Generation of a business plan for a logistics service provider

The purpose of this Master’s Thesis was to study the suitability of transportation of liquid wastes to the portfolio of the case company. After the preliminary study the waste types were narrowed down to waste oil and oily waste from ports. The thesis was executed by generating a business plan. The qualitative research of this Master’s Thesis was executed as a case study by collecting information from multiple sources. The business plan was carried out by first familiarizing oneself with literature related to business planning which was then used as a base for the interview of the customer and interviews of the personnel of the case company. Additionally, internet sources and informal conversational interviews with the personnel of the case company were used and these interviews took place during the preliminary study and this thesis. The results of this thesis describe the requirements for the case company that must be met to be able to start operations. Import of waste oil fits perfectly to the portfolio of the case company and it doesn’t require any big investments. Success of the import of waste oil is affected by price of crude oil, exchange rate of ruble and legislation among others. Transportation of oily waste from ports, in turn, is not a core competence of the case company so more actions are required to start operating such as subcontracting with a waste management company.

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.