We investigate the activity and performance of 64 Swedish registered mutual equity funds available in the Swedish Premium Pension System from October 2002 to December 2011. Fund activity is measured by applying the holdings based analysis Active Share combined with Tracking Error Volatility (TEV). Active Share is a relatively new measure that compares a fund’s holdings with its benchmark index constituents (Cremers & Petajisto, 2009; Petajisto, 2013). This is used as a proxy for the fund’s stock selection strategy. As a complement, TEV is used as a proxy for the factor timing strategy. Performance are measured by using Jensen’s (1968) model, Fama and French’s (1993) model and Carhart’s (1997) model. We document that Swedish funds in the Premium Pension System are relatively passive in term of Active Share compared to US funds. We attribute this finding to the relative number of stocks held by a fund compared to the market. Swedish equity funds hold a relatively larger share of the number of stocks in the Swedish market while US funds hold a relatively smaller share of the stocks in the US market. We run a panel regression analysis to test the relation between Active Share and various variables. We find that funds with higher TER fees and fewer stocks on average have higher Active Share. There are also indications that TEV is positively related to Active Share. However, the overall explanatory power of the variables is low. We attribute this as evidence that Active Share is an independent measure of fund activity. Overall, we find neutral performance for an equally weighted portfolio of all funds in the PPS. To examine the performance differences between different levels of activity, we sort funds into five portfolios based on Active Share and TEV. The results show that, given a medium-to-low TEV, funds with high Active Share significantly outperform funds with low Active Share. Furthermore, it appears that the fee rebate in the Premium Pension System is important especially for the passive funds. Without the rebate, the passive funds underperform significantly. We run a panel regression analysis on the future fund performance to test the predictive abilities of Active Share and TEV. The results indicate that Active Share does not explain future performance differences. Conversely, TEV is negatively related to future performance which can be explained by fund managers being overconfident

The fund market has grown substantially during the past decades and the majority of Swedish citizens are invested in funds directly or through pension savings. There is mixed evidence on the performance of Swedish equity funds depending on the method employed and the time period studied. In this study, we set out to estimate abnormal performance using acknowledged methods during a time-period that is both longer and more recent than previous studies. Our sample is survivorship-free and consists of 150 mutual equity funds during January 1993 to December 2011. We use a four-factor model to estimate abnormal performance compared to an index and additional risk factors. We find that the average performance is neutral net of costs and that funds outperform with 1.7 percent before costs, the difference is approximately the average management fee. Over time, we find that the average abnormal performance and the share of funds that have significant outperformance have decreased while the share of significant underperformance has increased. Since the study of fund performance started in the 1960's the twin questions has been; does funds outperform the market and is this a result of pure chance or are managers skilled? Since we observe funds with significant positive and negative abnormal performance, we want to know if the results can attributed to luck or skill. We employ the latest technique, a bootstrap simulation, to test for skill or luck. This is the first study to employ the bootstrap to distinguish skill from luck in sample of Swedish funds. By ranking funds on performance after costs, we find that the performance of the majority of funds can be attributed to skill or "bad skill". The evidence is strongest in the top 95th percentile and above, and from the bottom 50th percentile and below.

Literature reveals studies on mutual fund performance analysis and persistency, with various results. Some studies support hort term performance persistence, while the rest claiming no such persistency among the portfolios. This thesis is an attempt to analyze the performances of Turkish open-end mutual funds for the period of 2003-2010 and search for persistency by extending the time period to June 2011. For performance evaluation, single factor CAPM and ama-French&rsquo / s Three Factor Model are applied. Persistency analysis is done by tracking the relative fund performances on a monthly basis. The results of this study indicate that for the sample period, Turkish A Type mutual funds neither overperform nor underperform the overall market. Nearly all Jensen&rsquo / s alphas are found to be zero, statistically significant. This is also an implication that the mutual funds are earning their expected returns in an efficient mutual fund market in Turkey. The Fama-French&rsquo / s three factor model shows slightly better performance, on the other hand. The size and book to market equity factors are not found significant in general, however they are found jointly significant in all regressions. Persistency is analyzed by tracking the mutual fund erformances on monthly basis. When some mutual funds showed negative or positive performance persistency during the period individually, but the overall picture demonstrates a balanced distribution of performance groups. The number Loser-Loser performances is slightly more than the other three groups, resulting in a tendency for short term negative persistency for the sample analyzed between the period of January 2003 to June 2011.

本文利用向量自我迴歸模型所得出來的殘差值來模擬未預期到的總體經濟訊息，以期限利差和一個月定存利率來捕捉殖利率曲線，以違約利差和股利收益率來描繪資產報酬的條件機率分布，本文實證未預期到的期限利差和未預期到的違約風險與淨值市價比因子和市值規模因子包含相同的訊息，因此後續檢驗這些能夠捕捉未來投資機會的總體經濟訊息比起Fama-French三因子模型是否對台灣股票橫斷面的平均報酬更具有解釋能力。 實證方法採用Fama-MacBeth(1973)兩階段迴歸方法，Fama-French三因子模型實證結果顯示台灣股票市場存在著負向的淨值市價比效果，但卻不存在著規模效果，這與國外一些學者研究1980年代之後規模效果逐漸消失的結論相同。在實證未預期到的總體經濟訊息模型時，由於被解釋變數為股票超額報酬率，因此常數項應該為不顯著的關係，但此假設強烈的被未預期到的總體經濟訊息模型拒絕，代表此模型可能遺漏了重要的解釋變數。因此，Fama-French 三因子模型對台灣股票橫斷面平均報酬率的解釋能力比未預期到的總體經濟訊息模型更佳。 / The Fama and French factors HML and SMB are correlated with innovations in variables that describe investment opportunities. I find that shocks to term spread and shocks to default spread have the same information with the Fama and French factors HML and SMB. This paper investigates whether a model that includes shocks to the aggregate dividend yield and term spread, default spread, and one-month deposit interest rate can explain the cross section of average return on Taiwan stock market as well as the Fama and French can. Using the Fama-MacBeth (1973) two steps cross-sectional regressions, I find there exists the negative book-to-market effect on Taiwan stock market, but the size effect disappears. Since the dependent variables in the regression is excess returns, the intercept of the cross-sectional regression should be zero. This hypothesis is strongly rejected in the case of the model includes shocks to the Macroeconomics variables and the market portfolio. It means this model omits some important variables, so the Fama and French three-factor model can explain the cross section of average returns better.

在知識經濟時代下，無形資產的對於公司的重要性愈來愈高。有別於在工業時代下的生產重心，著重在大量的土地，機器設備...等有形的資產，在二十一世紀競爭中致勝的關鍵因素卻是那些無實體存在的知識累積，例如：研究發展的能力、員工的素質、顧客關係的維持…等;然而，會計處理對於無形資產卻是停留在歷史的取得成本，而不是現時的市場價值，更甚，有些無形資產根本無法入帳;因此，資本市場如何看待與反應公司的無形資產就是一項有趣的議題。本研究之研究目的是：依據Fama and French (1993)三因子模型，以橫斷面的分析方式，欲控制了系統風險、規模效果和淨值與市價比效果後，進一步分別探討研究發展活動與專利權對於股票報酬之影響，是否擁有投入愈多的研發活動與專利可以在股票市場獲得愈高的報酬？是否研究發展費用與專利權數對於股票報酬有遞延效果的影響？ 樣本期間從民國七十一年到民國九十三年，包含上市與上櫃公司，總共有21717筆觀察值，在研究發展活動方面，本研究採用了當期研究發展費用與依五年資本化後之研究發展費用二種替代變數，專利權方面，採用專利權數與累積專利權數二種代理變數，其實證結果發現： (1)當期研究發展費用溢酬與股票超額報酬呈現顯著的正向相關，將研究發展費用依五年資本化後，資本化後之研究發展費用溢酬仍與股票超額報酬呈現顯著的正向相關。 (2)專利權數之溢酬與股票超額報酬卻是顯著的負相關，累積專利權數之溢酬與股票超額報酬也是呈現顯著的負向關係，可能的原因是：在本研究樣本裡的大部分的專利權數量是非常集中在少部分的公司。 (3)研究發展溢酬對於超額報酬最多有三年的遞延效果，專利權溢酬對於超額報酬至少有五年遞延的效果。 (4)當期研究發展費用溢酬與資本化後之研究發展費用溢酬對於超額報酬有顯著不同的影響，二者比較下，當期研究發展費用溢酬對於股票報酬的影響程度大於資本化後之研究發展費用溢酬。可能的原因是:Fama and French三因子模型某種程度上代表著流量的概念，因此，當期研究發展費用溢酬的效果較為顯著。 (5)在專利權數之溢酬與累積專利權數之溢酬二者之間，對於超額報酬不具有顯著差異性的影響。可能的原因是:大部分的樣本都沒有專利權，因此，專利權數之溢酬與累積專利權數之溢酬沒有太大的差異。 (6)以研究發展與專利來說，二者對於超額報酬具有顯著不同差異的影響。 / Since the change in the global economy in the last decade, from manufacturing and industry-based to knowledge-based, it has created new interest in intellectual capital and increased the demand for measuring and reporting the effect on business and profitability. Nonetheless, accounting conventions based on historical cost often understate their value. Thus, from a practical point of view, how the stock market responses to the innovative activity is an interesting issue. Here, the major objective of this study is, on the basis of the three-factor model in Fama and French (1993), to investigate the relationship between innovation activities in firms and stock returns. That is, the aim in this study is to examine whether the intellectual capital, in particularly focusing on R&D and patents, has impact on stock returns. Does the market provide the premium for the value of the innovation in firms? Do the stocks with more innovation efforts worth the higher market rate of returns? Do R&D and patents have time lag effect on returns? We find that: (1) The return premiums are significantly greater for high-level of R&D than for low-level R&D. The mimicking returns both for the R&D-expense factor and capitalized-R&D factors are significantly positive related to excess stock returns. (2) Contrary to our intuition and expectation, the mimicking returns both for patent count and cumulated patent count are significantly negative associated with excess stock returns. One possible explanation is that the distribution of patented innovation is known to be extremely skewed, implying that a few patents are very valuable and many are worth almost nothing. (3) R&D-related return premiums have 3-year lag effect on excess stock returns at most. As for patent-related return premiums, it shows 5-year lag at least for excess stock returns. (4) R&D expenses have more impact on stock returns than the R&D capitalization. One possible explanation is that the “flow” concept is more suitable than the “stock” concept in the Fama and French (1993) regression of stock returns. (5) There is no difference between patent count and cumulated patent count in explaining stock returns. It is likely that, for a large proportion of the sample, they do not possess any patents. (6) When it comes to compare R&D to patents, we find that there is statistically significant difference between the two in explaining excess stock returns.

[Truncated abstract] This thesis examines competing asset-pricing models in Australia with the goal of establishing the model which best explains cross-sectional stock returns. The research employs Australian equity data over the period 1980-2001, with the major analyses covering the more recent period 1990-2001. The study first documents that existing asset-pricing models namely the capital asset pricing model (CAPM) and domestic Fama-French three-factor model fail to meet the widely applied Merton?s zero-intercept criterion for a well-specified pricing model. This study instead documents that the US three-factor model provides the best description of Australian stock returns. The three US Fama-French factors are statistically significant for the majority of portfolios consisting of large stocks. However, no significant coefficients are found for portfolios in the smallest size quintile. This result initially suggests that the largest firms in the Australian market are globally integrated with the US market while the smallest firms are not. Therefore, the evidence at this point implies domestic segmentation in the Australian market. This is an unsatisfying outcome, considering that the goal of this research is to establish the pricing model that best describes portfolio returns. Given pervasive evidence that liquidity is strongly related to stock returns, the second part of the major analyses derives and incorporates this potentially priced factor to the specified pricing models ... This study also introduces a methodology for individual security analysis, which implements the portfolio analysis, in this part of analyses. The technique makes use of visual impressions conveyed by the histogram plots of coefficients' p-values. A statistically significant coefficient will have its p-values concentrated at below a 5% level of significance; a histogram of p-values will not have a uniform distribution ... The final stage of this study employs daily return data as an examination of what is indeed the best pricing model as well as to provide a robustness check on monthly return results. The daily result indicates that all three US Fama-French factors, namely the US market, size and book-to-market factors as well as LIQT are statistically significant, while the Australian three-factor model only exhibits one significant market factor. This study has discovered that it is in fact the US three-factor model with LIQT and not the domestic model, which qualifies for the criterion of a well-specified asset-pricing model and that it best describes Australian stock returns.

NY, Columbia Univ., Graduate School of Arts and Sciences, Diss.--New York, 2003. / Kopie, ersch. im Verl. UMI, Ann Arbor, Mich. - Enth. 3 Beitr.

This thesis provides evidence of size and value premiums in returns in the Central and Eastern European (CEE) region, through its analysis of financial markets in 12 countries. Following the portfolio construction methodology of Fama and French (1996) we use a sample of 1245 stocks and record that small stocks outperform big stocks (size premium) and value stocks outperform growth stocks (value premium). In addition, we create nine portfolios to test the Fama and French three-factor model and show that the factor-mimicking portfolios that have been documented in the developed markets, SMB (small minus big) and HML (high minus low), also capture most of the cross-section variation in average stock returns in the CEE region. We demonstrate a similar pattern in terms of size return as documented in the U.S. market, but with small differences in the value returns found. Although the Gibbons-Ross-Shanken (GRS) test does not reject the null with 95%, we do not agree that the model completely explains the variation in average returns across the portfolios. The GRS rejects the null at 90% and implies that other factors are omitted from the model. Nevertheless, this thesis contributes to the literature applying asset pricing models to the CEE region, and should provide insights to investors active in the CEE...

Det är sedan länge känt att det finns en positiv korrelation mellan risk och avkastning. Investerare och bolag kan välja mellan flera olika prissättningsmodeller för att förutspå priset på en aktie. Forskare har, med den kända enfaktormodellen CAPM som utgångspunkt, utvecklat en modell som tar hänsyn till mer än bara marknadsfaktorn. Detta resulterade i framtagandet av Fama & French-trefaktormodellen (FF3) som även inkluderar storleksfaktorn SMB samt värdefaktorn HML. Syftet med studien är att utvärdera två prissättningsmodeller, CAPM och FF3, för att kunna bedöma deras prestanda vid värdering av förväntad avkastning. Tidigare forskning, inom området för nämnda modeller, berör ofta internationella marknader samt modellernas prestanda för portföljer. Vår studie utförs på utvalda enskilda svenska aktier inkluderade på Stockholmsbörsens Large Cap för januari år 2011 till december år 2015, genom att replikera tidigare forskning gjord av Bartholdy & Peare (2005). Utvalda bolag analyseras efter regressioner för modellerna för att kunna utvärdera dessa var för sig, samt för att se om FF3 har en högre justerad förklaringsgrad än CAPM för enskilda svenska aktier. Resultatet av studien visar att både CAPM och FF3 är applicerbara för utvalda enskilda svenska aktier. Ställs FF3 i förhållande till CAPM föreligger skillnad i justerad förklaringsgrad, dock är den ytterst marginell. Sammanfattningsvis bidrar studien med kunskapen om att CAPM och FF3 går att applicera på enskilda svenska aktier, men att det inte föreligger någon större skillnad i val av dessa två modeller. / Investors and companies can choose between multiple pricing models to predict the price of shares. With the known one factor model CAPM, researchers have developed a model that consider more than just the market factor. This resulted in the creation of the Fama & French three factor model (FF3), which also includes the size factor SMB and the value factor HML. The purpose of the study is to evaluate two pricing models, CAPM and FF3, to assess their performance when evaluating expected returns. Previous research often deal with international markets and model performance of portfolios. We study selected individual Swedish shares for January 2011 to December 2015 by replicating previous research by Bartholdy & Peare (2005). Selected companies are analysed by regressions for the models to be able to evaluate these separately, and to see if FF3 has a higher degree of explanation than CAPM for individual Swedish shares. The result of the study shows that both CAPM and FF3 are applicable for selected individual Swedish shares. There is a difference in the adjusted degree of explanation between the models but it is marginal. In conclusion, the study contributes with the knowledge that CAPM and FF3 can be applied to individual Swedish shares, but there is no major difference in the choice of these two models.

Notre thèse explore les facteurs de risque et les modèles des facteurs sur le marché boursier chinois A-share. Notre étude est basée sur le contexte du modèle facteur de Fama-French (FF). Tout d'abord, au chapitre 1, nous réexaminons l'applicabilité du Modèle Fama-French à Trois Facteurs (FF3F) et du dernier Modèle Fama-French à Cinq Facteurs (FF5F), compte tenu de plusieurs caractéristiques spéciales du marché boursier chinois. Les résultats empiriques montrent que le Modèle FF3F peut expliquer la majorité des variations de séries chronologiques des rentabilités des actions chinoises A-share. Au cours de la période d'échantillonnage, le marché bêta et le facteur SMB sont des déterminants importants pour expliquer la variation transversale des rentabilités des actions, cependant nous ne trouvons aucune prime de valeur. D’après la comparaison des performances des modèles FF3F et FF5F en présence de facteurs de rentabilité et d'investissement, le Modèle FF5F ne semble pas capturer plus de variations de rentabilités espérées que le modèle à trois facteurs, à l'exception des six portefeuilles pondérées en valeurs qui formés à partir de la taille et de la rentabilité opérationnelle.Dans le chapitre 2, nous examinons si les facteurs FF, SMB et HML, sont des proxys d'innovations de variables d'état sélectionnées (rendement de dividende agrégée, taux de T-bonds en un mois, l’écart de terme et l’écart de défaut) qui décrivent, sur la période recherche, les opportunités futures d'investissement sur le marché boursier chinois A-share. Les régressions chronologiques et les régressions des séries transversales sont réalisées sur cinq modèles comparatifs en utilisant l'approche à deux étapes Fama-MacBeth. Les facteurs FF ne perdent pas leur pouvoir explicatif, avec ou sans la présence des innovations des quatre variables d’états sélectionnées, à la fois dans les examens de séries chronologiques et les examens transversaux. Nous trouvons que l'information contenue dans l'innovation de rendements de dividende agrégés semble totalement capturée par la combinaison du marché bêta et du facteur de taille. Les facteurs FF ont pu jouer un rôle limité de capturer d'opportunités d'investissement alternatives représentées par les innovations des quatre variables d'état sélectionnées.Dans le chapitre 3, nous étudions si les facteurs FF sont des proxys de facteurs de risque de détresse et si différentes méthodes de construction des facteurs entraînent des résultats différents. Les résultats empiriques suggèrent qu'il n'y a pas de preuve significative que les facteurs FF représentent un risque de détresse sur le marché boursier chinois A-share. En comparant les résultats des régressions des séries chronologiques à partir de deux méthodes différentes, la performance du facteur de risque de détresse basé sur le DLI semble légèrement meilleure que celui basé sur le O-score. Cependant, le facteur de risque de détresse n'est pas un déterminant important des rentabilités transversales moyennes, et les facteurs FF ne peuvent pas représenter le facteur de risque de détresse dans la section transversale du marché boursier chinois A-share. / This dissertation is to explore the risk factors and factor models on Chinese A-share stock market based on the context of Fama-French (FF) factor model. First of all, chapter 1 re-examines the applicability of Fama-French Three-Factor (FF3F) Model and the latest Fama-French Five-Factor (FF5F) Model considering several special features of Chinese stock market. FF3F Model can explain a majority of time-series variation of the Chinese A-share stock returns. The market beta and SMB are important determinants in explaining the cross-sectional variation in the average stock returns over the sample period; however, we find no value premium. Comparing the performance of both FF3F Model and FF5F Model on Chinese A-share stock market, in the presence of profitability and investment factors, FF5F Model seems not capture more variations of expected stock returns than the three-factor model except the six value-weighted portfolios formed on size and operating profitability.Chapter 2 examines whether FF factors SMB and HML proxy for the innovations of selected state variables (aggregate dividend yield, one-month T-bill rate, term spread and default spread) that describe future investment opportunities on Chinese A-share stock market during the research period. Both time-series and cross-sectional regressions are performed on five comparative models using Fama-MacBeth two-stage approach. FF factors don’t lose their explanatory power with or without the presence of the innovations of selected four state variables in both the time-series and cross-sectional examinations. We find that the information contained in innovation of aggregate dividend yields seems totally captured by the combination of market beta and size factor. FF factors might have played a limited role in capturing alternative investment opportunities proxied by innovations of the selected four state variables.Chapter 3 investigates whether FF factors proxy for distress risk factor and whether different methods of constructing factors result in the different outcomes. The empirical results suggest that there is no significant evidence that FF factors are proxying for distress risk on Chinese A-share stock market. Comparing the time-series regression results by using two different methods, the distress risk factor constructed based on DLI seems to perform slightly better than that constructed based on O-score in capturing time-series average returns. However, the distress risk factor is not an important determinant of cross-sectional average returns, and FF factors cannot proxy as distress risk factor in the cross-section on Chinese A-share stock market.