In the dynamic landscape of investment, the comparison between conventional ETFs andESG-screened ETFs presents an interesting narrative of risk and return. With the ETF market soaringto $7.2 trillion in total net assets by 2021 and a surge in global enthusiasm for ESG investing, theintegration of financial and ethical considerations has become increasingly significant.This study delves into this comparison, dissecting the risk-return dynamics between conventional andESG-screened ETFs in developed markets. Against a backdrop of escalating interest in ESG criteria,two questions drive the study: How do the risk-return dynamics differ between conventional ETFs andESG-screened ETFs? Do ESG-screened ETFs outperform conventional ETFs relative to the S&P 500index? Leveraging Sharpe ratio calculations and GARCH modelling, the analysis extends into thepost-pandemic era, capturing recent market performances.Findings reveal mixed performance outcomes. While ESG-screened ETFs demonstrate stability,conventional ETFs achieve slightly higher risk-adjusted returns. Nonetheless, ESG-screened ETFsoffer stability without significant performance trade-offs, making them attractive for investors seekingalignment with ethical considerations. This research not only sheds light on ETF performancedynamics but also guides investors in integrating ESG principles into their investment strategies forbalanced financial and ethical outcomes.

This thesis provides an empirical analysis of the relationship between the value premium and financial distress. Measures of leverage and default are used as proxies for financial distress. Using both an international data set, 1991 to 2006 and a long time series data set for the United States, 1927 – 2007, the thesis adds knowledge about the role of the value premium in asset pricing theory. Generalised autoregressive conditional heteroscedastic modelling (GARCH) is used and information gathered on the volatility of the value premium. A vector autoregressive (VAR) framework and Granger Causality tests are utilised in order to offer a deeper examination of the relationship between risk premium and economic activity. The results add further evidence to support the view that the value premium appears to be linked to variables associated with financial distress, although it is noted that this does not necessarily mean that participants in financial markets behave rationally.

In chapter 1, we show (i) that the risk-return characteristics of our sample of 17 developed stock markets of the world have converged significantly toward each other during our study period 1974 2004, and (ii) that this international convergence in risk-return characteristics is driven mainly by the declining country effect, rather than the rising industry effect, suggesting that the convergence is associated with international market integration. Specifically, we first compute the risk-return distance among international stock markets based on the Euclidean distance and find that the distance thus computed has been deceasing significantly over time, implying a mean-variance convergence. In particular, the average risk-return distance has decreased by about 43% over our sample period. The speed of convergence, however, varies greatly across individual markets, largely reflecting the initial distance of each individual market from the international average risk-return characteristic. Lastly, we document that the risk-return characteristics of our sample of 14 emerging markets have been converging rapidly toward those of developed markets in recent years. This development notwithstanding, emerging markets still remain as a distinct asset class. In chapter 2, we examine the historical evolution of international earnings-to-price ratios for a sample of 17 markets over the period 1980 2004. We introduce a distance measure of earnings-to-price ratios among international stock markets and find that earnings-to-price ratios of 17 markets have significantly converged toward each other during the period. The average distance measure for 17 markets has decreased by about 80 percent during the period. The speed of convergence for individual markets varies and mainly reflects the initial distance of individual markets from the international average. We also find that although both country and industry effects account for convergence in earnings-to-price ratios among the sample markets, country effect dominates industry effect in terms of the magnitude. We further examine what could explain the declining country effect and document that the time trend of dividend-yield distance measure closely follows that of earnings-to-price distance measure. This result suggests that convergence in earnings-to-price ratio is mainly due to convergence in economic factors such as growth opportunities or discount rates rather than due to convergence in accounting practices.

Thesis supervisor: B Ravikumar. Includes bibliographic references (p. 132-135).

Yes / This paper investigates the impact of investor sentiment on the mean-variance relationship in 14 European stock markets. Applying three approaches to define investors’ neutrality and determine high and low sentiment periods, we find that individual investors’ increased presence and trading over high-sentiment periods would undermine the risk-return tradeoff. More importantly, we report that investors’ optimism (pessimism) is more determined by their normal sentiment state, represented by the all-period average sentiment level, rather than the neutrality value set in sentiment surveys.

Yes / This paper investigates the role of institutional investor sentiment in the mean–variance relation. We find market returns are negatively (positively) related to market’s conditional volatility over bullish (bearish) periods. The evidence indicates institutional investors to be sentiment traders as well.

Yes / This paper investigates the mean-variance relation during different time periods within trading days. We reveal that there is a positive mean-variance relation when the stock market is closed (i.e., overnight), but the positive relation is distorted when the market is open (i.e., intraday). The evidence offers a new explanation for the weak risk-return tradeoff in stock markets.

In 1979 Daniel Kahneman and Amos Tversky created the prospect theory. It became an accepted and appropriate theory in explaining decision making under risk. The prospect theory has been one of the most cited articles in economics and Kahneman received the Nobel Prize in Economic Sciences as a result of the creation and development of the theory. Therefore the prospect theory is considered to be more suitable compared to the previously accepted theory, the expected utility theory. Following the prospect theory, researchers have utilized it to describe individual but also corporate management decision making when faced with risk. In this thesis the authors will focus on the latter. Despite the prospect theory being a well-accepted theory, there have been several critics due to its limitations and Audia and Greve (2006) are one of these critics. Their study suggested that corporations under threat, i.e. small firms with low returns, act risk averse. The findings of Audia and Greve (2006) violate the prospect theory when considering small firms that have below target returns. They tested the theory on an industry that has the characteristics of having relatively high proportions of tangible assets. Audia and Greve (2006) also proposed that a similar conclusion could be drawn if tested on an industry characterized by having a high level of intangible assets. This thesis examines the applicability of the prospect theory in the Swedish automotive industry and staffing and recruitment industry. The characteristics of the two industries are that the automotive industry has a high proportion of tangible assets and the staffing and recruitment industry has a high level of intangibles. The authors test if the prospect theory can be used to describe the decision making of both industries but also test the theory on small and large firms. Following the results of this paper we show that the prospect theory can be applied to the Swedish automotive industry and staffing and recruitment industry, characterized by having high levels of tangible assets and intangible assets respectively. The theory can also be used to explain decision making under risk for small firms within both industries and large firms within the automotive industry. Even though the prospect theory was originally tested on individuals, the conclusion can be drawn that the prospect theory once again prevails as an explanation of the decision making in the management of corporations. It can describe the decision making of firms in the two industries having characteristics of different asset tangibility and for firms of different size.

My thesis will focus on optimal investment decisions, especially those that are planned for longer investment horizon. I will review the literature, showing that changes in investment opportunities can alter the risk-return tradeoff over time and that asset return predictability has an important effect on the variance and correlation structure of returns on bonds, stocks and T bills across investment horizons. The main attention will be given to pension funds, which are institutional investors with relatively long investment horizon. I will find the term structure of risk-return tradeoff in the empirical part of this paper. Later on I will add some variables into the model and investigate whether it can improve the results. Finally the optimal investment strategies will be constructed for various levels of risk tolerance and the results will be compared with strategies of Czech pension funds. I am going to use data from Thomson Reuters Datastream, Wharton Research Data Services and additionally from some other sources.

Siu, Tsz Hang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 59-61). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction and Literature Review --- p.1 / Chapter 2 --- Data and Methodology --- p.5 / Chapter 2.1 --- Portfolio Formation --- p.8 / Chapter 2.2 --- Delisting --- p.11 / Chapter 2.3 --- Rebalancing --- p.11 / Chapter 2.4 --- Performance Measurement --- p.12 / Chapter 3 --- Results --- p.16 / Chapter 3.1 --- Daily Portfolio Returns --- p.16 / Chapter 3.2 --- CAPM and Fama French Model --- p.18 / Chapter 3.3 --- Cumulative Returns --- p.22 / Chapter 3.4 --- Over Different Time Periods --- p.22 / Chapter 3.5 --- Analysis on Capital Market Theory --- p.24 / Chapter 3.6 --- Explanations --- p.27 / Chapter 3.6.1 --- Overconfidence --- p.27 / Chapter 3.6.2 --- Anchoring --- p.28 / Chapter 3.6.3 --- A Simple Model and Smoothing Effect --- p.29 / Chapter 3.6.4 --- Securities Selection --- p.32 / Chapter 3.6.5 --- Transaction Costs --- p.32 / Chapter 4 --- Conclusions --- p.33 / Chapter A --- Proof --- p.36 / Chapter B --- Tables and Figures --- p.40 / Bibliography --- p.59