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Investors are increasingly interested in sustainable investment products and integrating sustainability risk and opportunities into their investment process. This study examines the relationship between financial performance and sustainability ratings using ESG data from three major score providers - MSCI, Refinitiv, and Sustainalytics - and uses an Aggregate ESG Score on a sample of 953 European-listed firms. By creating portfolios, the study finds mixed results on the effects of ESG ratings on financial performance. The value-weighted portfolio showed a positive relationship, with the high ESG portfolio exhibiting a tendency towards higher unexpected excess returns compared to its low ESG counterpart. It also showed a higher risk-adjusted return evidenced by the Sharpe ratio metric and a higher cumulative excess return. On the other hand, results converged towards the low ESG portfolio when using an equally weighted approach. The study also confirmed the divergence across raters and finds that the agreement among raters on a firm's ESG score might reveal significant excess returns as evidenced in the matching strategy of the robustness test.

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In this study we examine whether the upside potential of hedge funds, measured as the maximum return achieved over the past 12 months, has predictive power over future fund performance. Our analyses yield mixed results. On the one hand, we find that the suggested upside potential measure is persistent and able to successfully predict future fund returns measured in absolute terms. On the other hand, we provide evidence that a higher hedge fund upside potential is not indicative of superior future performance in risk-adjusted terms. We also show that, on average, hedge funds with higher upside potential measures bear higher exposure to the direct market risk.

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These last two decades the shift from active to passive investing has gained lots of attraction from practitioners and academics. The share of global passive investment over active ones rose from twenty per cent in 2010 to forty per cent in 2020 and is forecasted to overtake active investments by 2026. The main purpose of this thesis is to determine the proportion of active and passive funds beating the market during different bear and bull markets. In addition, we will compare these proportions across countries, regions, bull and bear markets as well as between active and passive funds. In order to do so, we will calculate the average excess daily return of each fund over each period. If it is positive it means that the fund outperformed the market during the period. While if it is negative it underperformed compared to the market. With this methodology, we have been able to show that passive and active funds can beat bear markets. Accordingly, 65% of passive and 82% of active funds tend to beat the overall bear markets. While during the overall bull market these proportions reach 35% and 18%, respectively. In addition, the average daily excess returns of passive funds are seven times superior to that of active funds during bear markets. Whereas, this return is superior for active funds during the bull market while remaining negative. We also showed that the proportion of active and passive funds beating the market was superior in Europe. Furthermore, we demonstrated that these proportions reach fifty per cent in both regions combined for both types of investments.

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The concept of passive investing dates back to the 1970s, but recent strong inflows into passively managed funds have made it a popular topic of discussion. This strategy involves replicating the return of a specific benchmark, for example, Nikkei 225 index. Unlike active strategy, the objective is not to outperform markets. As a result, the passive approach requires fewer costs and fees, making it simple for all sorts of investors to invest their money. Although this strategy is gaining popularity, much research focuses on the implications of passive investing. One of the concerns is how the passive strategy can contribute to the comovement of stocks within a particular index. This study examines whether the increase in passive investing causes stocks in the Nikkei 225 index to comove. I use Nikkei 225 index data and perform a bivariate regression to estimate comovement. Next, I test whether the rise in passive investing induces comovement. I do this by taking the absolute changes of the estimated comovement and regressing them against the absolute change in passive ownership that I lag for one year. After studying data for 18 years, I can conclude that 1) stocks that are members of the Nikkei 225 index comove more with Nikkei 225 stocks than with non-Nikkei 225 stocks, and 2) the increase in passive ownership causes Nikkei 225 stocks to comove more with index stocks.

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This dissertation investigates what variables influence the user’s risk perception for Buy-Now Pay-Later credit products, mainly the influence of financial literacy and critical thinking on how a consumer perceives the related risks. An inquiry into the existing academic literature and up-to-date media sources has signaled the young consumer’s increasing reliability on unsecured retail debt, the associated risks, and opaque communication by BNPL providers. On the one hand, BNPL is a convenient and trendy tool to fill the void between a need/want and a paycheck. On the other hand, it is a serious debt product that currently falls out of the scope of stricter credit regulation. As debt products are inherently risky, the dissertation's secondary goal is to draft some advice on safeguarding consumers from possible issues relating to BNPL. The paper also investigates how various variables determine the likeliness of a respondent to use BNPL, including gender, age, the use of a credit card, and employment situation. In conclusion, the analysis has shown that financial literacy and being critical of financial benefits positively influence a consumer’s risk-assessing ability. It was also found that the provider’s conditions do not sufficiently warn consumers of the related risks and that people who realise they overspend using BNPL can better estimate the risks. The BNPL user archetype is a female student aged between 18 and 21 with a job and access to a credit card (for this sample).