This thesis estimates the quarterly electricity demand of Turkey. First of all proper seasonal time series model are found for the variables: electricity demand, temperature, gross domestic product and electricity price. After the right seasonal time series model are found Hylleberg, Engle, Granger and Yoo (1990) test is applied to each variable. The results of the test show that seasonal unit roots exist for the electricity price even it cannot be seen at the graph. The other variables have no seasonal unit roots when the proper seasonal time series model is chosen. Later, the cointegration is tested by looking at the vector autoregressive model. As the cointegration is seen vector error correction model is found. There is long-run equilibrium when the price is the dependent variable and independent variable is gross domestic product. Temperature is taken as exogenous variable and demand is not statistically significant.

This study presents our attempt to examine the linkages and to investigate the linkage of stock price indexes among Taiwan, China and its major trading countries. Our empirical analysis employs daily data on stock price indexes over the period of January 2, 2000 to May 10, 2010. The total number of observations is about 2500. This study employ a sequence of time-series methodologies, including unit root test, cointegration test, vector error correction model, Granger causality test, Criterion, autocorrelation test, heteroscedasticity test, GARCH and Bi-GARCH. The findings of this study as follows. First, after first difference, every stock price indexes series all became stationary. Second, we found there has no long-run interrelationship among these stock markets. Third, we found that Taiwan¡¦s stock market exits leading role to China¡¦s stock market, but other countries¡¦ stock market lead Taiwan¡¦s stock market. For China, the stock market of United States, Japan, Taiwan and Hong Kong has a leading role to China¡¦s stock market. Only the rela-tionship between South Korea and China¡¦s stock market is independent. Forth, the result of autocorrelation test and ARCH test indicates that the influence of stock price indexes of major trading countries to Taiwan and China¡¦s stock price index has changed over time. Finally, the result of study indicates that every stock market can forecast its future trend by using its past stock data and investor can use the past stock data of stock market of major trading countries to forecast Taiwan and China¡¦s stock market.

Tex., Rice Univ., Diss.--Houston, 2003. / Kopie, ersch. im Verl. UMI, Ann Arbor, Mich. - Enth. 3 Beitr.

Freie Universiẗat, Diss.--Berlin, 2005.

In this thesis, an analysis of Bitcoin, Monero price and volatility is conducted with respect to S&P500 and the VIX index. Moreover using Python, we computed correlation coefficients of nine cryptocurrencies with two different approaches: Pearson and Spearman from July 2016 -July 2018. Moreover the Pearson correlation coefficient was computed for each year from July2016 - July 2017 - July 2018. It has been concluded that in 2016 the correlation between the selected cryptocurrencies was very weak - almost none, but in 2017 the correlation increased and became moderate positive. In 2018, almost all of the cryptocurrencies were highly correlated. For example, from January until July of 2018, the Bitcoin - Monero correlation was 0.86 and Bitcoin - Ethereum was 0.82.

nÃo hà / Unit root tests have been widely used to validate or reject economic modelâs hypotheses. Because of this, many authors have created different versions of this kind of test in order to generate statistics which are more precise in identifying the presence of a unit root. Some authors have increased the power of these statistics using panel data. However, the use of panel data brings the possibility of dependence between cross-sections, this has been initially handled by the independence between cross-sections hypothesis. Only the second generation tests consider dependence between cross-sections. Nevertheless, in the literature there is no test which allows changes in the dependence between cross-sections over time. Thus, this paper uses Monte Carlo experiments to analyze the small sample properties of some statistics used to identify the presence of a unit root. It is noticed that the size of these statistics has a large distortion when the level of dependence between cross-sections changes. / Teste de raiz unitÃria tem sido muito importante no sentido de validar ou rejeitar as hipÃteses dos modelos econÃmicos. Devido essa importÃncia, diversos autores tÃm criado diferentes versÃes desse teste, a fim de gerar estatÃsticas que sejam mais precisas em identificar a presenÃa de raiz unitÃria. Usando dados em painel, alguns autores conseguiram aumentar o poder dessas estatÃsticas. No entanto, o uso de dados em painel trÃs a possibilidade de dependÃncia cross-section nos dados, fato esse inicialmente tratado pela hipÃtese de independÃncia cross-section. Somente nos testes chamados de segunda geraÃÃo à que se trata dependÃncia cross-section. Entretanto, nÃo hà na literatura nenhum teste que permita mudanÃas nesse nÃvel de dependÃncia ao longo do tempo. Com isso, esse trabalho pretende avaliar, por meio de um experimento de Monte Carlo, as propriedades de pequenas amostras de algumas estatÃsticas usadas para identificar a presenÃa de raiz unitÃria. Percebe-se que o tamanho dessas estatÃsticas sofre uma grande distorÃÃo para as situaÃÃes de mudanÃa no nÃvel de dependÃncia cross-section.

This thesis investigates through simulation why tests of unit root and stationarity occasionally result in different conclusions. The thesis focusses on the KPSS test and the ADF test and both review cases with and without a trend. The goal is to bring additional knowledge of whether one of the tests are more reliable in terms of size and power and when contradictory results occur. The result shows that both KPSS and ADF suffer from low power and size distortion and that the problems persists for the most common time series lengths. Problems particularly arise when the time series contains a trend or is a process with both an autoregressive and a moving average part. There is no clear evidence that one of the tests are superior to the other, it rather depends on sample size, parameter value and type of ARIMA process.

This study examines the relationship between financial inclusion and economic growth, more specifically if financial inclusion is an important factor for economic growth. A sub question was stated as well, if the six proxies of the financial inclusion measurement respectively have an impact on economic growth. To help examine this research area we have compiled panel data from 20 countries with different income levels over a time period of 19 years. The time period on which this study is focusing is 2002-2020. The tests conducted in this study are the Dickey-Fuller unit root test and the Arellano-Bond dynamic panel GMM method. Given the result of the dynamic panel estimation, we found that financial inclusion has a positive relation to economic growth. The result also indicated that three of the six proxies for financial inclusion were statistically significant and have a positive relation to economic growth. To conclude, the study found empirical evidence that financial inclusion is an important factor for economic growth.

This study examines the relationship between mean reversion and a black swan event on the Swedish stock market. The data is taken from the Mid Cap and the Large Cap and then compared with the OMXS index. The purpose is to try and find evidence of mean reversion on both lists and if a black swan event will interfere with the mean reverting behaviour. The results we could find was that there is mean reversion on the market for our time period 2005-2022. We could also find evidence of mean reversion during the three black swan events, 2008 financial crisis, Brexit, and Covid-19 pandemic.

This study aims at analysing how African oil benchmarks within the OPEC Reference Basket relative to the WTI and Brent benchmarks which are considered as global pricing benchmarks for the period starting from 1997-2008. The Nigerian Bonny Light and Algerian Saharan blend were the two benchmarks used for this study. A time series analysis was applied to the weekly price data series set and with the aid of a breakpoint unit root test and Cusum of Squared test to determine if there was a change in the persistence of the spread of each African benchmark relative to the global benchmarks. The results for from the unit root test indicated the presence of a structural break in the price spread in 2004 for the Bonny Light benchmark and in 2005 for the Saharan blend relative to both global benchmarks. The Cusum Squared test for the four benchmark pairings indicated a change in persistence of the price spreads. The null hypothesis was rejected for the alternative hypothesis of the price spread process having a relatively high persistence value after a while. The Cusum Test results showed a change in persistence for both African benchmarks relative to the WTI benchmark and no change in persistence relative to the Brent benchmark. The results of from the Time series analysis indicated the competitive nature of African benchmarks relative to global benchmarks and this could benefit exporting countries by virtue of setting up derivative markets. The derivative markets would allow for the trade of benchmark spreads, futures contracts, options and other financial instruments for African oil producers.