938 resultados para G7 Stock Markets
Resumo:
Tässä kauppatieteiden kandidaatintyössä tutkittiin millaisia vaikutuksia julkisesti noteerattujen yhtiöiden osakekurssissa tapahtuu, kun jo valmiiksi Helsingin pörssissä listattu yritys jakautuu kahdeksi uudeksi pörssiyritykseksi. Molempien yrityksien osakkeita voi tämän jakautumisen jälkeen vapaasti ostaa tai myydä. Aikaisempi tutkimus on pääsääntöisesti keskittynyt Yhdysvaltojen markkinoille ja näiden tutkimusten tuloksien perusteella on monessa tapauksessa havautta, että on mahdollista saavuttaa ylinormaaleja tuottoja, kun pörssiyritys jakautuu kahdeksi uudeksi pörssiyritykseksi. Tässä analyysissä jakautumiset ajallisesti tapahtuivat vuosien 1994 ja 2013 välisenä aikana Suomessa ja näitä jakautumia oli yhteensä 16 kappaletta. Tutkimuksessa on hyödynnetty tilastollisten menetelmien analyysiä sekä CAP-mallia, jotta voitaisiin löytää vastauksia seuraaviin kysymyksiin: Vaikuttaako pörssiyrityksen jakautuminen kahdeksi pörssiyritykseksi alkuperäisen yhtiön ja uuden yhtiön osakekursseihin? Onko vaikutus positiivinen, negatiivinen vai onko jakautumisella mitään havaittavaa vaikutusta? Tämän tutkimuksen tulokset antavat uutta tietoa tutkijoille, analyytikoille, opettajille, opiskelijoille, yrityksille ja yritysten johdolle sekä erityisesti sijoittajille. Tulosten mukaan on nähtävissä monia vaikutuksia osakekursseissa, kun pörssiyritys jakautuu. Vaikutus näyttää kuitenkin olevan jossain määrin yritys-riippuvainen. Kun sijoitetaan oikeaan aikaan, on monia jakautuvia yrityksiä, jotka antavat hyvän tuoton keskimäärin, mutta kuten tavallista ja tyypillistä osakemarkkinoille, on myös jakautuvia yhtiöitä, jotka antavat negatiivisia tuottoja tai tuotot ovat nollassa
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Stock markets employ specialized traders, market-makers, designed to provide liquidity and volume to the market by constantly supplying both supply and demand. In this paper, we demonstrate a novel method for modeling the market as a dynamic system and a reinforcement learning algorithm that learns profitable market-making strategies when run on this model. The sequence of buys and sells for a particular stock, the order flow, we model as an Input-Output Hidden Markov Model fit to historical data. When combined with the dynamics of the order book, this creates a highly non-linear and difficult dynamic system. Our reinforcement learning algorithm, based on likelihood ratios, is run on this partially-observable environment. We demonstrate learning results for two separate real stocks.
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Financial integration has been pursued aggressively across the globe in the last fifty years; however, there is no conclusive evidence on the diversification gains (or losses) of such efforts. These gains (or losses) are related to the degree of comovements and synchronization among increasingly integrated global markets. We quantify the degree of comovements within the integrated Latin American market (MILA). We use dynamic correlation models to quantify comovements across securities as well as a direct integration measure. Our results show an increase in comovements when we look at the country indexes, however, the increase in the trend of correlation is previous to the institutional efforts to establish an integrated market in the region. On the other hand, when we look at sector indexes and an integration measure, we find a decreased in comovements among a representative sample of securities form the integrated market.
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Evidence suggests that rational, periodically collapsing speculative bubbles may be pervasive in stock markets globally, but there is no research that considers them at the individual stock level. In this study we develop and test an empirical asset pricing model that allows for speculative bubbles to affect stock returns. We show that stocks incorporating larger bubbles yield higher returns. The bubble deviation, at the stock level as opposed to the industry or market level, is a priced source of risk that is separate from the standard market risk, size and value factors. We demonstrate that much of the common variation in stock returns that can be attributable to market risk is due to the co-movement of bubbles rather than being driven by fundamentals.
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In this paper, we focus on the tails of the unconditional distribution of Latin American emerging markets stock returns. We explore their implications for portfolio diversification according to the safety tirst principIe, tirst proposed by Roy (1952). We tind that the Latin American emerging markets have signiticantly fatter tails than industrial markets. especially, the lower tail of the distrihution. We consider the implication of the safety tirst principIe for a U .S. investor who creates a diversitied portfolio using Latin American stock markets. We tind that a U.S. investor gains by adding Latin American equity markets to her purely domestic portfolio. For different parameter specitications. we finu a more realistic asset allocation than the one suggested by the Iiterature haseu on the traditional mean-variance framework.
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Using quantitative data obtained from public available database, this paper discusses the difference between of the Brazilian GDP and the Brazilian Stock Exchange industry breakdown. I examined if, and to what extent, the industry breakdowns are similar. First, I found out that the Stock Exchange industry breakdown is overwhelming different from the GDP, which may present a potential problem to asset allocation and portfolio diversification in Brazil. Second, I identified an important evidence of a convergence between the GDP and the Stock Exchange in the last 9 years. Third, it became clear that the Privatizations in the late 90’s and IPO market from 2004 to 2008 change the dynamics of the Brazilian Stock Exchange. And fourth, I identified that Private Equity and Venture Capital industry may play an important role on the portfolio diversification in Brazil.
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This paper analyses three aspects of the share market operated by the Lima Stock Exchange: (i) the short-term relationship between the pricing, direction and volume of order flows; (ii) the components of the spread and the equilibrium point of the limit order book per share, and (iii) the pricing, order direction and trading volume dynamic resulting from shocks in the same variables when lagged. The econometric results for intraday data from 2012 show that the short-run dynamic of the most and least liquid shares in the General Index of the Lima Stock Exchange is explained by the direction of order flow, whose price impact is temporary in both cases.
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The current international integration of financial markets provides a channel for currency depreciation to affect stock prices. Moreover, the recent financial crisis in Asia with its accompanying exchange rate volatility affords a case study to examine that channel. This paper applies a bivariate GARCH-M model of the reduced form of stock market returns to investigate empirically the effects of daily currency depreciation on stock market returns for five newly emerging East Asian stock markets during the Asian financial crisis. The evidence shows that the conditional variances of stock market returns and depreciation rates exhibit time-varying characteristics for all countries. Domestic currency depreciation and its uncertainty adversely affects stock market returns across countries. The significant effects of foreign exchange market events on stock market returns suggest that international fund managers who invest in the newly emerging East Asian stock markets must evaluate the value and stability of the domestic currency as a part of their stock market investment decisions.
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This paper examines execution costs and the impact of trade size for stock index futures using price-volume transaction data from the London International Financial Futures and Options Exchange. Consistent with Subrahmanyam [Rev. Financ. Stud. 4 (1991) 11] we find that effective half spreads in the stock index futures market are small compared to stock markets, and that trades in stock index futures have only a small permanent price impact. This result is important as it helps to better understand the success of equity index products such as index futures and Exchange Traded Funds. We also find that there is no asymmetry in the post-trade price reaction between purchases and sales for stock index futures across various trade sizes. This result is consistent with the conjecture in Chan and Lakonishok [J. Financ. Econ. 33 (1993) 173] that the asymmetry surrounding block trades in stock markets is due to the high cost of short selling and the general reluctance of traders to short sell on stock markets. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
During 1999 and 2000 a large number of articles appeared in the financial press which argued that the concentration of the FTSE 100 had increased. Many of these reports suggested that stock market volatility in the UK had risen, because the concentration of its stock markets had increased. This study undertakes a comprehensive measurement of stock market concentration using the FTSE 100 index. We find that during 1999, 2000 and 2001 stock market concentration was noticeably higher than at any other time since the index was introduced. When we measure the volatility of the FTSE 100 index we do not find an association between concentration and its volatility. When we examine the variances and covariance’s of the FTSE 100 constituents we find that security volatility appears to be positively related to concentration changes but concentration and the size of security covariances appear to be negatively related. We simulate the variance of four versions of the FTSE 100 index; in each version of the index the weighting structure reflects either an equally weighted index, or one with levels of low, intermediate or high concentration. We find that moving from low to high concentration has very little impact on the volatility of the index. To complete the study we estimate the minimum variance portfolio for the FTSE 100, we then compare concentration levels of this index to those formed on the basis of market weighting. We find that realised FTSE index weightings are higher than for the minimum variance index.
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In this article we study the relationship between security returns cross-listed on the A share market of China and the H share market at the Stock Exchange of Hong Kong (SEHK). Most of these securities are also cross-listed on other markets. An important feature of this article is that we focus on the multilateral relationships between all cross-listed markets rather than concentrating only on the bi-lateral relationship between A and Hong Kong H shares. Using the impulse response functions and the variance decompositions from a Vector Autoregressive (VAR) process we show that the returns to the A share market are almost exclusively determined by domestic factors. In contrast, we find that the H share market is influenced by both the A share market within China and foreign stock markets elsewhere in the world. Impulse response functions suggest that innovations to the A share market and the Hong Kong H share market are partly transmitted to each other and to stock markets outside China. We show that liquidity has an important role to play in determining the impact that the home market has on cross-listed variance decompositions. © 2012 Copyright Taylor and Francis Group, LLC.
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This paper applies the vector AR-DCC-FIAPARCH model to eight national stock market indices' daily returns from 1988 to 2010, taking into account the structural breaks of each time series linked to the Asian and the recent Global financial crisis. We find significant cross effects, as well as long range volatility dependence, asymmetric volatility response to positive and negative shocks, and the power of returns that best fits the volatility pattern. One of the main findings of the model analysis is the higher dynamic correlations of the stock markets after a crisis event, which means increased contagion effects between the markets. The fact that during the crisis the conditional correlations remain on a high level indicates a continuous herding behaviour during these periods of increased market volatility. Finally, during the recent Global financial crisis the correlations remain on a much higher level than during the Asian financial crisis.
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We report an empirical analysis of long-range dependence in the returns of eight stock market indices, using the Rescaled Range Analysis (RRA) to estimate the Hurst exponent. Monte Carlo and bootstrap simulations are used to construct critical values for the null hypothesis of no long-range dependence. The issue of disentangling short-range and long-range dependence is examined. Pre-filtering by fitting a (short-range) autoregressive model eliminates part of the long-range dependence when the latter is present, while failure to pre-filter leaves open the possibility of conflating short-range and long-range dependence. There is a strong evidence of long-range dependence for the small central European Czech stock market index PX-glob, and a weaker evidence for two smaller western European stock market indices, MSE (Spain) and SWX (Switzerland). There is little or no evidence of long-range dependence for the other five indices, including those with the largest capitalizations among those considered, DJIA (US) and FTSE350 (UK). These results are generally consistent with prior expectations concerning the relative efficiency of the stock markets examined. © 2011 Elsevier Inc.
Resumo:
Since the seminal works of Markowitz (1952), Sharpe (1964), and Lintner (1965), numerous studies on portfolio selection and performance measure have been based upon the mean-variance framework. However, several researchers (e.g., Arditti (1967, and 1971), Samuelson (1970), and Rubinstein (1973)) argue that the higher moments cannot be neglected unless there is reason to believe that: (i) the asset returns are normally distributed and the investor's utility function is quadratic, or (ii) the empirical evidence demonstrates that higher moments are irrelevant to the investor's decision. Based on the same argument, this dissertation investigates the impact of higher moments of return distributions on three issues concerning the 14 international stock markets.^ First, the portfolio selection with skewness is determined using: the Polynomial Goal Programming in which investor preferences for skewness can be incorporated. The empirical findings suggest that the return distributions of international stock markets are not normally distributed, and that the incorporation of skewness into an investor's portfolio decision causes a major change in the construction of his optimal portfolio. The evidence also indicates that an investor will trade expected return of the portfolio for skewness. Moreover, when short sales are allowed, investors are better off as they attain higher expected return and skewness simultaneously.^ Second, the performance of international stock markets are evaluated using two types of performance measures: (i) the two-moment performance measures of Sharpe (1966), and Treynor (1965), and (ii) the higher-moment performance measures of Prakash and Bear (1986), and Stephens and Proffitt (1991). The empirical evidence indicates that higher moments of return distributions are significant and relevant to the investor's decision. Thus, the higher moment performance measures should be more appropriate to evaluate the performances of international stock markets. The evidence also indicates that various measures provide a vastly different performance ranking of the markets, albeit in the same direction.^ Finally, the inter-temporal stability of the international stock markets is investigated using the Parhizgari and Prakash (1989) algorithm for the Sen and Puri (1968) test which accounts for non-normality of return distributions. The empirical finding indicates that there is strong evidence to support the stability in international stock market movements. However, when the Anderson test which assumes normality of return distributions is employed, the stability in the correlation structure is rejected. This suggests that the non-normality of the return distribution is an important factor that cannot be ignored in the investigation of inter-temporal stability of international stock markets. ^
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My dissertation investigates the financial linkages and transmission of economic shocks between the US and the smallest emerging markets (frontier markets). The first chapter sets up an empirical model that examines the impact of US market returns and conditional volatility on the returns and conditional volatilities of twenty-one frontier markets. The model is estimated via maximum likelihood; utilizes the GARCH model of errors, and is applied to daily country data from the MSCI Barra. We find limited, but statistically significant exposure of Frontier markets to shocks from the US. Our results suggest that it is not the lagged US market returns that have impact; rather it is the expected US market returns that influence frontier market returns The second chapter sets up an empirical time-varying parameter (TVP) model to explore the time-variation in the impact of mean US returns on mean Frontier market returns. The model utilizes the Kalman filter algorithm as well as the GARCH model of errors and is applied to daily country data from the MSCI Barra. The TVP model detects statistically significant time-variation in the impact of US returns and low, but statistically and quantitatively important impact of US market conditional volatility. The third chapter studies the risk-return relationship in twenty Frontier country stock markets by setting up an international version of the intertemporal capital asset pricing model. The systematic risk in this model comes from covariance of Frontier market stock index returns with world returns. Both the systematic risk and risk premium are time-varying in our model. We also incorporate own country variances as additional determinants of Frontier country returns. Our results suggest statistically significant impact of both world and own country risk in explaining Frontier country returns. Time-variation in the world risk premium is also found to be statistically significant for most Frontier market returns. However, own country risk is found to be quantitatively more important.