The main objective of this thesis is to examine the dependency structure among different agricultural and energy commodity markets in the United States. For achieving this goal, the paper makes use of the Copula-GARCH(1,1) model to study the financial return volatility and the co-movement between pair of commodities including corn, soybean and gasoline over the pre-COVID 19 pandemic period (from 01-01-2018 to 01-01-2020) and the ongoing COVID 19 pandemic period (from 01-01-2020 to 01-04-2021). First, the study has shown that the time-dependent volatilities of commodity returns display volatility clustering effect in the two periods and the volatility of volatility of commodity markets is higher during the pandemic period. Second, it is observed that the correlations among different commodities have increased significantly in the ongoing pandemic period and we also find that the strongest co-movement is between returns of corn and soybean over the two periods. Finally, the results suggest that the (extreme) co-movements between agricultural commodities (corn and soybean) are governed by symmetry; that is they tend to boom and crash together during extreme shocks or events. On the other hand, the (extreme) co-movements between an agricultural commodity (corn or soybean) and the energy commodity (gas) appear to co-move asymmetrically and they tend to experience the market crash together but not the market boom.

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No / This study investigates the impact of LIFFE's introduction of individual equity futures contracts on the risk characteristics of the underlying stocks trading on the LSE. We employ the Fama and French three-factor model (TFM) to measure the change in the systematic risk of the underlying stocks which arises subsequent to the introduction of futures contracts. A GJR-GARCH(1,1) specification is used to test whether the futures contract listing affects the permanent and/or the transitory component of the residual variance of returns, and a control sample methodology isolates changes in the risk components that may be caused by factors other than futures contract innovation. The observed increase (decrease) in the impact of current (old) news on the residual variance implies that futures contract listing enhances stock market efficiency. There is no evidence that futures innovation impacts on either the systematic risk or the permanent component of the residual variance of returns.

No / This study assesses whether the widely documented momentum profits can be ascribed to time-varying risk as described by a GJR-GARCH(1,1)-M model. Consistent with rational pricing in efficient markets, we reveal that momentum profits are a compensation for time-varying unsystematic risks, common to the winner and loser stocks. We also find that, because losers have a higher propensity than winners of disclose bad news, negative return shocks increase their volatility more than it increases that of the winners. The volatility of the losers is also found to respond to news more slowly, but eventually to a greater extent, than that of the winners. Following Hong et al. (2000), we interpret this as a sign that managers of loser firms are reluctant to disclosing bad news, while managers of winner firms are eager to releasing good news

No / We study the price and liquidity effects following the FTSE 100 index revisions. We employ the standard GARCH(1,1) model to allow the residual variance of the single index model (SIM) to vary systematically over time and use a Kalman filter approach to model SIM coefficients as a random walk process. We show that the observed price effect depends on the abnormal return estimation methods. Specifically, the OLS-based abnormal returns indicate that the price effect associated with the index revision is temporary, whereas both SIM with random coefficients and GARCH(1,1) model suggest that both additions and deletions experience permanent price change. Added (removed) stocks exhibit permanent (temporary) change in trading volume and bid-ask spread. The analysis of the spread components suggests that the permanent change associated with additions is a result of non-information-related liquidity. We interpret the permanent price effect of additions and deletions combined with the permanent (temporary) shift in liquidity of added (removed) stocks as evidence in favour of the imperfect substitution hypothesis with some non-information-related liquidity effects in the case of additions.

During stormy weathers ships searched for safe havens to stay until the storm had subsided. In much similarity to these ships, investors on the financial markets search for safe assets when the markets start to shake. What could be considered a safe asset seems to be a never-ending discussion but many points out gold as one. However, no further observations of gold as a safe haven on the Swedish financial market has been made. The purpose of this research is to examine if gold could act as a safe haven in Sweden. The data used in this research is daily returns from OMXS30 and the 10-year Swedish government bond, where all returns also has been denominated in U.S. dollar. Further, statistical model has been used. The result show that gold potentially could act as a ‘safe haven’ for denominated stock returns but not for bond returns. Further, the result show that gold could act as a hedge for stock and bond return (non-denominated). The study concludes that gold does not act as a safe haven for stocks or bonds in Sweden. However, gold show weak safe haven attributes for denominated stock return.

This thesis focuses on stochastic processes and some of their properties are investigated which are necessary to determine the tools, the extremal index and the extremogram. Both mathematical tools measure extremal dependency within random time series. Two different models are introduced and related properties are discussed. The probability function of the Agent based model is surveyed explicitly and strong stationarity is proven. Data sets for both processes are simulated and clustering of the data is investigated with two different methods. Finally an estimation of the extremogram is used to interpret dependency of extremes within the data.

This paper examines the impact of USD and EUR exchange rates on the Swedish stock market performance for different economic sectors over a time period of ten years (2003-2013). The growing integration between foreign exchange markets and stock markets with the wide spread use of hedging and diversification policies made it necessary to test the degree of impact these two distinct markets share between each other. Number of studies, were done studying the relationship between the exchange rates and stock performance combining and comparing different economies and currencies. Nevertheless, research gap prevailed when it came at the point of the studying the relationship on Swedish stock and foreign exchange market. The research was conducted with the quantitative method. Initially we have tested how the performance of Swedish stock market is correlated with the return of the USD and EUR in different economic sectors over different time periods. Later, we try to investigate if there is any spillover effect flows from the exchange market to the Swedish stock market. The Pearson’s correlation coefficient and GARCH (1,1) model were applied to study the correlation and spillover effect between the exchange and stock return respectively. Our empirical study showed that there is very low correlation which is statistically insignificant between the two different markets. Correlations were found to be significantly varied across the different economic sectors in different time periods. Moreover empirical study supported that the spillover effect exists and showed that movement of exchange rates will affect the future performance of stock market. The significant conclusions were that USD and EUR can be used as portfolio diversification and during the volatile exchange market, investors should diversify or hedge their risk domestically and vice versa. The implications of this finding is particularly very important for the portfolio managers when devising their hedging policies and diversifying their portfolios in order to minimize their unsystematic risk.

This article examines the hedging positions derived from the Black-Scholes(B-S) model and the GARCH(1,1) models, respectively, when the log returns of underlying asset exhibits GARCH(1,1) process. The result shows that Black-Scholes and GARCH options deltas, one of the hedging parameters, are similar for near-the-money options, and Black-Scholes options delta is higher then GARCH delta in absolute terms when the options are deep out-of-money, and Black-Scholes options delta is lower then GARCH delta in absolute terms when the options are deep in-the-money. Simulation study of hedging procedure of GARCH(1,1) and B-S models are performed, which also support the above findings.

In this thesis, we have built an optimal portfolio using five assets from the Japanese market. We have investigated the use of GARCH(1,1) when forecasting the volatility of our optimal portfolio. Different time periods have been considered for optimizing our results. An equally-weighted portfolio has been used as a benchmark. Our results show that the optimal portfolio we constructed is more efficient than the equally-weighted portfolio in all chosen situations.