This thesis performs portfolio optimization using three allocation methods, Certainty Equivalence Tangency (CET), Global Minimum Variance (GMV) and Minimum Conditional Value-at-Risk (MinCVaR). We estimate expected returns and covariance matrices based on 7 stock market indices with a DCC-GARCH model including an ARMA (1.1) process and an external regressor of an implied volatility index (VIX). We then simulate returns using a rolling window of 500 daily observations and construct portfolios based on the allocation methods. The results suggest that the model can sufficiently estimate expected returns and covariance matrices and we can outperform benchmarks in form of equally weighted and historical portfolios in terms of higher returns and lower risk. Over the whole out-of-sample period the CET portfolio yields the highest mean returns and GMV and MinCVaR can significantly lower the variance. The inclusion of VIX has marginal effects on the forecasting accuracy and it seems to impair the estimation of risk.

<p>Networked embedded control systems are present almost everywhere. A recent trend is to introduce wireless sensor networks in these systems, to take advantage of the added mobility and flexibility offered by wireless solutions. In such networks, the sensor observations are typically quantized and transmitted over noisy links. Concerning the problem of closed-loop control over such non-ideal communication channels, relatively few works have appeared so far. This thesis contributes to this field, by studying some fundamentally important problems in the design of joint source--channel coding and optimal control.</p><p>The main part of the thesis is devoted to joint design of the coding and control for scalar linear plants, whose state feedbacks are transmitted over binary symmetric channels. The performance is measured by a finite-horizon linear quadratic cost function. The certainty equivalence property of the studied systems is utilized, since it simplifies the overall design by separating the estimation and the control problems. An iterative optimization algorithm for training the encoder--decoder pairs, taking channel errors into account in the quantizer design, is proposed. Monte Carlo simulations demonstrate promising improvements in performance compared to traditional approaches.</p><p>Event-triggered control strategies are a promising solution to the problem of efficient utilization of communication resources. The basic idea is to let each control loop communicate only when necessary. Event-triggered and quantized control are combined for plants affected by rarely occurring disturbances. Numerical experiments show that it is possible to achieve good control performance with limited control actuation and sensor communication.</p>

Networked embedded control systems are present almost everywhere. A recent trend is to introduce wireless sensor networks in these systems, to take advantage of the added mobility and flexibility offered by wireless solutions. In such networks, the sensor observations are typically quantized and transmitted over noisy links. Concerning the problem of closed-loop control over such non-ideal communication channels, relatively few works have appeared so far. This thesis contributes to this field, by studying some fundamentally important problems in the design of joint source--channel coding and optimal control. The main part of the thesis is devoted to joint design of the coding and control for scalar linear plants, whose state feedbacks are transmitted over binary symmetric channels. The performance is measured by a finite-horizon linear quadratic cost function. The certainty equivalence property of the studied systems is utilized, since it simplifies the overall design by separating the estimation and the control problems. An iterative optimization algorithm for training the encoder--decoder pairs, taking channel errors into account in the quantizer design, is proposed. Monte Carlo simulations demonstrate promising improvements in performance compared to traditional approaches. Event-triggered control strategies are a promising solution to the problem of efficient utilization of communication resources. The basic idea is to let each control loop communicate only when necessary. Event-triggered and quantized control are combined for plants affected by rarely occurring disturbances. Numerical experiments show that it is possible to achieve good control performance with limited control actuation and sensor communication. / QC 20101109