| 1. |
- Almasri, Abdullah, et al.
(författare)
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Forecasting risk premium using wavelet transform
- 2015. - 1
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Ingår i: Festschrift in honor of Professor Ghazi Shukur on the occasion of his 60th birthday. - : Linnaeus University Press. - 9789187925900 ; , s. 1-7
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Almasri, Abdullah, et al.
(författare)
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Testing for trends and causality in Swedish environmental data, using Wavelet analysis
- 2013
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Konferensbidrag (refereegranskat)abstract
- This paper utilizes Wavelet based methodology to estimate and test for trends and granger causality in temperature andprecipitation. We use quarterly data from Sweden for the period 1884 up to 2011. The analysis suggests that temperatureand precipitation in Sweden currently have a positive trend in 2011. Thus the recent lower levels of the variables 2009-2010are estimated to be temporary fluctuations or deviations from the trend. Moreover, in the short run there are feedbackeffects between the variables and over longer periods, 4-8 years, temperature granger cause precipitation.
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| 3. |
- Eriksson, Katarina
(författare)
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Finance and Supply Chain Management : Coordination of a Dyadic Supply Chain through Application of Option Contracts
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The purpose of this dissertation is to study the relationship between dyadic supply chain flexibility and dyadic supply chain profitability.In today’s global environment, competition is no longer limited to companies but has evolved to supply chains. Supply disruption, lead time uncertainty and stochastic demand can result in costly inefficiencies of up to 40% when companies are trying to coordinate ordering and production. A dyadic supply chain competing in a global economy cannot afford to end up with a 40% smaller share of the pie.This thesis applies theory and instruments from finance, specifically portfolio theory and real options theory when applying option contracts to create flexibility in a dyadic supply chain.The methodology applied was to conduct an initial literature review of prior research to establish research gaps (first paper). This resulted in the development of an algorithm (second paper) combining the base stock model and the option mechanism to create flexibility for an OEM and supplier to coordinate ordering and production bilaterally in a multi-period setting. In the third paper the algorithm was applied to a case study using data from two companies, which resulted in the algorithm being tested and validated. Furthermore, option contract theory was integrated with dyadic supply chain practise while Fisher portfolio paradox was addressed.The dissertation contributes in the following areas: the empirical contribution is evidence of the relationship between dyadic supply chain flexibility and profitability using quantitative data from two companies.The methodological contribution is a method for the objective valuation of dyadic supply chain flexibility and the measurement of profitability, by valuing the option contract.The theoretical contribution is achieved through the integration of portfolio and option theory into SCM while addressing Fisher’s portfolio paradox.The practical contribution is an algorithm that creates flexibility for an OEM and asupplier to coordinate ordering and production bilaterally and maintain its collaborative advantage when competing in a global economy, thus avoiding ending up with a 40% smaller share of the pie. In addition, this dissertation advances this topic in SCM into a quantitatively measurable theory.
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| 4. |
- Hibbs, Douglas A., Jr. 1944, et al.
(författare)
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Wage Dispersion and Productive Efficiency: Evidence For Sweden
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The effects of wage dispersion on productive efficiency is a topic rich in theoretical conjecture, a common object of Scandinavian polemical debate and at the same time an issue almost barren of systematic econometric evidence. The Swedish record of enormous compression of relative wages under the institutional regime of centralized solidarity bargaining, followed by substantial de-compression of wages after central bargaining broke down, supplies observations well suited for empirical testing of theories and assertions about the response of productive efficiency to shifts in wage distribution. Results presented in this paper obtained from regression experiments based on distribution-augmented production and labor productivity functions yield no support of 'fairness, morale and cohesiveness' theories implying that wage leveling within workplaces and industries may enhance productivity. We do find substantial evidence, however, that reduction of inter-industry wage differentials contributed positively to aggregate output and productivity growth, most likely for the structural reasons first emphasized by leading Swedish trade union economists almost a half century ago.
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| 5. |
- Li, Yushu
(författare)
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Essays on statistical testing using Wavelet methodologies
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis consists of five essays on the application of wavelet methodology to different tests in time series analysis. Essay I proposes a nonlinear Dickey-Fuller F test for unit roots against the first order Logistic Smooth Transition Autoregressive LSTAR (1) model. The asymptotic distribution of the test statistic is analytically derived while the size and power properties for small samples of the tests are investigated using Monte Carlo experiments. The results show that there is a serious size distortion for the test when Autoregressive Conditional Heterskedasticity (GARCH) errors appear in the Data Generating Process (DGP). To solve this problem, we use the wavelet technique to filter out the GARCH distortion and to improve the size property of the test under GARCH error. We also discuss the asymptotic distributions of the test statistics in GARCH and wavelet environments. Essay II uses the wavelet technique to improve the over-rejection problem of the traditional linear Dickey-Fuller tests for unit root when the data is associated with volatility such as a GARCH (1, 1) effect. We prove that the asymptotic distribution of the test in the wavelet environment is still the same as the traditional Dickey-Fuller type of test. The finite sample property is improved when the data suffers from GARCH error. An empirical example is illustrated with data on the net immigration to Sweden during the period 1950 to 2000. Essay III applies the wavelet ratio statistic to the Im-Pesaran-Shin (IPS) type of test and compares it with the IPS test by using Dickey-Fuller t statistic. Simulation results show again in power by employing the wavelet ratio test instead of the Dickey-Fuller t statistic in the panel data case. As the IPS test is sensitive to the cross sectional dependence, we further compare the robustness of both test statistics to the cross sectional. Finally we apply a residual based waves trapping methodology to reduce the over biased size problem brought up by the cross correlation for both test statistics. Essay IV uses simulated data to investigate the power of different causality tests in a two dimensional vector autoregressive (VAR) model. The data are presented in a non-linearenvironment that is modelled using a logistic smooth transition autoregressive (LSTAR)function. We use both linear and non-linear causality tests to investigate the uni-direction causality relationship and compare the power of these tests. When implementing the nonlinear test, we use separately the original data, the linear VAR filtered residuals, and the wavelet decomposed series based on wavelet multi resolution analysis (MRA). The simulation results show that the non-parametric test based on the wavelet decomposition series (which is a model free approach) has the highest power for exploring causality relationships in nonlinear models. Essay V first presents a power controlled turning points detecting method based on the theory of likelihood ratio test in statistical surveillance. Next we show how the outlier will influence the performance of this methodology. Due to the sensitivity of the surveillance system to the outliers, we finally present a wavelet multi resolution (MRA) based outlier elimination approach, which can be combined with the on-line turning point detecting process and will also alleviate the false alarm problem introduced by the outliers.
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| 6. |
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| 7. |
- Sahamkhadam, Maziar
(författare)
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Copula-based Portfolio Optimization
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis studies and develops copula-based portfolio optimization. The overall purpose is to clarify the effects of copula modeling for portfolio allocation andsuggest novel approaches for copula-based optimization. The thesis is a compilation of five papers. The first and second papers study and introduce copula-based methods; the third, fourth, and fifth papers extend their applications to the Black-Litterman (BL) approach, expectile Value-at-Risk (EVaR), and multicriteria optimization, respectively.The first paper focuses on applying copula-based forecasting models and studying tail dependence and how the risk model choice affects asset allocation. Using international stock markets, an analysis of the performance of several risk modeling portfolio strategies indicates that GARCH-EVT forecasting models, which use Gaussian or Student-t copulas, are best at reducing portfolio risk.In the second paper, vine copulas are applied to study portfolio strategies during the global financial and COVID-19 crises. Overall, we find that the Student-t drawable vine copula models perform best with regard to risk reduction, both for the entire 2005–2012 period as well as during the global financial crisis. For the COVID-19 crisis, however, we find that the asymmetric Joe C-vine copula model performs bestin reducing downside portfolio risk.The third paper includes a methodological contribution in that it incorporates dependency structure modeling with the BL approach and applying tail constraintsin reward-risk maximization. Our empirical analysis and robustness check indicate better performance for the CBL portfolios in terms of lower tail risk and higher risk-adjusted returns compared to the benchmark strategies.The fourth paper investigates EVaR as the risk measure in dynamic copula-based portfolio optimization and compares it to the common variance and conditional Value-at-Risk (CVaR). Using ten S&P 500 industry sectors, EVaR leads to a min-risk dynamic generalized additive models (GAMC-vine) portfolio that achieves higher out-of-sample average return and risk-adjusted ratios. Furthermore, EVaR shows a better portfolio ranking than CVaR and the copula-based variance and EVaR portfolios show higher-order stochastic dominance over CVaR strategies.The fifth paper develops a copula-based multi-objective portfolio (MOP) optimization. Applying the copula-based multi-objective portfolio optimization (MOP) optimization model, we investigate the impacts of objective functions and several multivariate risk models on portfolio performance. In general, there isevidence that the copula-based multicriteria portfolios perform better than those produced using the other predictive models in terms of the downside risk. With regard to portfolio attributes, the dividend yield and beta coefficient significantly reduce portfolio tail risk measures.
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