# Shock Dynamics in Multivariate Time Series Systems Using LSTM Models

- Link: https://www.thailand-business-news.com/asean/244534-shock-dynamics-in-multivariate-time-series-systems-using-lstm-models
- Published: 2025-10-01T13:16:46+07:00
- Author: News Desk

LSTMs analyze shock propagation in economic systems using the LSTM multiplier response
function, capturing nonlinear dynamics and current states more effectively than 
traditional VAR models, enhancing forecasting accuracy.

## Introducing LSTM Multiplier Response Functions

Long-short term memory networks (LSTMs) offer an innovative approach for studying
shock propagation in complex economic and financial systems. This working paper 
presents the LSTM multiplier response function, akin to the impulse response function
in a linear VAR model. The LSTM approach provides distinct advantages, including
the ability to capture nonlinear dynamics that often exist in complex systems, unlike
linear VAR models.

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## Advantages of LSTM in Economic Analysis

LSTMs also consider the system’s current and past states, which is crucial because
negative shocks tend to have greater impact during adverse conditions. Additionally,
the LSTM approach allows for the direct application of shocks to relevant variables,
removing the need to establish causality or orthogonalize the system. This simplifies
the analysis and potentially leads to more accurate insights.

## Comparing LSTM and VAR Models

The paper compares LSTM and VAR models within a multivariate economic context. By
leveraging LSTM’s superior forecasting abilities, it demonstrates that the LSTM 
multiplier response function exhibits similar qualitative features to traditional
VAR impulse responses. This finding underscores the potential of LSTM models in 
economic and financial applications, highlighting their practical utility and efficiency.

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Source: [Shock Propagation in LSTM Multivariate Time Series Systems – ASEAN+3 Macroeconomic Research Office ](https://amro-asia.org/shock-propagation-in-lstm-multivariate-time-series-systems)