Syfte: Undersökningens syftet är att mäta huruvida det går att få ut en överavkastning av aktier som väljs in i (respektive ut ur) OMX Stockholm Benchmark (OMXSB), som följd av att ett index ändrar sin komposition. Delsyftet är att undersöka om det går att se en signifikant ökning av handelsvolymen i anslutning till ändringsdagen. Metod: Studien tillämpar en eventstudie som undersökningsmetod av kvantitativ karaktär. Studien undersöker indexet OMXSB och innefattade totalt 111 stycken ingående och utgående aktier fördelat på 10 tillfällen. Två eventfönster har konstruerats; ett kring annonseringsdagen och ett kring ändringsdagen. Den procentuella handelsvolymen har mätts över eventfönstret kring ändringsdagen. Resultat: Den genomsnittliga kumulerade överavkastningen för eventfönstret vid annonseringsdagen uppgick till 1,02 % (-6 %) för de aktier som valdes in (ut). Det motsvarande resultatet 2,55 % (-0,41 %) framkom i eventfönstret för ändringsdagen. Handelsvolymen uppnådde i båda fallen en signifikant ökning dagen innan ändringen genomfördes. Slutsatser: Resultatet visade en signifikant överavkastning för aktier som valdes in (ut) i eventfönstret kring ändringsdagen (annonseringsdagen). Den signifikanta skillnaden av handelsvolymen tyder på att indexerarna handlar aktierna dagen innan ändringen genomförs. För aktier som väljs in gick det att se ett pristryck där priset höjdes fram till dagen innan ändringen genomfördes, som sedan återgick. Resultaten kan ha påverkats av externa faktorer vilket kan ha lett till en missvisande bild av den undersökta effekten. / Purpose: The study aims to investigate whether it is possible to get an abnormal return of stocks added to (or deleted from) the OMX Stockholm Benchmark index (OMXSB), as a result of a changes of the index composition. A subsidiary aim of the study is to investigate whether it is possible to see a significant increase in trading volume in close to the change day. Methodology: The study applies an event study as method of investigation of a quantitative character. The study examines the OMXSB and include a total of 111 added and deleted stocks distributed on 10 occasions. Two event windows have been designed: one around announcement day and one around change day. The percentage change of trading volume has been measured over the event window around the change day. Results: The average cumulative abnormal return for the event window around announcement day reached 1.02% (-6%) for the added (deleted) shares. Corresponding results of 2.55% (-0.41%) emerged in event window for change day. In both cases the trading volume reached a significant increase the day before the change was implemented. Conclusions: The results showed a significant abnormal return for stocks that were added (deleted) in the event window around the change day (announcement day). Trade volume suggests that index funds trade shares the day before the change day. For the added shares a price pressure could be identified up to the day before change day. The results may have been influenced by external factors which may have lead to a misleading picture of the investigated effect.

傳統探討分析師推薦資訊價值的研究多採用累積超額報酬的方式，近年來研究顯示個別投資人的績效顯著低於機構投資人，因此是否分析師推薦能夠幫助提升個別投資人的福利。本論文的第一個貢獻在檢定是否個別投資人能夠獲取分析師推薦的資訊價值，為區分推薦資訊分別對於個別與機構投資人的價值為何，本研究採用的每種投資人實際的交易利潤作為衡量指標。 研究結果顯示所有投資人都可以透過買入推薦獲取顯著的正報酬，但在賣出推薦上，僅外資與共同基金仍能維持獲取正的報酬。同時發現在推 薦事件期間，專業機構投資人的利潤顯著高於一般散戶的獲利。 進一步，本論文的第二的主題在探討此推薦的資訊價值對於不同投資人的差異，是否肇因於推薦券商所提供的私有資訊，因此進一步將各類投資人分成推薦券商的客戶與非客戶。結果顯示國內機構投資人的利潤在客戶的身上顯著高於非客戶的獲利，顯示推薦券商在對外公佈推薦資訊前的確提供私有資訊給其國內機構客戶，但此現象在賣出推薦並不存在。 第三，本論文進一步分析是否拿到推薦券商所提供私有資訊的客戶也是推薦券商的經紀業務收益的主要貢獻者。在比較推薦券商與非推薦券商在被推薦股票上的相對交易量(金額)中，發現推薦券商的確因為買入推薦股票而增加經紀業務量，但很驚訝的發現貢獻最多交易量的是個別投資人，而非拿到最多好處的機構投資人。 最後，本研究透過迴歸分析探討不同投資人的交易利潤與推薦券商所獲得的經紀業務量的關係。在控制推薦類型、推薦評等與被推薦股票之股票特性後，發現投資人的交易利潤與推薦券商的經紀業務收益成正相關，再次顯示券商推薦與其各項業務收益間的關係。 / Traditionally, information value of analysts’ recommendations has been well-recognized by cumulative abnormal returns. Recent studies show that individuals are underperformed, and therefore, it is a critical issue on if analysts’ recommendations are helpful to individuals’ welfares. The first contribution of this dissertation to the literature is to examine whether individual investors are capable of capturing the information value. To classify the information value of recommendations for individuals and institutions, respectively, I, thus, use a direct measure to calculate the actual trading profits of types of traders. To our best knowledge, this is the first paper that demonstrates the information value for types of investors. Our results indicate that, all investors get positive and significant profits in brokerages’ buy recommendations, no matter what types of investors are measured. As to sell recommendations, only foreign investors and mutual funds have positive returns. We also find that professional institutions earn more profits than retail investors during the recommendation event periods. Further, the second objective of this dissertation is to test whether the information values are caused by private information from brokerages’ houses, we separate the profits of types of investors into customers and non-customers based. The findings are that only domestic institutional customers of recommending brokerages are more beneficial than those of non-recommending brokerages in buy recommendations, which implies that brokerage houses may reveal private information to their own institutional customers before buy recommendations make public. This does not hold for sell recommendations. Third, we are interested in analyzing whether the private information that recommending brokerages provide to their own customers may, indeed, contribute to brokerages’ commission revenues. By comparing the trading volume of recommending brokerages and non-recommending brokerage for the covered stocks, we find that the volumes of covered stocks issued in the recommending brokerages are increased for buy recommendations. Particularly, we find that the main contribution of trading volume is from individuals. Furthermore, we run regressions to study the relationship between trading profits of types of investors and trading volume of recommending brokerages. After controlling recommendation types, consensus rating of recommendations, and stock characteristics, our results indicate that trading profits of all types of investors are positively related to commission revenues of brokerages. This may justify the importance of brokerage recommendations on their business relationships.

In this thesis we investigate the problem of portfolio re-balancing for fixed periods using a cost/risk adaptation model and stochastic optimization. The cost/risk adaptation model takes theory of optimal liquidity costs and risk preference to build a universe in which we try to find better strategies than conventional ones. The results are focused on the comparison between the conventional execution strategies versus our developed model. We have found that our model outperforms the conventional methods for all assets that has been evaluated, and especially for investors whom value exposure to the markets higher.

This thesis examines which factors that affect the number of trades in exchange-traded products (ETPs) on Nordic Derivatives Exchange. Multiple linear regression is used to model the relationship between the number of trades and 65 initially chosen predictor variables. The predictor variables include various indices, commodities, stocks, and volatility measures. Two models are presented, one of which includes a lagged dependent variable. These models explain 89% and 92% of the variance within the data. Foremost, the results confirm previous research advocating the volatility to play a significant role on the number of trades, but now also shown for ETPs. Currency exchange rates, equity indices and palladium are also shown to be statistically significant. In addition, interpretations of the results are given and suggestions for further research. / Den här uppsatsen undersöker vilka faktorer som påverkar antalet avslut i börshandlade produkter (ETP:er) på Nordic Derivatives Exchange. Multipel linjär regression används för att undersöka relationen mellan antalet avslut och 65 på förhand valda regressionsvariabler som vi anser intressanta att undersöka. Dessa regressionsvariabler består av bland annat olika index, råvaror, aktier samt volatilitetsmått. Två modeller presenteras, varav en inkluderar en laggad beroende variabel. Dessa två modeller förklarar 89 % respektive 92% av variationen i datan. Resultatet visar att volatiliteten har en signifikant påverkan med avseende på antal avslut vilket bekräftar tidigare forskning, men visas nu gälla även för ETPer. Valutakurser, aktieindex och palladium visas vara signifikanta. Vidare ges tolkning av resultatet och förslag på framtida forskning.

本文主要在探討影響台灣股票市場波動的因素，除了考慮以之前學者設定的 VAR(12)模型研究，另外以 SUR(5)模型來討論股市波動與基本面、交易面間的關係；最後，再以自我迴歸異質條件變異數模型來分析股市波動的特性。最重要的是，我們會根據誤差項的各類檢定結果來判定研究股市波動性質的最佳模型。 在聯立方程式的估計中，我們發現代表資訊到達指標的兩變數--週轉率與成交量成長率--會影響股票市場的波動。另外，我們找出交易面（成交量成長率）可能會影響基本面（匯率），這也就是說，在研究股市波動時，我們不需要特別區分變數的屬性。 在 GARCH 模型及 TGARCH 模型中，我們仍然可發現週轉率與成交量成長率會影響股市條件平均數或條件變異數；除此之外，好壞消息對股市日報酬率條件變異數（條件波動）應有不同的影響效果（壞消息的影響力較快反應）。而股市自身風險係數雖然統計檢定上不顯著異於零，但若未加入條件平均數的估計式，則可能會使模型得到較差的誤差項檢定結果，顯見股市自身風險應為影響投資人設定期望報酬率水準的重要因素之一。 從上述估計結果，我們可以知道，若散戶投資人能正確解讀市場上出現的各種新資訊之背後意義，將可使成交量成長率或週轉率（大部份可能代表無意義或不正確的交易行為）的變動幅度降低，進而有效地減少股票市場中股價異常波動的現象。 / My essay's topic focuses on discussing the factors that influence stock market volatility in Taiwan's stock market. Besides VAR(12) model as previous researchers have studied, I tries to set up SUR(5) models analyzing the relationship among the stock market volatility、the foundamental variables'volatilities and trading activities; Then I cited ARCH models ( autoregressive conditional heteroskedisticity models ) to find out the characteristics of stock market volatility. Most important of all, according to each misspecification test ( residual test ), I would specify the better models to describe the stock market volatility. In the estimations of system equations ( VAR(12)and SUR(5)models ), first I found that turnover rate and the growth rate of trading volume, which represent the information arrival indexes, could effect stock return's monthly conditional variance. Second, I especially found out the evidence that trading activities (trading volume growth) would probably have an impact on the macroeconomic variable ( exchange rate volatility ). It shows that we don't need to distinguish the attributes of those factors which could influence stock market volatility. In GARCH and TGARCH model, the positive influences of turnover and trading volume growth on daily stock return's conditional mean and conditional variance ( conditional volatility ) are still obvious, Within these TGARCH model, I discovered that bad news and good news could have different influences on stock market volatility ( the impact of bad news which resulted in downward movements of stock market volatility appeared faster that the good news'which caused upward movements). Stock market's self-risk(σ_t-1^{^2}) is statistically insignificant different from zero in GARCH models, but when I omitted this variable in daily stock return's conditional mean estimation equation, standardized residual might not obey the assumption of normal distribution. It apparently told us that the stock market's self-risk term ( σ_t-1^{^2} ) is one of the critical factors which influences investors to estimate expected return level. From those results above, we realized that if investors could precisely understand the real meanings of new information conveying in the stock market, it might decrease the levels of turnover and trading volume growth ( which could sometimes represent meaningless or inexact trading activities ), then effectively reduce the abnormal volatility phenomenon in stock market.

傳統貨幣需求函數的估計，使用的影響因素包括物價、所得及利率。但是近年股市的蓬勃發展，對貨幣需求造成了一定程度的影響。 Friedman 就股市對貨幣需求的影響提出 4 大效果，分別是交易效果、資產組合調整效果、財富效果及替代效果。其中替代效果為負，其他的效果為正。然而並非只有股市會對貨幣需求造成影響，貨幣需求同樣會影響股市。本文採用 Johansen Procedure 估計法，首先建立一般的貨幣需求模型，使用的雙變數包括貨幣需求、物價、所得及利率，實證結果確定這些變數存在 2 條共積關係，一是貨幣需求共積方程式，一是物價共積方程式。然後我們將股市成交量放入，同樣確定這些變數間具有 2 條共積關係。 Johansen Procedure 有 5 種模型，分別適用於不同的情況，我們要事先由資料來判斷使用哪一個模型並不容易，因此本文採用了多項標準，包括共積係數符號及其大小、向量誤差修正模型誤差項常態性與序列相關檢定、重要統計值(RSS、AIC、SC)等，用來作為選擇最適模型的依據。經由實證結果我們發現，不論是否加入股市成交量，模型三都是最適當的模型，也就是資料有不為零的平均數與線性趨勢，但共積方程式只有截距項。 就貨幣需求共積方程式殘差對各變數的影響來看，M1A 與 M1B 的連續增加，都會使股市成交量擴大，而 M1B 的連續增加還會形成物價上漲的壓力。而就物價共積方程式殘差對各變數的影響來看，解釋上較不容易。這可能是因為台灣地區物價長期處於穩定，加上台灣股市受到心理及消息面的影響性很大，要用總體變數作一個完整的解釋並不十分容易。雖然如此，貨幣市場與股票市場間的互動仍然極具有研究價值。 / Traditionally, when estimating the money demand, we use price index, income, and interest rate as its influcing factors. But the stock market that is booming these years has made certain influence on money demand. Milton Friedman pointed out that there are 4 effects that stock market can influcnce money demand. They are trading effect, portfolio reconstruction effect, wealth effect, and subsitution effect. Among these effects, subsitution effect has negative influence on money demand and other 3 effects have positive influence on mondy demand. However, not only does the stock market has influence on mondy demand, money demand also has influence on stock market. In my thesis, I applied Johansen Procedure estimation method. First, I established a traditional model on money demand. The variables I used including money demand, price index, income, and interest rate. From the empirical outcome we are sure that there are 2 cointegration equations among these variables.One is the money demand cointegration equation and the other is the price cointegration equation. Next we add the stock trading volume to the model. We also make sure that there are 2 cointegration relationships among them. There are 5 models in Johansen Procedure estimation method, and they are applied in different situations. It is not easy to decide which model to apply in advance. So in the thesis, we used many criteria, including the value and the sign of the coefficients, the the serial correlation and the normality test of the residuals from the vector error correction model, and important statistics(RSS, AIC, SC) to decide which model to apply. According to the empirical outcome, whether stock trading volume is included, model 3, which is there are means and linear trend in data but the cointegration equation only has intercept is the proper model we selected. About the residuals from the money demand cointegration quation's influence on variables, we find that the continuous increase in M1A and M1B will make enlarge the stock trading volume. Besides, the coutinuous increase in M1B will cause the price to raise. And about the residuals from the price cointegration equation's influence on variables, it is a little bit difficult to interpret. Maybe it is because the price is very stable in Taiwan and the stock market in Taiwan is affected by psychology side and information side easily. So it is not easy to use the macro economic variables to interpret fully. Althought it is the case, the interaction between the money market and the stock market still worth researching.

Bakgrund: Den 20:e april 2010 inträffade en explosion på BP:s oljeplattform Deepwater Horizon i Mexikanska Golfen. Explosionen uppstod på grund av metangas som under högt tryck expanderade på plattformen och sedan antändes. Detta ledde senare till att oljeplattformen sjönk och ett stort okontrollerat oljeläckage uppstod på cirka 1500 meters djup.          Att explosionen i den mexikanska golfen har påverkat BP negativt och varit mycket kostsamt för företaget är uppenbart, börskursen hade som mest sjunkit med cirka 60 procent. Det kan vara intressant att undersöka huruvida denna katastrof, utlöst av en enskild aktör, också har spridit sig över till andra aktörer i Olja & Gas sektorn. Syfte: Syftet med denna C-uppsats är att undersöka huruvida BP:s katastrof i den Mexikanska golfen har påverkat andra aktörer i samma sektor (Olja & Gas sektorn). Metod: Sekundärdata presenteras som en kvantitativ ansats i form av siffror och för att kunna dra slutsatserna använder vi oss av en deduktiv ansats.I denna studie tillämpas en metodikteknik i form av en eventstudie, där beräkningar av den abnorma och förväntade avkastningen baseras på marknadsmodellen. Vidare har två hypoteser testats, där syftet med Hypotes I är att pröva huruvida information om händelsen i den Mexikanska Golfen påverkar andra företag i samma sektor som BP. Syftet med Hypotes II är att testa samma företag under samma period som Hypotes I, men undersöker förändring i tradingvolymerna istället för i aktiekurserna. Teori: Effektiva Marknadshypotesen, Random Walk och Flockbeteende Slutsatser: Dessa båda undersökningar d.v.s. Hypotes I och Hypotes II pekar starkt på slutsatsen att eventet har haft inverkat på övriga bolag i sektorn. Vi kunde vid en jämförelse med tidigare studier som genomförts på andra katastrofer, konstatera att skeendet har både likheter och skillnader. / Background: On the 20th April 2010, the BP oil platform Deepwater Horizon, situated in the Mexican Gulf, exploded. The explosion was caused by methanol gas that, under high pressure expanded and thereafter ignited. The platform submerged and caused a severe and uncontrollable oil leakage at 1500 meters depth.It is obvious that the explosion in the Mexican Gulf has impacted BP in a negative manner and cause BP large financial loss, the company shares had at its worst point depreciated by 60 percent. It may be of interest to investigate whether this catastrophe, caused by one independent party, also have affected other companies within the Oil and Gas industry. Purpose: The aim of this assignment is to investigate whether BP’s catastrophe in the Mexican Gulf has affected other companies within the same industry. (Oil and Gas) Methodology: Secondary data is presented as a quantitative approach in the shape of values and we use a deductive approach in order to draw the conclusions.The methodology used in this study is event study, in which calculation of the abnormal and expected revenue are based on the market model. We will test two types of hypothesis, where the aim of Hypothesis I is to test in which way information about the event in the Mexican Gulf affects other companies in the same industry as BP. The aim of Hypothesis II is to test the same companies during the same period as Hypothesis I, but with a focus on analyzing trading volume instead of the stock market value. Theory: Efficient Market Hypothesis, Random Walk and Herd Behavior Conclusion: Both investigations, i.e. Hypothesis I and Hypothesis II indicate that the event has had an impact on other companies in the same industry. We could, in a comparative analysis with earlier studies, based on other catastrophes, conclude that the event demonstrates similarities as well as differences.