This thesis consists of four essays, three in the field of random effects models and one in the field of GARCH. The first essay in this thesis, ''Maximum likelihood based inference in the two-way random effects model with serially correlated time effects'', considers maximum likelihood estimation and inference in the two-way random effects model with serial correlation. We derive a straightforward maximum likelihood estimator when the time-specific component follow an AR(1) or MA(1) process. The estimator is also easily generalized to allow for arbitrary stationary and strictly invertible ARMA processes. In addition we consider the model selection problem and derive tests of the null hypothesis of no serial correlation as well as tests for discriminating between the AR(1) and MA(1) specifications. A Monte-Carlo experiment evaluates the finite-sample properties of the estimators, test-statistics and model selection procedures. The second essay, ''Asymptotic properties of the maximum likelihood estimator of random effects models with serial correlation'', considers the large sample behavior of the maximum likelihood estimator of random effects models with serial correlation in the form of AR(1) for the idiosyncratic or time-specific error component. Consistent estimation and asymptotic normality is established for a comprehensive specification which nests these models as well as all commonly used random effects models. The third essay, ''Specification and estimation of random effects models with serial correlation of general form'', is also concerned with maximum likelihood based inference in random effects models with serial correlation. Allowing for individual effects we introduce serial correlation of general form in the time effects as well as the idiosyncratic errors. A straightforward maximum likelihood estimator is derived and a coherent model selection strategy is suggested for determining the orders of serial correlation as well as the importance of time or individual effects. The methods are applied to the estimation of a production function using a sample of 72 Japanese chemical firms observed during 1968-1987. The fourth essay, entitled ''A simple efficient GMM estimator of GARCH models'', considers efficient GMM based estimation of GARCH models. Sufficient conditions for the estimator to be consistent and asymptotically normal are established for the GARCH(1,1) conditional variance process. In addition efficiency results are obtained for a GARCH(1,1) model where the conditional variance is allowed to enter the mean as well. That is, the GARCH(1,1)-M model. An application to the returns to the SP500 index illustrates. / <p>Diss. Stockholm : Handelshögskolan, 2001</p>

This thesis comprises four papers concerning trade durations and limit order book information. Paper [1], [2] and [4] study trader durations, e.g., the time between stock transactions in intra-day data. Paper [3] focus on the information content in the limit order book concerning future price movements in stock transaction data. Paper [1] considers conditional duration models in which durations are in continuous time but measured in grouped or discretized form. This feature of recorded durations in combination with a frequently traded stock is expected to negatively influence the performance of conventional estimators for intraday duration models. A few estimators that account for the discreteness are discussed and compared in a Monte Carlo experiment. An EM-algorithm accounting for the discrete data performs better than those which do not. Empirically, the incorporation of level variables for past trading is rejected in favour of change variables. This enables an interpretation in terms of news effects. No evidence of asymmetric responses to news about prices and spreads is found. Paper [2] considers an extension of the univariate autoregressive conditional duration model to which durations from a second stock are added. The model is empirically used to study duration dependence in four traded stocks, Nordea, Föreningssparbanken, Handelsbanken and SEB A on the Stockholm Stock Exchange. The stocks are all active in the banking sector. It is found that including durations from a second stock may add explanatory power to the univariate model. We also find that spread changes have significant effect for all series. Paper [3] empirically tests whether an open limit order book contains information about future short-run stock price movements. To account for the discrete nature of price changes, the integer-valued autoregressive model of order one is utilized. A model transformation has an advantage over conventional count data approaches since it handles negative integer-valued price changes. The empirical results reveal that measures capturing offered quantities of a share at the best bid- and ask-price reveal more information about future short-run price movements than measures capturing the quantities offered at prices below and above. Imbalance and changes in offered quantities at prices below and above the best bid- and askprice do, however, have a small and significant effect on future price changes. The results also indicate that the value of order book information is short-term. Paper [4] This paper studies the impact of news announcements on trade durations in stocks on the Stockholm Stock Exchange. The news are categorized into four groups and the impact on the time between transactions is studied. Times before, during and after the news release are considered. Econometrically, the impact is studied within an autoregressive conditional duration model using intradaily data for six stocks. The empirical results reveal that news reduces the duration lengths before, during and after news releases as expected by the theoretical litterature on durations and information flow.

This volume consists of four papers, which in principle could be read in any order. The common denominator is that they deal with contingent claims models of a firm's securities or related derivatives. A Framework for Valuing Corporate Securities Early applications of contingent claims analysis to the pricing of corporate liabilities tend to restrict themselves to situations where debt is perpetual or where financial distress can only occur at debt maturity. This paper relaxes these restrictions and provides an exposition of how most corporate liabilities can be valued as packages of two fundamental barrier contingent claims: a down-and-out call and a binary option. Furthermore, it is shown how the comparative statics of the resulting pricing formulae can be derived.A New Compound Option Pricing ModelThis paper extends the Geske (1979) compound option pricing model to the case where the security on which the option is written is a down-and-out call as opposed to a standard Black and Scholes call. Furthermore, we develop a general and flexible framework for valuing options on more complex packages of contingent claims - any claim that can be valued using the ideas in chapter 1. This allows us to study the interaction between the detailed characteristics of a firm's capital structure and the prices of for example stock options.Implementing Firm Value Based ModelsThis paper evaluates an implementation procedure for contingent claims models suggested by Duan (1994). Duan's idea is to use time series data of traded securities such as shares of common stock in order to estimate the dynamics of the firm's asset value. Furthermore, we provide an argument which allows us to relax the (common) assumption that the firm's assets may be continuously traded. It is sufficient to assume that the firm's assets are traded at one particular point in time.Asset Substitution, Debt Pricing, Optimal Leverage and MaturityChapters 1-3 have focused on the problem of pricing corporate securities.They have thus abstracted strategic aspects of corporate finance theory. This paper is an attempt to combine the contingent claims literature with the non-dynamic corporate finance literature. I allow the management of the firm to alter its investment policy strategically. This yields a model which allows us to examine the relationship between bond prices, agency costs, optimal leverage and maturity. / Diss. Stockholm : Handelshögsk.

When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to visual (V), proprioceptive (P), or visual + proprioceptive (VP) targets under different visual delay conditions (e.g. on V and VP trials, the visual target was available for the entire reach, it was removed with the go-signal or it was removed 1, 2 or 5 seconds before the go-signal). Subjects completed 5 blocks of trials, with 90 trials per block. For 12 subjects, the visual delay was kept consistent within a block of trials, while for the other 12 subjects, different visual delays were intermixed within a block of trials. To establish which sensory cue subjects weighted the most, we compared endpoint positions achieved on V and P reaches to VP reaches. Results indicated that all subjects weighted sensory cues in accordance with the MLE model across all delay conditions and that these weights were similar regardless of the visual delay. Moreover, while errors increased with longer visual delays, there was no change in reaching variance. Thus, manipulating the visual environment was not enough to change subjects’ weighting strategy, further i

In wireless communications, channel estimation is necessary for coherent symbol detection. This thesis considers a network which consists of two transceivers communicating with the help of a relay applying the amplify-and-forward (AF) relaying scheme. The training based channel estimation technique is applied to the proposed network where the numbers of the training sequence transmitted by the two transceivers, are different. All three terminals are equipped with a single antenna for signal transmission and reception. Communication between the transceivers is carried out in two phases. In the first phase, each transceiver sends a transmission block of data embedded with known training symbols to the relay. In the second phase, the relay retransmits an amplified version of the received signal to both transceivers. Estimates of the channel coefficients are obtained using the Maximum Likelihood (ML) estimator. The performance analysis of the derived estimates are carried out in terms of the mean squared error (MSE) and we determine conditions required to increase the estimation accuracy. / UOIT

We study here a model for a strand passage in a ring polymer about a randomly chosen location at which two strands of the polymer have been brought gcloseh together. The model is based on ¦-SAPs, which are unknotted self-avoiding polygons in Z^3 that contain a fixed structure ¦ that forces two segments of the polygon to be close together. To study this model, the Composite Markov Chain Monte Carlo (CMCMC) algorithm, referred to as the CMC ¦-BFACF algorithm, that I developed and proved to be ergodic for unknotted ¦-SAPs in my M. Sc. Thesis, is used. Ten simulations (each consisting of 9.6~10^10 time steps) of the CMC ¦-BFACF algorithm are performed and the results from a statistical analysis of the simulated data are presented. To this end, a new maximum likelihood method, based on previous work of Berretti and Sokal, is developed for obtaining maximum likelihood estimates of the growth constants and critical exponents associated respectively with the numbers of unknotted (2n)-edge ¦-SAPs, unknotted (2n)-edge successful-strand-passage ¦-SAPs, unknotted (2n)-edge failed-strand-passage ¦-SAPs, and (2n)-edge after-strand-passage-knot-type-K unknotted successful-strand-passage ¦-SAPs. The maximum likelihood estimates are consistent with the result (proved here) that the growth constants are all equal, and provide evidence that the associated critical exponents are all equal.<p> We then investigate the question gGiven that a successful local strand passage occurs at a random location in a (2n)-edge knot-type K ¦-SAP, with what probability will the ¦-SAP have knot-type Kf after the strand passage?h. To this end, the CMCMC data is used to obtain estimates for the probability of knotting given a (2n)-edge successful-strand-passage ¦-SAP and the probability of an after-strand-passage polygon having knot-type K given a (2n)-edge successful-strand-passage ¦-SAP. The computed estimates numerically support the unproven conjecture that these probabilities, in the n¨ limit, go to a value lying strictly between 0 and 1. We further prove here that the rate of approach to each of these limits (should the limits exist) is less than exponential.<p> We conclude with a study of whether or not there is a difference in the gsizeh of an unknotted successful-strand-passage ¦-SAP whose after-strand-passage knot-type is K when compared to the gsizeh of a ¦-SAP whose knot-type does not change after strand passage. The two measures of gsizeh used are the expected lengths of, and the expected mean-square radius of gyration of, subsets of ¦-SAPs. How these two measures of gsizeh behave as a function of a polygonfs length and its after-strand-passage knot-type is investigated.

Wireless communication systems such as multipoint communication systems (MCS) are becoming attractive as cost-effective means for providing network access in sparsely populated, rugged, or developing areas of the world. Since the radio spectrum is limited, it is desirable to use spectrally efficient modulation methods such as quadrature amplitude modulation (QAM) for high data rate channels. Many MCS employ time division multiple access (TDMA) and/or time division duplexing (TDD) techniques, in which transmissions operate in bursts. In many cases, a preamble of known symbols is appended to the beginning of each burst for carrier and symbol timing recovery (symbol timing is assumed known in this thesis). Preamble symbols consume bandwidth and power and are not used to convey information. In order for burst-mode communications to provide efficient data throughput, the synchronization time must be short compared to the user data portion of the burst. <p> Traditional methods of communication system synchronization such as phase-locked loops (PLLs) have demonstrated reduced performance when operated in burst-mode systems. In this thesis, a feedforward (FF) digital carrier recovery technique to achieve rapid carrier synchronization is proposed. The estimation algorithms for determining carrier offsets in carrier acquisition and tracking in a linear channel environment corrupted by additive white Gaussian noise (AWGN) are described. The estimation algorithms are derived based on the theory of maximum likelihood (ML) parameter estimation. The estimations include data-aided (DA) carrier frequency and phase estimations in acquisition and non-data-aided (NDA) carrier phase estimation in tracking. The DA carrier frequency and phase estimation algorithms are based on oversampling of a known preamble. The NDA carrier phase estimation makes use of symbol timing knowledge and estimates are extracted from the random data portion of the burst. The algorithms have been simulated and tested using Matlab® to verify their functionalities. The performance of these estimators is also evaluated in the burst-mode operations for 16-QAM and compared in the presence of non-ideal conditions (frequency offset, phase offset, and AWGN). The simulation results show that the carrier recovery techniques presented in this thesis proved to be applicable to the modulation schemes of 16-QAM. The simulations demonstrate that the techniques provide a fast carrier acquisition using a short preamble (about 111 symbols) and are suitable for burst-mode communication systems.

Climate factors like precipitation and temperature, being closely intertwined with agriculture, make a changing climate a big concern for the entire human race and its basic survival. Adaptation to climate is a long-running characteristic of agriculture evidenced by the varying types and forms of agricultural enterprises associated with differing climatic conditions. Nevertheless climate change poses a substantial, additional adaptation challenge for agriculture. Mitigation encompasses efforts to reduce the current and future extent of climate change. Biofuels production, for instance, expands agriculture’s role in climate change mitigation. This dissertation encompasses adaptation and mitigation strategies as a response to climate change in the U.S. by examining comprehensively scientific findings on agricultural adaptation to climate change; developing information on the costs and benefits of select adaptations to examine what adaptations are most desirable, for which society can further devote its resources; and studying how ethanol prices are interrelated across, and transmitted within the U.S., and the markets that play an important role in these dynamics. Quantitative analysis using the Forestry and Agricultural Sector Optimization Model (FASOM) shows adaptation to be highly beneficial to agriculture. On-farm varietal and other adaptations contributions outweigh a mix shift northwards significantly, implying progressive technical change and significant returns to adaptation research and investment focused on farm management and varietal adaptations could be quite beneficial over time. Northward shift of corn-acre weighted centroids observed indicates that substantial production potential may shift across regions with the possibility of less production in the South, and more in the North, and thereby, potential redistribution of income. Time series techniques employed to study ethanol price dynamics show that the markets studied are co-integrated and strongly related, with the observable high levels of interaction between all nine cities. Information is transmitted rapidly between these markets. Price seems to be discovered (where shocks originate from) in regions of high demand and perhaps shortages, like Los Angeles and Chicago (metropolitan population centers). The Maximum Likelihood approach following Spiller and Huang’s model however shows cities may not belong to the same economic market and the possibility of arbitrage does not exist between all markets.

Due to lack of soil sampling during a conventional cone penetration testing (CPT), it is necessary to classify soils based on recorded tip and sleeve friction and pore pressure (if available) values. However, currently available soil classification models are based on deterministic and judgemental determination of soil classification boundaries which do not address the uncertainties intristic to the problem. Moreover, size and quality of databases used in the development of these soil classification models are undocumented and thus questionable. Similar limitations do also exist in the development of SPT-CPT correlations which are widely used in SPT dominated design such as soil liquefaction triggering. To eliminate these discussed limitations, within the confines of this study it is attempted to present (1) a new probabilistic CPT- based soil classification methodology, and (2) new SPT-CPT correlations which address the uncertainties intrinsic to the problems. For these purposes, a database composed of 400 CPT/SPT boring data pairs was compiled. It is intended to develop probabilistic models, which will correlate CPT tip and sleeve friction values to actual soil classification and CPT tip resistance to SPT blow count N. The new set of correlations, model parameters of which estimated by implementing maximum likelihood methodology, presented herein are judged to represent a robust and defensible basis for (1) prediction of soil type based on CPT data and, (2) estimation of SPT-N value for given CPT data.

Wireless communication systems such as multipoint communication systems (MCS) are becoming attractive as cost-effective means for providing network access in sparsely populated, rugged, or developing areas of the world. Since the radio spectrum is limited, it is desirable to use spectrally efficient modulation methods such as quadrature amplitude modulation (QAM) for high data rate channels. Many MCS employ time division multiple access (TDMA) and/or time division duplexing (TDD) techniques, in which transmissions operate in bursts. In many cases, a preamble of known symbols is appended to the beginning of each burst for carrier and symbol timing recovery (symbol timing is assumed known in this thesis). Preamble symbols consume bandwidth and power and are not used to convey information. In order for burst-mode communications to provide efficient data throughput, the synchronization time must be short compared to the user data portion of the burst. <p> Traditional methods of communication system synchronization such as phase-locked loops (PLLs) have demonstrated reduced performance when operated in burst-mode systems. In this thesis, a feedforward (FF) digital carrier recovery technique to achieve rapid carrier synchronization is proposed. The estimation algorithms for determining carrier offsets in carrier acquisition and tracking in a linear channel environment corrupted by additive white Gaussian noise (AWGN) are described. The estimation algorithms are derived based on the theory of maximum likelihood (ML) parameter estimation. The estimations include data-aided (DA) carrier frequency and phase estimations in acquisition and non-data-aided (NDA) carrier phase estimation in tracking. The DA carrier frequency and phase estimation algorithms are based on oversampling of a known preamble. The NDA carrier phase estimation makes use of symbol timing knowledge and estimates are extracted from the random data portion of the burst. The algorithms have been simulated and tested using Matlab® to verify their functionalities. The performance of these estimators is also evaluated in the burst-mode operations for 16-QAM and compared in the presence of non-ideal conditions (frequency offset, phase offset, and AWGN). The simulation results show that the carrier recovery techniques presented in this thesis proved to be applicable to the modulation schemes of 16-QAM. The simulations demonstrate that the techniques provide a fast carrier acquisition using a short preamble (about 111 symbols) and are suitable for burst-mode communication systems.