The green bond market has grown rapidly in the past years but still only stands for 1 percent of the total bond market. More issuers need to issue green bonds for the green bond market to grow, and investors need to invest in new issuers. A weakness of the green bond market is that there is no universal definition of sustainability. This thesis investigates the green bond market from investors’ perspectives, focusing on the role of trust in the green bond market. The thesis is qualitative research containing eight interviews with people on pension funds, asset management firms, an insurance company, and a fixed-income institute. The interviews were supplemented with a short questionary. The main findings are that trust has a vital role in the green bond market. Trust between investors and issuers can be strengthened through increased transparency from the issuer. Issuers’ general sustainability work is essential for investors when investing in green bonds. The research identified that the green bond market growth would benefit if a third-party actor would vouch for the company’s sustainability work. A recommendation to facilitate market growth is to establish a voluntary standardized sustainability rating with clear financial incentives for the issuer. It would enhance issuers’ sustainability awareness and increase transparency for the investors as the rating would be on the issuers’ initiative. / Den gröna obligationsmarknaden har vuxit kraftigt de senaste åren men står endast för 1 procent av den totala obligationsmarknaden. För att marknaden ska växa behöver fler emittenter utfärda gröna obligationer samtidigt som investerare behöver investera i nya emittenter. En svaghet för den gröna obligationsmarknaden är att det saknas en universell definition av hållbarhet. Detta arbete undersöker den gröna obligationsmarknaden från en investerares perspektiv med fokus på tillitens betydelse på marknaden. Arbetet är en kvalitativ studie som baseras på åtta intervjuer med personer inom pensionsbolag, kapitalförvaltning, försäkringsbolag och ett ränteinstitut. Intervjuerna kompletterades med en kort enkät. De viktigaste resultaten visar på att tillit har en betydande roll på den gröna obligationsmarknaden. Tillit mellan investerare och emittenter kan stärkas genom ökad transparens från emittentens sida. Resultat visar även på att emittentens generella hållbarhetsarbete är viktigt för investerare när de investerar i en grön obligation. Det identifieras att den gröna obligationsmarknaden skulle kunna dra fördel av om det existerar en tredjepartsaktör som kan bekräfta en emittents hållbarhetsarbete. Ett förslag som eventuellt skulle kunna leda till marknadstillväxt är att införa ett standardiserat hållbarhetsbetyg kopplat till tydliga finansiella incitament för både emittenten och investeraren. Detta skulle öka transparensen för investerare samt kunna förbättra emittentens medvetenhet gällande hållbarhet eftersom bedömningen skulle göras på emittentens initiativ.

隨著金融市場的開放，越來越多的金融商品被開發出來以迎合市場參予者的需求，利率衍生性金融商品是一種以利率為標的的一種新金融商品，而這種新金融商品的交易量也是相當的可觀。我們在設計金融商品的第一步就是要去定價，在現實社會中利率是隨機波動的而不是像在B-S的選擇權公式中是固定的。隨機利率模型的用途就是在描述利率隨機波動的行為，進而對利率衍生性金融商品定價。本文嘗試以隨機利率模型估計台灣公債市場的殖利率曲線，而殖利率曲線的建立對於固定收益證券及其衍生性金融商品的定價是很重要的。在台灣大部分的利率模型的研究都是利用模擬的方式做比較，這也許是因為資料取得上的問題，本文利用CKLS(1992)所提出的方式以GMM(Generalized Method of Moment)的估計方法，利用隨機利率模型估計出台灣公債市場的殖利率曲線。本文中將三種隨機利率模型做比較他們分別為: Vasicek model (Vasicek 1977),、隨機均數的Vasicek 模型 (BDFS 1998) ，以及隨機均數與隨機波動度的Vasicek 模型 (Chen,Lin 1996). 後面兩個模型是首次出現在台灣的研究文獻中。在本文的附錄中將提出如何利用偏微分方程式(PDE)的方法求解出這三個模型的零息債券價格的封閉解(Closed-Form Solution)。文中利用台灣商業本票的價格當作零息債券價格的近似值，再以RMSE (Root mean squared Price Prediction Error)作為利率模型配適公債市場價格能力的指標。本文的主要貢獻在於嘗試以隨機利率模型估計出台灣公債市場的殖利率曲線，以及介紹了兩種首次在台灣研究文獻出現的利率模型，並且詳細推導其債券價格的封閉解，這對於想要建構一個新的隨機利率模型的研究人員而言，這是一個相當好的一個練習。 / With the growth in the area of financial engineering, more and more financial products are designed to meet demands of the market participants. Interest rate derivatives are those instruments whose values depend on interest rate changes. These derivatives form a huge market worth several trillions of dollars. The first step to design or develop a new financial product is pricing. In the real world interest rate is not a constant as in the B-S option instead it changes over time. Stochastic interest rate models are used for capturing the volatile behavior of interest rate and valuing interest rate derivatives. Appropriate models are necessary to value these instruments. Here we want to use stochastic interest rate models to construct the yield curve of Taiwan Government Bond (TGB) market. It is important to construct yield curve for pricing some financial instruments such as interest rate derivatives and fixed income securities. 　In Taiwan Although most of the research surrounding interest rate models is intended towards studying their usefulness in valuing and hedging complex interest rate derivatives by simulation. But just a few papers focus on empirical study. Maybe this is due to the problems for data collection. In this paper we want to use stochastic interest models to construct the yield curve of Taiwan’s Government Bond market. The estimation method that we use in this paper is GMM (Generalized Method of Moment) followed CKLS (1992). I introduce three different interest rate model, Vasicek model (Vasicek 1977), Vasicek with stochastic mean model (BDFS 1998) and Vasicek with stochastic mean and stochastic volatility model (Chen,Lin 1996). The last two models first appear in Taiwan’s research. In the Chapter 3, I will introduce these models in detail and in the appendix of my thesis I will show how to use PDE approach to derive each model’s zero coupon bond price close-form solution. In this paper we regard Taiwan CP (cmmercial Paper) rates as a proxy of short rate to estimate the parameters of each model. Finally we use these models to construct the yield curve of Taiwan Government Bonds market and to tell which model has the best fitting bond prices performance. Our metric of performance for these models is RMSE (Root mean squared Price Prediction Error). The main contribution of this study is to construct the yield curve of TGB market and it is useful to price derivatives and fixed income securities and I introduce two stochastic interest rates models, which first appear in Taiwan’s research. I also show how to solve the PDE for a bond price and it is a useful practice for someone who wants to construct his/her own model.

[Truncated abstract] Given the theoretical and historical evidence that support the benefit of investing internationally. there is Iittle knowledge available of proper international portfolio construction in terms of how much should be invested in foreign countries, which countries should be targeted, and types of assets to be included in the portfolio. The prospects of these benefits depend on the market volatilities, cross-country correlations, and currency risks to change in the future. Another important issue in international portfolio diversification is the growth of newly emerging markets which have different characteristics from the developed ones. Addressing the issues, the thesis intends to investigate the nature of volatility, conditional correlations, and the impact of currency risks in international portfolio, both in developed and emerging markets. Chapter 2 provides literature review on volatility spillovers, conditional correlations, and forecasting both VaR and conditional correlations using GARCH-type models. Attention is made on the estimated models, type of assets, regions of markets, and tests of forecasts. Chapter 3 investigates the nature of volatility spillovers across intemational assets, which is important in determining the nature of portfolio's volatility when most assets are seems to be connected. ... The impacts of incorporating volatility spillovers and asymmetric effect on the forecast performance of conditional correlation will also be examined in this thesis. The VARMA-AGARCH of McAleer, Hoti and Chan (2008) and the VARMA-GARCH model of Ling and McAleer (2003) will be estimated to accommodate volatility spillovers and asymmetric effect. The CCC model of Bollerslev (1990) will also be estimated as benchmark as the model does not incorporate both volatility spillovers and asymmetric effects. Given the information about the nature of conditional correlations resulted from the forecasts using a rolling window technique, Section 2 of Chapter 4 investigates the nature of conditional correlations by estimating two multivariate GARCH models allowing for time-varying conditional correlations, namely the DCC model of Engle (2002) and the GARCC model of McAleer et al. (2008). Chapter 5 conducts VaR forecast considering the important role of VaR as a standard tool for risk management. Especially, the chapter investigates whether volatility spillovers and time-varying conditional correlations discussed in the previous two chapters are of helps in providing better VaR forecasts. The BEKK model of Engle and Kroner (1995) and the DCC model of Engle (2002) will be estimated to incorporate volatility spillovers and conditional correlations, respectively. The DVEC model of Bollerslev et al. (1998) and the CCC model of Bollerslev (1990) will be estimated to serve benchmarks, as both models do not incorporate both volatility spillovers and timevarying conditional correlations. Chapter 6 concludes the thesis and lists somc possible future research.

The volatility transmission in financial markets has important implications for investment decision making, portfolio diversification and overall macroeconomic stability. This paper analyses volatility transmission across four South African financial markets that is the stock, bond, money and foreign exchange markets, using daily data for the period 2000-2010. It also shows whether the volatilities in the SA financial markets present a different behaviour in bull and bear market phases. The effects of the international markets volatility to the local markets volatility was also looked at in this study. To obtain estimates of market volatility, the study experimented with various volatility models that include the GARCH, EGARCH and TARCH. To examine volatility interaction and the transmission of volatility shocks, a VAR model was estimated together with block exogeneity, impulse response and variance decomposition. The study found that there is limited volatility transmission across the SA financial markets. The study also found that the money market is the most exogenous of all markets since the other three financial markets volatility is insignificant to the money market (see impulse response results). For the bond market, volatility transmission was characterized with a decreasing trend. With regard to international markets volatility, it concluded that, the shocks in the international markets will eventually affect the movement in the local markets. The results also highlighted that, world and local markets are important in accelerating the volatility transmission in SA financial markets depending on whether they are in their bull or bear phases. In the case of South Africa, the study found that volatility transmission across markets is higher during bear market periods than bull market periods. Basing on the study results which show that the volatility transmission is limited across SA financial markets, the implication to local and international investors is that there is a greater potential for diversifying risk by investing in different South African financial markets.

Made available in DSpace on 2014-06-11T19:24:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-10-23Bitstream added on 2014-06-13T19:30:57Z : No. of bitstreams: 1 caetite_an_me_arafcl.pdf: 1252633 bytes, checksum: 194f2f4deb25bdb917728eeb4f75dad4 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Esta dissertação apresenta uma análise, a partir de uma ótica pós-keynesiana, da trajetória do volume total de crédito e de títulos para o financiamento empresarial e, mais especificamente, para os macro-setores indústria, comércio e serviços, no Brasil, entre os anos 1996-2007. Esse período é dividido em dois (1996-2003 e 2004-2007) sendo o primeiro caracterizado pela estabilidade do volume e fluxo desses recursos e o último pela evolução consistente dos mesmos. / This thesis analyses, through a post-keynesian perspective, the trajectory of the total volume of credit and bonds to finance business and, more specifically, for the industrial macro-sectors, commerce and service, in Brazil, between 1996-2007. The period is two folded (1996-2003 and 2004-2007), being the former characterized by the volume and flow of those resources and the later through its consistent evolution.

This thesis contains three essays in the field of real-time econometrics, and more particularly<p>forecasting.<p>The issue of using data as available in real-time to forecasters, policymakers or financial<p>markets is an important one which has only recently been taken on board in the empirical<p>literature. Data available and used in real-time are preliminary and differ from ex-post<p>revised data, and given that data revisions may be quite substantial, the use of latest<p>available instead of real-time can substantially affect empirical findings (see, among others,<p>Croushore’s (2011) survey). Furthermore, as variables are released on different dates<p>and with varying degrees of publication lags, in order not to disregard timely information,<p>datasets are characterized by the so-called “ragged-edge”structure problem. Hence, special<p>econometric frameworks, such as developed by Giannone, Reichlin and Small (2008) must<p>be used.<p>The first Chapter, “The impact of macroeconomic news on bond yields: (in)stabilities over<p>time and relative importance”, studies the reaction of U.S. Treasury bond yields to real-time<p>market-based news in the daily flow of macroeconomic releases which provide most of the<p>relevant information on their fundamentals, i.e. the state of the economy and inflation. We<p>find that yields react systematically to a set of news consisting of the soft data, which have<p>very short publication lags, and the most timely hard data, with the employment report<p>being the most important release. However, sub-samples evidence reveals that parameter<p>instability in terms of absolute and relative size of yields response to news, as well as<p>significance, is present. Especially, the often cited dominance to markets of the employment<p>report has been evolving over time, as the size of the yields reaction to it was steadily<p>increasing. Moreover, over the recent crisis period there has been an overall switch in the<p>relative importance of soft and hard data compared to the pre-crisis period, with the latter<p>becoming more important even if less timely, and the scope of hard data to which markets<p>react has increased and is more balanced as less concentrated on the employment report.<p>Markets have become more reactive to news over the recent crisis period, particularly to<p>hard data. This is a consequence of the fact that in periods of high uncertainty (bad state),<p>markets starve for information and attach a higher value to the marginal information content<p>of these news releases.<p>The second and third Chapters focus on the real-time ability of models to now-and-forecast<p>in a data-rich environment. It uses an econometric framework, that can deal with large<p>panels that have a “ragged-edge”structure, and to evaluate the models in real-time, we<p>constructed a database of vintages for US variables reproducing the exact information that<p>was available to a real-time forecaster.<p>The second Chapter, “Real-time nowcasting of GDP: a factor model versus professional<p>forecasters”, performs a fully real-time nowcasting (forecasting) exercise of US real GDP<p>growth using Giannone, Reichlin and Smalls (2008), henceforth (GRS), dynamic factor<p>model (DFM) framework which enables to handle large unbalanced datasets as available<p>in real-time. We track the daily evolution throughout the current and next quarter of the<p>model nowcasting performance. Similarly to GRS’s pseudo real-time results, we find that<p>the precision of the nowcasts increases with information releases. Moreover, the Survey of<p>Professional Forecasters does not carry additional information with respect to the model,<p>suggesting that the often cited superiority of the former, attributable to judgment, is weak<p>over our sample. As one moves forward along the real-time data flow, the continuous<p>updating of the model provides a more precise estimate of current quarter GDP growth and<p>the Survey of Professional Forecasters becomes stale. These results are robust to the recent<p>recession period.<p>The last Chapter, “Real-time forecasting in a data-rich environment”, evaluates the ability<p>of different models, to forecast key real and nominal U.S. monthly macroeconomic variables<p>in a data-rich environment and from the perspective of a real-time forecaster. Among<p>the approaches used to forecast in a data-rich environment, we use pooling of bi-variate<p>forecasts which is an indirect way to exploit large cross-section and the directly pooling of<p>information using a high-dimensional model (DFM and Bayesian VAR). Furthermore forecasts<p>combination schemes are used, to overcome the choice of model specification faced by<p>the practitioner (e.g. which criteria to use to select the parametrization of the model), as<p>we seek for evidence regarding the performance of a model that is robust across specifications/<p>combination schemes. Our findings show that predictability of the real variables is<p>confined over the recent recession/crisis period. This in line with the findings of D’Agostino<p>and Giannone (2012) over an earlier period, that gains in relative performance of models<p>using large datasets over univariate models are driven by downturn periods which are characterized<p>by higher comovements. These results are robust to the combination schemes<p>or models used. A point worth mentioning is that for nowcasting GDP exploiting crosssectional<p>information along the real-time data flow also helps over the end of the great moderation period. Since this is a quarterly aggregate proxying the state of the economy,<p>monthly variables carry information content for GDP. But similarly to the findings for the<p>monthly variables, predictability, as measured by the gains relative to the naive random<p>walk model, is higher during crisis/recession period than during tranquil times. Regarding<p>inflation, results are stable across time, but predictability is mainly found at nowcasting<p>and forecasting one-month ahead, with the BVAR standing out at nowcasting. The results<p>show that the forecasting gains at these short horizons stem mainly from exploiting timely<p>information. The results also show that direct pooling of information using a high dimensional<p>model (DFM or BVAR) which takes into account the cross-correlation between the<p>variables and efficiently deals with the “ragged-edge”structure of the dataset, yields more<p>accurate forecasts than the indirect pooling of bi-variate forecasts/models. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished

Thesis deals with the attraction of Czech government bonds from the perspective of foreign investors in relation with the current economic development in CEE region, and further in the rest of the world. Analysis is targeted to issue of the Czech government bonds in turn of 2009 and 2010. After the analysis and description of foreign investors representing huge part of the entire demand for the Czech government bonds on the domestic and foreign markets the paper further covers individual pros and cons of the instrument. The empirical analysis is conducted as the comparison of the yields and risk of Czech goventment bonds with the similar instruments issued by Hungarian and Slovakian governments. Separate part of the thesis covers the characteristics of used instruments (Czech T-Notes and T-Bills) and legal adjustments of the auctions through which these instruments are placed on the domestic market. Thesis also contains a separate chapters covering the results of former issues of the Czech government bonds abroad and the analysis of tax consequences resulting from holding and selling the Czech government bonds by foreign investors.

Bond markets are crucial for the stability and efficiency of the national financial system. Low liquidity prevents market developments and makes investors reluctant to trade actively. It is therefore crucial to maintain liquidity in bond markets. This thesis aims to investigate investor activity and liquidity in the Swedish government and mortgage bond markets. By creating indices using a combination of public trading data (actual trades) and private trading data (potential trades) to measure investor activity, a new liquidity proxy is created. The indices capture two aspects of investor activity, both the quantity of the bonds as well as the trading frequency. High levels of activity imply a liquid market and low levels of activity imply a lack of liquidity. Since Swedish and international investors are exposed to different risks even when investing in the same market, this thesis has segmented investors into four groups: Swedish investors in the government bond market, Swedish investors in the mortgage bond market, foreign investors in the government bond market and foreign investors in the mortgage bond market. To further understand the driving factors of market activity, regression analysis is conducted. From the existing literature a total of 11 potential explanatory variables have been identified. Due to the various market conditions in each investor group, it is no surprise that the variables influence the groups differently. Bond market return, short term interest rate and term risk structure are found to be highly significant for all investor groups. Moreover, stock market return and macroeconomic news are identified to be relevant variables when explaining shifts in investor behaviour. Positive developments in bond and stock market returns boost investor activity, while negative developments halt activity. Short term interest rate and the term risk spread are found to have similar effects, positive influence in the government bond market and negative influence in the mortgage bond market. For international investors, two spreads reflecting Swedish market conditions in relation to international benchmarks are included in the analysis. Both spreads are found to be highly significant, indicating that foreign investors choose to trade in the bond markets with the most desirable conditions. / En välfungerande obligationsmarknad är avgörande för ett lands finansiella stabilitet. Brist på likviditet hindrar marknadsutveckling och medför att investerare blir ovilliga att handla aktivt. Det är därför viktigt att behålla likviditeten i obligationsmarknader. Den här uppsatsen undersöker aktiviteten och likviditeten i de svenska marknaderna för statsobligationer och bostadsobligationer. För att mäta aktiviteten har en kombination av offentlig handelsdata (utförda transaktioner) och privat handelsdata (potentiella transaktioner) använts. Den uppmätta aktiviteten avspeglar storleken på transaktionerna såväl som frekvensen av transaktionerna. Hög aktivitet i marknaden indikerar att likviditeten på marknaden är hög, låg aktivitet indikerar att det råder brist på likviditet i marknaden. Svenska och internationella investerare kan uppleva olika marknadsförhållanden och utsättas för olika risker även när man handlar i samma marknad. Därför har den här studien valt att dela upp investerarna i fyra olika grupper; svenska investerare av statsobligationer, svenska investerare av bostadsobligationer, utländska investerare av statsobligationer och utländska investerare av bostadsobligationer. För att förstå de underliggande faktorerna som driver dessa investerargruppen att vara aktiva på marknaden har regressionsanalys med 11 förklarande variabler använts. På grund av de olika marknadsförhållandena för svenska och utländska investerare, skiljer sig även de drivande faktorerna. Avkastning på obligationsmarknaderna, kortfristiga räntesatsen samt löptidsstrukturen för obligationer visar sig vara signifikanta för alla investerargrupper. Dessutom tyder resultaten på att avkastningen på aktiemarknaden och makroekonomiska nyheter också har betydande inflytande på aktivitet. Positiv utveckling i obligationsmarknaden och aktiemarknaden stimulerar marknadsaktivitet. Den kortfristiga räntan och löptidsstrukturen visar sig ha liknande effekter, positivt inflytande på marknaden för statsobligationer och negativt inflytande på marknaden för bostadsobligationer. För internationella investerare har även två spreadar som återspeglar svenska marknadsförhållanden i relation med utländska marknadsförhållanden inkluderats i regressionsanalysen. Båda spreadarna visar sig vara betydande för utländska investerare. Detta tyder på att utländska investerare väljer att vara aktiva i den marknaderna som de anser ha de mest önskvärda handelsförhållandena.

In South Africa, over-the-counter (OTC) bond options may be used in order to either hedge or speculate. However, since 2001, this market deteriorated significantly. The current research assessed the role of the local bond option market, reasons for the deterioration of the South African OTC bond option market, and how this bond option market could possibly be restored as a primary hedging instrument. The opinions of individuals operating in this market were obtained using a questionnaire. In the opinion of the respondents, wide bid–offer spreads, regulatory interferences and poor participation within this market caused market deterioration. The market could be restored as a hedging instrument if effective market integration exists, interbank trading regularly takes place, liquidity was enhanced, transparency increased and investor knowledge improved. Future research could focus on regulatory transformation, the types of derivatives used for hedging, and an assessment of appropriate continuous professional development interventions for investors. / Business Management / M. Com. (Business Management)

The thesis consists of four papers on numerical complexityanalysis of weak approximation of ordinary and partialstochastic differential equations, including illustrativenumerical examples. Here by numerical complexity we mean thecomputational work needed by a numerical method to solve aproblem with a given accuracy. This notion offers a way tounderstand the efficiency of different numerical methods. The first paper develops new expansions of the weakcomputational error for Itˆo stochastic differentialequations using Malliavin calculus. These expansions have acomputable leading order term in a posteriori form, and arebased on stochastic flows and discrete dual backward problems.Beside this, these expansions lead to efficient and accuratecomputation of error estimates and give the basis for adaptivealgorithms with either deterministic or stochastic time steps.The second paper proves convergence rates of adaptivealgorithms for Itˆo stochastic differential equations. Twoalgorithms based either on stochastic or deterministic timesteps are studied. The analysis of their numerical complexitycombines the error expansions from the first paper and anextension of the convergence results for adaptive algorithmsapproximating deterministic ordinary differential equations.Both adaptive algorithms are proven to stop with an optimalnumber of time steps up to a problem independent factor definedin the algorithm. The third paper extends the techniques to theframework of Itˆo stochastic differential equations ininfinite dimensional spaces, arising in the Heath Jarrow Mortonterm structure model for financial applications in bondmarkets. Error expansions are derived to identify differenterror contributions arising from time and maturitydiscretization, as well as the classical statistical error dueto finite sampling. The last paper studies the approximation of linear ellipticstochastic partial differential equations, describing andanalyzing two numerical methods. The first method generates iidMonte Carlo approximations of the solution by sampling thecoefficients of the equation and using a standard Galerkinfinite elements variational formulation. The second method isbased on a finite dimensional Karhunen- Lo`eve approximation ofthe stochastic coefficients, turning the original stochasticproblem into a high dimensional deterministic parametricelliptic problem. Then, adeterministic Galerkin finite elementmethod, of either h or p version, approximates the stochasticpartial differential equation. The paper concludes by comparingthe numerical complexity of the Monte Carlo method with theparametric finite element method, suggesting intuitiveconditions for an optimal selection of these methods. 2000Mathematics Subject Classification. Primary 65C05, 60H10,60H35, 65C30, 65C20; Secondary 91B28, 91B70. / QC 20100825