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Books > Business & Economics > Finance & accounting > Finance > Investment & securities
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Quantitative Portfolio Management - with Applications in Python (Hardcover, 1st ed. 2020)
Loot Price: R1,052
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Quantitative Portfolio Management - with Applications in Python (Hardcover, 1st ed. 2020)
Series: Springer Texts in Business and Economics
Expected to ship within 10 - 15 working days
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This self-contained book presents the main techniques of
quantitative portfolio management and associated statistical
methods in a very didactic and structured way, in a minimum number
of pages. The concepts of investment portfolios, self-financing
portfolios and absence of arbitrage opportunities are extensively
used and enable the translation of all the mathematical concepts in
an easily interpretable way. All the results, tested with Python
programs, are demonstrated rigorously, often using geometric
approaches for optimization problems and intrinsic approaches for
statistical methods, leading to unusually short and elegant proofs.
The statistical methods concern both parametric and non-parametric
estimators and, to estimate the factors of a model, principal
component analysis is explained. The presented Python code and web
scraping techniques also make it possible to test the presented
concepts on market data. This book will be useful for teaching
Masters students and for professionals in asset management, and
will be of interest to academics who want to explore a field in
which they are not specialists. The ideal pre-requisites consist of
undergraduate probability and statistics and a familiarity with
linear algebra and matrix manipulation. Those who want to run the
code will have to install Python on their pc, or alternatively can
use Google Colab on the cloud. Professionals will need to have a
quantitative background, being either portfolio managers or risk
managers, or potentially quants wanting to double check their
understanding of the subject.
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