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- Creators: Si, Jennie
Description
One necessary condition for the two-pass risk premium estimator to be consistent and asymptotically normal is that the rank of the beta matrix in a proposed linear asset pricing model is full column. I first investigate the asymptotic properties of the risk premium estimators and the related t-test and Wald test statistics when the full rank condition fails. I show that the beta risk of useless factors or multiple proxy factors for a true factor are priced more often than they should be at the nominal size in the asset pricing models omitting some true factors. While under the null hypothesis that the risk premiums of the true factors are equal to zero, the beta risk of the true factors are priced less often than the nominal size. The simulation results are consistent with the theoretical findings. Hence, the factor selection in a proposed factor model should not be made solely based on their estimated risk premiums. In response to this problem, I propose an alternative estimation of the underlying factor structure. Specifically, I propose to use the linear combination of factors weighted by the eigenvectors of the inner product of estimated beta matrix. I further propose a new method to estimate the rank of the beta matrix in a factor model. For this method, the idiosyncratic components of asset returns are allowed to be correlated both over different cross-sectional units and over different time periods. The estimator I propose is easy to use because it is computed with the eigenvalues of the inner product of an estimated beta matrix. Simulation results show that the proposed method works well even in small samples. The analysis of US individual stock returns suggests that there are six common risk factors in US individual stock returns among the thirteen factor candidates used. The analysis of portfolio returns reveals that the estimated number of common factors changes depending on how the portfolios are constructed. The number of risk sources found from the analysis of portfolio returns is generally smaller than the number found in individual stock returns.
ContributorsWang, Na (Author) / Ahn, Seung C. (Thesis advisor) / Kallberg, Jarl G. (Committee member) / Liu, Crocker H. (Committee member) / Arizona State University (Publisher)
Created2011
Description
This report provides an overview of scramjet-powered hypersonic vehicle modeling and control challenges. Such vehicles are characterized by unstable non-minimum phase dynamics with significant coupling and low thrust margins. Recent trends in hypersonic vehicle research are summarized. To illustrate control relevant design issues and tradeoffs, a generic nonlinear 3DOF longitudinal dynamics model capturing aero-elastic-propulsive interactions for wedge-shaped vehicle is used. Limitations of the model are discussed and numerous modifications have been made to address control relevant needs. Two different baseline configurations are examined over a two-stage to orbit ascent trajectory. The report highlights how vehicle level-flight static (trim) and dynamic properties change over the trajectory. Thermal choking constraints are imposed on control system design as a direct consequence of having a finite FER margin. The implication of this state-dependent nonlinear FER margin constraint, the right half plane (RHP) zero, and lightly damped flexible modes, on control system bandwidth (BW) and FPA tracking has been discussed. A control methodology has been proposed that addresses the above dynamics while providing some robustness to modeling uncertainty. Vehicle closure (the ability to fly a trajectory segment subject to constraints) is provided through a proposed vehicle design methodology. The design method attempts to use open loop metrics whenever possible to design the vehicle. The design method is applied to a vehicle/control law closed loop nonlinear simulation for validation. The 3DOF longitudinal modeling results are validated against a newly released NASA 6DOF code.
ContributorsDickeson, Jeffrey James (Author) / Rodriguez, Armando A (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Si, Jennie (Committee member) / Wells, Valana (Committee member) / Kawski, Mattias (Committee member) / Arizona State University (Publisher)
Created2012
Description
A systematic top down approach to minimize risk and maximize the profits of an investment over a given period of time is proposed. Macroeconomic factors such as Gross Domestic Product (GDP), Consumer Price Index (CPI), Outstanding Consumer Credit, Industrial Production Index, Money Supply (MS), Unemployment Rate, and Ten-Year Treasury are used to predict/estimate asset (sector ETF`s) returns. Fundamental ratios of individual stocks are used to predict the stock returns. An a priori known cash-flow sequence is assumed available for investment. Given the importance of sector performance on stock performance, sector based Exchange Traded Funds (ETFs) for the S&P; and Dow Jones are considered and wealth is allocated. Mean variance optimization with risk and return constraints are used to distribute the wealth in individual sectors among the selected stocks. The results presented should be viewed as providing an outer control/decision loop generating sector target allocations that will ultimately drive an inner control/decision loop focusing on stock selection. Receding horizon control (RHC) ideas are exploited to pose and solve two relevant constrained optimization problems. First, the classic problem of wealth maximization subject to risk constraints (as measured by a metric on the covariance matrices) is considered. Special consideration is given to an optimization problem that attempts to minimize the peak risk over the prediction horizon, while trying to track a wealth objective. It is concluded that this approach may be particularly beneficial during downturns - appreciably limiting downside during downturns while providing most of the upside during upturns. Investment in stocks during upturns and in sector ETF`s during downturns is profitable.
ContributorsChitturi, Divakar (Author) / Rodriguez, Armando (Thesis advisor) / Tsakalis, Konstantinos S (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2010
Description
This thesis addresses the design and control of three phase inverters. Such inverters are
used to produce three-phase sinusoidal voltages and currents from a DC source. They
are critical for injecting power from renewable energy sources into the grid. This is
especially true since many of these sources of energy are DC sources (e.g. solar
photovoltaic) or need to be stored in DC batteries because they are intermittent (e.g. wind
and solar). Two classes of inverters are examined in this thesis. A control-centric design
procedure is presented for each class. The first class of inverters is simple in that they
consist of three decoupled subsystems. Such inverters are characterized by no mutual
inductance between the three phases. As such, no multivariable coupling is present and
decentralized single-input single-output (SISO) control theory suffices to generate
acceptable control designs. For this class of inverters several families of controllers are
addressed in order to examine command following as well as input disturbance and noise
attenuation specifications. The goal here is to illuminate fundamental tradeoffs. Such
tradeoffs include an improvement in the in-band command following and output
disturbance attenuation versus a deterioration in out-of-band noise attenuation.
A fundamental deficiency associated with such inverters is their large size. This can be
remedied by designing a smaller core. This naturally leads to the second class of inverters
considered in this work. These inverters are characterized by significant mutual
inductances and multivariable coupling. As such, SISO control theory is generally not
adequate and multiple-input multiple-output (MIMO) theory becomes essential for
controlling these inverters.
used to produce three-phase sinusoidal voltages and currents from a DC source. They
are critical for injecting power from renewable energy sources into the grid. This is
especially true since many of these sources of energy are DC sources (e.g. solar
photovoltaic) or need to be stored in DC batteries because they are intermittent (e.g. wind
and solar). Two classes of inverters are examined in this thesis. A control-centric design
procedure is presented for each class. The first class of inverters is simple in that they
consist of three decoupled subsystems. Such inverters are characterized by no mutual
inductance between the three phases. As such, no multivariable coupling is present and
decentralized single-input single-output (SISO) control theory suffices to generate
acceptable control designs. For this class of inverters several families of controllers are
addressed in order to examine command following as well as input disturbance and noise
attenuation specifications. The goal here is to illuminate fundamental tradeoffs. Such
tradeoffs include an improvement in the in-band command following and output
disturbance attenuation versus a deterioration in out-of-band noise attenuation.
A fundamental deficiency associated with such inverters is their large size. This can be
remedied by designing a smaller core. This naturally leads to the second class of inverters
considered in this work. These inverters are characterized by significant mutual
inductances and multivariable coupling. As such, SISO control theory is generally not
adequate and multiple-input multiple-output (MIMO) theory becomes essential for
controlling these inverters.
ContributorsSarkar, Aratrik (Author) / Rodriguez, Armando A. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2015