Modules running in the period selected: 5.
Click on the module to see the timetable and course details.
Course | Name | Total credits | Online | Teacher credits | Modules offered by this teacher |
---|---|---|---|---|---|
Master’s degree in Banking and Finance | Mathematical finance (2015/2016) | 9 | 9 | ||
Master’s degree in Banking and Finance | Mathematical finance (2014/2015) | 9 | 9 | ||
Master’s degree in Banking and Finance | Mathematical finance (2013/2014) | 9 | 9 | ||
Master’s degree in Banking and Finance | Mathematical finance (2012/2013) | 9 | 9 | ||
Bachelor's degree in Applied Mathematics | Financial Market Mathematics (2011/2012) | 12 | 3 | (Parte 2) |
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MyUnivrDi seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:
Topic | Description | Research area |
---|---|---|
MSC 49J20 - Optimal control problems involving partial differential equations | Optimal control problems involving partial differential equations |
Quantitative Methods for Economics
Existence theories |
MSC 49K20 - Problems involving partial differential equations | Problems involving partial differential equations |
Quantitative Methods for Economics
Optimality conditions |
MSC 49L20 - Dynamic programming method | An optimal control problem is defined starting from a dynamics, a set of controls acting on this dynamics and a cost (or gain), functional of the control and the associated dynamics. The objective is to minimize (or maximize) this cost (or gain). The value function (function of the initial time and position) is defined as the optimal value, i.e. the minimum (or maximum) value of the cost (or gain), associated to the problem. I study optimal control problems for which the dynamics is given by a stochastic differential equation. By the dynamic programming approach the value function can be characterized as the solution (in the weak viscosity sense) of a partial differential equation called the Hamilton-Jacobi-Bellman equation. |
Quantitative Methods for Economics
Hamilton-Jacobi theories, including dynamic programming |
MSC 49Lxx - Hamilton-Jacobi theories, including dynamic programming | Hamilton-Jacobi theories, including dynamic programming |
Quantitative Methods for Economics
Hamilton-Jacobi theories, including dynamic programming |
MSC 62F03 - Hypothesis testing | ... |
Quantitative Methods for Economics
Parametric inference |
MSC 62F40 - Bootstrap, jackknife and other resampling methods | .. |
Quantitative Methods for Economics
Parametric inference |
MSC 62G10 - Hypothesis testing | .. |
Quantitative Methods for Economics
Nonparametric inference |
MSC 62G15 - Tolerance and confidence regions | ... |
Quantitative Methods for Economics
Nonparametric inference |
MSC 65C30 - Stochastic differential and integral equations | Stochastic differential and integral equations |
Quantitative Methods for Economics
Probabilistic methods, simulation and stochastic differential equations |
MSC 65D07 - Splines | .... |
Quantitative Methods for Economics
Numerical approximation and computational geometr |
MSC 65J22 - Inverse problems | ... |
Quantitative Methods for Economics
Numerical analysis in abstract spaces |
MSC 65M80 - Fundamental solutions, Green's function methods, etc. | ... |
Quantitative Methods for Economics
Partial differential equations, initial value and time-dependent initial- boundary value problems |
MSC 90B18 - Communication networks | Communication networks |
Quantitative Methods for Economics
Operations research and management science |
MSC 91G10 - Portfolio theory | Portfolio theory |
Quantitative Finance
Mathematical finance |
MSC 91G20 - Derivative securities | Derivative securities |
Quantitative Finance
Mathematical finance |
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