19 resultados para Chinese stock market

em RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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Companhia das Quintas, Limited Company wishes to conquer the Chinese market with its wines. For that, it decided to enter in a partnership with a local importer and distributor. This project analyses the macroeconomic factors of the country, the local market and the consumer behavior, using on-site research that included interviews with professionals of the industry, unstructured observation of the consumer and existing statistical data analysis. Finally, the project presents a marketing plan to make this partnership a success.

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This paper analyzes the in-, and out-of sample, predictability of the stock market returns from Eurozone’s banking sectors, arising from bank-specific ratios and macroeconomic variables, using panel estimation techniques. In order to do that, I set an unbalanced panel of 116 banks returns, from April, 1991, to March, 2013, to constitute equal-weighted country-sorted portfolios representative of the Austrian, Belgian, Finish, French, German, Greek, Irish, Italian, Portuguese and Spanish banking sectors. I find that both earnings per share (EPS) and the ratio of total loans to total assets have in-sample predictive power over the portfolios’ monthly returns whereas, regarding the cross-section of annual returns, only EPS retain significant explanatory power. Nevertheless, the sign associated with the impact of EPS is contrarian to the results of past literature. When looking at inter-yearly horizon returns, I document in-sample predictive power arising from the ratios of provisions to net interest income, and non-interest income to net income. Regarding the out-of-sample performance of the proposed models, I find that these would only beat the portfolios’ historical mean on the month following the disclosure of year-end financial statements. Still, the evidence found is not statistically significant. Finally, in a last attempt to find significant evidence of predictability of monthly and annual returns, I use Fama and French 3-Factor and Carhart models to describe the cross-section of returns. Although in-sample the factors can significantly track Eurozone’s banking sectors’ stock market returns, they do not beat the portfolios’ historical mean when forecasting returns.

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The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.

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This paper studies the changes in European stock market indexes composition from 1995 to 2015. It was found that there are mixed price effects producing abnormal returns around the effective replacement of added and deleted stocks. The price pressure hypothesis seems to hold for added stocks in some indexes but not for deleted stocks as there is not a clear inversion of behaviour after the replacement. Finally, the building and back testing of a trading strategy aiming to capture some of those abnormal returns shows it yields a Sharpe Ratio of 1.4 and generates an annualised alpha of 11%.

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This paper analyses the Portuguese stock market since it reopened in 1977, with a special focus on the evolution of the statistic and stochastic characteristics of the market return throughout this 36 year period. The market return for the period of time between 1977 and 2012 (September 28th) is estimated and then compared with the return that would have been achieved with Government bonds and treasury bills, which allows us to confirm that the hierarchy of return / risk across the different financial instruments is verified. The market risk premium for this 36 year period is also estimated and a comparison with other markets is performed, suggesting that the Portuguese market’s risk has not been compensated by an adequate return. The study also examines the evolution of the Portuguese market’s volatility in the 1977-2012 period and compares it with other markets, showing the existence of extremely high peaks during the first 11 years, but indicating a downwards trend throughout the whole period under analysis. Finally, the correlation between market returns for Portugal and for other countries and the degree of integration are estimated and their evolution throughout time is assessed, leading to the conclusion that the performance of the Portuguese stock market has become increasingly correlated with major European markets – correlation with some markets close to 0.70 from 2000 onwards-, but that country-specific risk factors are still relevant.

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The recent financial crisis has drawn the attention of researchers and regulators to the importance of liquidity for stock market stability and efficiency. The ability of market-makers and investors to provide liquidity is constrained by the willingness of financial institutions to supply funding capital. This paper sheds light on the liquidity linkages between the Central Bank, Monetary Financial Institutions and market-makers as crucial elements to the well-functioning of markets. Results suggest the existence of causality between credit conditions and stock market liquidity for the Eurozone between 2003 and 2015. Similar evidence is found for the UK during the post-crisis period. Keywords: stock

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This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.

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This study aims to replicate Apple’s stock market movement by modeling major investment profiles and investors. The present model recreates a live exchange to forecast any predictability in stock price variation, knowing how investors act when it concerns investment decisions. This methodology is particularly relevant if, just by observing historical prices and knowing the tendencies in other players’ behavior, risk-adjusted profits can be made. Empirical research made in the academia shows that abnormal returns are hardly consistent without a clear idea of who is in the market in a given moment and the correspondent market shares. Therefore, even when knowing investors’ individual investment profiles, it is not clear how they affect aggregate markets.

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Throughout the last years technologic improvements have enabled internet users to analyze and retrieve data regarding Internet searches. In several fields of study this data has been used. Some authors have been using search engine query data to forecast economic variables, to detect influenza areas or to demonstrate that it is possible to capture some patterns in stock markets indexes. In this paper one investment strategy is presented using Google Trends’ weekly query data from major global stock market indexes’ constituents. The results suggest that it is indeed possible to achieve higher Info Sharpe ratios, especially for the major European stock market indexes in comparison to those provided by a buy-and-hold strategy for the period considered.

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In this paper we analyze the role of deposit insurance in providing the market with liquidity in times of financial turmoil. To do so, we look at the variation in insured and uninsured deposits between 2005Q3 and 2011Q3, controlling for liquidity, solvency and capital adequacy indicators, and find evidence that deposit insurance does provide some confidence in keeping funds in banks in times of turmoil. Additionally we follow an event study methodology to assess the impact of deposit insurance oriented policies on bank holding companies stock market returns, and find a TBTF effect.

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In this paper we investigate what drives the prices of Portuguese contemporary art at auction and explore the potential of art as an asset. Based on a hedonic prices model we construct an Art Price Index as a proxy for the Portuguese contemporary art market over the period of 1994 to 2014. A performance analysis suggests that art underperforms the S&P500 but overperforms the Portuguese stock market and American Government bonds. However, It does it at the cost of higher risk. Results also show that art as low correlation with financial markets, evidencing some potential in risk mitigation when added to traditional equity portfolios.

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Strategic alliances represent a key driver for internationalization and growth, being the purpose of this work project to better understand the intertwined relationship between trust and the existence of an alliance management position. Previous research supports the positive impact of such position in stock market returns. However, little attention has been given to the impact of such position on the level of trust in the collaborative arrangement, which is deemed to be a key driver for alliance success. A qualitative comparative case-study of three Portuguese SMEs is used to draw conclusions from the literature to real life business cases and it demonstrates the positive impact of an alliance management position on trust.

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In the stock market, information takes on special relevance, due to the market’s permanent updating and the great fluidity of information existent therein. Just as in any other negotiations, the party with the better information has a bargaining advantage, as it is able to make more advantageous business decisions. However, unlike most other markets, the proper functioning of the stock market is greatly dependent on investors’ trust in the market itself. As such, if there are investors who, due to any condition they possess or office they hold, have access to relevant information which is not accessible to the general public, distrust is bred within the market and, consequently, investment is lessened. Thus, there is a need to prevent those who hold privileged information from using it in abusive ways. In Portugal, abuse of privileged information is set out and punished criminally in Article 378. of the Portuguese Securities Code (‘Código dos Valores Mobiliários’). In this dissertation, I have set out, firstly, to analyze the inherent conditions for there to be a crime of abuse of privileged information; secondly, to analyze two well-known cases, which took place and were decided in other jurisdictions, and attempt to understand how these cases would fall under Article 378. of the Portuguese Securities Code. Whereas the first case, Chiarella v. United States, was scrutinize under Article 378 of the Portuguese Securities Code, in the second, Lafonta v. AMF, the conclusion arrived at was that the crime taken place was different. This analysis allowed, on one hand, the application to a particular case of prerequisites and concepts which were explained, at a first approach, from a more theoretical perspective; on the other hand, it also allowed the further development of specific aspects of the regime, namely the difference between an insider and a tipee, as well as to more clearly set out the limits to the precise character of the information at hand.

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The present research analyses overnight returns’ outperformance in relation to daytime returns. In a first stage, it will be assessed whether these returns are robust throughout time, markets and across different scopes of analysis (e.g. weekdays, months, states of the economy). In a second stage, several hypothesis will be empirically tested, in an attempt to understand what drives non-trading period returns (e.g. liquidity, market volatility). Even though several authors have analysed overnight returns and suggested several explanatory factors, there seems to be no consensus in the literature regarding its drivers.