In december 2019, the first cases of covid-19 were reported in Wuhan, China. Since then, the virus has spread rapidly around the world. In order to try to stop the spread of the virus, isolation has become actual. Except affecting the public health, the virus has caused deep traces in the global economy. A clear stock market fall on the Swedish stock exchange could be observed in February-March 2020. The financial crisis that has arisen is the first crisis many of the young investors, of the age 18–30 years old have to manage. Due to the economic crisis that has arisen, this study aimed to describe young investors' decision-making in the financial market during the period 1 January 2020 to 5 May 2020. The research question goes as follows: What factors influence young investors' decision-making in the financial market during an economic crisis? The study was conducted on the basis of the Theory of Behavioral Finance. This theory assumes that the individual's decision-making in the financial market is largely influenced by emotions and other psychological factors. Furthermore, the theory is based on a number of different assumptions about human psychological and behavioral phenomena that influence investment decisions. The procedure for conducting the study was to make a descriptive quantitative study. This meant that a questionnaire was passed on to young investors and that the answers were then compiled in diagrams and tables. The results indicated that the factors overconfidence, representativeness bias and anchoring bias seemed most likely to describe young investors' decision-making in the financial market during an economic crisis. At the same time, a reasonable interpretation seemed to be that herding behavior and risk and loss aversion cannot describe the young investors' decision-making to a large extent. The importance of mental accounting could not be determined in this context, as the answers received provided an incomplete basis for deciding this. To be able to draw conclusions about the role of mental accounting in decision-making, several issues that dealt with this would have been useful. One suggestion for continued research is to study other factors that may underlie young investors' decision-making during an economic crisis.

Bakgrund: Efter många år av högkonjunktur är den svenska ekonomin prognostiserad att föras in i en lågkonjunktur under 2023. Hög inflation hanteras med stigande räntor vilket påverkar investerare på flera sätt, men det finns också en rad börspsykologiska faktorer som kan ha en inverkan på investerare och deras beslut. En åldersgrupp som aldrig investerat under en lågkonjunktur är generation Z. Det är därför intressant att undersöka hur börspsykologiska faktorer påverkar generation Z:s investeringsbeslut under ingången av en lågkonjunktur. Syfte: Syftet med arbetet är därför att undersöka och åskådliggöra vilka börspsykologiska faktorer som har en påverkan på generation Z:s beslutsfattande i ingången av en lågkonjunktur.  Metod: Studien har antagit en kvantitativ insamlingsmetod med en deduktiv ansats, detta genom en genomgripande litteraturstudie följt av en enkätundersökning. Analysen har antagit ett deskriptivt förhållningssätt men har också bestått av enkel linjär regression. Slutsats: Resultatet av undersökningen visar att det finns tendenser av samtliga börspsykologiska biaser i generation Z. Av regressionsanalysen att döma går det dock endast att utläsa signifikanta samband mellan biaserna overconfidence, herding behaviour och anchoring bias mot generation Z:s investeringsbeslut under ingången av en lågkonjunktur.

De par leur nature scientifique, les sciences économiques visent, entre autre, à observer, qualifier, ainsi que quantifier des phénomènes économiques afin de pouvoir en dégager diverses prévisions. Ce mémoire se penche sur ces prévisions et, plus particulièrement, sur les facteurs pouvant biaiser les prévisionnistes au niveau comportemental en référant à l’effet d’ancrage, un biais propre à l’économie comportementale – une sous-discipline des sciences économiques. Il sera donc question de comprendre, par une analyse selon la discipline que représente l’économie comportementale, ce qui peut les affecter, avec un accent mis sur l’effet d’ancrage plus précisément. L’idée générale de ce dernier est qu’un agent peut être biaisé inconsciemment par la simple connaissance d’une valeur précédente lorsqu’il est demandé de faire une estimation ultérieure. De cette façon, une analyse des salaires des joueurs de la Ligne Nationale de Hockey (NHL) selon leurs performances passées et leurs caractéristiques personnelles, de 2007 à 2016, a été réalisée dans ce travail afin d’en dégager de possibles effets d’ancrage. Il est alors possible de constater que les directeurs généraux des équipes de la ligue agissent généralement de façon sensible et rationnelle lorsque vient le temps d’octroyer des contrats à des joueurs mais, néanmoins, une anomalie persiste lorsqu’on porte attention au rang auquel un joueur a été repêché. Dans un tel contexte, il semble pertinent de se référer à l’économie comportementale afin d’expliquer pourquoi le rang au repêchage reste une variable significative huit ans après l’entrée d’un joueur dans la NHL et qu’elle se comporte à l’inverse de ce que prévoit la théorie à ce sujet. / Economic analysis, by its nature, involves observing, qualifying and quantifying economic data with the ultimate goal of making forecasts. In this masters thesis, I am interested in factors that could bias a forecaster's behavior – with special focus on phenomena, like the anchoring effect, that have been proposed in behavioral economics. At a fundamental level, the anchoring effect states that an agent's ability to accurately forecast may be affected by placing unwarranted emphasis on certain economic variables. To study this effect, I analyze how the salaries of National Hockey League (NHL) players are determined by the players' characteristics and past performance. From the results, it would appear that NHL general managers are generally sensible and rational when it comes to using historical data to make decisions about player salaries. However, there is a persistent anomaly regarding the draft position of a player. Although one would not expect the draft position to be very important after eight years of experience in the NHL, the analysis shows that it is remains a significant determinant of player salary. Behavioral economics and more specifically, the anchoring effect, helps explain why this might be so.

大型股過去一直被認為平均報酬率低於小型股，但如果從個股來看，不少大型股的績效並不會比指數差。考慮到一般非專業投資人在投資股票時，選擇大型股還是比小型股容易，本論文試圖建構一套在實務上較可行的大型個股選股策略—選擇市值第二大的股票，並定期調整個股。我們以美股標準普爾500指數中前兩大市值的股票，分為兩種投資組合做比較，結果發現，市值最大的股票不容易創造超額報酬，市值第二大的股票，反而締造極佳的超額報酬，此現象在過去3年、5年、10年，尤其較過去20年更為明顯。原因在於市值排名第二的股票，多半屬於排名仍在持續上升的成長股，這些個股基本面尚未到達頂點，故股價還會反應一段時間的基本面利多，採取類似動能策略(Momentum Strategy)的方法，報酬率容易超越指數；市值最大者則因為基本面普遍伴隨市值排名已經到頂，加上投資人對於排名第一的股票，多半易產生定錨效應(Anchoring Effect)，即認為股價可能已經反應其該有的價值，較難創造超額報酬，傾向賣出。故同樣投資大型股，選擇市值第二名的股票會優於第一名。 / According to The Size Effect Theory, small cap securities generally generate greater returns than those of large cap companies. However, this trend has involved into the difficulties of stock picking due to the large number of small caps. In this paper I propose a strategy against the size effect theory, “Second is Better”, to pick the second largest market value security as the single stock investment. I examine the performances of the No.1 and the No.2 largest market cap stocks in the S&P500 and apply a 6-month rebalance to construct two different portfolios, which is similar to the concept of Momentum Strategy that buy the past winners and sell the past losers. I find the No.2 stock outperforms than No.1 stock and generate amazing excess returns in the near mid-to-long-term periods. Because No.1 stocks are more likely to experience Momentum Crash than No.2 stocks due to investor’s anchoring bias as they believe the No.1 stock might have been peaked. No.2 stocks are usually in the growing stages that many investors believe the 2nd largest caps still yet to peak during market value expansion.

The purpose of this study is to examine the investment behaviour of women during the current recession and how demographic factors impact psychological biases related to investment behaviour. This research aims to examine the impact of age, marital status, education, income, cultural background and financial literacy on various biases such as overconfidence, confirmation bias, herding behaviour, representativeness bias, anchoring bias, risk- and loss aversion.  A questionnaire was conducted to collect data, resulting in a dataset of 558 observations. Using a deductive approach, based on theories of thirty-six hypotheses was tested using ordered logistic regression analysis. The primary findings revealed multiple connections between the demographic profiles of female investors and their investment behaviours, concerning psychological biases. Furthermore, this paper contributes to the ongoing debate about the relationship between investment behaviour and economic recession and provides stakeholders with valuable insights to tailor their communications and strategies to engage female investors. By analysing existing behavioural finance theories and empirical data, the study aims to improve understanding of women's investment preferences and attitudes across different demographic groups. Finally, the study aims to increase women's interest in managing their wealth and improving their financial decisions.

This thesis explores the impact of two behavioural finance concepts, social psychology and psychology, on household financial decisions. Under social psychology, I investigate whether the variety and intensity of social engagement enhances stock market participation. With regard to psychology, I examine two behavioural biases. First, I investigate whether mental accounting influences portfolio choice in three asset classes and whether financial advice and housing tenure increase (decrease) the effects of mental accounts on portfolio choice. Second, I examine whether households’ self-reported housing wealth are anchored on published house price indices and whether anchoring bias is mediated by market information, mortgage refinancing decisions and social factors. The main contributions and findings in the three studies are as follows. First, although there is an elaborate body of research concerning the relationship between social engagement mechanisms and portfolio choice, most studies investigate specific mechanisms in isolation. Using three waves in the British Household Panel Survey (BHPS), I bring together five social engagement measures in one model and show that socially engaged individuals are more likely to participate in the stock market. Consistent with Granovetter’s (1973) theory of social networks I find that a weak tie (measured by social group involvement) has a positive effect on stock market participation whereas a strong tie (measured by talking to neighbours) has no effect. More trusting individuals are more likely to participate in the stock market, as are those who identify with a political party. In contrast, the degree to which religion is important appears to have little impact. These results are robust using different specifications. Overall, the results of this study demonstrate that the likelihood of stock market participation increases with the variety and intensity of social engagement. Second, despite the established theoretical underpinnings of mental accounting in behavioural portfolio theory (BPT) and recent extensions, not much is known about their implications in real life situations. I use a recent UK household survey, the Wealth and Assets Survey (WAS), which has comprehensive information about financial assets to investigate whether there are differences in the ownership and portfolio share of three asset classes among individuals who exhibit no mental account, a single mental account and multiple mental accounts, and the conditional influences of financial advice, housing, cognitive ability, time preference and risk tolerance. Overall I find that mental accounting together with financial advice and housing tenure explain variations in both the probability of ownership and portfolio share in the three asset classes. Households that exhibit a single mental account have low share of investments in, and are less likely to own, a risky asset when compared to those that exhibit no mental account or exhibit multiple mental accounts. I also find that, when compared to having no mental account, exhibiting a single mental account or multiple mental accounts increases both the probability and investment share in a fairly safe asset but decreases portfolio share in safe assets. In addition, among those that exhibit a single mental or multiple mental accounts, financial advice decreases portfolio share in risky assets and fairly safe assets and increases portfolio share in safe assets. Housing tenure increases both the probability and portfolio share in risky assets, decreases portfolio share in fairly safe assets and increases portfolio share in safe assets. These results are consistent using multi-equation regressions, sub-samples, reparametrised variables and poisson regressions. Finally, as little is known about how households derive the self-reported house prices estimates that are commonly used to determine housing wealth, the third study examines whether households are anchored on published house price indices. The key conjecture is that, while assessing the values of their homes, homeowners place more weight on house price news at the expense of property characteristics and other market information. I find support for this hypothesis using sixteen waves of the BHPS, multiple methods, and both regional and national house price indices. I conclude that changes in self-reported housing wealth are anchored on changes in published house price indices. Specifically, ownership through a mortgage and greater financial expectations increase anchoring effects while mortgage refinancing decreases the effects. Moreover, use of money raised from refinancing for home investment, as opposed to other consumption purposes, has a positive association with change in self-reported house value and both uses reduce anchoring bias. In addition, I find that computer use increases anchoring bias and, among social engagement mechanisms, religiosity reduces anchoring while other measures have no effect. These results are robust to internal instrumental variables, national aggregate house prices, alternative indices and sub-samples.