Structural minimization of tracking error
The structural tracking error minimization (STEM) approach produces stable tracking portfolios out-of-sample in the crucial investment period. Full version:
Quantitative Finance
Blog about big data processing and data-driven investments
The structural tracking error minimization (STEM) approach produces stable tracking portfolios out-of-sample in the crucial investment period. Full version:
Quantitative Finance
Before you start the investment you need to document two very important points.
You have downloaded the application and you would like to start book keeping.
How to start?
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The first version of MoneyBuilder is available.
Three months ago I have started to develop personal finance application for myself. You can ask me, why you need another personal finance application?
Today, the investment into indices has become a widely used strategy in portfolio management. While Index Funds and ETFs try to represent the performance of a single index, other portfolio strategies use indices as portfolio components to concentrate on the allocation task. Because an index cannot be purchased directly, it has to be rebuilt. This is called index tracking.
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In today’s Portfolio Management many strategies are based on the investment into indices. This is a consequence of various empirical studies that show that the allocation over asset classes, countries etc. provides a greater performance contribution than the selection of single assets. For every portfolio containing indices as components the problem is that an index cannot be purchased directly. So it has to be rebuilt. This is called index tracking. The goal is to approximate the risk and return profile of an index.
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