The Bochum work entails specially constructed model architectures that convert managers’ sound waves into spectrograms, that is, visualisations of sound. Using deep learning models that specialise in detecting patterns in the grid-like structures of these visualisations, they train the models to predict firm earnings for the next year.
In another model architecture, they use a pre-trained speech recognition system provided by Meta AI, which processes the raw waveform of audio signals at the millisecond level.
The researchers then fine-tune them in the context of earnings prediction. They have thus found a way to tap into a potentially vital information pool that has simply not been used before in the context of earnings prediction. Their large sample of conference calls from US public firms over a period of five years yields significant predictive power.
A way to go
The authors warn, however, that their impressive results cannot readily and easily be used in practice. The modelling process has inherent limitations and is only in its infancy.
The research literally constitutes a big data challenge, as audio data is inherently large and had to be run on high-end computers through a platform that provides a suite of cloud computing services.
Nonetheless, their work provides initial evidence that trading strategies based on managers’ vocal cues can beat the market by almost 9 per cent on average. Specifically, the vocal-cue models developed for this research project substantially outperform the benchmark models that are currently state of the art.
Moreover, motivated by the desire of analysts to consider vocal cues in their forecasts, the researchers tested whether their model can improve professional analysts’ earnings forecasts.
Combining the forecasts from financial analysts with predictions based on the vocal-cue models (inadvertently provided by managers) does indeed systematically outperform analysts forecasts alone. This suggests that these cues constitute significant untapped potential for financial analysts.
Over time, this may well become a major source of information on what to expect from corporate earnings in the future. This is especially the case, as voice analysis seems to work particularly well in turbulent market phases such as the Covid-19 crisis, during which the value of numbers alone may be constrained.
Indeed, the Bochum project covers the pandemic years of 2019-22, and has proven its worth against this background.
Returning to my comment on presentation skills, body language is now an established indicator of integrity, intentions, emotions and a whole lot more. Voice may potentially be just as powerful.
