Intellectual capital, knowledge management practices and firm performance

Researchers have widely recognised and accepted that firm performance is increasingly related to knowledge-based issues. Two separately developed literature streams, intellectual capital (IC) and knowledge management (KM), have been established as the key discussions related to knowledge-based competitive advantage of the firm. Intellectual capital has provided evidence on the strategic key intangible resources of the firm, which could be deployed to create competitive advantage. Knowledge management, in turn, has focused on the managerial processes and practices which can be used to leverage IC to create competitive advantage. Despite extensive literature on both issues, some notable research gaps remain to be closed. In effect, one major gap within the knowledge management research is the lack of understanding related to its influence on firm performance, while IC researchers have articulated a need to utilise more finegrained conceptual models to better understand the key strategic value-creating resources of the firm. In this dissertation, IC is regarded as the entire intellectual capacity, knowledge and competences of the firm that can be leveraged to achieve sustained competitive advantage. KM practices are defined as organisational and managerial activities that enable the firm to leverage its IC to create value. The objective of this dissertation is to answer the research question: “What is the relationship between intellectual capital, knowledge management practices and firm performance?” Five publications have addressed the research question using different approaches. The first two publications were systematic literature reviews of the extant empirical IC and KM research, which established the current state of understanding regarding the relationship between IC, KM practices and firm performance. Publications III and IV were empirical research articles that assessed the developed conceptual model related to IC, KM practices and firm performance. Finally, Publication V was among the first research papers to merge IC and KM disciplines in order to find out which configurations could yield organisational benefits in terms of innovation and market performance outcomes.

Pairs trading profitability in the Finnish stock market: A comparison between three methods

Pairs trading is an algorithmic trading strategy that is based on the historical co-movement of two separate assets and trades are executed on the basis of degree of relative mispricing. The purpose of this study is to explore one new and alternative copula-based method for pairs trading. The objective is to find out whether the copula method generates more trading opportunities and higher profits than the more traditional distance and cointegration methods applied extensively in previous empirical studies. Methods are compared by selecting top five pairs from stocks of the large and medium-sized companies in the Finnish stock market. The research period includes years 2006-2015. All the methods are proven to be profitable and the Finnish stock market suitable for pairs trading. However, copula method doesn’t generate more trading opportunities or higher profits than the other methods. It seems that the limitations of the more traditional methods are not too restrictive for this particular sample data.

VAIC-menetelmän soveltuvuus osaketuottojen ennustamiseen Nasdaq Helsinki -pörssissä

Aineeton pääoma on tärkeä osa yritysten kilpailukykyä ja sijoittajan näkökulmasta olisi mielenkiintoista pystyä vertailemaan yritysten aineettoman pääoman käytön tehokkuutta. Tutkimuksessa tarkasteltava VAIC-menetelmä tuottaa vertailuluvun tähän arviointiin tilinpäätöksestä saatavien tietojen avulla. Tutkimuksessa käsitellään kahden toimialakokonaisuuden (IT ja kulutustavarat ja -palvelut) yrityksiä Nasdaq Helsingin päälistalta tarkasteluperiodilla 2006¬-2013. Yrityksille laskettiin vuosittain VAIC-luvut, joiden perusteella muodostetaan ylä- ja alakvartiiliportfoliot. Näiden portfolioiden tuottoja verrattiin toisiinsa sekä kvartiiliportfolioiden ulkopuolelle jääneiden yritysten ja koko toimialan keskimääräiseen tuottoon. Tuottoja tarkasteltiin myös riskisuhteutetusti Sharpen ja vinous-ja huipukkuuskorjatun Sharpen (SKASR) luvulla. Lisäksi VAIC-arvon ja osaketuottojen välistä korrelaatiota tarkasteltiin sekä vuosittain että koko tarkasteluperiodin osalta. Ensimmäinen hypoteesi oletti korkeampien VAIC-arvojen johtavan korkeampiin portfoliotuottoihin, mutta hypoteesi jouduttiin hylkäämään molempien toimialojen osalta. Toinen hypoteesi tarkasteli korrelaatiota VAIC-arvojen ja osaketuottojen välillä, mutta saatujen tulosten mukaan se ei ollut tilastollisesti merkitsevää. VAIC-menetelmä edellyttäisikin jatkokehitystä tai sitä tulisi käyttää yhdessä muiden suorituskykymittareiden kanssa taloudellisesti hyödynnettävissä olevan tiedon tuottamiseksi sijoittajille.