In this dissertation, three related issues concerning empirical time series models for energy financial markets and the stock market were investigated. The purpose of this dissertation was to analyze the interdependence of price movements, focusing on the forecasting models for crude oil prices and the hedging models for gasoline prices, and to study the change in the contemporaneous causal relationship between investors' activities and stock price movements in the Korean stock market. In the first essay, the nature of forecasting crude oil prices based on financial data for the oil and oil product market is examined. As crack spread and oil-related Exchange-Traded Funds (ETFs) have enabled more consumers and investors to gain access to the crude oil and petroleum products markets, I investigated whether crack spread and oil ETFs were good predictors of oil prices and attempted to determine whether crack spread or oil ETFs were better at explaining oil price movements. In the second essay, the effectiveness of diverse hedging models for the unleaded gasoline price is examined using futures and ETFs. I calculated the optimal hedge ratios for gasoline futures and gasoline ETF utilizing several advanced econometric models and then compared their hedging performances. In the third essay, the contemporaneous causal relationship between multiple players' activities and stock price movements in the Korean stock market was investigated using the framework of a DAG model. The causal impacts of three players' activities in regard to stock return and stock price volatility are examined, concentrating on foreign investor activities. Within this framework, two Korean stock markets, the KSE and KOSDAQ markets, are analyzed and compared. Recognizing the global financial crisis of 2008, the change in casual relationships was examined in terms of pre- and post-break periods. In conclusion, when a multivariate econometric model is developed for multi-markets and multi-players, it is necessary to consider a number of attributes on data relations, including cointegration, causal relationship, time-varying correlation and variance, and multivariate non-normality. This dissertation employs several econometric models to specify these characteristics. This approach will be useful in further studies of the information transmission mechanism among multi-markets or multi-players.