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Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2021
License: CC BY NC ND
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Recolector de Ciencia Abierta, RECOLECTA
Bachelor thesis . 2021
License: CC BY NC ND
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
UCrea
Bachelor thesis . 2021
License: CC BY NC ND
Data sources: UCrea
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El filtro de Kalman con aplicaciones en inversiones

The Kalman filter with investment applications
Authors: Cobo Carrilo, Marcos;

El filtro de Kalman con aplicaciones en inversiones

Abstract

RESUMEN: El filtro de Kalman es un algoritmo recursivo desarrollado por Rudolf E. Kalman en 1960 que sirve para poder identificar el estado de un sistema dinámico lineal discreto, en presencia de ruido aleatorio. Fue un componente fundamental del sistema de guiado y estabilización del módulo incluido en el Apolo XI (primera nave tripulada en llegar a la Luna en 1969) y desde entonces, su interés y rango de aplicaciones se ha extendido a muchos otros campos. En este TFG deduciremos rigurosamente las ecuaciones que modelan el filtro de Kalman para, posteriormente, diseñar nuestro propio filtro de Kalman atendiendo al objetivo de filtrar y predecir los movimientos de un activo financiero, más en concreto, pares de divisas dentro del mercado FOREX. Desarrollaremos una estrategia fundamentada en el filtro de Kalman y comprobaremos los rendimientos obtenidos de operar con ella en distintos pares de divisas a lo largo de los últimos dos años. Finalmente, extraeremos algunas conclusiones del potencial que posee el filtro de Kalman dentro del campo de la economía, y en concreto, dentro del mundo de las inversiones.

ABSTRACT: The Kalman filter is a recursive algorithm developed by Rudolf E. Kalman in 1960 to identify the state of a discrete linear dynamic system in the presence of random noise. It was a fundamental component of the guidance and stabilisation system of the Apollo XI lander (the first manned spacecraft to reach the Moon in 1969) and since then, its interest and range of applications has been extended to many other fields. In this project we will rigorously derive the equations that model the Kalman filter to, subsequently, design our own Kalman filter with the objective of filtering and predicting the movements of a financial asset, more specifically, currency pairs within the FOREX market. We will develop a strategy based on the Kalman filter and we will check the returns obtained from trading with it on different currency pairs over the last two years. Finally, we will draw some conclusions about the potential of the Kalman filter in the field of economics, and in particular, in the world of investments.

Grado en Matemáticas

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Spain
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Keywords

Technical analysis, Bollinger bands, BackTesting, Matriz de covarianza, Covariance matrix, Tikhonov regularization, Error cuadrático medio, Filtro de Kalman, Regularización de Tikhonov,, Mean squared error, Kalman filter, Bandas de Bollinger, FOREX, Ánálisis técnico,, Python

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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