Syfte: Uppsatsens syfte är att testa den svaga formen av marknadseffektivitet på ett antal aktiemarknader genom teknisk analys i form av system med glidande medelvärden.   Teoretisk referensram: Den teoretiska referensramen utgår ifrån den effektiva marknadshypotesen men omfattar även behavioral finance och teknisk analys.   Metod: Uppsatsen är av förklarande karaktär med ett positivistiskt synsätt och ett deduktivt angreppssätt. Testen av marknadseffektivitetens svaga form sker genom en kvantitativ undersökning av sekundärdata. I undersökningen genomförs en hypotesprövning där en passiv investeringsstrategi jämförs mot aktiva investeringsstrategier byggda på system med glidande medelvärden. Undersökningen omfattar åren 2002-2009 och sker på tio väletablerade aktieindex, i Norden samt på tillväxtmarknader och på etablerade marknader, vilket ger cirka 17 500 observationer.   Empiri: Hypotesprövningen visar att system med glidande medelvärden har kunnat skapa riskjusterad överavkastning samt kunnat förutse framtida kursrörelser på aktiemarknaderna i Danmark, Norge, Sverige och Hong Kong. På aktiemarknaderna i Finland, Brasilien, Indien, Japan, Tyskland och USA har systemen som testats inte kunnat skapa riskjusterad överavkastning och/eller inte kunnat förutse framtida kursrörelser.   Analys: Det finns flera faktorer som påverkat resultaten i olika grad vilket gör att endast indikationer om grad av effektivitet på de olika marknaderna ges i slutsatsen.   Slutsatser: På aktiemarknaderna i Danmark, Norge, Sverige och Hong Kong ges indikationer om att kraven för svag marknadseffektivitet inte uppnåtts. Medan det på aktiemarknaderna i Finland, Brasilien, Indien, Japan, Tyskland och USA ges indikationer om att kraven för svag marknadseffektivitet varit uppfyllda.

Bachelor thesis within Business Administration Title: Behavioral Finance – The Student Perspective Authors: Kamran Sairafi, Karl Selleby, Thom Ståhl Tutor: Urban Österlund Date: 2008-05-30 Background: History is full of examples on how humans can create investment bubbles through speculation; from the Dutch tulip mania to the Dot Com bubble humans have proven to be capable of creating economical chaos. Classical economical theories hold the assumption that individuals act rationally regarding decisions of an economical nature. Since the information on the stock market is available to everyone who seeks it, the appearance of investment bubbles should not be possible. Behavioral finance is an academic branch which seeks to explore these phenomenons through the psychological factors affecting humans in investment decisions. Purpose: The purpose of the report is twofold. Firstly it is to examine the characteristics of investment interested business students enrolled at Jönköping International Business School. Secondly it looks into the decision-making process and choices of the population from the perspective of behavioral finance. Method: This research holds an abductive approach and is based on qualitative data. Data collection was done through an Internet-based questionnaire containing several different questions on the areas related to the inquiries. In some cases statistical analysis was conducted to test for significant correlation between key characteristics. Results: A statistically proven correlation could be discerned between trading experience and frequency; for each additional year an individual engaged in trading the frequency increased. Herd behavior was detected in a majority of the sample. When faced with a scenario in which their immediate surrounding opposed their own analysis of a stock, the greater part of the sample would reconsider their position. Two main sub-groups were detected. The first was characterized by its high tolerance of risk; the second subgroup was characterized by its inconsistency in behavior. Conclusions: This paper found that the behavior of respondents in the chosen population was best described as “student behavior”; a somehow irrational behavior explained by the learning process in which business students exist.

If you happen to be an American and have trouble sleeping, do not attempt to fall asleep watching the nightly news because it is anything but boring. At a glance, the American economy seems to be in shambles. The United States has an all-time high deficit, the housing market has crashed or is in the process of doing so, capital markets are becoming increasingly volatile and credit institutions in and outside the US are reporting heavy losses. The American presidential elections will take place this November, and there is no question that the economy will be one of the main issues. How has the unstable economic atmosphere affected the financial behavior of households in the United States and where have they received the financial information and advice from? Have the changes that they have made in their personal savings/investments and asset portfolios changed in any way and if so, are these changes based on rational decisions or mere hunches? This paper intends to answer these questions through a qualitative approach by interviewing eight tailor picked households in the United States. We take a constructionist ontological position assuming that social entities have a reality that is constructed by the perception of social actors. Furthermore, we have taken the epistemological Interpretevist stance assuming that we study the world by looking at its social actors. We have utilized a number of theories to aid us through our deductive approach where we collect theory, then collect data, analyze the findings, confirm or reject existing theory, then revisit the existing theory with the new data. The main theories include the Efficient Market Hypothesis, Behavioral Finance, Metacommunication and Dissemination of Information and Animal Spirits including all their subsidiary theories. The interview process involved utilizing an unstructured format and once interviews were collected, they were compiled into summarized form through an emotionalist approach. Conclusions were then drawn by finding common denominators between the interviewees’ sentiments. We found the signs of Keynes’ Animal Spirits, overreaction to information, and amplification of information through private sources. Furthermore, we have been able to find that advice had changed over the past year although we were unable to conclude how it had changed. Finally, a number of findings including people’s risk averse behavior towards volatile stock markets gave us an overall picture of the Efficient Market Hypothesis being less true in this situation than Behavioral Finance.

In previous research, aggregation of returns has been found as a way to counteract the risk averse behavior that is the result of investors' myopia. This paper expands the study of aggregation by analyzing its effect on forward looking probabilities. Namely, through the disaggregation of future information, subjects become myopic and trade with varying risk preferences. In an experimental market, subjects trading securities with disaggregated forward looking information are found to 'buy high and sell low', while subjects trading the same securities, but with aggregated information, trade with more consistent risk preferences.

Sverige klassificerades år 2004 som det aktietätaste landet i världen, då hela 77 procent av befolkningen var exponerad mot aktiemarknaden i någon form. År 2012 uppgick innehaven på svenska börsen till 3 715 miljarder kronor. Utvecklingen på aktiemarknaden är därför något som berör merparten av Sveriges befolkning. Investerare har sedan börsens introduktion försökt förutse marknadens utveckling för att finna de vinnande aktierna. Detta har utmynnat i flera olika sätt att analysera marknaden, exempelvis genom teknisk och fundamental analys. En tredje omtalad metod är kalenderanomalier, vilket baseras på kända mönster som tenderar att inträffa under vissa perioder på handelsåret. Detta sätt att prediktera börsens utveckling har väckt författarnas intresse och ligger till grund för studiens genomförande. Studien har undersökt fem av de mest kända kalenderanomalierna; Januarieffekten, Januaribarometern, Turn-of-the-month, Sell-in-May och Holiday Effect. Syftet har varit att utvärdera om dessa anomalier existerar på Stockholmsbörsens tio officiella branschindex, samt om investerare kan utnyttja dem för att uppnå högre riskjusterad avkastning än respektive index. För att utvärdera anomaliernas existens samt investerares möjlighet till överavkastning har författarna skapat 55 syntetiska portföljer. Detta motsvarar en portfölj för varje anomali och bransch, samt för OMXSB. Undersökningsperioden som portföljerna varit aktiva på sträcker sig från 2000-01-03 till 2012-12-31. När portföljerna inte varit aktiva på marknaden har dessa investerats i SSVX 3 mån, vilket har använts som riskfri ränta i studien. Med ett deduktivt angreppssätt och en positivistisk kunskapssyn har författarna genomfört en kvantitativ undersökning på Stockholmsbörsens officiella branschindex. Studiens teoretiska referensram baseras på tre välkända teorier, varav två motsätter sig anomaliers existens medan den tredje bekräftar. De teorier som talar mot kalenderanomaliers existens är Random Walk och Effektiva Marknadshypotesen medan Behavioral Finance är den teori som ställer sig positiv till anomalierna. För att säkerställa studiens statistiska resultat har en regressionsanalys samt ett t-test används. Dessutom har Jensens Alfa legat till grund för att beräkna portföljernas riskjusterade avkastning. Studiens resultat bekräftar att kalenderanomalier existerar på flera av Stockholmsbörsens branschindex samt OMXSB. Starkaste anomalierna är Turn-ofthe-month och Sell-in-May som återfinns på flera av branscherna medan resterande kalenderanomalier endast uppvisat svaga resultat. Intressantast ur en investerares perspektiv är givetvis om resultatet går att använda för att uppnå överavkastning. Totalt är det 16 portföljer som kan användas av investerare för att uppnå högre riskjusterad avkastning än respektive index. Resultatet indikerar därför att den svenska marknaden inte är helt effektiv men att kalenderanomalier inte alltid går att utnyttja.

The post earnings announcement drift is a market anomaly causing a firms cumulative abnormal returns to drift in the direction of an earnings surprise. By measuring quarterly earnings surprises using two measures. The first based upon a times series prediction and the other based upon on analyst forecast errors. This study finds evidence that the drift ex-ists in Sweden and that investor’s systematically underreacts towards positive earnings sur-prises. Further this study shows that the cumulative average abnormal returns is larger for surprises caused by analyst forecast errors. While previous studies have tried to explain the drift by taking on additional risk or illiquidity in the stocks. This study provides evidence supporting that investors limitations in weighting new information causes an underreaction, hence a drift in the stock prices.

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<p>Bachelor thesis within Business Administration</p><p>Title: Behavioral Finance – The Student Perspective</p><p>Authors: Kamran Sairafi, Karl Selleby, Thom Ståhl</p><p>Tutor: Urban Österlund</p><p>Date: 2008-05-30</p><p>Background: History is full of examples on how humans can create investment</p><p>bubbles through speculation; from the Dutch tulip mania to the</p><p>Dot Com bubble humans have proven to be capable of creating</p><p>economical chaos. Classical economical theories hold the assumption</p><p>that individuals act rationally regarding decisions of an</p><p>economical nature. Since the information on the stock market is</p><p>available to everyone who seeks it, the appearance of investment</p><p>bubbles should not be possible. Behavioral finance is an academic</p><p>branch which seeks to explore these phenomenons through the</p><p>psychological factors affecting humans in investment decisions.</p><p>Purpose: The purpose of the report is twofold. Firstly it is to examine the</p><p>characteristics of investment interested business students enrolled</p><p>at Jönköping International Business School. Secondly it looks into</p><p>the decision-making process and choices of the population</p><p>from the perspective of behavioral finance.</p><p>Method: This research holds an abductive approach and is based on qualitative</p><p>data. Data collection was done through an Internet-based</p><p>questionnaire containing several different questions on the areas</p><p>related to the inquiries. In some cases statistical analysis was conducted</p><p>to test for significant correlation between key characteristics.</p><p>Results: A statistically proven correlation could be discerned between</p><p>trading experience and frequency; for each additional year an individual</p><p>engaged in trading the frequency increased. Herd behavior</p><p>was detected in a majority of the sample. When faced with a</p><p>scenario in which their immediate surrounding opposed their own</p><p>analysis of a stock, the greater part of the sample would reconsider</p><p>their position. Two main sub-groups were detected. The first</p><p>was characterized by its high tolerance of risk; the second subgroup</p><p>was characterized by its inconsistency in behavior.</p><p>Conclusions: This paper found that the behavior of respondents in the chosen</p><p>population was best described as “student behavior”; a somehow</p><p>irrational behavior explained by the learning process in which</p><p>business students exist.</p>

<p>The financial portfolio model often referred to as the Black-Litterman model is analyzed using two approaches; a mathematical and a behavioral finance approach. After a detailed description of its framework, the Black-Litterman model is derived mathematically using a sampling theoretical approach. This approach generates a new interpretation of the model and gives an interpretable formula for the mystical parameter<b> τ</b>, the weight-on-views. Secondly, implications are drawn from research results within behavioral finance. One of the most interesting features of the Black-Litterman model is that the benchmark portfolio, against which the performance of the portfolio manager is evaluated, functions as the point of reference. According to behavioral finance, the actual utility function of the investor is reference-based and investors estimate losses and gains in relation to this benchmark. Implications drawn from research results within behavioral finance indicate and explain why the portfolio output given by the Black-Litterman model appears more intuitive to fund managers than portfolios generated by the Markowitz model. Another feature of the Black-Litterman model is that the user assigns levels of confidence to each asset view in the form of confidence intervals. Research results within behavioral finance have, however, shown that people tend to be badly calibrated when estimating their levels of confidence. Research has shown that people are overconfident in financial decision-making, particularly when stating confidence intervals. This is problematic. For a deeper understanding of the use of the Black-Litterman model it seems that we should turn to those financial fields in which social and organizational context and issues are taken into consideration, to generate better knowledge of the use of the Black-Litterman model.</p>