Duration models and value at risk using high-frequency data for the peruvian stock market
Most empirical studies in nance use data on a daily basis which is obtained by retaining the last observation of the day and ignoring all intraday records. However, as a result of the increased automatization of nancial markets and the evolution of computational trading systems, intraday data b...
| Autor Principal: | Téllez De Vettori, Giannio |
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| Otros Autores: | Najarro Chuchón, Ricardo |
| Formato: | Tesis de Maestría |
| Idioma: | Inglés |
| Publicado: |
Pontificia Universidad Católica del Perú
2017
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| Materias: | |
| Acceso en línea: |
http://tesis.pucp.edu.pe/repositorio/handle/123456789/7890 |
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| Sumario: |
Most empirical studies in nance use data on a daily basis which is obtained by retaining
the last observation of the day and ignoring all intraday records. However, as a result of
the increased automatization of nancial markets and the evolution of computational trading
systems, intraday data bases that record every transaction along with their characteristics have
been stablished. These data sets prompted the development of a new area of research ( nance
with high frequency data), and in 1980 a literature based on the mechanisms of trading began
(forms of trading, rules on securities trading, market structure, etc.), originating the Theory
of Market Microstructure for the valuation of nancial assets, whose models advocate that
timing transmits information. Then the literature proposed an extension to risk management
by calculating the implied volatility, which is estimated by the realized volatility on an intraday
level, and its applications for a ner value at risk (VaR). |
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