Dynamic linkages of real estate and stock markets in Finland

Traditionally real estate has been seen as a good diversification tool for a stock portfolio due to the lower return and volatility characteristics of real estate investments. However, the diversification benefits of a multi-asset portfolio depend on how the different asset classes co-move in the short- and long-run. As the asset classes are affected by the same macroeconomic factors, interrelationships limiting the diversification benefits could exist. This master’s thesis aims to identify such dynamic linkages in the Finnish real estate and stock markets. The results are beneficial for portfolio optimization tasks as well as for policy-making. The real estate industry can be divided into direct and securitized markets. In this thesis the direct market is depicted by the Finnish housing market index. The securitized market is proxied by the Finnish all-sectors securitized real estate index and by a European residential Real Estate Investment Trust index. The stock market is depicted by OMX Helsinki Cap index. Several macroeconomic variables are incorporated as well. The methodology of this thesis is based on the Vector Autoregressive (VAR) models. The long-run dynamic linkages are studied with Johansen’s cointegration tests and the short-run interrelationships are examined with Granger-causality tests. In addition, impulse response functions and forecast error variance decomposition analyses are used for robustness checks. The results show that long-run co-movement, or cointegration, did not exist between the housing and stock markets during the sample period. This indicates diversification benefits in the long-run. However, cointegration between the stock and securitized real estate markets was identified. This indicates limited diversification benefits and shows that the listed real estate market in Finland is not matured enough to be considered a separate market from the general stock market. Moreover, while securitized real estate was shown to cointegrate with the housing market in the long-run, the two markets are still too different in their characteristics to be used as substitutes in a multi-asset portfolio. This implies that the capital intensiveness of housing investments cannot be circumvented by investing in securitized real estate.

Accuracy in book papers' sales forecasting

The main objective of this thesis was to study if the quantitative sales forecasting methods will enhance the accuracy of the sales forecast in comparison to qualitative sales forecasting method. A literature review in the field of forecasting was conducted, including general sales forecasting process, forecasting methods and techniques and forecasting accuracy measurement. In the empirical part of the study the accuracy of the forecasts provided by both qualitative and quantitative methods is being studied and compared in the case of short, medium and long term forecasts. The SAS® Forecast Server –tool was used in creating the quantitative forecasts.

A Bayesian Approach for Forecasting Heat Load in a District Heating System

The growing population in cities increases the energy demand and affects the environment by increasing carbon emissions. Information and communications technology solutions which enable energy optimization are needed to address this growing energy demand in cities and to reduce carbon emissions. District heating systems optimize the energy production by reusing waste energy with combined heat and power plants. Forecasting the heat load demand in residential buildings assists in optimizing energy production and consumption in a district heating system. However, the presence of a large number of factors such as weather forecast, district heating operational parameters and user behavioural parameters, make heat load forecasting a challenging task. This thesis proposes a probabilistic machine learning model using a Naive Bayes classifier, to forecast the hourly heat load demand for three residential buildings in the city of Skellefteå, Sweden over a period of winter and spring seasons. The district heating data collected from the sensors equipped at the residential buildings in Skellefteå, is utilized to build the Bayesian network to forecast the heat load demand for horizons of 1, 2, 3, 6 and 24 hours. The proposed model is validated by using four cases to study the influence of various parameters on the heat load forecast by carrying out trace driven analysis in Weka and GeNIe. Results show that current heat load consumption and outdoor temperature forecast are the two parameters with most influence on the heat load forecast. The proposed model achieves average accuracies of 81.23 % and 76.74 % for a forecast horizon of 1 hour in the three buildings for winter and spring seasons respectively. The model also achieves an average accuracy of 77.97 % for three buildings across both seasons for the forecast horizon of 1 hour by utilizing only 10 % of the training data. The results indicate that even a simple model like Naive Bayes classifier can forecast the heat load demand by utilizing less training data.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

Esimiesten muuttuvat osaamistarpeet media- ja kustannusalan murroksessa

Organisaatioiden toimintaympäristö on muuttunut ratkaisevasti ja muutos jatkuu. Muutok-sen kiihtyvä nopeus, asioiden epävarmuus ja kompleksisuus aiheuttavat uudenlaisia haas-teita työelämälle, osaamistarpeiden ennakoinnille ja tulevaisuuden suunnittelulle. Esi-miesosaaminen vaikuttaa merkittävästi siihen, miten hyvin organisaatioissa pystytään hyö-dyntämään sen muuta inhimillistä pääomaa ja tämä tutkimus osallistuu keskusteluun siitä, millä tavalla esimiesosaamisen tulisi kehittyä, jotta se pystyy vastaamaan käynnissä ole-vaan yhteiskunnalliseen, sosiaaliseen ja teknologiseen muutokseen. Tutkimuksen tavoit-teena on ennakoida digitaalisen murroksen keskellä olevan media- ja kustannusalan orga-nisaation esimiesosaamisessa tarvittavia muutoksia. Tutkimus on luonteeltaan laadullinen ja primääritutkimusaineisto koostuu kohdeorganisaatiossa esimiesten, toimitusjohtajan ja henkilöstöpäällikön haastatteluista. Tutkimuksen mukaan tulevaisuudessa tarvittavat esimiesosaamiset eivät merkittävästi eroa tämän päivän paradigman mukaisista osaamisista. Monien osaamisten merkitys kuitenkin korostuu. Esimiesten ja muiden työntekijöiden osaamisten nähdään lähestyvän toisiaan ja tulevaisuudessa rajat esimiesten ja tiimiläisten osaamistarpeiden välillä vähenevät entises-tään. Esimiestyössä monet osaamistarpeet, kuten esimerkiksi epävarmuuden sietokyky, kuitenkin korostuvat. Esimiehen merkittävänä tehtävänä nähdään jatkossa entistä vah-vemmin vastuunkantaminen työyhteisössä.

FUTURES OF FINNISH FOOD SYSTEM BY 2050. The perspective of resilience

Modern food systems face complex global challenges such as climate change, resource scarcities, population growth, concentration and globalization. It is not possible to forecast how all these challenges will affect food systems, but futures research methods provide possibilities to enable better understanding of possible futures and that way increases futures awareness. In this thesis, the two-round online Delphi method was utilized to research experts’ opinions about the present and the future resilience of the Finnish food system up to 2050. The first round questionnaire was constructed based on the resilience indicators developed for agroecosystems. Sub-systems in the study were primary production (main focus), food industry, retail and consumption. Based on the results from the first round, the future images were constructed for primary production and food industry sub-sections. The second round asked experts’ opinion about the future images’ probability and desirability. In addition, panarchy scenarios were constructed by using the adaptive cycle and panarchy frameworks. Furthermore, a new approach to general resilience indicators was developed combining “categories” of the social ecological systems (structure, behaviors and governance) and general resilience parameters (tightness of feedbacks, modularity, diversity, the amount of change a system can withstand, capacity of learning and self- organizing behavior). The results indicate that there are strengths in the Finnish food system for building resilience. According to experts organic farms and larger farms are perceived as socially self-organized, which can promote innovations and new experimentations for adaptation to changing circumstances. In addition, organic farms are currently seen as the most ecologically self-regulated farms. There are also weaknesses in the Finnish food system restricting resilience building. It is important to reach optimal redundancy, in which efficiency and resilience are in balance. In the whole food system, retail sector will probably face the most dramatic changes in the future, especially, when panarchy scenarios and the future images are reflected. The profitability of farms is and will be a critical cornerstone of the overall resilience in primary production. All in all, the food system experts have very positive views concerning the resilience development of the Finnish food system in the future. Sometimes small and local is beautiful, sometimes large and international is more resilient. However, when probabilities and desirability of the future images were questioned, there were significant deviations. It appears that experts do not always believe desirable futures to materialize.

Utilizing analytic modelling process in industrial retail context

Nykypäivän monimutkaisessa ja epävakaassa liiketoimintaympäristössä yritykset, jotka kykenevät muuttamaan tuottamansa operatiivisen datan tietovarastoiksi, voivat saavuttaa merkittävää kilpailuetua. Ennustavan analytiikan hyödyntäminen tulevien trendien ennakointiin mahdollistaa yritysten tunnistavan avaintekijöitä, joiden avulla he pystyvät erottumaan kilpailijoistaan. Ennustavan analytiikan hyödyntäminen osana päätöksentekoprosessia mahdollistaa ketterämmän, reaaliaikaisen päätöksenteon. Tämän diplomityön tarkoituksena on koota teoreettinen viitekehys analytiikan mallintamisesta liike-elämän loppukäyttäjän näkökulmasta ja hyödyntää tätä mallinnusprosessia diplomityön tapaustutkimuksen yritykseen. Teoreettista mallia hyödynnettiin asiakkuuksien mallintamisessa sekä tunnistamalla ennakoivia tekijöitä myynnin ennustamiseen. Työ suoritettiin suomalaiseen teollisten suodattimien tukkukauppaan, jolla on liiketoimintaa Suomessa, Venäjällä ja Balteissa. Tämä tutkimus on määrällinen tapaustutkimus, jossa tärkeimpänä tiedonkeruumenetelmänä käytettiin tapausyrityksen transaktiodataa. Data työhön saatiin yrityksen toiminnanohjausjärjestelmästä.

Heat Demand Forecasting Models’ Development: Use of Data Mining Tools in SQL Server Analysis Services

This thesis introduces heat demand forecasting models which are generated by using data mining algorithms. The forecast spans one full day and this forecast can be used in regulating heat consumption of buildings. For training the data mining models, two years of heat consumption data from a case building and weather measurement data from Finnish Meteorological Institute are used. The thesis utilizes Microsoft SQL Server Analysis Services data mining tools in generating the data mining models and CRISP-DM process framework to implement the research. Results show that the built models can predict heat demand at best with mean average percentage errors of 3.8% for 24-h profile and 5.9% for full day. A deployment model for integrating the generated data mining models into an existing building energy management system is also discussed.

Modelling of changes in electricity end-use and their impacts on electricity distribution

The electricity distribution sector will face significant changes in the future. Increasing reliability demands will call for major network investments. At the same time, electricity end-use is undergoing profound changes. The changes include future energy technologies and other advances in the field. New technologies such as microgeneration and electric vehicles will have different kinds of impacts on electricity distribution network loads. In addition, smart metering provides more accurate electricity consumption data and opportunities to develop sophisticated load modelling and forecasting approaches. Thus, there are both demands and opportunities to develop a new type of long-term forecasting methodology for electricity distribution. The work concentrates on the technical and economic perspectives of electricity distribution. The doctoral dissertation proposes a methodology to forecast electricity consumption in the distribution networks. The forecasting process consists of a spatial analysis, clustering, end-use modelling, scenarios and simulation methods, and the load forecasts are based on the application of automatic meter reading (AMR) data. The developed long-term forecasting process produces power-based load forecasts. By applying these results, it is possible to forecast the impacts of changes on electrical energy in the network, and further, on the distribution system operator’s revenue. These results are applicable to distribution network and business planning. This doctoral dissertation includes a case study, which tests the forecasting process in practice. For the case study, the most prominent future energy technologies are chosen, and their impacts on the electrical energy and power on the network are analysed. The most relevant topics related to changes in the operating environment, namely energy efficiency, microgeneration, electric vehicles, energy storages and demand response, are discussed in more detail. The study shows that changes in electricity end-use may have radical impacts both on electrical energy and power in the distribution networks and on the distribution revenue. These changes will probably pose challenges for distribution system operators. The study suggests solutions for the distribution system operators on how they can prepare for the changing conditions. It is concluded that a new type of load forecasting methodology is needed, because the previous methods are no longer able to produce adequate forecasts.

Erikoistilanteiden huomiointi päivittäistavarakaupan myymälätäydennyksessä

Päivittäistavarakauppa toimialana vaatii hektisyytensä, volyymien suurten vaihtelujen ja tuotteiden ominaispiirteiden takia nopeaa reagointikykyä toimitusketjun sopeuttamisessa. Tällöin pienikin tarkkuuden parantaminen myyntiennusteessa voi aiheuttaa merkittäviä positiivisia kerrannaisvaikutuksia koko ketjussa. Tässä diplomityössä tutkittiin kahta teemaa: Säätilan ja vähittäismyynnin välistä korrelaatiota, sekä tuotteen kampanjassa olon aiheuttamaa kannibalisointivaikutusta muiden tuotteiden menekkiin. Tutkimus toteutettiin työn tilaajan kannalta merkittäväksi mielletyillä tavararyhmillä historialliseen myynti –, sää- ja kampanjadataan perustuen. Tutkimuksen tuloksena todettiin lämpötilan olevan yksittäinen merkittävin tuotteiden menekkiin vaikuttava sääparametri. Kampanjan aiheuttaman myynnin kannibalisointivaikutuksen havaittiin olevan merkittävintä saman tuotesegmentin sisällä, erityisesti lyhyissä kampanjoissa. Työssä luotiin toimintamallit molempiin tutkittuihin teemoihin ennusteperusteisen tarvesuunnittelujärjestelmän ennustetarkkuuden parantamisen työkaluiksi.

The Dynamic Relationship between Finnish Stock Market and Commodities

Since different stock markets have become more integrated during 2000s, investors need new asset classes in order to gain diversification benefits. Commodities have become popular to invest in and thus it is important to examine whether the investors should use commodities as a part for portfolio diversification. This master’s thesis examines the dynamic relationship between Finnish stock market and commodities. The methodology is based on Vector Autoregressive models (VAR). The long-run relationship between Finnish stock market and commodities is examined with Johansen cointegration while short-run relationship is examined with VAR models and Granger causality test. In addition, impulse response test and forecast error variance decomposition are employed to strengthen the results of short-run relationship. The dynamic relationships might change under different market conditions. Thus, the sample period is divided into two sub-samples in order to reveal whether the dynamic relationship varies under different market conditions. The results show that Finnish stock market has stable long-run relationship with industrial metals, indicating that there would not be diversification benefits among the industrial metals. The long-run relationship between Finnish stock market and energy commodities is not as stable as the long-run relationship between Finnish stock market and industrial metals. Long-run relationship was found in the full sample period and first sub-sample which indicate less room for diversification. However, the long-run relationship disappeared in the second sub-sample which indicates diversification benefits. Long-run relationship between Finnish stock market and agricultural commodities was not found in the full sample period which indicates diversification benefits between the variables. However, long-run relationship was found from both sub-samples. The best diversification benefits would be achieved if investor invested in precious metals. No long-run relationship was found from either sample. In the full sample period OMX Helsinki had short-run relationship with most of the energy commodities and industrial metals and the causality was mostly running from equities to commodities. During the first sub period the number of short-run relationships and causality shrunk but during the crisis period the number of short-run relationships and causality increased. The most notable result found was unidirectional causality from gold to OMX Helsinki during the crisis period.

Forecasting with social media – Using Facebook likes to predict the results of the 2015 Finnish Parliamentary elections

Already one-third of the human population uses social media on a daily basis. The biggest social networking site Facebook has over billion monthly users. As a result, social media services are now recording unprecedented amount of data on human behavior. The phenomenon has certainly caught the attention of scholars, businesses and governments alike. Organizations around the globe are trying to explore new ways to benefit from the massive databases. One emerging field of research is the use of social media in forecasting. The goal is to use data gathered from online services to predict offline phenomena. Predicting the results of elections is a prominent example of forecasting with social media, but regardless of the numerous attempts, no reliable technique has been established. The objective of the research is to analyze how accurately the results of parliament elections can be forecasted using social media. The research examines whether Facebook “likes” can be effectively used for predicting the outcome of the Finnish parliament elections that took place in April 2015. First a tool for gathering data from Facebook was created. Then the data was used to create an electoral forecast. Finally, the forecast was compared with the official results of the elections. The data used in the research was gathered from the Facebook walls of all the candidates that were running for the parliament elections and had a valid Facebook page. The final sample represents 1131 candidates and over 750000 Facebook “likes”. The results indicate that creating a forecast solely based on Facebook “likes” is not accurate. The forecast model predicted very dramatic changes to the Finnish political landscape while the official results of the elections were rather moderate. However, a clear statistical relationship between “likes” and votes was discovered. In conclusion, it is apparent that citizens and other key actors of the society are using social media in an increasing rate. However, the volume of the data does not directly increase the quality of the forecast. In addition, the study faced several other limitations that should be addressed in future research. Nonetheless, discovering the positive correlation between “likes” and votes is valuable information that can be used in future studies. Finally, it is evident that Facebook “likes” are not accurate enough and a meaningful forecast would require additional parameters.

Helsinki hub – new traffic flows and business networks

This thesis is the Logistics Development Forum's assignment and the work dealing with the development of the Port of Helsinki as part of Helsinki hub. The Forum aims to develop logistics efficiency through public-private co-operation and development of the port is clearly dependent on both factors. Freight volumes in the Port of Helsinki are the biggest single factor in hub and, therefore, the role of the port of the entire hub development is strong. The aim is to look at how the port will develop as a result of changes in the foreign trade of Finland and the Northern European logistics trends in 25 years time period. Work includes the current state analysis and scenario work. The analyses are intended to find out, which trends are the most important in the port volume development. The change and effect of trends is examined through scenarios based on current state. Based on the work, the structure of Finnish export industry and international demand are in the key role in the port volume development. There is significant difference between demands of Finnish exporting products in different export markets and the development between the markets has different impacts on the port volumes by mass and cargo type. On the other hand, the Finnish economy is stuck in a prolonged recession and competition between ports has become a significant factor in the individual port's volume development. Ecological valuesand regulations have changed the competitive landscape and maritime transport emissions reductions has become an important competitive factor for short routes in the Baltic Sea, such as in the link between Helsinki and Tallinn.

Modelling the exothermic heat and the demand of cooling in paper and pulp industry biological wastewater treatment

This master thesis presents a study on the requisite cooling of an activated sludge process in paper and pulp industry. The energy consumption of paper and pulp industry and it’s wastewater treatment plant in particular is relatively high. It is therefore useful to understand the wastewater treatment process of such industries. The activated sludge process is a biological mechanism which degrades carbonaceous compounds that are present in waste. The modified activated sludge model constructed here aims to imitate the bio-kinetics of an activated sludge process. However, due to the complicated non-linear behavior of the biological process, modelling this system is laborious and intriguing. We attempt to find a system solution first using steady-state modelling of Activated Sludge Model number 1 (ASM1), approached by Euler’s method and an ordinary differential equation solver. Furthermore, an enthalpy study of paper and pulp industry’s vital pollutants was carried out and applied to revise the temperature shift over a period of time to formulate the operation of cooling water. This finding will lead to a forecast of the plant process execution in a cost-effective manner and management of effluent efficiency. The final stage of the thesis was achieved by optimizing the steady state of ASM1.

Keskikokoisen maatilan biokaasu- ja aurinkosähköratkaisujen kannattavuus Etelä-Savossa

Tässä kandidaatintyössä perehdytään biokaasun syntyprosessiin ja sen hyödyntämismahdollisuuksiin, sekä vertaillaan biokaasun tuotannon määrää Suomessa ja Saksassa. Työssä tarkastellaan biokaasuvoimalan kannattavuutta keskikokoisen maatilan yhteydessä Etelä-Savossa ja käydään läpi biokaasuvoimalalle Suomessa myönnettäviä tukimuotoja. Tukimuotojen lisäksi käydään läpi erilaisia lupia ja hyväksyntöjä, joita maatilan yhteyteen rakennettava biokaasu-voimalaitos tarvitsee. Työn toisessa osassa käydään läpi aurinkoenergian hyödyntämismahdollisuuksia, aurinkosähköjärjestelmän komponentteja, sekä perehdytään aurinkopaneelin toimintaperiaatteeseen. Tarkastellaan biokaasuvoimalan lisäksi myös aurinkovoimalan kannattavuutta maatilan yhteydessä ja vertaillaan biokaasu- ja aurinkovoimalan ominaisuuksia keskenään. Lisäksi vertaillaan aurinkosähkön tuotantoa Suomessa ja Saksassa. Työn tavoitteena on selvittää biokaasu- ja aurinkosähkövoimalan kannattavuus esimerkkimaatilalla. Biokaasulaitoksen hinta-arvio saatiin vastauksena tarjouspyyntöön ja aurinkosähköjärjestelmän hinta arvioitiin kotimaisten toimittajien aurinkosähköpakettien hintojen avulla. Biokaasuvoimalan sähköntuottoennuste sekä huolto- ja käyttökustannukset perustuvat kirjallisuudesta saatuihin arvoihin. Aurinkovoimalan sähköntuottoennuste ja paneelien suuntauksen vaikutusta tuotantoon laskettiin PVGIS:n laskurilla sekä HOMER-ohjelmistolla. Kannattavuuslaskelmien perusteella kumpikaan voimalaitostyyppi ei tutkituilla voimalaitosten suuruuksilla ole kannattava 20 tai edes 30 vuoden pitoajalla esimerkkimaatilalla nykyisellä sähkönhinnalla ja tukitasolla. Aurinkosähköjärjestelmälle saadaan kuitenkin 20 vuoden takaisinmaksuaika, jos se hankitaan ilman lainarahaa. Tällöin voidaan ajatella, että laitos on kannattava. Biokaasulaitoksen kannattavuutta parantaisivat tukien ja sähkön hinnan nousun ohella kaasun ja lämmön myyntimahdollisuudet, joita esimerkkimaatilalla ei ole. Aurinkovoimalan kannattavuutta parantaisivat puolestaan tukien ja korkeamman sähkön hinnan lisäksi paremmin paneelien tuotantoa seuraava kulutus, jolloin pienempi osuus sähköstä päätyisi myyntiin.