|
|
Bias and Accuracy in Equity Research: The Case of CFA Challenge
Hloušek, Pavel ; Novák, Jiří (advisor) ; Máková, Barbora (referee)
This thesis analyses drivers of optimistic bias in equity research and substance of ability in explaining differences in accuracy among equity analysts. I have shown the existence of a relevant reason for optimistic bias in equity research, which is not related to conflict of interest - the usually referred driver of the bias. Then I have supported the stream of literature showing that analyst's ability is not a strong determinant of analyst's accuracy. A new perspective on the topics is offered by using a sample of equity reports from valuation competition CFA Research Challenge. Contribution of the thesis lies (i) in working with a sample of analysts who do not face the conflicts of interest proposed by the literature to be causing optimistic bias, which offers a unique opportunity to test whether such conflict-of- interest-free analysts issue biased recommendations and in (ii) using success in CFA Challenge as a new proxy for ability of equity analysts. The methods used are an analysis of bias and accuracy of target prices, hit-ratio of investment recommendations, and analysis of returns - estimated by CAPM, Fama French three-factor model and Carhart four-factor model.
|
|
|
Fundamental Analysis and Stock Return: The Case of Big Tech
Tran Nguyen, Thai Nhat Phi ; Krištoufek, Ladislav (advisor) ; Máková, Barbora (referee)
Bibliographic note TRAN NGUYEN, Thai Nhat Phi. Fundamental Analysis and Stock Return: The Case Of Big Tech. Prague 2020. 102 pp. Bachelor thesis (Bc.) Charles University, Faculty of Social Sciences, Institute of Economic Studies. Thesis supervisor doc. PhDr. Ladislav Krištoufek Ph.D. Abstract Six out of the ten most valuable companies by market capitalisation are, at their core, technology companies and four of these have at some time crossed the $1 trillion market cap, which has ignited a public discussion regarding their astronomic valuations and the tech bubble. This work addresses this development, with the analysis of four companies, namely Google, Apple, Facebook and Amazon (GAFA), which have dominated their respective fields of business in the "new economy". We go beyond the stock analysis and also examine the company's fundamentals and their effect on the valuations, furthermore we fuse the insights of both analyses to offer a more comprehensive evaluation of these four companies. The results suggest that their stock value accurately portrays their market dominance and that it is deeply rooted in the companies' fundamentals which are fairly well reflected in the stock price movements. Ultimately, we find that these companies do not contribute to the tech bubble as GAFA show unparalleled financial...
|
|
|
Portfolio optimization for an P2P investor on Zonky
Jonáš, Filip ; Polák, Petr (advisor) ; Máková, Barbora (referee)
This thesis analyzes the Czech peer-to-peer lending platform Zonky. The goal was to find the optimal portfolio for a risk-averse investor investing in Zonky loans. For this purpose, the Modern portfolio theory from Markowitz was used. Based on the provided loan book containing information about loans which Zonky has provided since its foundation we examined the statistical properties of the individual risk categories represented by the interest rate charged. The optimization was done using the Excel Solver tool assuming that the loan categories are uncorrelated as well as considering the correlation we found using the variance- covariance matrix. For both cases, the portfolio minimizing the standard deviation as well as the portfolio which maximizes the Sharpe ratio was found. Generally, both types of portfolios were comprised mainly of loans with lower interest rate. According to our results, it seems that such loans offer better relationship between risk and return compared to categories which are riskier. Also, we showed that the platform's recovery rate has a significant impact on the performance of the loan categories especially of those which are among the riskiest. Furthermore, we demonstrated that the correlation between individual risk categories should not be ignored when a portfolio...
|
|
|
Bias and Accuracy in Equity Research: The Case of CFA Challenge
Hloušek, Pavel ; Novák, Jiří (advisor) ; Máková, Barbora (referee)
This thesis analyses drivers of optimistic bias in equity research and substance of ability in explaining differences in accuracy among equity analysts. I have shown the existence of a relevant reason for optimistic bias in equity research, which is not related to conflict of interest - the usually referred driver of the bias. Then I have supported the stream of literature showing that analyst's ability is not a strong determinant of analyst's accuracy. A new perspective on the topics is offered by using a sample of equity reports from valuation competition CFA Research Challenge. Contribution of the thesis lies (i) in working with a sample of analysts who do not face the conflicts of interest proposed by the literature to be causing optimistic bias, which offers a unique opportunity to test whether such conflict-of- interest-free analysts issue biased recommendations and in (ii) using success in CFA Challenge as a new proxy for ability of equity analysts. The methods used are an analysis of bias and accuracy of target prices, hit-ratio of investment recommendations, and analysis of returns - estimated by CAPM, Fama French three-factor model and Carhart four-factor model.
|
|
|
Fractal Dimension and Efficient Markets
Máková, Barbora ; Krištoufek, Ladislav (advisor) ; Víšek, Jan Ámos (referee)
The efficient market hypothesis is one of the most important propositions in finance theory and has been subjected to years of rigorous empirical testing. We examine power of a new tool for evaluating market efficiency, fractal dimension. Characteristics and abilities of fractal dimension measure are explored through extensive Monte Carlo simulations. We prove that it provides an accurate evaluation of market's efficiency and its changes. This approach is highly innovative and creates new possibilities for examination of markets. The uniqueness of fractal dimension is in its ability to assign a numerical ranking to examined series describing the level of (in)efficiency; it is accurate for small samples of observations and quickly reflects changes in market efficiency structure. Powered by TCPDF (www.tcpdf.org)
|
|
|
Price Determinants and Bidding Strategies in Internet Auctions
Máková, Barbora ; Gregor, Martin (advisor) ; Stakhovych, Lyudmyla (referee)
This paper presents an empirical analysis of price determinants and bidders' behaviour in on-line auctions eBay.de and Aukro.cz. We focus on the effect of sellers' feedback rating score and the phenomenon of sniping. Our dataset used for the analysis consists of 7054 auctions with 209449 bids from eBay, and 2223 auctions with 8779 bids from Aukro. Buyers in on-line auctions cannot personally inspect the quality of the product, so they have to rely on the seller's honesty. In this setting, the seller's rating may significantly contribute to the final price formation. Sniping is a bidding strategy, whereby a bidder waits until the last moment of the bidding period to place her bid. According to a theory, sniping should cause a reduction in the final price, and there should be a positive relationship between the probability of bidding and bidder's experience. The empirical results for both auction web sites show that the seller's feedback rating score has a significant impact on the final price. The tests regarding sniping provide distinctive results only for eBay. The effect of sniping on the final price is not clear since we have obtained different results for different specifications, but we found out that experience of a bidder increases the probability of placing a sniping bid. JEL Classification D44...
|
|
|
Odhad zajišťovacího poměru (Hedge Ratio) v řízení zásob
Máková, Barbora ; Černý, Michal (advisor) ; Cahlík, Tomáš (referee)
Companies dependent on commodities for their production have to deal with volatile commodity prices and should employ measures for risk reduction as unfavourable spot price development may cause significant losses. A useful tool for diminishing the risk is hedging on futures market; however, this approach faces a crucial question of optimal hedge ratio determination (ratio between spot and futures units). Our thesis examines nine different ways of optimal hedge ratio estimation (naive, Sharpe, mean extended Gini coefficient, generalized semivariance, value at risk, and minimum variance through OLS, error correction, GARCH, and bivariate GARCH models) and evaluates their efficiency using the data on eight different commodities. The results differ across the respective commodities and cannot be generalized. Two conclusions resulting from the analysis refer to performance of naive and OLS hedge ratios and constant vs time varying hedge ratios. We find that complex hedge ratios, such as bivariate GARCH or VaR hedge ratios, do not outperform naive and OLS hedge ratios and that the results of constant hedge ratios are mostly as good as results of time-varying hedge ratios.
|
guest ::
