Asset graphs are vital visual presentation tools for highlighting financial data in the form of network structures.
Financial portfolios in the form of assets decluttering not with complex relationships that arise from different components of business including ownership, management, and geographic location among other elements.
The complexity of investment portfolios is witnessed not only in the contributing factors but also in the consequences of the investments such as returns and costs.
With the various attributes surrounding assets, it is fundamental that an entire representation of the influences, relationships, and outcomes of these attributes to the assets are understood by any investor or stakeholder from a financial perspective.
The clarity of these properties and their relationship/impact on the assets can be highlighted in explicit terms using network graphs. A network graph is characterized by nodes and edges and the relationships between the various entities representing the nodes and edges.
Some of the financial clarity provided by these graphs include:-
Asset graphs are useful tools used in the identification of the network structure of a portfolio. The relationships between different entities in the portfolio cascade down to each attribute, highlighting the nodes and the edges of the portfolio. The visualization of these entities and the corresponding relationships are essential tools for marking a portfolio.
Asset mapping asset is critical in ascertaining ownership and responsibility and in bolstering transparency and visibility of an investment in its entirety. The decluttering not only amplifies the investment intelligence but it also provides better visibility for management and decision making.
Asset graphs are also resourceful tools in highlighting the quality of diversification. The network structure of a portfolio highlights the asset diversity in a robust manner that facilitates institution based and data-driven decision making. Using the image created by asset graphs, the diversification structure can be established, and the key drivers identified so as to assess the validity of the existing structure.
Utilizing network diagnostics in an asset graph is a very fundamental application of asset graphs. By exploring the network effect, the risk aspect of the investment portfolio can be identified at the preexisting condition or can be simulated. Therefore, the asset graph can be used in risk management as an early warning system for risk concentration, forensic analysis and diagnostics of portfolio scenarios, stress testing among other risk management applications.
Besides, the visibility provided by asset graphs on the entity relations highlights the various businesses and activities surrounding and asset and hence the asset graph provides a better view of the contagion risk that an asset is likely to face based on its relationships with other businesses or business activities as described by the butterfly effect.
Lastly, exploring the network effect, not only provides the risk exposures, but it also provides the decision makers with an opportunity to optimize the ensuing benefits identified from the asset graph. The analysis provided be used to determine trends and hence predictive utilized to create better products for future applications, new products based on behavior change and alternative solutions for the market as portrayed by the patterns.