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Using Time-Delay Neural Networks for Forex Event Signals

Article Quant Q&A · Author: MithPaul
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Summary

The document asks whether a time-delay neural network (TDNN) could use economic-calendar information to predict forex prices. Its motivating challenge is that news effects may persist beyond the release time and may appear in market movements beforehand, so the signal may need to represent temporal relationships rather than only the immediate event.

The reply points to a published case study applying TDNNs to technical forecasting in forex and mentions MATLAB as a possible implementation environment. It offers a starting reference, not a worked application to calendar events. The exchange provides no dataset design, feature encoding, training procedure, validation results, or evidence that a TDNN can forecast the effects of scheduled news. Those steps would need to be established independently.

Key ideas

  • Economic-calendar events may influence forex prices over extended periods and may be anticipated before release.
  • A TDNN is proposed as a way to model time-dependent information for a trading signal.
  • A cited study applies neural networks to forex forecasting, but the exchange does not report its results.
  • The reply mentions MATLAB as an implementation option without giving a modeling workflow.

Tags

ForexMachine learningEvent-driven
Full text
# Applying Time Delay Neural Network to financial events


# Applying Time Delay Neural Network to financial events












I have an IT background and I would like to use data from a forex calendar like this one to predict prices.

The problem is that calendar news impacts can last for days or weeks or even can effect previous hours to their release.

Since I would like to use this fundamental information as signal for a trading system, I have read about Time Delay Neural Networks and I think it could be useful for this task.

Does anyone knows or can point to references on how can I apply a Time Delay Neural Network to accomplish this? Thanks beforehand!

## Answer by Quantopik (score 0, accepted)

https://quant.stackexchange.com/a/18706

I suggest you to read as reference the following paper:

> Yao, Jingtao, and Chew Lim Tan. "A case study on using neural networks to perform technical forecasting of forex." Neurocomputing 34.1 (2000): 79-98.

The authors applied TDNNs to the forex markets and I think it could be useful for you purposes; you can find the pdf version of the paper here.

As regards the available tools to construct this kind of model, I know you can implement that in `matlab`, by exploiting `timedelaynet.

Hope this will help.

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This summary was written by Stratmill's research agent from the original; it is not a copy of the source.