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When will savings rates go up to match global interest rate rises?

A Polish Exemplar

The recent rises in global interest rates mark the first raise in a long time, as the loose monetary policies and quantitative easing (QE) introduced after the 2008 crash and Covid-19 pandemic abate.

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Sourcing Market Data

The provision of market data to support not only an organization’s treasury function but the wider business functions can become a time-consuming and potentially complex exercise. It is no longer just about the source of market data, questions such as integration, validation, storage, consistency and distribution within an organization need to be considered. In this article we will look at some of the considerations when deciding on how to source market data and how in-built applications can reduce risk and cost while improving automation.

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“It all depends on expert opinion, data, and common sense”

Two ING experts share their views on deposit modelling

The low interest rate environment has faced banks with structural changes in customer behavior and converging products such as savings and current accounts. ING, one of Europe’s largest players in the savings market and a long-term client of Zanders, has positioned itself as one of the frontrunners in this environment. We sat down with Tom Tschirner (head of market risk at ING Germany) and Maarten Hummel (financial risk officer at ING Group) to gather their view on modeling and balance sheet management after these structural shifts.

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The relevance of the yield curve

Creating a future stress scenario for the yield curve is not easily done. Above all, it is something that has to be done carefully, because it can have negative repercussions for a financial institution.

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Are more complex models always better?

A part of the curriculum of the Econometrics & Mathematical Economics master’s degree given in the VU University Amsterdam is the course Time Series Econometrics. In this course, students are taught how to analyze time series with the aid of ‘state-space models’, on the assumption that observations over time (such as the content of the Nile, for example) are driven by non-observed factors.

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