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We develop a dynamic trading strategy in the Linear Quadratic Regulator (LQR) framework. By including a price mean-reversion signal into the optimization program, in a trading environment where market impact is linear and stage costs are quadratic, we obtain an optimal trading curve that reacts...
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Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear-quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...
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The linear-quadratic (LQ) optimization is a close to standard technique in the optimal control framework. LQ is very well researched and there are many extensions for more sophisticated scenarios like nonlinear models. Usually, the quadratic objective function is taken as a prerequisite for...
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Chapter 1. Multi-horizon MPC and Its Application to theIntegrated Power and Thermal Management ofElectrified Vehicles (Qiuhao Hu) -- Chapter 2. Data/Moment-Driven Approaches for FastPredictive Control of Collective Dynamics (Giacomo Albi) -- Chapter 3. Finite-Dimensional Receding Horizon...
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