Introducing BISTRO: a foundational model for unconditional and conditional forecasting of macroeconomic time series

Batuhan Koyuncu, Byeungchun Kwon, Marco Jacopo Lombardi, Fernando Perez-Cruz and Hyun Song Shin

No 1337, BIS Working Papers from Bank for International Settlements

Abstract: This article introduces the BIS Time-series Regression Oracle (BISTRO), a general purpose time series model for macroeconomic forecasting. Its edge over traditional econometric approaches lies in its ability to deal with generic unconditional and conditional forecasting tasks, without requiring to adjust the model to the macroe conomic tasks being tackled. Building on the transformer architecture underlying LLMs, BISTRO is fine-tuned on the large repository of macroeconomic data main tained at the BIS. We show that BISTRO provides reliable unconditional forecasts for key macroeconomic aggregates and illustrate how using it for conditional fore casting can help unveiling patterns of nonlinearity in the data.

Keywords: forecasting; scenarios; large language models (search for similar items in EconPapers)
JEL-codes: C32 C45 C55 C87 (search for similar items in EconPapers)
Date: 2026-03
New Economics Papers: this item is included in nep-ets and nep-for
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