Estimating Core and Volatile Non-Contractual Bank Deposits

Summary

The response outlines a simple way to separate stable and volatile portions of non-contractual deposit balances for behavioral analysis. It proposes smoothing daily balances with a moving average to reduce seasonal effects while retaining the underlying trend. The smoothing window is selected by balancing how straight the estimated trend appears against how much growth pattern it still preserves. For each observation, an extreme value based on a chosen confidence interval is then compared with the trend to estimate the volatile share; the residual share is treated as core.

The suggested balance components are assigned different maturity buckets, with the volatile portion placed in the shortest bucket and the core portion in a longer selected bucket. The reply notes that a higher confidence level raises the estimated volatile share and shortens the implied duration. It recommends analyzing the two components separately for interest-rate sensitivity. This is a brief heuristic, not a validated model: it gives no formal method for choosing the window or confidence level and does not establish regulatory or accounting requirements.

Key ideas

• Smooth daily balances with a moving average to reduce seasonal variation while retaining a trend.
• Choose a smoothing window that balances trend smoothness against visible growth behavior.
• Compare an extreme-value estimate with the trend to estimate the volatile share.
• Assign volatile and core portions to different maturity buckets and analyze their rate sensitivity separately.
• Higher confidence levels increase the estimated volatile portion and reduce the implied duration.

Tags

# Non-contractual accounts behavioural study


# Non-contractual accounts behavioural study












I need to carry a non-contractual accounts behavoiural study for a bank. The objective is to estimate core/non core ratios and then bucket and ftp them. Any recipe where to start? I have 3yrs of historical data, daily closing balances. From what I googled I understand that I need some kind of seasonal vs growth trend segregation. But only guidelines, nothing in particular. Visually represented my data has (e.g. current accounts) very heavy seasonal bias with highs in shoulder seasons and lows in the festive seasons ;)). How to isolate it? How do I then calculate the true core/volatile ratio?

## Answer by Peaches (score 0)

https://quant.stackexchange.com/a/24547

Here is one of the easier ways to value a non-contractual book. 1.Get your trend line. Using moving averages smooth the data to remove the seasonal bias. Select n that gives the straightest line but still shows the growth trend. 2.Find your percentile extreme value (EV) based on chosen conf. interval. 3.Calculate the ratio of EV to your trend line for each data point. This is essentially your volatile ratio. 4.Put the volatile portion into the shortest bucket, the core into the longer selected tractor. Points: The higher the conf. interval the higher the volatile ratio will be. It will also shorted the duration of the book. For rates sensitivity must use the two components separately. Hope that helps

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