Abstract
This paper deals with the issue of forecastability of sales activities of independent financial advisers (agents). Employing the most common quantitative methods on a diverse sample of timelines from multiple advisory companies, we have found that under most settings, these methods offer sub-par performance with high relative errors and no statistical differences between them. When a more granular approach is applied (reflecting sales unit size), ARIMA and the simple moving average emerge as significantly less accurate. This outcome is true for all sales units regardless of their size, when relative error is concerned. Thus, our analysis confirms the difficult forecastability of financial sales, speaking against the utilisation of more sophisticated forecasting methods, which mostly fail when compared to their much simpler and less costly counterparts.
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Notes
Total sample n = 134 US companies.
Results for 3-month–2-year forecasting horizon, total sample n = 186 US companies.
Autumn annual prediction, published usually by November of the previous year.
Scale dependent measures such as MAE or RMSE are disqualified by different units among the timelines.
See Hyndman and Athanasopoulos (2018), chapter Time series cross-validation for details on this technique.
In detail: 10.2 years for big units, 7.9 for medium units and 5.2 for small units.
Other common variation metrics (mean, standard deviation) are not usable because of different units used by individual time series.
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Acknowledgements
This work was supported by the Czech Science Foundation under Grant No. 16-21506S: New sources of systemic risk on financial markets (2016–2018).
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Šindelář, J. Sales forecasting in financial distribution: a comparison of quantitative forecasting methods. J Financ Serv Mark 24, 69–80 (2019). https://doi.org/10.1057/s41264-019-00068-3
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DOI: https://doi.org/10.1057/s41264-019-00068-3