Forecasting financial short time series


We study the application of time series forecasting methods to massive datasets of short financial time series. In our example, the time series arise from analyzing monthly expenses and incomes in personal financial records. Differently from traditional time series forecasting applications, we work with series of very short depth (as short as 24 data points), which prevents from
using classical exponential smoothing methods. However, this shortcoming is compensated by the the size of our dataset: millions of time series. The latter allows tackling the problem of time series prediction from a pattern recognition perspective. Specifically, we propose a method for short time series
prediction based on time series clustering and distance-based regression. We experimentally show that this strategy leads to improved accuracy compared to exponential smoothing methods. We additionally describe the underlying big data platform developed to carry out the forecasts in an efficient manner (comparisons to millions of elements in near real-time).

DOI Code: 10.1285/i20705948v11n1p42

Keywords: Financial time series, Forecasting, Conditional mean, HoltWin- ter, Clustering


Akaike, H. (1969). Fitting autoregressive models for prediction. Annals of the institute of Statistical Mathematics, 21(1):243–247.

Bosq, D. (2012). Nonparametric statistics for stochastic processes: estimation and prediction , volume 110. Springer Science & Business Media.

De Gooijer, J. G. and Hyndman, R. J. (2006). 25 years of time series forecasting. International journal of forecasting, 22(3):443–473.

Holt, C. C. (2004). Forecasting seasonals and trends by exponentially weighted moving averages. International journal of forecasting, 20(1):5–10.

Hyndman, R. J., Koehler, A. B., Ord, J. K., and Snyder, R. D. (2008). Forecasting with exponential smoothing: the state space approach. Springer Verlag.

Schwarz, G. et al. (1978). Estimating the dimension of a model. The annals of statistics, 6(2):461–464.

Winters, P. R. (1960). Forecasting sales by exponentially weighted moving averages. Management science, 6(3):324–342.

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