Using seventeen years of data from 1991 to 2008, I derive a pricing model for farmland values. This valuation model is the first using agricultural commodity futures as a proxy for “ex ante” income projections for the crops grown or livestock grazed on United States farmland. While not all inclusive, the model is tested regionally including the Corn Belt, Delta States, Lake States, Mountain, Pacific Northwest, Pacific West and Southeast Regions. Additionally, I test whether interest rate futures contracts have a relationship with farmland values as interest rates have been proven to be a reliable predictor in past research. Farmland capitalization rates and anticipated inflation have hypothesized relationships, but are mainly used as control variables in the study. In general, agricultural commodity futures contracts are a poor predictor of changes in farmland market values. When examining relationships with quarterly percentage change regression models of the included variables, I find the Mountain region provides the most reliable pricing model where both live cattle and Minnesota wheat futures contracts has a positive statistically significant relationships with farmland market values. Also, wheat futures prices have a significant relationship with farmland values in the Corn Belt region. Interest rate futures contracts, farmland capitalization rates and anticipated inflation are not statistically significant in the majority of the regions. As a robustness check, I model the price levels of the variables using Johansen’s cointegration procedure. This time-series econometric methodology provides results in regards to long-run equilibrium relationships between the variables. The results are only slightly better. Corn, orange juice and sugar futures contracts have positive statistically significant relationships with farmland market values in multiple regions. Again, wheat has a statistically significant positive relationship with farmland values in the Corn Belt region. The Mountain region and interest rate futures contracts are not applicable for the cointegration tests as they are not integrated to the order of one.

This study mainly explores the effect of market states (price and returns) on the relationship between spot and futures oil prices and targets three important issues: long-run cointegration, causalities, and market efficiency. Based on previous studies exhibiting bi-directional causality between spot and futures oil prices, this study employs quantile regressions to examine the possible feedback effect in their long-run cointegration and their causalities. In particular, it allows for exploring the possible asymmetric responses between spot and futures markets. The empirical results herein find that the long-run cointegrated relationship between contemporaneous spot and futures prices is impacted by the states of the spot markets. Similarly, whether futures oil prices lead spot oil prices is relevant with the states of the futures markets. This study also examines the efficiency of crude oil markets and shows that the efficiency is related to the length of futures contracts. These findings offer some implicative suggestions and strategies.

Using seventeen years of data from 1991 to 2008, I derive a pricing model for farmland values. This valuation model is the first using agricultural commodity futures as a proxy for “ex ante” income projections for the crops grown or livestock grazed on United States farmland. While not all inclusive, the model is tested regionally including the Corn Belt, Delta States, Lake States, Mountain, Pacific Northwest, Pacific West and Southeast Regions. Additionally, I test whether interest rate futures contracts have a relationship with farmland values as interest rates have been proven to be a reliable predictor in past research. Farmland capitalization rates and anticipated inflation have hypothesized relationships, but are mainly used as control variables in the study. In general, agricultural commodity futures contracts are a poor predictor of changes in farmland market values. When examining relationships with quarterly percentage change regression models of the included variables, I find the Mountain region provides the most reliable pricing model where both live cattle and Minnesota wheat futures contracts has a positive statistically significant relationships with farmland market values. Also, wheat futures prices have a significant relationship with farmland values in the Corn Belt region. Interest rate futures contracts, farmland capitalization rates and anticipated inflation are not statistically significant in the majority of the regions. As a robustness check, I model the price levels of the variables using Johansen’s cointegration procedure. This time-series econometric methodology provides results in regards to long-run equilibrium relationships between the variables. The results are only slightly better. Corn, orange juice and sugar futures contracts have positive statistically significant relationships with farmland market values in multiple regions. Again, wheat has a statistically significant positive relationship with farmland values in the Corn Belt region. The Mountain region and interest rate futures contracts are not applicable for the cointegration tests as they are not integrated to the order of one.

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...

Fung Wing Tsan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 130-133). / Abstract --- p.i / Acknowledgment --- p.iii / Chapter Chapter 1 --- INTRODUCTION --- p.1 / Chapter Chapter 2 --- THE PRICING OF STOCK INDEX FUTURES --- p.9 / Chapter I. --- The Theoretical Framework --- p.9 / Chapter II. --- Evidence from the US Markets --- p.17 / Chapter III. --- Evidence from Other Markets --- p.21 / Chapter Chapter 3 --- THE PRICE DISCOVERY ROLE OF FUTURES MARKET --- p.24 / Chapter I. --- The Potential of Lead/Lag Relationship between the Stock Index Futures Price and the Stock Index --- p.24 / Chapter II. --- Empirical Evidence for the Lead/Lag Relationship --- p.27 / Chapter Chapter 4 --- THE HEDGING FUNCTION OF STOCK INDEX FUTURES MARKET --- p.30 / Chapter I. --- The Traditional Approach --- p.31 / Chapter II. --- Working's Speculative Hedge Approach --- p.32 / Chapter III. --- The Risk-Minimizing Approach --- p.33 / Chapter IV. --- The Portfolio Allocation Approach --- p.40 / Chapter Chapter 5 --- AN INTRODUCTION TO THE HANG SENG INDEX FUTURES MARKET --- p.44 / Chapter Chapter 6 --- PRICING EFFICIENCY OF THE HANG SENG INDEX FUTURES MARKET --- p.51 / Chapter I. --- Pricing Efficiency of the Hang Seng Index Futures Market with no Transaction Costs --- p.51 / Chapter II. --- Pricing Efficiency of the Hang Seng Index Futures Market with Transaction Costs --- p.59 / Chapter III. --- The Pattern of the Mispricing Series --- p.66 / Chapter IV. --- Test of Pricing Efficiency using Intraday Prices --- p.70 / Chapter Chapter 7 --- PRICE DISCOVERY ROLE OF THE HANG SENG INDEX FUTURES MARKET --- p.85 / Chapter I. --- The Granger-Causality Test --- p.86 / Chapter II. --- Error-Correction Model and Long-Run Relationship between the Stock Price and the Hang Seng Index Futures Price --- p.93 / Chapter III. --- The Simultaneous-Equation Error-Correction Model --- p.96 / Chapter Chapter 8 --- HEDGING EFFECTIVENESS OF THE HANG SENG INDEX FUTURES MARKET --- p.104 / Chapter I. --- The Effectiveness of Hang Seng Index Futures in Reducing Risks Of Stock Portfolios --- p.104 / Chapter II. --- The Hedged Portfolio as an Alternative to Fixed-Income Asset --- p.115 / Chapter III. --- The Effectiveness of Hang Seng Index Futures in Improving Risk´ؤReturn 'Trade-Off --- p.119 / Chapter Chapter 9 --- conclusion --- p.126 / References --- p.130

This thesis examines the relationship between spot prices, futures prices, and ending stocks for storable commodities. We used Granger causality and DAGs to determine causal relationships and cointegration tests to determine long-run relationships. We use VAR/VECM and consider innovation accounting techniques to see how volatility in one market affects the price behavior and volatility in the other market. Results suggest that for agricultural commodities, innovations in futures price permanently increase the level of spot prices while accounting for much of spot price variance over time. For national oil, shocks to futures price decrease the level of spot price in the long run. In regional oil markets, there are transitory impulse responses. Futures price plays a small role in the volatility of spot prices for oil over time. Overall results are mixed, with oil suggesting futures markets may have a price stabilizing effect and agriculture commodities indicating spot price destabilization.

Choy Siu Kai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 35-37). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1-2 / Chapter Chapter 2 --- Literature Review --- p.3-9 / Chapter Chapter 3 --- An Overview of Hong Kong Security Market and Data Description --- p.10-18 / Chapter Chapter 4 --- Methodology --- p.19-24 / Chapter Chapter 5 --- Futures and Mini Futures Results --- p.25-28 / Chapter Chapter 6 --- Index and Futures Contracts Results --- p.29-32 / Chapter Chapter 7 --- Conclusion --- p.33-34 / References --- p.35-37 / Appendix --- p.38-40 / Tables --- p.41-52 / Graphs --- p.53-57

<p>Diss. Stockholm : Handelshögskolan, 2007 viii, s. [1]-4: sammanfattning, s. [7]-104: 3 uppsatser</p>

by Lee Yiu Cho. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaf 47). / ACKNOWLEDGMENT --- p.iii / ABSTRACT --- p.iv / TABLE OF CONTENTS --- p.v / LIST OF CHARTS --- p.vi / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Chapter II. --- THE HANG SENG INDEX OPTION --- p.3 / Chapter III. --- LITERATURE REVIEW --- p.6 / Chapter IV. --- METHODOLOGY & DATA COLLECTION --- p.9 / Methodology --- p.9 / The Black-Scholes Model --- p.9 / Data Collection --- p.11 / Data Manipulation --- p.13 / Limitation of Data --- p.14 / Chapter V. --- EMPIRICAL RESULTS --- p.16 / General Trading Pattern --- p.16 / Comparison of Actual and Theoretical Premiums --- p.17 / Analysis for 2 Sub-periods --- p.19 / Correlation Between Deviations and Variables --- p.22 / The Degree of in-the-money or out-of-the-money --- p.22 / Actual Premium Level --- p.23 / Transaction Volume --- p.25 / Chapter VI. --- CONCLUSION --- p.26 / CHARTS --- p.29 / BIBLIOGRAPHY --- p.47

This thesis consists of three distinct parts. Part I introduces the basic concepts and the notion of general quadratic term structures (GQTS) essential in some of the following chapters. Part II focuses on credit risk models and Part III studies forward price term structure models using both the classical and the geometrical approach.  Part I is organized as follows. Chapter 1 is divided in two main sections. The first section presents some of the fundamental concepts which are a pre-requisite to the papers that follow. All of the concepts and results are well known and hence the section can be regarded as an introduction to notation and the basic principles of arbitrage theory. The second part of the chapter is of a more technical nature and its purpose is to summarize some key results on point processes or differential geometry that will be used later in the thesis. For finite dimensional factor models, Chapter 2 studies GQTS. These term structures include, as special cases, the affine term structures and Gaussian quadratic term structures previously studied in the literature. We show, however, that there are other, non-Gaussian, quadratic term structures and derive sufficient conditions for the existence of these GQTS for zero-coupon bond prices. On Part II we focus on credit risk models.   In Chapter 3 we propose a reduced form model for default that allows us to derive closed-form solutions for all the key ingredients in credit risk modeling: risk-free bond prices, defaultable bond prices (with and without stochastic recovery) and survival probabilities. We show that all these quantities can be represented in general exponential quadratic forms, despite the fact that the intensity of default is allowed to jump producing shot-noise effects. In addition, we show how to price defaultable digital puts, CDSs and options on defaultable bonds. Further on, we study a model for portfolio credit risk that considers both firm-specific and systematic risk. The model generalizes the attempt of Duffie and Garleanu (2001). We find that the model produces realistic default correlation and clustering effects. Next, we show how to price CDOs, options on CDOs and how to incorporate the link to currently proposed credit indices. In Chapter 4 we start by presenting a reduced-form multiple default type of model and derive abstract results on the influence of a state variable $X$ on credit spreads when both the intensity and the loss quota distribution are driven by $X$. The aim is to apply the results to a real life situation, namely, to the influence of macroeconomic risks on the term structure of credit spreads. There is increasing support in the empirical literature for the proposition that both the probability of default (PD) and the loss given default (LGD) are correlated and driven by macroeconomic variables. Paradoxically, there has been very little effort, from the theoretical literature, to develop credit risk models that would take this into account. One explanation might be the additional complexity this leads to, even for the ``treatable'' default intensity models. The goal of this paper is to develop the theoretical framework necessary to deal with this situation and, through numerical simulation, understand the impact of macroeconomic factors on the term structure of credit spreads. In the proposed setup, periods of economic depression are both periods of higher default intensity and lower recovery, producing a business cycle effect. Furthermore, we allow for the possibility of an index volatility that depends negatively on the index level and show that, when we include this realistic feature, the impacts on the credit spread term structure are emphasized. Part III studies forward price term structure models. Forward prices differ from futures prices in stochastic interest rate settings and become an interesting object of study in their own right. Forward prices with different maturities are martingales under different forward measures. This mathematical property implies that the term structure of forward prices is always linked to the term structure of bond prices, and this dependence makes forward price term structure models relatively harder to handle. For finite dimensional factor models, Chapter 5 applies the concept of GQTS to the term structure of forward prices. We show how the forward price term structure equation depends on the term structure of bond prices. We then exploit this connection and show that even in quadratic short rate settings we can have affine term structures for forward prices. Finally, we show how the study of futures prices is naturally embedded in the study of forward prices, that the difference between the two term structures may be deterministic in some (non-trivial) stochastic interest rate settings. In Chapter 6 we study a fairly general Wiener driven model for the term structure of forward prices. The model, under a fixed martingale measure, $\Q$, is described by using two infinite dimensional stochastic differential equations (SDEs). The first system is a standard HJM model for (forward) interest rates, driven by a multidimensional Wiener process $W$. The second system is an infinite SDE for the term structure of forward prices on some specified underlying asset driven by the same $W$. Since the zero coupon bond volatilities will enter into the drift part of the SDE for these forward prices, the interest rate system is needed as input to the forward price system. Given this setup, we use the Lie algebra methodology of Bj\o rk et al. to investigate under what conditions, on the volatility structure of the forward prices and/or interest rates, the inherently (doubly) infinite dimensional SDE for forward prices can be realized by a finite dimensional Markovian state space model. / Diss. Stockholm : Handelshögskolan, 2006