Thesis (Ph.D.)--Northcentral University, 2008. / Adviser: William Shriner. Includes bibliographical references.

This thesis is focused on Managed Futures, which is one of alternative investment instruments. Even though its popularity in developed countries rises, it is a rarity in Czech financial market. The main intent is to clarify specifications, historical roots, legal framework and other characteristic aspects. Part of the work will be devoted to the analysis of performance, risk, correlation with other investments and the possibility of inclusion in a portfolio of experienced Czech investor.

Su, Yiwen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (p. 76-84). / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Literature Review --- p.9 / Chapter 2.1 --- Hedge Ratio Review --- p.9 / Chapter 2.2 --- Estimating the Hedge Ratio --- p.13 / Chapter 2.2.1 --- Static Hedge Ratio --- p.13 / Chapter 2.2.2 --- "Dynamic Hedge Ratio, Multivariate GARCH Frame-work and DCC Model" --- p.14 / Chapter 3 --- Futures Market Efficiency --- p.19 / Chapter 3.1 --- Market Efficiency and Cointegration Test --- p.20 / Chapter 4 --- Model Specifications and Hedging Strategy --- p.24 / Chapter 4.1 --- Model Specifications --- p.24 / Chapter 4.1.1 --- BGARCH-DCC Model --- p.25 / Chapter 4.1.2 --- Symmetric BGARCH-DCC Model --- p.28 / Chapter 4.1.3 --- Asymmetric BGARCH-DCC Model --- p.31 / Chapter 4.2 --- Hedge Ratio --- p.33 / Chapter 4.2.1 --- MV Hedge Ratio --- p.34 / Chapter 4.2.2 --- Zero-VaR Hedge Ratio --- p.35 / Chapter 4.3 --- Evaluation of Hedge Effectiveness --- p.38 / Chapter 5 --- Data Description and Empirical Results --- p.39 / Chapter 5.1 --- Preliminary Data Analysis --- p.39 / Chapter 5.2 --- Estimation Results --- p.42 / Chapter 5.3 --- Dynamic Hedging Performance --- p.53 / Chapter 6 --- Conclusion --- p.68 / Chapter A --- Equation Derivation --- p.72 / Bibliography --- p.76

This study concerns the evaluation of alternative pricing strategies involving options on feed grains futures contracts during the period of 1973-1986. To predict the option premiums that would have occurred at various points in this time period, the study did research on market premiums of options on corn futures contracts from March 1, 1985 until December 31, 1985. The research showed that market premiums conformed closely to the premiums estimated by Black model of options pricing. The generalized stochastic dominance with absolute risk aversion function intervals is applied in the study in order to evaluate the strategies. The results showed that under different risk preferences, (DARA and CARA), the commodity options strategies dominate the cash sale strategy, but do not dominate the hedging by selling futures contract strategy. Options may provide alternatives for feed grains producers and traders. Put (call) options provided protection from losses resulting from falling (raising) cash price and may somtimes raise average income/margin of feed grain producers and traders.

This write-up is submitted in partial fulfilment of the Master of Management Degree in Finance and Investments Degree. / Growth in commodity exporting economies, such as South Africa, is highly dependent on the revenue generated from exports. It is thus evident that as commodity prices fluctuate, income and the balance of payments will be accordingly impacted. This is further exacerbated by strong dependence on the imports of certain commodities. Oil is one such commodity on whose imports South Africa is highly dependent. Although natural gas is also imported, it is in lower quantities and is as such expected to impact South Africa to a lower extent. Coal, on the other hand, is among the main commodity exports and was expected to have an impact on (and be impacted by) South African macroeconomic fundamentals. In this study, we use a VECM and MGARCH model to test the interaction between South African macroeconomic variables and these three commodities. Our VECM findings indicate that oil and exchange rates are inflationary. This implies that an increase in oil prices and/or exchange rates (indicating a depreciation of the Rand against the U.S. Dollar) results in an increase in inflation. Inflation, on the other hand, propagates higher coal prices and to a lesser extent, higher interest rates. We account the latter to South Africa’s inflation targeting regime and the former to demand and supply dynamics which occur at RBCT as production costs increase (short-term coal export contracts and spot market sales). Natural gas is found to have weak impacts on interest rates and exchange rates. Our MGARCH model shows that only the innovations in natural gas and oil prices spillover into interest rates and exchange rate. There is no direct spillover captured. However, there is strong direct spillover from oil to inflation. Lastly, interest rates are found to have a strong direct volatility spillover to both oil and natural gas. We attribute this to the exchange rate impact that interest rates have and is supported by the exchange rate impact on commodity price volatility. We conclude that an in-depth understanding of triggers is pertinent for monetary and fiscal policy decisions in South Africa. Although the South African economy is relatively diversified compared to other developing countries, commodity price fluctuations do have a significant impact on economic performance. / MT2017

This study gives an insight into the behaviour and performance of large speculators and large hedgers in 29 US futures markets. Using a trading determinant model and priced risk factors such as net positions and sentiment index, results suggest hedgers (speculators) exhibit significant positive feedback trading in 15 (7) markets. Information variables like the S&P500 index dividend yield, corporate yield spread and the three months treasury bill rate were mostly unimportant in large players’ trading decisions. Hedgers had better market timing abilities than speculators in judging the direction of the market in one month. The poor market timing abilities and poor significance of positive feedback results suggest higher trading frequency intervals for speculators. Hedging pressures, which measure the presence of risk premium in futures markets, were insignificant mostly in agricultural markets. As a robust test of hedging pressures, price pressure tests found risk premium to be still significant for silver, crude oil and live cattle. The positive feedback behaviour and negative market timing abilities suggest hedgers in heating oil and Japanese yen destabilize futures prices, and points to a need to check CFTC’s (Commodity Futures Trading Commission) position limits regulation in these markets. In fact, large hedgers in these two markets are more likely to be leading behaviour, in that they have more absolute net positions than speculators. Alternatively stated, positive feedback hedgers in these two markets are more likely to lead institutions and investors to buy (sell) overpriced (underpriced) contracts, eventually leading to divergence of prices away from fundamentals. / Atlhought hedgers in crude oil had significant positive feedback behaviour and negative market timing skills, they would not have much of a destabilizing effect over remaining players because the mean net positions of hedgers and speculators were not far apart. While the results are statistically significant, it is suggested these could be economically significant, in that there have been no regulation on position limits at all for hedgers compared to speculators who are imposed with strict limits from the CFTC. Further, mean equations were regressed against decomposed variables, to see how much of the futures returns are attributed to expected components of variables such as net positions, sentiment and information variables. While the expected components of variables are derived by ensuring there are enough ARMA (autoregressive and moving average) terms to make them statistically and economically reliable, the unexpected components of variables measure the residual on differences of the series from its mean. When decomposing net positions against returns, it was found expected net positions to be negatively related to hedgers’ returns in mostly agricultural markets. Speculators’ expected (unexpected) positions were less (more) significant in explaining actual returns, suggesting hedgers are more prone in setting an expected net position at the start of the trading month to determine actual returns rather than readjusting their net positions frequently all throughout the remaining days of the month. While it important to see how futures returns are determined by expected and unexpected values, it is also essential to see how volatility is affected as well. / In an attempt to cover three broad types of volatility measures, idiosyncratic volatility, GARCH based volatility (variance based), and PARCH based volatility (standard deviation) are used. Net positions of hedgers (expected and unexpected) tend to have less effect on idiosyncratic volatility than speculators that tended to add to volatility, reinforcing that hedgers trading activity hardly affect the volatility in their returns. This suggest they are better informed by having a better control over their risk (volatility) measures. The GARCH model showed more reliance of news of volatility from previous month in speculators’ volatility. Hedgers’ and speculators’ volatility had a tendency to decay over time except for hedgers’ volatility in Treasury bonds and coffee, and gold and S&P500 for speculators’ volatility. The PARCH model exhibited more negative components in explaining current volatility. Only in crude oil, heating oil and wheat (Chicago) were idiosyncratic volatility positively related to return, reinforcing the suggestion for stringent regulation in the heating oil market. Expected idiosyncratic volatility was lower (higher) for hedgers (speculators) as expected under portfolio theory. Markets where variance or standard deviation are smaller than those of speculators support the price insurance theory where hedging enables traders to insure against the risk of price fluctuations. Where variance or standard deviation of hedgers is greater than speculators, this suggest the motivation to use futures contracts not primarily to reduce risk, but by institutional characteristics of the futures exchanges like regulation ensuring liquidity. / Results were also supportive that there was higher fluctuations in currency and financial markets due to the higher number of contracts traded and players present. Further, the four models (GARCH normal, GARCH t, PARCH normal and PARCH t) showed returns were leptokurtic. The PARCH model, under normal distribution, produced the best forecast of one-month return in ten markets. Standard deviation and variance for both hedgers’ and speculators’ results were mixed, explained by a desire to reduce risk or other institutional characteristics like regulation ensuring liquidity. Moreover, idiosyncratic volatility failed to accurately forecast the risk (standard deviation or variance based) that provided a good forecast of one-month return. This supports not only the superiority of ARCH based models over models that assume equally weighted average of past squared residuals, but also the presence of time varying volatility in futures prices time series. The last section of the study involved a stability and events analysis, using recursive estimation methods. The trading determinant model, mean equation model , return and risk model, trading activity model and volatility models were all found to be stable following the effect of major global economic events of the 1990s. Models with risk being proxied as standard deviation showed more structural breaks than where variance was used. Overall, major macroeconomic events didn’t have any significant effect upon the large hedgers’ and speculators’ behaviour and performance over the last decade.

The aim of this thesis is a development of a new class of financial models with random parameters, which are computationally efficient and have the same level of performance as existing ones. In particular, this research is threefold. I have studied the evolution of storable commodity and commodity futures prices in time using a new random parameter model coupled with a Kalman filter. Such a combination allows one to forecast arbitrage-free futures prices and commodity spot prices one step ahead. Another direction of my research is a new volatility model, where the volatility is a random variable. The main advantage of this model is high calibration speed compared to the existing stochastic volatility models such as the Bates model or the Heston model. However, the performance of the new model is comparable to the latter. Comprehensive numerical studies demonstrate that the new model is a very competitive alternative to the Heston or the Bates model in terms of accuracy of matching option prices or computing hedging parameters. Finally, a new futures pricing model for electricity futures prices was developed. The new model has a random volatility parameter in its underlying process. The new model has less parameters, as compared to two-factor models for electricity commodity pricing with and without jumps. Numerical experiments with real data illustrate that it is quite competitive with the existing two-factor models in terms of pricing one step ahead futures prices, while being far simpler to calibrate. Further, a new heuristic for calibrating two-factor models was proposed. The new calibration procedure has two stages, offline and online. The offline stage calibrates parameters under a physical measure, while the online stage is used to calibrate the risk-neutrality parameters on each iteration of the particle filter. A particle filter was used to estimate the values of the underlying stochastic processes and to forecast futures prices one step ahead. The contributory material from two chapters of this thesis have been submitted to peer reviewed journals in terms of two papers: • Chapter 4: “A fast calibrating volatility model” has been submitted to the European Journal of Operational Research. • Chapter 5: “Electricity futures price models : calibration and forecasting” has been submitted to the European Journal of Operational Research.

In the thesis we analyze sixteen commodity futures markets belonging to four families (energy type, grains, metals and other agricultural commodities) utilizing futures prices of front, back and roll futures contracts. As the tests for cointegration between front and back futures prices give us contradictory results we concentrate on roll contracts defined as the difference between front and back commodity futures contracts. We found that all commodity roll futures except natural gas and wheat futures exhibit long memory, which is usually connected with the fractal market hypothesis. Further, we employ specific ARMA and ARFIMA models and rolling window one-day-ahead technique to predict roll futures contract prices. Based on analysis of relation between resulting predictability and liquidity of roll futures contracts we concluded that lowest predictability is linked with the lowest liquidity among all commodities except metals and found evidence that predictability is positively dependent on liquidity among all commodities except metals, lumber, soybean oil and soybeans. The revealed dependence is strongest for energy type commodities. The relations and dependencies on the commodity futures markets are of high importance for all market participants such as hedge managers, investors, speculators and also for...

This dissertation consists of two essays. First essay investigates the implications of researcher data requirement on the risk-adjusted returns of firms. Using the monthly CRSP data from 1925 to 2013, we present evidence that firms which survive longer have higher average returns and lower standard deviation of annualized returns than the firms which do not. I further demonstrate that there is a positive relation between firms’ survival and average performance. In order to account for the positive correlation between survival and average performance, I model the relation of survival and pricing errors using a Farlie-Gumbel-Morgenstern joint distribution function and fit resulting the moment conditions to the data. Our results show that even a low correlation between firm survival time and pricing errors can lead to a much higher correlation between the survival time and average pricing errors. Failure to adjust for this data selection biases can result in over/under estimates of abnormal returns by 5.73 % in studies that require at least five years of returns data. Second essay examines diversification benefits of commodity futures portfolios in the light of the rapid increase in investor participation in commodity futures market since 2000. Many actively managed portfolios outperform traditional buy and hold portfolios for the sample period from January, 1986 to October, 2013. The evidence documented through traditional intersection test and stochastic discount factor based spanning test indicates that financializaiton has reduced segmentation of commodity market with equity and bond market and has increased the riskiness of investing in commodity futures markets. However, diversifying property of commodity portfolios have not disappeared despite the increased correlation between commodity portfolios returns and equity index returns.

Thesis (M.M. (Finance & Investment)--University of the Witwatersrand, Faculty of Commerce, Law and Management, Wits Business School, 2017 / This paper provides an empirical analysis of the effect of commodity price volatility on the volatility of the South African exchange rate and subsequently the returns on the equity of commodity producing firms listed on the JSE. GARCH and VAR models evaluate South African exchange rate and stock market data between the years 1995 and 2015. Results show that there exists a spill over and bidirectional relationships between the equity returns volatility and the volatility of the exchange rate. Findings also indicated that international commodity price shocks transmitted into the South African Rand. / MT2017