Stock Market reaction to the CSR announcements of American fast food companies

The purpose of this study is to examine whether Corporate Social Responsibility (CSR) announcements of the three biggest American fast food companies (McDonald’s, YUM! Brands and Wendy’s) have any effect on their stock returns as well as on the returns of the industry index (Dow Jones Restaurants and Bars). The time period under consideration starts on 1st of May 2001 and ends on 17th of October 2013. The stock market reaction is tested with an event study utilizing CAPM. The research employs the daily stock returns of the companies, the index and the benchmarks (NASDAQ and NYSE). The test of combined announcements did not reveal any significant effect on the index and McDonald’s. However the stock returns of Wendy’s and YUM! Brands reacted negatively. Moreover, the company level analyses showed that to their own CSR releases McDonald’s stock returns respond positively, YUM! Brands reacts negatively and Wendy’s does not have any reaction. Plus, it was found that the competitors of the announcing company tend to react negatively to all the events. Furthermore, the division of the events into sustainability categories showed statistically significant negative reaction from the Index, McDonald’s and YUM! Brands towards social announcements. At the same time only the index was positively affected by to the economic and environmental CSR news releases.

Pricing of Liquidity Risks in London Stock Exchange

This thesis aims to investigate pricing of liquidity risks in London Stock Exchange. Liquidity Adjusted Capital Asset Pricing Model i.e. LCAPM developed by Acharya and Pedersen (2005) is being applied to test the influence of various liquidity risks on stock returns in London Stock Exchange. The Liquidity Adjusted Capital Asset Pricing model provides a unified framework for the testing of liquidity risks. All the common stocks listed and delisted for the period of 2000 to 2014 are included in the data sample. The study has incorporated three different measures of liquidity – Percent Quoted Spread, Amihud (2002) and Turnover. The reason behind the application of three different liquidity measures is the multi-dimensional nature of liquidity. Firm fixed effects panel regression is applied for the estimation of LCAPM. However, the results are robust according to Fama-Macbeth regressions. The results of the study indicates that liquidity risks in the form of (i) level of liquidity, (ii) commonality in liquidity (iii) flight to liquidity, (iv) depressed wealth effect and market return as well as aggregate liquidity risk are priced at London Stock Exchange. However, the results are sensitive to the choice of liquidity measures.

Information Content of Bank Credit Rating Changes: Evidence from Europe

This thesis examines the short-term impact of credit rating announcements on daily stock returns of 41 European banks indexed in STOXX Europe 600 Banks. The time period of this study is 2002–2015 and the ratings represent long-term issuer ratings provided by S&P, Moody’s and Fitch. Bank ratings are significant for a bank’s operation costs so it is interesting to investigate how investors react to changes in creditworthiness. The study objective is achieved by conducting an event study. The event study is extended with a cross-sectional linear regression to investigate other potential determinants surrounding rating changes. The research hypotheses and the motivation for additional tests are derived from prior research. The main hypotheses are formed to explore whether rating changes have an effect on stock returns, when this possible reaction occurs and whether it is asymmetric between upgrades and downgrades. The findings provide evidence that rating announcements have an impact on stock returns in the context of European banks. The results also support the existence of an asymmetry in capital market reaction to rating upgrades and downgrades. The rating downgrades are associated with statistically significant negative abnormal returns on the event day although the reaction is rather modest. No statistically significant reaction is found associated with the rating upgrades on the event day. These results hold true with both rating changes and rating watches. No anticipation is observed in the case of rating changes but there is a statistically significant cumulative negative (positive) price reaction occurring before the event day for negative (positive) watch announcements. The regression provides evidence that the stock price reaction is stronger for rating downgrades occurring within below investment grade class compared with investment grade class. This is intuitive as investors are more concerned about their investments in lower-rated companies. Besides, the price reaction of larger banks is more mitigated compared with smaller banks in the case of rating downgrades. The reason for this may be that larger banks are usually more widely followed by the public. However, the study results may also provide evidence of the existence of the so-called “too big to fail” subsidy that dampens the negative returns of larger banks.

Low-Volatility Anomaly in Helsinki Stock Exchange

International research shows that low-volatility stocks have beaten high-volatility stocks in terms of returns for decades on multiple markets. This abbreviation from traditional risk-return framework is known as low-volatility anomaly. This study focuses on explaining the anomaly and finding how strongly it appears in NASDAQ OMX Helsinki stock exchange. Data consists of all listed companies starting from 2001 and ending close to 2015. Methodology follows closely Baker and Haugen (2012) by sorting companies into deciles according to 3-month volatility and then calculating monthly returns for these different volatility groups. Annualized return for the lowest volatility decile is 8.85 %, while highest volatility decile destroys wealth at rate of -19.96 % per annum. Results are parallel also in quintiles that represent larger amount of companies and thus dilute outliers. Observation period captures financial crisis of 2007-2008 and European debt crisis, which embodies as low main index annual return of 1 %, but at the same time proves the success of low-volatility strategy. Low-volatility anomaly is driven by multiple reasons such as leverage constrained trading and managerial incentives which both prompt to invest in risky assets, but behavioral matters also have major weight in maintaining the anomaly.