On Assessing Valuation Robots
Loading...
URL
Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
2022-10-17
Department
Major/Subject
Data Science
Mcode
SCI3115
Degree programme
Master's Programme in ICT Innovation
Language
en
Pages
50
Series
Abstract
Valuation is the act of determining how much an investment is worth. This analysis is performed on a daily basis by market analysts who try to set the fair price of a company in order to decide whether or not to invest on it. This task is quite challenging since it requires estimating non-observable parameters such as the expected future performance of a company and how much return do the investors expect to get out of it. This thesis provides a statistical framework for assessing systematic valuation agents. The framework allows for a medium and long term evaluation of quantamental algorithms in a wide range of perspectives such as value-pricing bias, information assimilation, forecast-actual bias, model sensitivity, value components and financial performance. The main assessment methods here are designed for discounted models, although some are easily adapted to multiple based valuation models. This allows for a rich comparison across the value components of discounted cash flows and multiple based approaches. Additionally, these methods can be applied for assessing human analysts provided that they have enough points on their forecast history.Description
Supervisor
Ilmonen, PauliinaThesis advisor
Beveratos, AlexiosKeywords
valuation, statistical methods, quantitative approach, quantamental, systematic financial agents