Esta tese apresenta três ensaios em macroeconomia aplicada e que possuem em comum o uso de técnicas estatísticas e econométricas em problemas macroeconômicos. Dentre os campos de pesquisa da macroeconomia aplicada, a tese faz uso de modelos macroeconômicos microfundamentados, em sua versão DSGE-VAR, e da macroeconomia financeira por meio da avaliação do comportamento da correlação entre os retornos das ações usando modelos Garch multivariados. Além disso, a tese provoca a discussão sobre um novo campo de pesquisa em macroeconomia que surge a partir do advento da tecnologia. No primeiro ensaio, aplicamos a abordagem DSGE-VAR na discussão sobre a reação do Banco Central do Brasil (BCB) as oscilações na taxa de câmbio, especificamente para o caso de uma economia sob metas de inflação. Para tanto, baseando-se no modelo para uma economia aberta desenvolvido por Gali e Monacelli (2005) e modificado por Lubik e Schorfheide (2007), estimamos uma regra de política monetária para o Brasil e examinamos em que medida o BCB responde a mudanças na taxa de câmbio. Além disso, estudamos o grau de má especificação do modelo DSGE proposto. Mais especificamente, comparamos a verossimilhança marginal do modelo DSGE às do modelo DSGE-VAR e examinamos se o Banco Central conseguiu isolar a economia brasileira, em particular a inflação, de choques externos. Nossas conclusões mostram que as respostas aos desvios da taxa de câmbio são diferentes de zero e menores do que as respostas aos desvios da inflação. Finalmente, o ajuste do modelo DSGE é consideravelmente pior do que o ajuste do modelo DSGE-VAR, independentemente do número de defasagens utilizadas no VAR o que indica que de um ponto de vista estatístico existem evidências de que as restrições cruzadas do modelo teórico são violadas nos dados. O segundo ensaio examina empiricamente o comportamento da correlação entre o retorno de ações listadas na BMF&BOVESPA no período de 2000 a 2015. Para tanto, utilizamos modelos GARCH multivariados introduzidos por Bollerslev (1990) para extrair a série temporal das matrizes de correlação condicional dos retornos das ações. Com a série temporal dos maiores autovalores das matrizes de correlação condicional estimadas, aplicamos testes estatísticos (raiz unitária, quebra estrutural e tendência) para verificar a existência de tendência estocástica ou determinística para a intensidade da correlação entre os retornos das ações representadas pelos autovalores. Nossas conclusões confirmam que tanto em períodos de crises nacionais como turbulências internacionais, há intensificação da correlação entre as ações. Contudo, não encontramos qualquer tendência de longo prazo na série temporal dos maiores autovalores das matrizes de correlação condicional. Isso sugere que apesar das conclusões de Costa, Mazzeu e Jr (2016) sobre a tendência de queda do risco idiossincrático no mercado acionário brasileiro, a correlação dos retornos não apresentou tendência de alta, conforme esperado pela teoria de finanças. No terceiro ensaio, apresentamos pesquisas que utilizaram Big Data, Machine Learning e Text Mining em problemas macroeconômicos e discutimos as principais técnicas e tecnologias adotadas bem como aplicamos elas na análise de sentimento do BCB sobre a economia. Por meio de técnicas de Web Scraping e Text Mining, acessamos e extraímos as palavras usadas na escrita das atas divulgadas pelo Comitê de Política Monetária (Copom) no site do BCB. Após isso, comparando tais palavras com um dicionário de sentimentos (Inquider) mantido pela Universidade de Harvard e originalmente apresentado por Stone, Dunphy e Smith (1966), foi possível criar um índice de sentimento para a autoridade monetária. Nossos resultados confirmam que tal abordagem pode contribuir para a avaliação econômica dado que a série temporal do índice proposto está relacionada com variáveis macroeconômicas importantes para as decisões do BCB. / This thesis presents three essays in applied macroeconomics and who have in common the use of statistical and econometric techniques in macroeconomic problems. Among the search fields of applied macroeconomics, the thesis makes use of microfounded macroeconomic models, in tis DSGE-VAR version, and financial macroeconomics through the evaluation of the behavior of correlation between stock returns using multivariate Garch models. In addition, leads a discussion on a new field of research in macroeconomics which arises from the advent of technology. In the first experiment, we applied the approach to dynamic stochastic general equilibrium (DSGE VAR in the discussion about the reaction of the Central Bank of Brazil (CBB) to fluctuations in the exchange rate, specifically for the case of an economy under inflation targeting. To this end, based on the model for an open economy developed by Gali and Monacelli (2005) and modified by Lubik and Schorfheide (2007), we estimate a rule of monetary policy for the United States and examine to what extent the CBC responds to changes in the exchange rate. In addition, we studied the degree of poor specification of the DSGE model proposed. More specifically, we compare the marginal likelihood of the DSGE model to the DSGE-VAR model and examine whether the Central Bank managed to isolate the brazilian economy, in particular the inflation, external shocks. Our findings show that the response to deviations of the exchange rate are different from zero and lower than the response to deviations of inflation. Finally, the adjustment of the DSGE model is considerably worse than the adjustment of the DSGE-VAR model, regardless of the number of lags used in the VAR which indicates that a statistical point of view there is evidence that the restrictions crusades of the theoretical model are violated in the data. The second essay examines empirically the behavior of the correlation between the return of shares listed on the BMF&BOVESPA over the period from 2000 to 2015. To this end, we use models multivariate GARCH introduced by Bollerslev (1990) to remove the temporal series of arrays of conditional correlation of returns of stocks. With the temporal series of the largest eigenvalues of matrices of correlation estimated conditional, we apply statistical tests (unit root, structural breaks and trend) to verify the existence of stochastic trend or deterministic to the intensity of the correlation between the returns of the shares represented by eigenvalues. Our findings confirm that both in times of crises at national and international turbulence, there is greater correlation between the actions. However, we did not find any long-term trend in time series of the largest eigenvalues of matrices of correlation conditional. In the third test, we present research that used Big Data, Machine Learning and Text Mining in macroeconomic problems and discuss the main techniques and technologies adopted and apply them in the analysis of feeling of BCB on the economy. Through techniques of Web Scraping and Text Mining, we accessed and extracted the words used in the writing of the minutes released by the Monetary Policy Committee (Copom) on the site of the BCB. After that, comparing these words with a dictionary of feelings (Inquider) maintained by Harvard University and originally presented by Stone, Dunphy and Smith (1966), it was possible to create an index of sentiment for the monetary authority. Our results confirm that such an approach can contribute to the economic assessment given that the temporal series of the index proposed is related with macroeconomic variables are important for decisions of the BCB.

A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. In this thesis we revisit the problem whether idiosyncratic risk is priced by the stock market and what the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. On the other hand, the mean-reverting unconditional volatility is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of 'knowledge' of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. The difference between the correlations between the idiosyncratic volatility estimators used by other studies and the true risk metric - the mean-reverting volatility - is the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency.

Motivated by the recent evidence of investors' preference for stocks with lottery- type payoffs documented on the U.S. stock markets, I investigate preferences for stocks that appear to be like lotteries in Europe. Across 14 markets, lottery- type stocks, characterized by high idiosyncratic skewness, high idiosyncratic volatility and low price, underperform and exhibit a "lottery premium". Fur- thermore, preferences for lottery-type stocks can help to explain the puzzling negative relation between past idiosyncratic volatility and returns, which does not persist after controlling for past extreme positive returns. Examining the relation between national revenues from gambling and "lottery premium" I find that countries featuring higher gambling revenues also exhibit a higher "lottery premium". Overall, the results indicate that lottery preferences might impact investment decisions and stock prices. JEL Classification G11, G12 Keywords gambling, lottery-type stocks, idiosyncratic volatility, maximum returns Author's e-mail p.vokata@gmail.com Supervisor's e-mail novakji@fsv.cuni.cz

This dissertation contains two essays. The first essay investigates the measure of FX liquidity and determinants of the change in FX liquidity. Using 20 cross currency exchange rates over spanning period of 1999 to 2016, funding constraints and global risks are responsible for the main drivers of changing in FX liquidity. The magnitudes of both G7 and emerging volatility index are offsetting each other in all the regression models indicating that FX investors take diversification trading strategies to diversify their portfolios. The financial crisis provides an evidence that the more financial constraint issues contribute to the change in FX market illiquidity more than non-financial crisis period. Extending to liquidity predictability, I find, however, that the lag of market FX liquidity is responsible for the change in FX liquidity than any other explanatory variables My second essay investigates the momentum returns of U.S. equities by presenting comprehensive approaches. Traditionally, momentum portfolios are constructed by ranking based on excess returns. Using this sorting technique, I confirm that there is a presence of momentum returns in U.S. equities for all of the 48 industries. The results also indicate that the portfolios that are sorted by idiosyncratic volatility as well as by diversification strategy cannot achieve the highest returns as for sorting based on excess returns. Further, I examine the momentum portfolio predictability using the inverse conditional volatility proposed by Moreira and Muir (2017), and show that the momentum returns are affected by the size of liquidity and the risk factors rather than by the economic variables.

Standard asset pricing theories suggest that only systematic risk is priced. Empirical studies report a relationship between idiosyncratic volatility or risk (IVOL) and asset price. The most common explanation for this anomaly is that households under-diversify creating a Bad Model problem. This paper uses an Intermediary Asset Pricing Model (IAPM) as a way to control for under-diversification in evaluating the relationship between IVOL and asset price. We find that IVOL premia is lower in an IAPM. Our findings indicate that under-diversification can explain the anomaly partially.

This study tires to find out how a firm¡¦s advertising and customer satisfaction influence firms¡¦ abnormal return and we uses the abnormal return (i.e. Jensne¡¦s £\) as the proxy of firm¡¦s shareholder value. We expect firms¡¦ advertising and customer satisfaction will have a positive impact on abnormal return while having a negative impact on firms¡¦ risk. In addition, we also consider under different market state whether advertising and customer satisfaction have an asymmetric effect. Compare with Carhart (1997) four factor model, this paper also takes the factor of VIX into account, and we use Markov regime switching model to recognize bull market and bear market because it can help us get a more accurate estimation. We choose the Generalized method of moments (GMM) to estimate the impact of advertising and customer satisfaction on shareholder value and discuss that whether advertising and customer satisfaction are able to lift up shareholder value or not. The outcome shows that advertising doesn¡¦t have significantly positive impact on firms¡¦ abnormal return under bull market and bear market. However, customer satisfaction has a significantly positive relationship with firms¡¦ abnormal return under bull market and bear market. And we find that if firms maintain the level of customer satisfaction under bear market, it will be more efficiently to lift up firms¡¦ abnormal return rather than spending more money on advertising.

I examine the informational efficiency of stock markets by testing the relation between idiosyncratic volatility and equity mispricing. I find that the level of mispricing declines with idiosyncratic volatility consistent with the notion that greater levels of firm-specific risk reflect greater participation of informed traders in the market for the stock. However, I also find that mispricing increases with idiosyncratic volatility for highly volatile stocks, and this is attributed to both noise trading and arbitrage risk. In addition, I investigate the link between agency costs and equity mispricing, and whether it exists due to information asymmetry or the degree of conflict of interests between managers and shareholders. I provide evidence that the level of agency costs is positively related with mispricing. In contrast to previous studies' claim that the information asymmetry level is a key determinant in the equity mispricing, I find that the conflict of interests is more important than information asymmetry in explaining equity mispricing. Furthermore, the evidence suggests that stock option grants, originally intended to resolve conflicts of interests, actually exaggerate this problem.

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This thesis presents three essays on credit ratings of regulated utilities, dividend signaling, and asymmetric information and security issuances and repurchases. Chapter 2 investigates the practices of credit rating agencies by using the regulated utility industry as a natural testing ground. Following deregulation and the Enron scandal, the general opinion among industry professionals is that utilities are being punished by rating agencies. Contrary to this popular belief, we find that the utility credit ratings are significantly higher compared to those of other firms, and this significance is more pronounced in the post-deregulation period. Although rating agencies often cite regulatory reasons for placing utilities on negative credit watches, these firms ratings are rarely downgraded after being placed on negative watches. Chapter 3 provides a rational explanation for the disappearing dividend trend. Dividends serve as signaling device and, under models of dividend signaling under information asymmetry, cost of signaling increases with volatility of firms cash flows. Declining propensities to pay dividends imply that (1) information asymmetries have become lower and/or (2) cost of signaling has increased. We find evidence consistent with both. In particular, firms with higher information asymmetries and lower stock price informativeness are more likely to pay dividends: the increasing stock price informativeness has made dividend signaling less valuable, and a significant portion of disappearing dividend trend could be explained by rising risk and increasing stock price informativeness. Chapter 4 investigates the motivations for debt and equity issuances and repurchases in hot and cold markets. I find that firms issue equity in hot markets to reduce adverse selection costs associated with asymmetric information. In particular, firms issuing equity in hot markets possess high asymmetric information while firms issuing equity in cold markets possess less severe asymmetric information. I also find that credit ratings and market-to-book ratios could explain why firms might repurchase equity or issue debt in hot markets rather than issue equity: firms with high credit ratings and low market-to-book ratios are more likely to issue debt even in hot equity markets, and firms with low market-to-book ratios are more likely to repurchase equity in any market. / Finance

Speech contains certain attributes characteristic for a speaker, so-called idiosyncratic features. This thesis focuses on the form of these features in intentional voice disguise - whether speakers are able to change them in a substantial way, or if they tend to remain stable in spite of intentional speech modifications. It was also investigated whether any general tendencies to similar changes of such features under voice disguise exist among the speakers. The observed features were statistical f0 indicators, f0 contours, vowel formants, long- term formant distributions, spectral characteristics of sibilants, intensity, intensity contours, speech and articulation rate, %V and local articulation rate contours. In f0 median and standard deviation, vowel formants, LTFDs, intensity, articulation rate, and %V, prominent shifts under voice disguise were observed in general; in the majority of these parameters, the shifts differed among speakers. However it was found that the value of %V generally tends to rise under voice disguise. Also, intensity showed an increase in majority of cases. In f0 contours, similar patterns were observed among speakers in normal speech, however, in disguised speech, greater differences appeared among speakers; speakers tend to employ nonstandard dynamic f0 patterns more...