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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 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). / Tesis

Identiferoai:union.ndltd.org:PUCP/oai:tesis.pucp.edu.pe:123456789/7890
Date20 February 2017
CreatorsTéllez De Vettori, Giannio, Najarro Chuchón, Ricardo
ContributorsRodríguez, Gabriel
PublisherPontificia Universidad Católica del Perú
Source SetsPontificia Universidad Católica del Perú
LanguageEnglish
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Formatapplication/pdf
SourcePontificia Universidad Católica del Perú, Repositorio de Tesis - PUCP
Rightsinfo:eu-repo/semantics/openAccess, Atribución-NoComercial-SinDerivadas 2.5 Perú, http://creativecommons.org/licenses/by-nc-nd/2.5/pe/

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