Unveiling the Winning Contribution Patterns for Enhanced Financial Health
DOI:
https://doi.org/10.61190/fsr.v32i2.3358Keywords:
financial resilience, saving, machine learningAbstract
In this paper, we examine the issue of saving in the context of financial resilience. We examine unique dataset(s) of investor transactions to determine the relationship between investor behaviours, household savings, and investment outcomes. We examine these real-world observed behaviours through advanced data analytics in the form of machine learning to explore previously unknown patterns and seek a determination of any causal relationships.
We examine trading over a 3-year period ending August 2022, providing us with the opportunity to observe behaviour during rising markets, declining markets and the turbulent phases during transitions. Our datasets included investors who work with financial advisors and those who prefer “do it yourself”.
Trading behaviours over this period, demonstrated an active savings strategy to be the most effective strategy for building wealth. On average, an active savings strategy was 5X more effective at building wealth and resilience than relying on investment returns or complex trading strategies.
We conclude that;
- Saving is a ‘force of nature’. The math isn’t new, but it works and we observed it working in the ‘real world”.
- Saving is simpler, more reliable, and more powerful than investment returns for building financial resilience.
- Frequent and disciplined saving is more effective than periodic or just-in-time saving.
- Saving is a universal strategy - the observed results were the same regardless of age groups, genders, risk tolerances and income levels.
- Keeping it simple is a legitimate strategy for building wealth. Saving and saving often - is not only easy to prescribe but effective.
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Copyright (c) 2024 Chuck Grace, Adam Metzler, Yang Miao, Leon, Alireza Fazelli
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