This thesis deals with the socio-economic development of the Liberec Region. In itself, the socio-economic progression is a very complex issue richly structured organizationally as well as institutionally. Matters regarding the realization of the socio-economic program were even more complicated by the completion of the second phase of the transformation of the public administration. The search for an optimal methodology for creating the strategic documentation together with tools for the realization of regional development plans is far from over. While the negotiation and approval of the strategic documentation is a complicated process, the realization of those plans is what causes most of the difficulties. In my opinion, the local Council of the Liberec Region has so far not been able to create adequate organizational and personnel capacity for the realization and the monitoring of the realization process of the existing documentation. The use of the EU funds for the realization of the plans as well as the cohesion policy of the Liberec region, just like the rest of the Czech Republic, in my opinion, is insufficient.

This diploma thesis deals with complex evaluation of tourism competitiveness of five Moravian regions. First chapter explains basic definitions related to the tourism and regional competitiveness. Second chapter analyzes in detail natural conditions, economics, transport, people and tourism of the regions. In the third chapter, the competitiveness of Moravian regions in three areas (economics, people and tourism) and as a whole is examined through the method of the economic n-angle.

Starka fundamentala förhållanden i kapitalmarknaden har bidragit till att driva upp priserna på fastigheter i allmänhet och inom de geografiska områden där institutionella och internationella aktörer investerar i synnerhet.Detta arbete jämför olika geografiska kontorsmarknader från ett investerarperspektiv, med syfte att kartlägga i vilken typ av geografiskt läge direktägda fastigheter ger starkast risk-justerad avkastning för en långsiktig investerare. Delvis genom att kartlägga marknadernas (städernas bästa geografiska läge för kontor) historiska tillväxt för att kunna kategorisera dem som primära eller sekundära marknader, men framför allt genom att utvärdera rådande direktavkastningskrav på respektive studerad marknad.Efter redogörelse över centrala begrepp och essentiella parametrar inom ämnet adresseras riskmåttet volatilitet som ett möjligt argument till varför fastigheter i så kallade sekundära lägen bör anses ha lägre risk än vad marknaden uttrycker i form av direktavkastningskrav. Med framlagda argument presenteras därefter två alternativa modeller för att fastställa direktavkastningskrav på olika geografiska marknader. Arbetet avslutas med en förenklad tillämpning av modellerna på två stora fastighetsbestånd av olika karaktär; Hufvudstaden vars fastigheter uteslutande är belägna på primära marknader, och Klövern, vars bestånd i Sverige är spritt över 12 orter men i starka lägen på respektive ort.Till studierna inhämtades data från IPD, Datscha, Nordanö och PwC. Insamlad data underbygger tesen att hyresnivåer på fastigheter i primära lägen drabbas hårdast av globala kriser och generellt är mer volatila än i sekundära lägen. Vid förenklad tillämpning av presenterade modeller kunde även konstateras att ett diversifierat bestånd ger bättre risk-justerad avkastning över tid vilket även går i linje med portföljteori och faktumet att marknadsrisken förblir densamma oberoende av hur många tillgångar som ingår i en portfölj.Utifrån detta arbete kan det även argumenteras för att en optimal fastighetsportfölj bör vara överviktad mot fastigheter i sekundära lägen sett till aktuella värderingar. / Strong fundamental conditions in the capital market have contributed to rising prices for real estate in general and in the geographical areas where institutional and international investors invest in particular. The core of this thesis is to compare different geographical office markets from an investor perspective, with the purpose of mapping what type of geographic location properties provide the strongest risk-adjusted return over time. In particular, to map the markets' historical growth to be able to categorize them as primary or secondary markets for offices, but above all by evaluating current yields on each market. After explaining central concepts and essential parameters within the subject, the risk measurement volatility is addressed as a possible argument to explain why real estate in the so-called secondary markets should be considered to have a lower risk than what the market expresses in the form of current yields. With submitted arguments, two alternative models are presented to determine yields in different geographic markets. The thesis ends with a simplified application of the models on two large property portfolios of different character; Hufvudstaden, whose properties are exclusively located in primary locations, and Klövern, whose properties are spread over 12 Swedish cities but in strong locations. Data from IPD, Datscha, Nordanö and PwC were collected for the studies. Overall, collected data supported the thesis that rents from properties in primary locations are being hit hardest by global crises and are generally more volatile than in secondary locations. In the simplified application of presented models, it could also be stated that a diversified portfolio provides stronger risk-adjusted returns over time, which is also in line with portfolio theory and the fact that market risk is the same regardless of how many assets that are included in a portfolio. From this thesis it can also be argued that an optimal real estate portfolio should be overweight to properties in secondary locations based on current values.

The objective of the thesis Specifics of real estate market in the Olomouc region is to analyse the real estate market of the districts of the Olomouc region. Then compare the market specifics of these districts and compare the selected location within the Czech Republic. The first part of the thesis is focused on the theoretical description and terms related to the real estate market. Then it describes the subjects of the real estate market and the factors that influence this market. Next chapter is focused on the regional policy and its impact on the real estate market. In the next part is the analysis of real estate market in the Olomouc region itself. There is the comparison of the districts in the Olomouc region. The analysis is focused mainly on the price development of selected types of real estate in the selected location and then is compared within the Czech Republic.

本篇論文旨在分析神經網路學習績效，並提出一套學習演算法，結合倒傳遞網路(BP)與理解神經網路(RN)，命名為RNBP，這套學習演算法將與傳統的BP做比較，以兩個不同的財務金融領域的應用，一個是選擇權上Black-Scholes訂價模式的模擬，一個是金融交換上利率的預測。主要績效的評估準則是以學習的效率與模擬、預測的準確度為依據。 此外，本論文的另一個重點是提出一套對於神經網路系統進一步分析的方法與工具，敏感度分析(Sensitivity Analysis)與滯留區(Dead Region)分析，藉以瞭解神經網路系統是否具有效地良好學習或被一般化的能力，從神經網路的角度來說，這也是BP與RNBP的另一個績效比較標準。本研究的結果顯示RNBP在預測準確度上較BP為優良，但是在學習效率與預測能力的穩定性上並沒有呈現一致性的結論；此外，敏感度分析與滯留區分析的結果也幫助神經網路在應用領域上有更深入的瞭解。 在過去，神經網路的應用者往往忽略了進一步瞭解神經網路的重要性與可行性，本論文的貢獻在於藉由分析神經網路所學習的知識，幫助應用者進一步瞭解神經網路表達的訊息在應用領域上所隱含的實質意義。 / The study attempts to analyze the learning performance of neural networks in applications, and propose a new learning procedure for the layered feedforward neural network systems, named KNBP, which binds RN and BP learning algorithms. Two artificial neural networks, BP and KNBP, here are both applied to two financial fields, the simulation of Black-Scholes pricing model for the call options and the midrates forecasting in financial swaps. The explicit performance comparison between the two artificial neural network systems is mainly based on two criteria, which are learning efficiency and forecasting effectiveness. Then we propound a mathematical methodology of sensitivity analysis and the dead regions to deeply explore inside the network structures to see whether the models of ANNS are actually well trained or valid, and thus setup an alternative comparable criterion. The results from this study show that RNBP performs better than BP in forecasting effectiveness, but RNBP obtains neither a consistent learning efficiency in cases nor a stable forecasting ability. Furthermore, the sensitivity analysis and the dead region analysis provide a deeper view of the ANNs in the applied fields. In the past, most studies applying neural networks ignored the importance that it is feasible and advantageous to obtain more useful information via analyzing neural networks. The purpose of the research is to help further understanding to the information discovery resulted from neural networks in practical applications.