Study programme competencies |
Code
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Study programme competences / results
|
A1 |
Alcanzar un conocimiento básico en un área de Ingeniería/Ciencias Aplicadas, como punto de partida para un adecuado modelado matemático, tanto en contextos bien establecidos como en entornos nuevos o poco conocidos dentro de contextos más amplios y multidisciplinares. |
A2 |
Modelar ingredientes específicos y realizar las simplificaciones adecuadas en el modelo que faciliten su tratamiento numérico, manteniendo el grado de precisión, de acuerdo con requisitos previamente establecidos. |
A3 |
Determinar si un modelo de un proceso está bien planteado matemáticamente y bien formulado desde el punto de vista físico. |
A4 |
Ser capaz de seleccionar un conjunto de técnicas numéricas, lenguajes y herramientas informáticas, adecuadas para resolver un modelo matemático. |
A5 |
Ser capaz de validar e interpretar los resultados obtenidos, comparando con visualizaciones, medidas experimentales y/o requisitos funcionales del correspondiente sistema físico/de ingeniería. |
A6 |
Ser capaz de extraer, empleando diferentes técnicas analíticas, información tanto cualitativa como cuantitativa de los modelos. |
A7 |
Saber modelar elementos y sistemas complejos o en campos poco establecidos, que conduzcan a problemas bien planteados/formulados. |
A8 |
Saber adaptar, modificar e implementar herramientas de software de simulación numérica. |
B1 |
Saber aplicar los conocimientos adquiridos y su capacidad de resolución de problemas en entornos nuevos o poco conocidos dentro de contextos más amplios, incluyendo la capacidad de integrarse en equipos multidisciplinares de I+D+i en el entorno empresarial. |
B2 |
Poseer conocimientos que aporten una base u oportunidad de ser originales en el desarrollo y/o aplicación de ideas, a menudo en un contexto de investigación, sabiendo traducir necesidades industriales en términos de proyectos de I+D+i en el campo de la Matemática Industrial |
B3 |
Ser capaz de integrar conocimientos para enfrentarse a la formulación de juicios a partir de información que, aun siendo incompleta o limitada, incluya reflexiones sobre las responsabilidades sociales y éticas vinculadas a la aplicación de sus conocimientos. |
B4 |
Saber comunicar las conclusiones, junto con los conocimientos y razones últimas que las sustentan, a públicos especializados y no especializados de un modo claro y sin ambigüedades. |
B5 |
Poseer las habilidades de aprendizaje que les permitan continuar estudiando de un modo que habrá de ser en gran medida autodirigido o autónomo, y poder emprender con éxito estudios de doctorado. |
Learning aims |
Learning outcomes |
Study programme competences / results |
Knowledge of the management of the most popular financial products, specially options and bonds |
AC1 AC2 AC5 AC6 AC7
|
BJ1 BC3 BR1
|
|
Knowledge and application of the usual techniques of stochastic calculus to solve the pricing problems |
AC2 AC6 AC7
|
BJ1 BR1
|
|
Knowledge of the dynamic hedging methodology to pose Black-Scholes mathematical models |
AC2 AC3 AC7
|
BJ1 BC1 BR1
|
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For a given financial derivative, ability to pose the most suitable Black-Scholes pricing model |
AC1 AC2 AC4 AC7
|
BC1 BC2 BC3 BR1
|
|
Knowledge of the most suitable numerical methods to solve the Balck-Scholes models for the different financial products, either with one or two stochastic factors. |
AC4 AC5 AC8
|
BC1 BC2 BC3 BR1
|
|
Knowledge about models of financial risk and the associated computations |
AC1 AC2 AC5 AC6 AC7
|
BJ1 BC1 BC2 BC3 BR1
|
|
Contents |
Topic |
Sub-topic |
1. Financial markets and financial derivatives |
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2. Discounted value of riskless financial products |
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3. Pricing models for risky assets |
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4. Dynamic hedging methodologies and Black Scholes models |
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5. Black-Scholes models for options and bonds with one stochastic factor |
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6. Black-Scholes models for options and bonds with two stochastic factors |
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Calculo de riscos financeiros: risco de valoración e de contraparte: Definicións, metodoloxía e uso. |
|
Planning |
Methodologies / tests |
Competencies / Results |
Teaching hours (in-person & virtual) |
Student’s personal work hours |
Total hours |
Problem solving |
A2 A3 A4 A5 A6 A7 B5 B3 B1 |
0 |
60 |
60 |
Problem solving |
A2 A3 A4 A5 A6 A7 B5 B3 B1 |
0 |
36 |
36 |
Objective test |
A2 A3 A6 A7 B5 |
4 |
0 |
4 |
Guest lecture / keynote speech |
A1 A2 A3 A4 A5 A6 A7 A8 B2 B5 B3 B1 B4 |
42 |
0 |
42 |
|
Personalized attention |
|
8 |
0 |
8 |
|
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies |
Methodologies |
Description |
Problem solving |
A set of problems is delivered to the student, some of them shorter to understand and practice concepts and technique, others are more complex. |
Problem solving |
- In the .pdf documents exhibited during lectures the are some easy exercises to review and apply the explained concepts
- Moreover, some bibliographic references are indicated that contain exercises related to the developed subject |
Objective test |
Several problems are posed to be solved by the student who can use the slides containing the explanations in the lectures |
Guest lecture / keynote speech |
- Previously to lecture sessions, a .pdf document with the slides to use in the lecture is delivered to students
- Table PC and videoconference facilities will be used so that lectures can be followed by the students from the different campus
- Paricipation of students with quetions and comments will be encouraged. Questions will be solved and comments will be illustrated by means of Windows Journal computer application |
Personalized attention |
Methodologies
|
Problem solving |
|
Description |
Those problems solved by each student making part of the qualifications will be assessed |
|
Assessment |
Methodologies
|
Competencies / Results |
Description
|
Qualification
|
Objective test |
A2 A3 A6 A7 B5 |
A written exam of practical applications of the lectured contents will take place in a fixed date. In case of failing, a recovery exam will take place in a later fixed date |
50 |
Problem solving |
A2 A3 A4 A5 A6 A7 B5 B3 B1 |
A set of exercises proposed to be solved outside classroom timetable will be evaluated |
50 |
|
Assessment comments |
|
Sources of information |
Basic
|
C. Vázquez (2010). An introduction to Black-Scholes modeling and numerical methods in derivatives pricing. MAT Serie A
D. Brigo, M. Morini, A.Pallavicini (2013). Counterparty credit risk, collateral and funding. Wiley Financial Series
J. Gregory (2010). Counterparty credit risk: the new challenge for global financial markets. Wiley Financial Series
T.Mikosch (1998). Elementary Stochastic Calculus with Finance in View. World Scientific, (Singapur)
P.G.Zhang (1998). Exotic Options, A guide to second generation option. World Scientific (Singapur)
K.Dowd (2005). Measuring market risk. Wiley Financial Series
P.Wilmott, S.Howison, J.Dewynne (1996). Option Pricing: Mathematical Models and Computation. Oxford Financial Press
J.C.Hull (2000). Options, Futures and Other Derivatives. Prentice-Hall Inc., (New Jersey)
A. Pascucci (2011). PDE and martingale methods in option pricing. Bocconi University Press, Springer
P.Wilmott, S.Howison, J.Dewynne (1996). The mathematics of Financial Derivatives, A Student Introduction. Cambridge University Press
R.Seydel (2007). Tools for Computational Finance. Universiteitext, Springer-Verlag |
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Complementary
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Recommendations |
Subjects that it is recommended to have taken before |
Stochastic numerical methods/614855226 |
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Subjects that are recommended to be taken simultaneously |
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Subjects that continue the syllabus |
Professional software in finance/614855218 |
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