My dissertation investigated business cycle effects on US sectoral stock returns. The first chapter examined the relationship between the business cycle and sectoral stock returns. First, I calculated constant correlation coefficients between the business cycle and sectoral stock returns. Then, I employed the DCC GARCH model to estimate time-varying correlation coefficients for each pair of the business cycle and sectoral stock returns. Finally, I ran regression of sectoral returns on dummy variables designed to capture the four stages of the business cycle. I found that though sectoral stock returns were closely related to the business cycle, they did not share some of its main characteristics. The second chapter developed two models in order to discuss possible asymmetric business cycle effects on US sectoral stock returns. One was a GARCH model with asymmetric explanatory variables and the other one was an ARCH-M model with asymmetric external regressors. In the second model, square root of conditional variance of the business cycle proxy was characterized as positive or negative risk, depending on the algebraic sign of past innovations driving the business cycle proxy. I found that some sectors changed their cyclicities from expansions to recessions. Negative shocks to business cycles had most power to influence sectoral volatilities. Positive and negative parts of business cycle risk had same effects on some sectors but had opposite effects on other sectors. A general conclusion of both models was that business cycle had stronger effects than own sectoral effects in driving sectoral returns. The third chapter discussed Chinese business cycle effects on US sectoral stock returns at two horizons. At a monthly horizon, the third lag of Chinese IP growth rate had positive effects on most sectors. The second lag of US IP growth rate had positive effects on almost all sectors. At a quarterly horizon, besides the extensive positive effects of the first lag of Chinese IP growth rate, the third and fourth lags also had effects on some sectors. The US IP growth rate had the same pattern, namely positive first and fourth lag effects and negative third lag effects. Using a 5-year rolling fixed window, I found that these business cycle effects were time-varying. The major changes in parameters resulted from the elimination of quota on textiles by WTO, the terrorist attacks on the US, and the 2007 financial crisis.

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Blockchain technology has received tremendous attention during the last decade. Huge investments incentives have been made into Blockchain technology and companies worldwide are adapting the new modern innovation. Advocates for Blockchain technology claims that the safe and transparent distributed decentralized ledger has the potential to transform entire industries. One of the biggest operational risks for financial institutions is risks associated with cyber security and cybercrimes. It is argued that Blockchain technology should reduce possibilities for cyber-attacks, increase transparency, and reduce risk. No previous research has been found to confirm this research proposition with perspective to stock return. Still, there remain uncertainties regarding how Blockchain technology affects individual businesses, operational activities and stock behaviours. This research gap is aimed to be partly bridged with this thesis in a Swedish setting.  The primary purpose with this study is therefore to study if the introduction of Blockchain technology in Swedish corporations have an impact of stock return volatility. The longitudinal research methodology of this thesis is designed to satisfy a deductive, quantitative research design, with objectivist ontological assumptions and epistemological positivist approach to generate axiological value-free results. Multiple Linear Regressions and Panel data regression have been performed as well as t-tests to test two hypotheses with regard to systematic risk and total risk as measurements for historical volatility of returns.   The primary findings show a non-significant slight reduction for total risk of stock return, and a slight increase in the systematic risk of stock return. Using mathematical set theory one can argue that the unsystematic risk of stock return decreases. This has proven to be in line with previous theoretical research suggestions which states that operational risk should be reduced. However, the effects observed through the statistical procedures are quite small. Thus, this could indicate that investors’ perceptions of Blockchain technology are still associated with negative issues.  Financial theories such as asymmetry of information, adverse selection, signalling, risk-return fundamentals and behavioural aspects of finance are applied to describe the results, together with previous research, to use the theoretical framework in a coherent way. More research is emphasized to further explore this phenomenon, in order to draw generalizable, significant conclusions though different geographical contexts and markets.  <img src="blob:https://umu.diva-portal.org/2dd6dec1-d82a-4a8e-8093-18a24087fcb2" />

This thesis examines whether the level of Swedish economic policy uncertainty (EPU) can predict excess returns on the Swedish stock market. We run out-of-sample forecasting using an EPU-based predictive model constructed with the official Swedish EPU index developed by Armelius et al. (2017). Forecasting errors for one-, two-, three-, six-, and twelve-month holding periods and four measures of central tendency are analysed and compared against a random walk benchmark. The findings suggest that EPU has limited forecasting ability for excess stock returns in Sweden, and the EPU-based model demonstrates superior forecasting accuracy only in two out of twenty instances, both for the one-month holding period. However, the forecast errors remain relatively large, casting doubt on the model's ability to outperform the market. Furthermore, the EPU-based model consistently underestimates excess returns, questioning its usefulness as a predictor. Notably, the random walk benchmark's forecast error improves with longer holding periods, raising doubts about the predictability of market movements in the long term.

It is widely accepted that banks are one of the most significant financial intermediaries in any economy, facilitating the flow of capital between savers and borrowers. While this may be the case in many advanced economies, including the US, little research has been done on how the quantitative easing (QE) program of central banks affects bank performance. This paper examines the impact of the Federal Reserve’s (the Fed’s) quantitative easing (QE) policies and announcements on bank stocks in the United States (US) during the Covid period. While we do not dismiss the role of investor sentiment, we discover that QE interventions improved bank stock returns albeit with a lag in the case of balance sheet expansion. Furthermore, the impact varied with a greater response from banks with stronger balance sheets. Banks with weaker balance sheets were more sensitive to QE interventions as well. These findings have practical implications for policymakers, regulators, banks and market participants to make informed decisions during crises

Short selling, and its informational role in the formation of stock prices have been the epicenter of prior literature. Is there a relationship between short selling and abnormal returns? While numerous studies found a negative relationship, researchers do not unanimously agree on the existence, nor the strength, of this relationship. Using net short positions extracted from the registry of the FI for stocks listed in the OMX Stockholm 30 Exchange from January 2017 to December 2020, we examine this relationship exclusively in Sweden. The results have been scrutinized via regression analysis to verify if there is any significant relationship between the announcements of total net short positions and the non-adjusted, as well as the risk-adjusted abnormal returns. We did not find enough evidence to validate previous studies that supported the notion that heavily shorted stocks generate negative abnormal returns for the long buyers. There was a perceptible increase in both risk-adjusted and non-adjusted abnormal returns within a three-day window after the announcement of a short position. Yet, the value was merely zero, inferring that a higher level of short interest does not lead to negative stock returns.

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The accountability of marketing investments continues to be a key area of concern for researchers and practitioners (MSI Research Priorities, 2008). In particular, market-based assets, specifically customer relationships, and their potential impact on firm performance are a significant source of interest. Though research in this area continues to grow, little is understood about how investments in human capital and the acquisition of alliance partners through factor markets relate to customer relationship management and the impact of customer relationships on performance. This dissertation presents two studies which, together, investigate how investments in market-based assets influence on abnormal stock returns. In the first study, the resource-based view of the firm (Barney 1991) is used to posit several hypotheses related to investments in human capital. The hypotheses are tested using ten years of data from the U.S. airline industry and analyzed using a mixed-effects methodology. Results indicate that investments in customer service personnel impact abnormal stock returns through their impact on customer relationships. Moreover, these investments tend to have decreasing returns in terms of their impact on customer relationships, and the relative strength of this relationship is shown to be contingent upon a firm's service delivery capabilities, advertising expenditures, and operating focus. This study helps clarify how market-based assets are managed, how investments in specific resources used to manage them relate to stock returns, and why the same dollar invested in human capital by different firms can lead to different levels of returns. The second study also takes a resource-based view of the firm and the management of market-based assets. From this perspective, alliances are considered as external resources acquired in strategic factor markets (Barney 1986) for the purpose of complimenting a focal firm's strategy and performance. This study investigates the long-term impact of alternative types of alliances and the potential impact of alliance partners' customer relationship management capabilities on a focal firms' performance. Just as in study one, ten years of U.S. airline data are used, and a mixed-effects methodology is implemented to test hypotheses. Results indicate that the direct benefits of horizontal marketing alliances tend to be positive, but dependent upon the extensiveness of the alliance. Furthermore, it is revealed that the impact of a partner's customer relationship management capabilities on a focal firm's performance is contingent upon whether the partner's capabilities are similar or dissimilar relative to the focal firm. In short, results indicate that when differences exist, the positive impact of a focal firm's customer relationship management capabilities can be reduced to almost zero if that firm allies with a less competent partner. Taken together, these studies tend to suggest that firms which learn to successfully manage investments in customer relationships may risk nullifying expected positive returns if they simultaneously select alliance partners which are less successful at managing such investments. Similarly, firms which are not able to improve their own management of customer relationships can potentially limit the potential negative consequences by allying with more able firms. In all, this dissertation helps address the accountability issue for marketers.

Thesis advisor: Peter Ireland / It is not unreasonable to surmise that public sentiment views stock market behavior as an indicator of economic health. Historically, movements in the the stock market indeed correspond to business cycles, but this is not always the case, and the COVID-19 pandemic serves as a distinct case to highlight such an irregularity. The contrast between the behavior of the stock market and that of the economy during the pandemic compels an analysis of the pandemic's actual impact on the stock market, and this paper finds a negative and significant relationship between the interpolated daily closing prices of the S&P 500 and the daily number of COVID-19 cases. / Thesis (BA) — Boston College, 2023. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

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