Closed-End Fund Discount -Case: Norvestia & Neomarkka

Tutkimuksen tavoitteena oli määrittää, kuinka suljettuja sijoitusrahastoja tulisi arvioida, jotta voitaisiin ymmärtää, miksi suljetut sijoitusrahastot arvostetaanalennuksella suhteessa niiden substanssiarvoon. Aiemmat yritykset selittää suljettujen rahastojen substanssialennusilmiö esitettiin kirjallisuuskatsauksessa. Tutkimuksen empiirinen osio suoritettiin aineistotutkimus- ja kyselytutkimusmenetelmin hyödyntäen suomalaisia suljettuja sijoitusrahastoja Norvestia Oyj:tä ja Neomarkka Oyj:tä. Teoriaosiossa esitettiin, kuinka substanssialennus on kausaalisten tekijöiden ja markkinatunnelman funktio. Suljettu sijoitusrahasto arvostetaanyli tai alle substanssiarvonsa riippuen johdon aiheuttamien kustannusten, heikosti informoitujen sijoittajien ja rahaston ulkoisen epälikviditeetin suhteesta johdon suorituskykyyn, rahaston avaamisen mahdollisuuteen ja sisäisiin likviditeettietuihin. Suomalaiset suljetut sijoitusrahastot arvostetaan alle substanssiarvonsa mahdollisesti johdon heikon suorituskyvyn, sopimuseriarvoisuuden, heikosti informoitujen sijoittajien läsnäolon ja rahaston osakkeiden epälikviditeetin takia.

Marketing-Sales Cooperation and its Relation on Direct Sales Performance: an Example of a Medium-sized Oil Company

The study touches upon marketing-sales departments’ cooperation and investigates marketing-sales cooperative model within the case company. So that research increases understanding of linkages between Marketing and Sales departments with an illustrative example of Russian medium-sized oil company (LLC Neste St. Petersburg), the subsidiary of Finnish-based Neste Oil. The empirical study is done from marketing and sales perspectives. And for sales main attention was brought to direct sales, both B2B and B2C. Research considers all five domains of cooperation, and among others, study reveals the attitude towards external (market) and internal (product) knowledge, and its mutual use by marketing and sales managers. A qualitative research method, participant observations, and in-depth interviews with upper-management made it possible to explore all facets of joint work. Moreover, research responses the changes in a model of cooperation between marketing and sales when moving from medium size to large company.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.