本文在大樣本同質性(LHP)假設下，架構出Variance-Gamma因子聯繫結構模型。建立債權群組損失分配時，由於Variance-Gamma分配與常態分配相同皆具有累加性，因此作為因子結構模型會比起Double-t因子聯繫結構模型具較佳解析性。本文進一步比較Variance-Gamma因子聯繫結構模型與高斯因子聯繫結構模型以及Double-t因子聯繫結構模型。iTraxx指數分券實證結果顯示，Variance-Gamma因子聯繫結構模型最為精確，能有效刻劃高斯因子聯繫結構模型所缺少之尾端損失機率機率分配，以及改正Double-t因子聯繫結構模型過份高估尾端損失之缺點。此外利用調整Variance-Gamma分配之偏態及峰態係數，可以求出更精準的評價結果。最後本文介紹iTraxx分券的交易策略，並且針對不同風險予以避險，研究結果顯示，規避標的債權群組之信用價差風險後，往往無法規避違約相關性變化的風險，投資人在進行策略交易時應更審慎評估。

Global bond market capitalization amounts to approximately $100 trillion, compared to $60 trillion in the equity markets. Despite debt financing being a large part of the global financial market, the measurements and greenhouse gas reduction investment strategies to date are not nearly as thorough as for equity financing. More recently, the problem has been brought into light by the World Bank, expressing concerns about the crucial role of debt financing activities in the current and upcoming threats caused by climate change. A commonly used credit derivative in debt financing is credit default swaps (CDS), which is an agreement between two parties to exchange the credit risk of a reference entity. The buyer of the contract makes fixed periodic payments to the seller of the contract, who collects the premiums in exchange for making the protection buyer whole in the case of a defaulting reference entity. This thesis aims to minimize the greenhouse gas emission exposure for two CDS indices, iTraxx Main and CDX.IG, each consisting of 125 equally weighted constituents, or companies. The CDS indices are widely used high liquid fixed income instruments. In 2017, iTraxx Main had a monthly trading volume of $330-440 billion notional, and CDX.IG a corresponding volume of $200-275 billion. In order to rate the greenhouse gas emissions of the constituents, the ECOBAR model was used. The model utilizes a discrete ranking score system, where the aim is to obtain as low score as possible. To minimize the ECOBAR score for the baskets, Markowitz Modern Portfolio Theory was used, implemented by using a quadratic programming algorithm. By optimizing the portfolios while retaining a low tracking error and high correlation toward the CDS indices, underlying investment properties were retained. We show that one can construct replicated portfolios of the CDS indices that have significantly lower ECOBAR scores than the indices themselves, whilst still maintaining a low tracking error and high correlation with the actual indices. When constructing baskets of fewer constituents, one can replicate the indices with merely 10-30 constituents, without worsening the tracking error or correlation substantially, and obtain an even lower ECOBAR score for the respective portfolios.

This thesis is focused on the credit derivatives market. The aim is to identify and quantify the causal dependence of the development of credit derivatives market in relation to the dynamics of macroeconomic indicators and on this basis the possible prediction. At first, it shows with the help of literature review of their present and history and gives a better look to the different types of credit derivatives. The following section deals with the use of these underlying instruments in practice, their possible trading, insurance, or speculation, whether on the OTC markets or organized exchanges. The following describes the events in the capital and commercial markets during the financial crisis that is between the years 2005-2010, from which are taken the data for the empirical part. The empirical part is based on correlation analysis (multiple regression model) of a few selected and described macroeconomic indicators enriched with Granger causality test. In the conclusion may be find the discussion of the results and possible recommendations for potential investors.