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    Interpolation of financial time series data in a virtual geographic environment

    Borna, Kambiz

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    Borna, K. (2022).pdf (260.8Kb)
    Date
    2022-06
    Citation:
    Borna, Kambiz. (2022, June). Interpolation of Financial Time Series Data in a Virtual Geographic Environment. Paper presented at the 62nd Annual Conference of the New Zealand Association of Economists, Wellington.
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/5733
    Abstract
    This paper introduces a new approach to visualising and interpolating financial time series data, e.g., Bitcoin prices, in a spatial domain using the notion of spatialization: forming a spatial representation of non-spatial phenomena. The proposed algorithm first utilises the temporal components of the observations, i.e., date and time, to build a 2D virtual geographic map. It then uses the assigned coordinates to the observations and their values to estimate unknown values and construct a 3D topographic map. We assess the 3D maps using the price time series of Bitcoin with 30-minute frequency, and the results show the reliability of the 3D maps in analysing the time series data.
    Keywords:
    Bitcoin, financial time series data, time series data, financial markets, spatialisation, algorithms
    ANZSRC Field of Research:
    350203 Financial econometrics
    Copyright Holder:
    Author

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    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use. These documents or images may be used for research or private study purposes. Whether they can be used for any other purpose depends upon the Copyright Notice above. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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    • Accounting and Finance Conference Papers [70]

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