence of a systematic optimism bias in analysts’ earnings forecasts.” (Claus and
Thomas, 1999, p. 11)
“Very few firms had negative values for 2-year-ahead forecasts, even though quite a
few firms reported losses in the current year.” (Claus and Thomas, 1999, p. 13)
“The contrast between our results and the traditional estimates of risk premium is
even starker in light of the well-known optimism in analyst forecasts.” (Claus and
Thomas, 1999, p. 19)
They point out that a downward adjustment in the implied risk premium would be
required to account for that optimism.
Finally, Claus and Thomas (1999) claim that their approach produces less variable
estimates than the dividend growth approach, and they believe this is a desirable
property, claiming that this is consistent with the view that the abnormal earnings
approach provides more reliable estimates. This is based on a comparison of the
resulting annual averages for k (the discount rate for projected abnormal earnings) and
for k* (the discount rate for projected dividends).
However, a counterargument would be as follows: since the resulting differences in
variability cannot be attributed to price variability, as the same prices are used in both
cases, it would be possible to attribute the lower variability of the earnings approach to
the management of disclosed earnings that they were not able to control for. In contrast,
dividend payments, even when based on managed earnings, are still dependent on a
decision, by a firm, that takes into account its capacity to make cash distributions to
investors, rendering dividends a more informative or even reliable indication of the
firm’s profitability prospects.
Gebhardt et al. (2001) use a similar approach to Claus and Thomas (1999): implied
costs of equity are estimated as the internal rate of return on projected earnings.
However, instead of making an attempt at estimating a market-wide average equity risk
premium, they test for several determinants of individual firm equity risk premiums.
Not surprisingly, proxies for risk (such as sector membership) and the magnitude of
growth opportunities (book-to-market ratio and forecasted long-term growth rate) prove
to be significant. Together with the dispersion in analyst earnings forecasts, they explain
approximately 60% of the variation in the cross section of implied costs of capital.
9. 7
At the time, this article was part of an effort to answer the call by Elton (1999) for the
need for new approaches to risk premium estimation. Elton’s argument was as follows:
“Our approach is distinct from most of the prior empirical work on asset pricing in that
it does not rely on average realized returns.” (Elton, 1999, p. 2)
Operationally, they limit their earnings forecasting horizon to 3 years, instead of the 5-
year horizon in Claus and Thomas (1999), due to the availability of analyst forecasts,
thus circumventing the need for estimating the implied growth rate up to five years, as
described in Claus and Thomas (1999). They then make projections of annual earnings
up to 12 years. At t = 12 a terminal is value is computed. From t = 3 to t = 12, they
make the assumption that each firm’s return on equity (ROE) declines linearly to the
industry average. From t = 13 on, ROE is assumed to be equal to the cost of equity,
implying that there is no positive net present value contribution. This assumption is
used for all firms in their analysis, which range in number from 1,044 in 1979 to 1,333
in 1995. As in Claus and Thomas (1999), their proxy for the risk-free rate is also the 10-
year Treasury bond yield.
Because of these small differences in approach to Claus and Thomas (1999), they obtain
an average 2.7% equity risk premium for the entire period. However, their annual non-
weighted mean for the equity risk premium ranges from a high of 5.2% in 1979 to a low
of -0.2% in 1984. Note that these two years were not included in the Claus and Thomas
(1999) study which, as mentioned previously, covered the period from 1985 to 1998. In
their common coverage period (1985-1995), the two studies reported very similar
results, at least in terms of annual changes in the risk premium level. The overall period
averages in the common period are 3.44% p. a. (Claus and Thomas, 1999) and 3.17% p.
a. (Gebhardt et al., 2001). It should also be noted that the Claus and Thomas (1999)
“market-wide” premiums were computed as size-weighted averages of individual firm
estimates, not to mention the fact that the sample size in Claus and Thomas (1999) was
much larger, especially towards the end of the period they analyzed.
As a result of the dissatisfaction with the use of historical returns in tests of asset pricing
models, Elton’s American Finance Presidential Address (1999) makes a plea for the
adoption of new approaches.
Initially, he reminds us that “almost all of the testing” (Elton, 1999, p. 1199) involves
the use of realized returns as a proxy for expected returns, with the crucial reliance on
the belief that information surprises tend to cancel each other out over a study period, so
that realized returns would be an unbiased estimate of expected returns. As the reader
perfectly knows, asset pricing models do not purport to explain the setting of realized
returns, but of equilibrium expected returns.
Elton (1999) goes on to highlight long periods during which the average of stock market
returns was lower than the risk-free rate (from 1973 to 1984 in the US), as well as
periods in which the returns on risky longer-term bonds were also lower than the risk-
free rate (1927 to 1981). As he describes it, “… 11 and over 50 years is an awfully long
time for such a weak condition [that a risky asset should earn more than the risk-free
asset] not to be satisfied.” (Elton, 1999, p. 1199)
His main argument is that the plausible explanation of such apparently anomalous
results is that realized returns are poor measures of expected returns, since
10. 8
“… information surprises highly influence a number of factors in our asset pricing
model. I believe that developing better measures of expected return and alternative
ways of testing asset pricing theories that do not require using realized returns
have a much higher payoff than any additional development of statistical tests that
continue to rely on realized returns as a proxy for expected returns.” (Elton, 1999,
p. 1199-1200) [Emphasis added]
A simple, but useful formalization of Elton’s (1999) point is as follows. Realized
returns can be decomposed into expected and unexpected returns:
1( ) (2)t t t tR E R e
where Rt is return in period t, Et-1(Rt) is expected return at t, conditional on the
information set available at time t - 1, and et is unexpected return.
In the discussion of stock market returns, the existing theories say that unexpected
return is caused by systematic factor shocks or unique firm-specific events. When one
uses realized returns as a proxy for expected returns, the hope is that unexpected returns
are independent. This would mean that, over long observation intervals, such as that
used as the basis for U.S. market premiums (usually, from 1926 on), those unexpected
returns tend to a mean of zero.
Elton’s argument, however, is that there tend to be information surprises which are very
large, or that a sequence of such surprises is correlated. This would make their
cumulative effect so large as to have a significant and permanent effect on the realized
mean, and would not disappear even as the observation interval becomes large.
The model he proposes is:
1( ) (3)t t t t tR E R I
where It is a significant information event. For Elton (1999), It is often equal to zero, but
occasionally it is a very large number (positive or negative). Hence, unexpected returns,
et = It + εt are in fact a mixture of two distributions, one with the usual properties (the εt,
independent and with zero mean), and a jump process for It.
Elton (1999) mentions the “McDonald’s effect” as an example of such a process. This
had to do with the fact that, in the 1950’s and 1960’s, there tended to be positive
earnings surprises for several years in succession. The series of high positive returns on
McDonald’s stock, when efficient frontiers were constructed on the basis of realized
returns tended to produce portfolios dominated by McDonald’s, and these “were simply
not credible”. (Elton, 1999, p. 1201)
Another example, and much closer to the present paper, is the effect of important
market-wide crises, such as that in the latter part of 2008. The effect of such a shock on
realized returns and their eventual use as the basis of estimates of risk premiums is
illustrated in Sanvicente (2012), with a focus on the use of such estimates by regulatory
agencies in Brazil.
11. 9
3. Calculation of ERP implicit in current Brazilian market prices
The starting point in our ERP estimation methodology is the so-called Gordon model,
first proposed in Gordon (1959), which assumes that a stock’s dividends grow at the
constant rate g per period. The stock’s intrinsic value corresponds to the present value
of the stream of future dividends, discounted at ke, the firm’s opportunity cost of equity.
Given that dividends are assumed to grow at a constant rate, intrinsic value (V0) is the
present value of a perpetual stream of cash flows, and is obtained as follows:
1
0 (4)
e
D
V
k g
where D1 is the dividend per share to be paid at the end of the first period (year).
Under the assumption that observed prices (P0) are equal to intrinsic values, except for a
random error, we can state that prices will contain information on the stock’s required
return, so that required return could be estimated as follows, for each individual stock:
1
0
(5)e
D
k g
P
We then construct the required return on the market portfolio, assumed to be equal to
the expected return, given the assumed equivalence of observed prices and intrinsic
values, by computing an average of the required returns for a representative sample of
individual stocks. In the tests run in this paper, we use a simple average, implying that
the proxy for the market portfolio is an equally-weighted portfolio of the stocks
included in the sample. Therefore, our assumed equality between observed prices and
intrinsic values is being proposed, not on a security-by-security basis, but on average for
the entire sample representing the market.
Prices P0 are directly observed. Given that 1 0 (1 )D D g , and D0 (current dividend per
share) is also observed, the remaining task is to estimate the so-called “sustainable”
growth rate g (see Ross et al., 2012). Without changing either financing or dividend
policy, a firm can maintain the growth rate in both earnings and dividends through the
following relationship:
(6)g ROE b
where ROE = return on equity, or net income after taxes/net worth, and b = earnings
retention rate, or (1 – payout).
Since information on recent values of ROE, payout ratios and dividends per share are
available from financial statements, and prices are directly and continuously observed,
all the necessary data for estimating individual stock values for ke and calculating their
simple average are easily accessible.
In turn, the risk-free rate is obtained from current quotes of U.S. Treasury notes. Since
these instruments pay their income in U.S. dollars, we convert the local market data
using the Brazilian Real/U.S. dollar rate at each point in time.
12. 10
The sample of individual stocks is processed as follows, for each month in the series:
a. Closing prices, 12-month net income, dividends and net worth per share are
collected. Obviously, stocks not traded at the end of any month are excluded from
the sample for that month. This still leaves a sample size, from January 1995 to
September 2015, of at least 90 firms, using only one class of stock for each firm in
the sample, which does not include financial institutions.
b. ROE and payout are computed as the ratios of net income/net worth, both on a per
share basis, and dividends per share/after-tax net income per share, respectively.
c. ROE and payout values are used for estimating g.
d. Equation (5) is then used in the estimation of ke, given the estimated values of D1 and
g, and the observed prices P0.
e. The simple average of the resulting individual values of ke is computed. This is the
estimate for the expected (required) return on the market.
f. The last step to calculate the ERP is to subtract, from the expected return on the
market (E(r)), the risk-free rate, obtained from current quotes of U.S. Treasury notes.
The procedure outlined above resulted in the following monthly series for the Brazilian
market’s ERP depicted in Figure 1.
Figure 1: Implied ERP (% p. a.) in Brazil, Jan. 1995 to Sept. 2015.
Figure 1 demonstrates that the implied version of the ERP for the Brazilian market is
very sensitive to the occurrence of economic or financial crises, as it should be. The
equity risk premium increased during the second semester of 1998 and the first semester
of 1999, a period marked first by the Russian crisis, immediately followed by Brazil’s
change of exchange rate regime. We can also note sharp increases in the ERP in the
second semester of 2001 (WTC 9/11 attacks); during the end of 2002 and until the end
of 2003 (Lula’s first presidential campaign and first year in office) and in the second
semester of 2008 (Subprime Crisis and Lehman Brothers Default).
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
30,00%
jan/95
jul/95
jan/96
jul/96
jan/97
jul/97
jan/98
jul/98
jan/99
jul/99
jan/00
jul/00
jan/01
jul/01
jan/02
jul/02
jan/03
jul/03
jan/04
jul/04
jan/05
jul/05
jan/06
jul/06
jan/07
jul/07
jan/08
jul/08
jan/09
jul/09
jan/10
jul/10
jan/11
jul/11
jan/12
jul/12
jan/13
jul/13
jan/14
jul/14
jan/15
jul/15
Equity Risk Premium (ERP)
13. 11
This sensitivity, in spite of being a drawback of the approach of estimating ERP with
current market prices, is a distinct advantage. It makes the ERP estimate responsive to
current market conditions, and hence a substantially more representative “price” of risk
than the estimates based on historical returns.
When a crisis ensues, there is an increase in the overall market aversion to risky assets;
investors demand higher returns in order to hold such assets. This is equivalent to seeing
investors discount future cash flows to those assets at higher rates, of which the ERP is
a common component. This process produces lower market valuations. In our approach,
this is represented by lower values for P0, higher values for ke, and hence, higher
estimates for the ERP. This sensitivity to changes in market conditions is a property that
the historical ERP approach does not possess. A dramatic example of the failure of the
historical ERP in this regard is provided in Sanvicente (2012), using data for the 2008
global financial crisis.
4. Methodology and data
We propose to explain the time series of implied ERP for Brazil using market variables,
or “fundamentals”. We believe they contain sufficient information about
macroeconomic data and expectations, with the advantage of being observed more
frequently and with no significant delays.
The basic specification proposes that the equity risk premium in Brazil is a function of
the exchange rate, the volatility of the Brazilian stock exchange, the volume traded in
the local stock market, the basic domestic interest rate, the U.S. liquidity premium,
Brazil’s country risk, the level of the stock exchange in the U.S., the price of gold, and
the domestic credit risk premium:
DERP = f(RPTAX, DVOLATIBOV, RVOLUMEIBOV, DCDI, DLIQPREM,
DRISKBR, RSP500, RGOLD, DCREDRISK)
Where:
DERP = first difference for the estimated value of the ERP
RPTAX = % change in the exchange rate of Reais to US$
DVOLATIBOV = first difference for historical Ibovespa volatility
RVOLUMEIBOV = % change in volume of trading in the Brazilian stock market
DCDI = first difference in domestic interest rates, proxied by the interbank market rate
DLIQPREM = first difference in the liquidity premium in international markets,
measured by the difference between US TBond (30-year) and TNote (10-year) yields
DRISKBR = first difference for the Brazil country risk spread, as measured by J. P.
Morgan’s EMBI+
RSP500 = rate of return on the S&P 500 index
RGOLD = % change in gold prices
DCREDRISK = first difference in a measure of credit default risk in Brazil, represented
by the spread between the average commercial bank lending rate to corporations and the
CDI (Brazilian Interbank Rate) on an annual basis.
14. 12
5. Results
Every individual variable listed above was checked for stationarity and unit roots, and
transformed with the calculation of first differences or the computation of a rate-of-
return format, that is, a log return format, as indicated in their definitions.
Initially, an analysis of partial correlation coefficients revealed, as prime candidates for
explaining the time series of changes (first differences) in the estimated equity risk
premium for Brazil in the 1995-2015 period: (a) changes in the level of volatility in the
local stock market (DVOLATIBOV, partial correlation coefficient of 0.1999); (b)
changes in the domestic market basic interest rate (DCDI, 0.2934); (c) changes in the
liquidity premium (DLIQPREM. 0.2173); (d) changes in the country risk premium
(RRISKBR, 0.3182); (e) returns on the international stock market, as proxied by the
S&P500 (RSP500, -0.2916). Since we are using monthly data for the January 1995 to
September 2015 period, and given the computation of first differences or relative
changes in several variables, this means the use of 248 observations.
All these variables, with the exception of the return on the international stock market,
have positive partial correlations with the changes in the estimated ERP. Since they are
all proxies for one type of risk or another, or compensations for risk, indications are
that, when they rise, required returns on the local stock market also increase, as a
response to higher risk levels. In the particular case of DCDI, the reason is more likely
an increase in the risk-free rate that is part of the required rate at which expected cash
flows to equities are discounted, resulting in lower stock prices and, given our method
of estimating the ERP, resulting in higher ERP values.
The only variable for which a substantial negative partial correlation is found is
RSP500. The result can be interpreted in the following manner: when stock prices rise
in the U.S. market, so that returns on the S&P500 are positive, since this is seen as good
news, we tend to observe higher prices in the local stock market, leading to lower
estimated ERP values.
In terms of partial correlations involving pairs of possible candidates as explanatory
variables, and eventual sources of multicollinearity problems, the high positive
correlations between changes in the exchange rate (RPTAX) and both the price of gold
(RGOLD) and the country risk premium (DRISKBR) stand out, at 0.6977 and 0.5318,
respectively, as well as the negative correlation (-0.4807) for the pair DRISKBR-
RSP500. Cases such as these, however, are dealt with in the estimation of a reasonable
model for explaining DERP, in what follows, after the use of variance-inflation factor
(VIF) analysis. This analysis revealed that the highest factor value was equal to 6.0531
for RPTAX. Since the rule of thumb is to consider excluding a variable for which VIF >
10, no variable was excluded. The full model was then estimated and the results are
displayed in Table 2.
15. 13
Table 2: Regression model results. Dependent variable is DERP = first difference
of estimated equity risk premium (ERP). 248 observations.
Variable Coefficient
(standard error)
Intercept 0.0009
(0.0007)
RPTAX -0.0135
(0.0210)
DVOLATIBOV 0.0263
(0.0403)
RVOLUMEIBOV -0.0047
(0.0030)
DCDI 0.1084***
(0.0285)
DLIQPREM 1.7708***
(0.5966)
DRISKBR 0.2206**
(0.1103)
RSP500 -0.0530***
(0.0167)
RGOLD 0.0041
(0.0129)
DCREDRISK 0.0128
(0.0180)
Adj. R-squared 0.2372
F statistic
Prob(F- statistic)
9.5330
(0.0000)
DW statistic 1.7364
Note: The Newey-West procedure was used to adjust for heteroscedasticity.
A residual serial correlation test for ARCH effects was performed, but the null
hypothesis of inexistence of an ARCH effect was not rejected at 5%.
***, ** indicate significance at the 1% and 5% levels, respectively.
The specification Ramsay RESET test was implemented, and it was found that the
fitted-square variable was not significant, obviating the need for using non-linear forms
of explanatory variables and including additional variables, since this procedure is often
used to test for relevant variable omission. In particular, it can be argued that the impact
of possibly relevant macroeconomic variables is subsumed in the behavior of basic
market variables.
Next, in order to check for the impact of the 2008 global financial crisis on the
estimated relationship between changes in the ERP and the proposed determining
factors, a Chow break-even point test was performed, assuming that the break had
occurred in September 2008. The resulting F statistic, for 85 and 153 degrees of
freedom is equal to 0.2528, with a p-value equal to 1.0000. Hence, the null hypothesis
of the stability of the relationship is not rejected. (For an explanation of this test, see
Kennedy, 2003.)
The results indicate that four of the proposed factors are influential in the explanation of
changes in the estimated equity risk premium and, by construction, thanks to the
methodology with which the ERP is estimated, in the explanation of stock market
prices: changes in the basic interest rate (DCDI); changes in the country risk premium
(DRISKBR); changes in the liquidity premium (DLIQPREM). The coefficients of all
these variables have the expected sign (positive), since they either represent common
sources of market risk, or correspond to the basic rate that would be used by the market
16. 14
to discount future cash flows to equities. The fourth empirically relevant variable
(RSP500) has a negative coefficient, and the manner in which it affects the value of
ERP in the Brazilian market was previously explained, corresponding to the fact that
prices in various national equity markets tend to co-vary in the same direction.
In order to provide a comparison with the results from the procedure commonly used
for estimating the equity risk premium, we also consider testing for the significance and
direction of the relationship between current fundamentals and the historical average
constructed as the difference between past returns on the S&P500 and U.S. T-note rates.
The averages were constructed over 60-month moving periods, as usually proposed by
the users of such an approach. The resulting ERP series is displayed in Figure 2.
Figure 2 Equity risk premium estimate for the usual applications in the Brazilian
market, where the proxy for the market portfolio is the S&P500 index.
The risk premium is calculated using 60 previous monthly returns for that
index, and the risk-free rate is the yield on the 10-year U.S. Treasury
Note.
The highest levels for historical ERP occur in 1999, but almost one full year after the
currency crisis in Brazil, and the other crises that more directly affected the U.S. market,
in Sept. 2001 and Sept. 2008, would have involved ERP values of only 5.03% and -
0.95% (!) p. a., respectively. Furthermore, the correlation coefficient between the ERP
series, estimated with current prices and with historical prices, is not even positive,
being equal to -0.0412 over the entire period.
In a deliberate effort to belabor the point, we also used the historical ERP series as
dependent variable in our proposed equation, regressing it against current values of
fundamentals for the Brazilian market (with the exclusion of RSP500). The equation’s
adjusted R2
is equal to 0.0133, and three variables are significant at the 5% level:
DCREDRISK and RGOLD (with negative coefficients), and RPTAX, with a positive
-15,00%
-10,00%
-5,00%
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
jan/95
jan/96
jan/97
jan/98
jan/99
jan/00
jan/01
jan/02
jan/03
jan/04
jan/05
jan/06
jan/07
jan/08
jan/09
jan/10
jan/11
jan/12
jan/13
jan/14
jan/15
17. 15
coefficient. Intuitively, only the last result makes any sense – when the exchange rate
increases, so does the required return on the market portfolio.
6. Conclusion
This paper has examined potential market variables that can explain the movements in
the Brazilian market equity risk premium and, therefore, stock market prices. Monthly
samples from January 1995 until September 2015 were used in the construction of the
implied equity risk premium for the Brazilian market. The authors believe that using the
implied premium is a superior measure to the commonly used historic premiums
because the market should be affected by expected changes of returns, and not by
historic prices. Major findings are that the Brazilian market seems to be affected by two
local variables: 1) changes in local interest rates; 2) economic conditions that determine
the country risk premium. And it is also affected by two international market variables:
the U.S. liquidity premium and the level of U.S. equity prices. Other market variables
like the Real/U.S. dollar exchange rate, gold prices, stock market trading volume and
credit default risk were discarded as not being influential in the explanation of stock
market prices, possibly because the underlying economic factors are already represented
by the significant variables.
In an attempt to model the Brazilian market one should look at those four variables for
an explanation of our equity risk premium. Investors tend to demand higher rates of
return to invest in equities in Brazil than to invest in the U.S. The reasons for this
include the higher level of local interest rates and the higher sovereign risk. Those
explanations combined show why the Brazilian market is more complex and risky,
inducing rational investors to require higher expected rates of return.
Finally, the paper presented evidence of how inadequate the use of historically-based
premiums is for representing the market compensation for risk, leading to important
questions about the reasonableness of their use in so many practical applications.
7. References
Brown, S. J., Goetzmann, W. N. & Ross, S. A. (1995) Survival. The Journal of Finance,
50(3), 853-873.
Camacho, P. & Lemme, C. (2004). The cost of equity capital and the risk premium for
evaluating projects of Brazilian companies abroad: A study of the period from 1997 to
2002. Latin American Business Review, 5(3), 1-23.
Claus, J. & Thomas, J. (1999). The equity risk premium is much lower than you think it
is: empirical estimates from a new approach. Working paper. Columbia Business
School.
_____________. (2001). Equity premia as low as three percent? Evidence from
analysts’ earnings forecasts for domestic and international stock market. Journal of
Finance, 56, 1629-1666.
18. 16
Damodaran, A. (2011) Equity Risk Premiums (ERP): Determinants, Estimation and
Implications – The 2011 Edition. Retrieved on 15 Dec. 2011, from
http://pages.stern.nyu.edu/~adamodar/.
Easton, P., Taylor, G., Shroff, P., & Sougiannis, T. (2002). Using forecasts of earnings
to simultaneous estimate growth and the rate of return on equity investments. Journal of
Accounting Research, 40, 657-676.
Elton, E. J. (1999). Expected return, realized return, and asset pricing tests. Journal of
Finance, 54(4)1199-1220.
Ferreira, L. F. (2011). Determinantes macroeconômicos do prêmio implícito por risco
de mercado no Brasil. Dissertação de Mestrado em Economia, Insper, São Paulo.
Available at <http://tede.insper.edu.br/tde_busca/processaPesquisa.php?nrPagina=6>.
Gebhardt, W. R., Lee, C. M. C. & Swaminathan, B. (2001). Toward an implied cost of
capital. Journal of Accounting Research, 39(1), 135-176.
Gordon, M. J. (1959). Dividends, earnings and stock prices. Review of Economics and
Statistics, 41(2), 99-105.
Hail, L., & Leuz, C. (2006). International differences in the cost of equity capital: Do
legal institutions and securities regulation matter? Journal of Accounting Research, 44,
485-532.
Hribar, P., & Jenkins, N. (2004). The effect of accounting restatements on earnings
revisions and the estimated cost of capital. Review of Accounting Studies, 9, 337-356.
Hsing, Yu, Phillips, A., & Phillips, C. (2011). Stock Prices and Aggregate Economic
Variables: The Case of Brazil. International Research Journal of Applied Finance,
II(5).
Ibbotson, R. (2010). Stocks, Bonds, Bills and Inflation Yearbook (SBBI) 2010 Edition,
Morningstar.
Javakhadze, D, Ferris, S. P., & French, D. W. (2016). Managerial Social Capital and
Financial Development: A Cross-Country Analysis. The Financial Review, v. 51(1), 37-
68.
Kennedy, P. (2003). A Guide to Econometrics, 5th. Ed. The MIT Press, Cambridge,
Massachusetts.
Lima, B. F., & Sanvicente, A. Z. (2013). The quality of corporate governance and cost
of equity in Brazil. Journal of Applied Corporate Finance, 25(1), 72-80.
Lintner, J. (1965). The valuation of risk assets and the selection of risky investments in
stock portfolios and capital budgets. Review of Economics and Statistics, 47(1), 13-37.
Mehra, R., & Prescott, E. C. (1985). The equity premium: a puzzle. Journal of
Monetary Economics, 15, 145-161.
19. 17
Minardi, A. M. A. F., Sanvicente, A. Z., Montenegro, C. M. G., Donatelli, D. H., &
Bignotto, F. G. (2007). Estimando o custo de capital de companhias fechadas no Brasil
para uma melhor gestão estratégica de projetos. Insper Working Paper – WPE:
088/2007. Retrieved on February 15, 2012, from
http://www.insper.org.br/sites/default/files/2007_wpe088.pdf
Mossin, J. (1966). Equilibrium in a capital asset market. Econometrica, 34(4), 768-783.
Nekrasov, A., & Ogneva, M. (2011). Using earnings forecasts to simultaneously
estimate firm-specific cost of equity and long-term growth. Review of Accounting
Studies, 16, 414-457.
Pastor, L., Sinha, M., & Swaminathan, B. (2008). Estimating the intertemporal risk-
return tradeoff using the implied cost of capital. Journal of Finance, 63, 2859-2897.
Ross, S. A., Westerfield, R. J. & Jaffe, J. F. (2012). Corporate Finance, 11th
ed. Boston,
MA, McGraw-Hill.
Sanvicente, A. Z. (2012). Problemas de estimação de custo de capital de empresas
concessionárias no Brasil: uma aplicação à regulamentação de concessões rodoviárias.
RAUSP, 47(1), 81-95.
Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium. Journal of
Finance, 19(3), 425-442.