Global ETD Search

21	An investigation of Sustainable Assets, Equitiesand the Bond market during the Globalpandemic, COVID-19 Rahm, Vincent, de la Rosa, Frej January 2022 (has links) ESG investing has been a hot topic during several years and there have been numerousstudies examining the relationship between sustainable assets and non-sustainable assetsincluding green bonds, social bonds, environmental bonds, ESG-bonds and ESG indices;conventional bonds, S&P 500, common stocks and non-ESG indices. During negative marketshocks several ESG stocks and indices have been shown to outperform common stocks andindices. Green bonds demonstrated an asymmetric relationship to other assets providinginvestors with an opportunity for diversification. We’ve looked at the relationship andperformance of sustainable assets and non-sustainable assets by using Markowitz portfoliometrics and Engle Rs’ DCC-GARCH. Our findings propose green bonds and treasuries toprovide hedging and diversification opportunities during crises but demonstrate sustainablefixed income assets to underperform non-sustainable fixed income assets during the COVID19 market shock as opposed to previous studies. Conventional bonds; COVID-19; DCC-GARCH ESG; Green bond Economics Nationalekonomi
22	Quantitative Portfolio Construction Using Stochastic Programming / Kvantitativ portföljkonstruktion med användning av stokastisk programmering : En studie inom portföljoptimering Ashant, Aidin, Hakim, Elisabeth January 2018 (has links) In this study within quantitative portfolio optimization, stochastic programming is investigated as an investment decision tool. This research takes the direction of scenario based Mean-Absolute Deviation and is compared with the traditional Mean-Variance model and widely used Risk Parity portfolio. Furthermore, this thesis is done in collaboration with the First Swedish National Pension Fund, AP1, and the implemented multi-asset portfolios are thus tailored to match their investment style. The models are evaluated on two different fund management levels, in order to study if the portfolio performance benefits from a more restricted feasible domain. This research concludes that stochastic programming over the investigated time period is inferior to Risk Parity, but outperforms the Mean-Variance Model. The biggest aw of the model is its poor performance during periods of market stress. However, the model showed superior results during normal market conditions. / I denna studie inom kvantitativ portföljoptimering undersöks stokastisk programmering som ett investeringsbeslutsverktyg. Denna studie tar riktningen för scenariobaserad Mean-Absolute Deviation och jämförs med den traditionella Mean-Variance-modellen samt den utbrett använda Risk Parity-portföljen. Avhandlingen görs i samarbete med Första AP-fonden, och de implementerade portföljerna, med era tillgångsslag, är därför skräddarsydda för att matcha deras investeringsstil. Modellerna utvärderas på två olika fondhanteringsnivåer för att studera om portföljens prestanda drar nytta av en mer restrektiv optimeringsmodell. Den här undersökningen visar att stokastisk programmering under undersökta tidsperioder presterar något sämre än Risk Parity, men överträffar Mean-Variance. Modellens största brist är dess prestanda under perioder av marknadsstress. Modellen visade dock något bättre resultat under normala marknadsförhållanden. Asset Allocation Dynamic Portfolio Construction Stochastic Programming Scenario Generation Multivariate GARCH DCC-GARCH Copula-GARCH Transaction Costs Mean-Absolute Deviation Risk Parity Mean-Variance Tillgångsallokering Dynamisk Portfölj Konstruktion Stokastisk Programmering Scenario Generation Multivariat GARCH DCC-GARCH Copula- GARCH Transaktionskostnader Mean-Absolute Deviation Risk Parity Mean-Variance Computational Mathematics Beräkningsmatematik
23	Analysis of Interdependencies among Central European Stock Markets / Analysis of Interdependencies among Central European Stock Markets Mašková, Jana January 2011 (has links) The objective of the thesis is to examine interdependencies among the stock markets of the Czech Republic, Hungary, Poland and Germany in the period 2008-2010. Two main methods are applied in the analysis. The first method is based on the use of high-frequency data and consists in the computation of realized correlations, which are then modeled using the heterogeneous autoregressive (HAR) model. In addition, we employ realized bipower correlations, which should be robust to the presence of jumps in prices. The second method involves modeling of correlations by means of the Dynamic Conditional Correlation GARCH (DCC-GARCH) model, which is applied to daily data. The results indicate that when high-frequency data are used, the correlations are biased towards zero (the so-called "Epps effect"). We also find quite significant differences between the dynamics of the correlations from the DCC-GARCH models and those of the realized correlations. Finally, we show that accuracy of the forecasts of correlations can be improved by combining results obtained from different models (HAR models for realized correlations, HAR models for realized bipower correlations, DCC-GARCH models).
24	Swedish Equity Sectors Risk Management with Commodities : Revisiting dynamic conditional correlations and hedge ratios Engström, Daniel, Gustafsson, Niklas January 2017 (has links) The purpose of this study is to investigate changes in dynamic conditional correlations between Swedish equity sector indices and commodities using oil, gold, copper and a general commodity index. Additionally the purpose is to evaluate which of the two methods, DCC- GARCH or GO-GARCH that is more efficient in estimating correlation for hedge ratio calculation. Daily data on the FTSE30 index of Sweden and its sector indices have been studied between the years 1994 and 2017. A DCC-GARCH (1,1) and GO-GARCH (1,1) model with one autoregressive term AR(1) using multivariate Student t- and Multivariate Affine Negative Inverse Gaussian distribution were used to estimate conditional correlations. Correlations between Swedish FTSE30, its sector indices and commodities are considerably lower than previous research has found American or emerging markets correlation with commodities to be. This suggests better diversification opportunities with commodities for the Swedish market. Optimal hedge ratios (OHR) was calculated and back tested using a rolling window analysis with 1000 days forecast length and 20 days re-estimation window and evaluated using a calculated hedge effectiveness index (HE). Determined by HE, copper is the best hedge for the Swedish composite FTSE30 and sector indices using conditional correlation from the GO-GARCH during the data period. Gold is considered as a semi-strong safe haven due to its negative correlation with all sectors. Additionally, this study identifies a temporarily large increase in the correlation between the Swedish equities sectors and composite index with commodities around the years 2015/2016. This study also emphasizes the difference between stressful and calm periods in the market. Hedging hedge commodities futures hedge ratio conditional correlation DCC GO-GARCH DCC-GARCH GARCH Dynamic conditional correlation oil GSCI copper gold safe haven optimal hedge ratio finance economics markets risk risk management hedge effectiveness Risk riskhantering råvaror terminer futures hedging hedge GARCH Economics Nationalekonomi

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