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Impact des gains ou pertes non réalisés sur les rentabilités des actions : théories et tests dans un cadre théorique alternatif d'utilité / Impact of the unrealized gain or loss on stock returns : theory and tests in an alternative utility frameworkLi, Shoujun 03 June 2016 (has links)
Cette thèse applique la théorie des prospects et la théorie du regret à l’étude sur la performance des actions et à expliquer une anomalie du marché connue appelé l’effet momentum. Cette thèse propose un modèle théorique qui lie les facteurs comportementaux à la performance des actions et à l’effet momentum, et ensuite réalise des tests empiriques pour examiner le modèle théorique. Dans le chapitre 2, le modèle est établi sur un concept des gains/pertes potentiels, qui indiquent si un investisseur se trouve actuellement dans une situation gagnante ou perdante. Ensuite, le modèle montre que les investisseurs sont très réticents à vendre leurs stocks dans une situation des grands gains ou des grandes pertes. Les chapitres 3 et 4 effectuent des tests empiriques sur le modèle des gains/pertes potentiels. L'échantillon des tests comprend tous les stocks de NYSE et l'AMEX de l’année 1982 à 2012. Les tests sont en mesure de confirmer l'influence des gains/pertes potentiels sur les rendements des actions. En outre, une stratégie de coût nul d’Extrémité moins Moyen (EMM), basée sur le modèle théorique, est documentée pour être rentable après contrôlée pour des risques. Dans le chapitre 5, le modèle des gains/pertes potentiels est développé dans une version dynamique. Il suggère que l'influence des gains/pertes potentiels pourrait persister pendant une période de intermédiaire à long terme, et génère une tendance à la hausse de la performance pour les actions avec un grand gain/perte potentiel. Les tests empiriques dans ce chapitre se concentrent sur l'évolution de série temporelle des rendements. Les tests montrent que les actions avec un grand gain/perte potentiel ont une plus forte tendance à la hausse. Le chapitre 6 applique les résultats du chapitre précédent pour expliquer l'effet momentum. La tendance à la hausse correspond à une auto-corrélation positive des rendements, ce qui est l'une des sources qui contribuent au profit de momentum. Les tests empiriques dans ce chapitre regardent la similitude entre la stratégie de momentum et les gains/pertes potentiels, et examinent également la corrélation entre le profit de momentum et le profit de la stratégie EMM. Les tests montrent que des gains/pertes potentiels pourraient contribuer à l'effet momentum, mais ne sont pas la seule source. L'effet momentum peut être le résultat d'une combinaison de plusieurs facteurs complexes. / This dissertation applies the prospect theory and the regret theory to the study on the stock performance and to explain one well-known market anomaly called the momentum effect. The dissertation proposes a theoretical model that links the behavior factors to stock performance and the momentum effect, and performed empirical test to examine the theoretical model. In chapter 2, the model is established on the concept of the potential gain/loss, which indicates if an investor is currently at a winning or a losing position. The model then shows that the investors are highly reluctant to sell their stocks in a large gain or in a large loss situation. The chapter 3 and 4 perform empirical tests on the model of potential gain/loss. The test sample includes all stocks in NYSE and AMEX from 1982 to 2012. The tests are able to confirm the influence of the potential gain/loss on stock returns. Moreover, a zero-cost Extremity minus Middle (EMM) strategy based on the theoretical model is documented to be profitable after controlling for risks. In chapter 5, the model of potential gain/loss is developed into a dynamic version. It suggests that the influence of a potential gain/loss could persist over an intermediate to long term, and generates an upward trend in performance for stocks with large potential gain/loss. The empirical tests in this chapter focus on the time serial evolution of returns. The tests show that stocks with large potential gain/loss have a stronger upward trend. The chapter 6 applies the results from the previous chapter to explain the momentum effect. The upward trend corresponds to a positive return autocorrelation, which is one of the sources that contribute to the momentum profit. The empirical tests in this chapter look into the similarity between the momentum strategy and the potential gain/loss, and also examine the correlation between the momentum profit and the profit from the EMM strategy. Tests show that the potential gain/loss could contribute to the momentum effect, but is not the only source. The momentum effect could be a result of a combination of many complex factors.
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Momentum and reversal effects in Brazil / Efeito momento e efeito contrário no BrasilJoão Paulo de Barros Improta 05 November 2012 (has links)
In financial markets, momentum effect can be defined as the tendency of prices to maintain their short term movements. On the other hand, reversal effect is usually understood to be the change in direction of long term price movements. This paper examines whether momentum and reversal effects were in evidence in the Brazilian stock market between January 1999 and June 2012. After calculating 1296 trading strategies, no evidence of reversal effect is found. With regard to momentum effect, some weak evidence is presented for the very short term. Exposure to risk factors can explain returns on strategies, including returns on momentum strategies. The results are borne out with different market proxy specifications and size subsamples. When compared to previous studies, the results raise the question of whether the reversal effect is vanishing from the Brazilian stock market and whether the traces of momentum are sufficient to confirm its existence. Furthermore, evidence of seasonality is found for June in momentum strategies and for November in both reversal and momentum strategies. Subsequent tests reveal that the effects of seasonality are limited to small stocks. / Nos mercados financeiros, o efeito momento pode ser definido como a tendência dos preços em manter seus movimentos de curto prazo. Por outro lado, o efeito contrário é geralmente entendido como a mudança na direção dos movimentos de longo prazo dos preços. O presente trabalho examina a existência dos efeitos momento e contrário no mercado acionário brasileiro no período compreendido entre janeiro de 1999 e junho de 2012. A partir do cálculo de 1296 estratégias de investimento, nenhuma evidência de efeito contrário é encontrada. Com relação ao efeito momento, observou-se apenas uma fraca evidência no curtíssimo prazo. A exposição aos fatores de risco é capaz de explicar os retornos das estratégias, inclusive os retornos das estratégias de momento. Os resultados são robustos ao se utilizar diferentes especificações de proxy de mercado e subamostras de valor de mercado. Quando comparados a trabalhos anteriores, os resultados colocam em questão se o efeito contrário está desaparecendo no mercado acionário brasileiro e se as fracas evidências do efeito momento são suficientes para confirmar sua existência. Ademais, são observadas evidências de sazonalidade no mês de junho nas estratégias de momento e, no mês de novembro, em ambas as estratégias. Testes posteriores revelam que esses efeitos de sazonalidade estão restritos à subamostra de baixo valor de mercado.
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動能效果與財務危機預測之研究余美儀 Unknown Date (has links)
1997年爆發亞洲金融風暴,隔年(1998年)起公司發生財務危機事件層出不窮,1998年至2005年間最為嚴重;2007年全球金融海嘯至今,投資人擔心買到地雷股,對於投資股票市場仍採觀望態度。在經過層層把關的財報背後究竟隱藏多少危機?這些危機難道是不可預測的嗎?其實,公司爆發財務危機並非一夕之間產生的問題,就如同人類的慢性病不是一天造成的,是長期忽略身體健康警訊造成的結果,事出必有因,因此許多學者便開始探究財務危機背後的成因,試圖找出一些指標供投資人作為投資前之考量因素。
本研究主要之目的在於探究財務危機之預測指標,分別探討Beta、公司規模、淨值市價比以及前一年平均報酬(負的動能效果)是否可作為財務危機之預測指標。本研究之樣本公司為1983年至2007年之台灣上市公司,利用Altman提出之Z-score模型將公司區分為危機公司以及正常公司,再將樣本公司依Beta、公司規模、淨值市價比以及前一年平均報酬分別分組,探討這些變數是否可作為財務危機之預測指標。實證結果指出Beta及淨值市價比無法作為財務危機之預測指標,但公司規模及前一年平均報酬(負的動能效果)可以作為財務危機之預測指標。 / With the Asian financial crisis breaking out in 1997, many companies began to suffer financial distress in the following year, and the situations were getting even worse during 1998 and 2005. Faced the new waves of financial tsunami across the world starting from 2007, the investor, therefore, have been adopting a wait-and-see attitudes towards the stock market, fearing of being hit by the “tank stocks”。How many financial problems hidden behind the carefully prepared financial statements? Are they unpredictable? As a matter of fact, just like the human chronic diseases which actually caused by long-term ignorance of health warning, corporate financial distress never happens suddenly. Thus a number of scholars are dedicated to study the reasons for financial problems, attempting to figure out certain indicators capable of being prior reference for investment decision-making.
This paper aims to study the predictors of financial distress. Beta, firm size, book-to-market ratio and average monthly prior-year return (negative momentum effect) are to be considered respectively to determine their possibilities of being predictors. The sample companies discussed in this paper are chosen among the listed companies during 1983 and 2007 in Taiwan. They are grouped into two categories of crisis company and normal company by using the Z-score model developed by Altman. Then the sample companies are divided in terms of Beta, firm size, book-to-market ratio and average monthly prior-year return so as to trace these variables’ likelihood to predict bankruptcy. It eventually turns out that firm size and average monthly prior-year return could serve as predictors of financial distress, other than Beta and book-to-market ratio.
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Os efeitos disponibilidade e momento no mercado acionário brasileiro: um estudo empíricoPires, Mila Rodrigues 04 February 2013 (has links)
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Previous issue date: 2013-02-04 / O objetivo deste trabalho foi testar a presença de dois efeitos no mercado acionário brasileiro: disponibilidade e momento, amplamente estudados para o mercado norte-americano em publicações anteriores. Utilizando uma amostra de 70 empresas foram analisadas séries temporais de retornos mensais do período de ago/2006 a jan/2011, cujos resultados não foram suficientes para rejeitar a hipótese de não eficiência do mercado brasileiro. No teste do efeito disponibilidade, apenas uma das quatro estratégias testadas com a utilização do indicador de retorno do mês anterior da ação gerou retornos positivos (2,27% ao mês), e os indicadores de volume anormal e 'presença na mídia' geraram retornos negativos nas estratégias testadas. No caso do efeito momento, das 16 estratégias estudadas, a única que proporcionou retorno positivo estatisticamente significativo foi a que considerou o período de três meses de formação e manutenção das carteiras (2,01% ao mês). / The objective of this study was to test the presence of two effects in the Brazilian stock market: availability and momentum, widely studied for the American market in previous publications. Using a sample of 70 companies a time series of data returns from Aug/2006 to Jan/2011 was analyzed and the results were not sufficient to reject the hypothesis of an efficient market. In the availability effect test, only one of the four strategies tested using the return of the preceding month indicator had a positive return (2,27% p.m), whilst abnormal volume and "media presence" indicators generated negative returns. In the momentum effect test, out of the 16 studied strategies, the only statistically significant positive return was with portfolio considering three months for the formation and maintenance periods (2,01% p.m).
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Cross-Section of Stock Returns: : Conditional vs. Unconditional and Single Factor vs. Multifactor ModelsVosilov, Rustam, Bergström, Nicklas January 2010 (has links)
<p>The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama & French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama & French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted.</p><p>To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama & French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama & French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange.</p><p>We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.</p>
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Cross-Section of Stock Returns: : Conditional vs. Unconditional and Single Factor vs. Multifactor ModelsVosilov, Rustam, Bergström, Nicklas January 2010 (has links)
The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama & French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama & French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted. To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama & French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama & French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange. We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.
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