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Thesis (Ph. D.)--University of Wisconsin--Madison, 1932. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1957. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 174-180).

This dissertation mainly explores the effect of investor sentiment on stock returns and volatility on Growth Enterprise in China using monthly data from Shenzhen Stock Exchange of China from June 2010 to November 2019. Using five explicit and market-related implicit indicators an investor sentiment has been measured and constructed with the help of principal component analysis. The analysis has been done by employing a vector autoregression(VAR) model and impulse response functions (IRFs) generated from a VAR model to examine the relationship between the unanticipated changes in investor sentiment and stock returns and volatility. We also establish EGARCH model to test the validity of previous results and if the asymmetric impact of positive and negative news on market returns volatility. The results show a significant impact of investor sentiment on stock return and volatility. We also document that there is a positive leverage effect between investor sentiment and the volatility of returns. The findings of this paper can help both individual and institutional investors have a better understanding of GEM market and improve their investment returns by incorporating investor sentiment into their asset forecasting model. This paper also provides policymakers guidance on reducing volatility on stock markets from the perspective of investor sentiment. Additionally, this paper has important contributions to behavioral finance and adds to the limited number of studies on investor sentiment and stock return in not only the Chinese market but emerging markets.

This thesis examines returns around earnings announcements for companies with seasonality in earnings. Earnrank is used as a measure of seasonality where earnrank for a company is calculated quarterly by taking last five years of earnings data, ranking them and taking the average of the ranks for the respective quarter. For seasonal firms, we find robust evidence that abnormal returns are created when such firms announce their earnings for the highest seasonality quarter as measured by their earnrank. Additionally, the results were consistent for different time periods and abnormal returns were found to increase over time. We also performed the analysis industry-wise and found significant difference in returns for most and least seasonal firms in Manufacturing, Financial and Construction sectors. The results for Construction sector is in conflict to our hypothesis and require further exploration. We also study which kind of firms exhibit seasonality and found evidence for high seasonality in large firms, value firms, old firms, firms with lower turnover and firms with lower accruals. Lastly, we studied factors determining abnormal returns relative to the four-factor model and found size to be a significant explanatory variable. The long-short portfolio based on seasonality generated an alpha of 62 basis points per month. / Master of Science

When faced with an investment opportunity in commercial real estate, the investor requires knowledge of the discount rate since it can be used to convert expected future cash flows from the property in today's terms and in doing so, place a value on the property. The so-called required rate of return would be the appropriate conversion rate since it compensates the investor for risk and, if attainable, will induce the investor to invest. An inaccurate assessment of the discount rate could, depending on the direction of the error, lead to a potential over or under estimation of the property value. A number of single or multiple variable frameworks for required return have been derived by other researchers for the US, UK and EU property markets. Each of the variables encountered in these frameworks acts as a proxy for some aspect of systematic risk associated with the investment. However, locally, such models are either not extensively published or well described and are limited to single explanatory variables. Some professionals prefer to avoid frameworks and simply divert to qualitative, gut-feel and experienced based considerations in order to derive at required return rate. This dissertation addressed the possible local need for an explanatory framework of required return on commercial property. The scope of work entailed: (i) a review of the literature to establish the theoretical determinants of return and (ii) an empirical study to test a short-list of parameters for Retail, Offices and Industrial sites in Cape Town, Pretoria, Bloemfontein and Durban, respectively. Three categories of explanatory variables were identified: (i) Capital market variables and alternative investment opportunities in the form of stocks on the JSE, (ii) economic activity indicators and (iii) property market fundamental parameters. The empirical study entailed a three-phase methodology, which included the following steps: (i) data sampling and processing, (ii) screening variables through the simple regression and correlation coefficients and (iii) multiple regression complemented by statistical significance testing. Between 69% and 98.2 % (alpha=O.1) of the variation in returns could be explained in terms of the variation by the explanatory variables that passed the rigorous screening process. The relative good results are likely to be related to the higher explanatory power of the multi-factor approach. The remaining unexplained portion of return can potentially be decreased by using larger samples and pursuing some of the other recommendations for additional research. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2006.

When faced with an investment opportunity in commercial real estate, the investor requires knowledge of the discount rate since it can be used to convert expected future cash flows from the property in today's terms and in doing so, place a value on the property. The so-called required rate of return would be the appropriate conversion rate since it compensates the investor for risk and, if attainable, will induce the investor to invest. An inaccurate assessment of the discount rate could, depending on the direction of the error, lead to a potential over or under estimation of the property value. A number of single or multiple variable frameworks for required return have been derived by other researchers for the US, UK and EU property markets. Each of the variables encountered in these frameworks acts as a proxy for some aspect of systematic risk associated with the investment. However, locally, such models are either not extensively published or well described and are limited to single explanatory variables. Some professionals prefer to avoid frameworks and simply divert to qualitative, gut-feel and experienced based considerations in order to derive at required return rate. This dissertation addressed the possible local need for an explanatory framework of required return on commercial property. The scope of work entailed: (i) a review of the literature to establish the theoretical determinants of return and (ii) an empirical study to test a short-list of parameters for Retail, Offices and Industrial sites in Cape Town, Pretoria, Bloemfontein and Durban, respectively. Three categories of explanatory variables were identified: (i) Capital market variables and alternative investment opportunities in the form of stocks on the JSE, (ii) economic activity indicators and (iii) property market fundamental parameters. The empirical study entailed a three-phase methodology, which included the following steps: (i) data sampling and processing, (ii) screening variables through the simple regression and correlation coefficients and (iii) multiple regression complemented by statistical significance testing. Between 69% and 98.2 % (alpha=O.1) of the variation in returns could be explained in terms of the variation by the explanatory variables that passed the rigorous screening process. The relative good results are likely to be related to the higher explanatory power of the multi-factor approach. The remaining unexplained portion of return can potentially be decreased by using larger samples and pursuing some of the other recommendations for additional research. / Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2006.

This thesis aims at investigating the puzzling relationship between cor- porate acquisitions and expected stock returns by reviewing numerous studies on this topic through the use of state of the art meta-analysis tools. Such an analysis is required because many papers examined this relationship but their results varied. We therefore collected 421 estimates from 20 papers and led multiple regressions to test for the presence of publication bias. Throughout this analysis we indeed found evidence supporting the existence of publication bias. Furthermore, we decided to apply Bayesian Model Averaging to reduce the model uncertainty and find out why our abnormal returns estimates greatly vary across stud- ies. Our results suggest that one of the most important drivers are the standard-error terms. This subsequently proves that publication bias is the most responsible for the heterogeneity amongst our estimates. Our analysis fails to demonstrate any positive effects from M&A activity on a firm post-acquisition performance. We suggest that other motives are under-represented in the underlying theory that aims to assess M&A outcomes. Keywords Mergers and Acquisitions, Stock Returns, Abnormal Re- turns, Meta-Analysis, Publication bias Author's e-mail thibault.parreau@gmail.com Supervisor's e-mail...

Background: During the Covid-19 pandemic, there was a boom in the growing market of e-commerce in Sweden,driving change in consumer behavior online. Competition between companies led to more lenient return policies, which also brings an increased probability of return. The suffering actor is the environment, which is harmed by the extra transports that could have been avoided.  Purpose: The study aims to indicate solutions to reduce the amount of returns made, increase awareness of environmental impact, and find what steps in the purchasing process customers can change in order to benefit the environment. This study will compare consumers in generation X and generation Z to reveal potential differences and give insight in how the attitude may change in the future.  Method: The study collects qualitative data through semi-structured interviews with a total of 14 respondents. A deductive approach was used, by building on existing literature and frameworks with our own collection of data. The data was analyzed through coding, and then presented in themes.  Conclusion: The results show that the major generational difference lies in the view on sustainability where generation Z is keen on coming up with solutions on how to avoid returns, while generation X have a more hopeless approach toward returns management. Further, consumers from both generations highlight the importance of information, and how it must be stated in a concise way for it to be acknowledged. A dilemma clearly arises among the young consumers where sustainability is valued, but keeping up with trends is important to reach a social status. We interpret the response on our model, Returns Model of Consumer Behavior and Logistics (Figure 4), as proof that providing information regarding the reality of returns management has a major impact on consumers regardless of age group.

Over the years, investors demand greater transparency on how their funds are being invested. Whilst in the past it would have been enough for investment firms to seek primarily financial returns against all else; it is now becoming more common for investors to demand some form of positive impact above and beyond financial returns. In response to this, many strategies that seek more than just financial returns have been developed and impact investing being one such strategy. This research explores how fund managers and, or investors operating in the impact investment space communicate their practices to stakeholders in order to obtain an understanding of what they understand impact investing to be, and for those who may be investing for impact, understand the type of impact they seek to attain and also to appreciate how impact is being measured. The research findings suggest that despite much effort being put into the development of impact investing as a distinctive field, there are still a number of issues to iron out particularly with how companies communicate impact. The confusion and use of related terminology interchangeably is also an issue that is found to be detracting instead of adding to the development of the field.