Can voice analysis help predict future earnings?

Can voice analysis help predict future earnings?

A group of researchers at Ruhr University Bochum, Germany, have just completed an impressively original and methodologically sound research project on how the speech patterns of managers can help to predict future earnings.  

So far earnings prediction models have relied only on numerical financial data, but their research paper – "Listen Closely: Using Vocal Cues to Predict Future Earnings" – suggests that vocal cue models can do better and outperform the standard approaches. 

This work caught my attention immediately as I have been teaching presentation skills for years, of which voice is a fundamental element. 

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Predicting earnings has long been a challenge for investment practitioners because the process entails complex interactions between many operational activities.  

Yet, accurate data on this issue is the starting point and single most important input to firm and equity models in this context. In fact, the entire profession of financial analysts revolves around predicting future firm performance. 

Despite all this, the cues literally spoken by managers constitute a so-far overlooked element of this process. Collectively, research in the fields of psychology, neuroscience, accounting and finance unanimously suggest that vocal cues convey useful information. The structure of voice can accurately reflect cognitive states and thus also emotional states. 

However, no study so far has considered predicting future earnings in this manner. Interestingly too, there is anecdotal evidence that although analysts themselves acknowledge the value of vocal cues, they have not been able to incorporate this information systematically into their forecasts.  

Understanding vocal cues

Yet, the case for achieving this is clear. Because speech production is so complex, managers cannot fully prevent what they really think and believe from subtly permeating how they say things. This means that the tone and structure of voice can reveal issues that are not actually stated.

By contrast, people can of course control what they say through the words they choose. 

It is possible to interpret the message conveyed through what are referred to as the granular and sequential nature of vocal waves. Granular means that even small speech units are potentially valuable. For example, anger is associated with a larger jaw opening than sadness, which will in turn affect the voice structure. 

Sequential refers to the voice 'melody'. The statement 'you can predict earnings changes' is essentially factual, if stated neutrally. But by raising one’s voice at the end, it can be converted into a question, and a clear emphasis on you shifts the message to the receiver role. 

Slight shifts in an individual’s emotional state can therefore affect the speech-production process, affecting several dimensions of the sound structure, including frequency, amplitude and overall range. At least 24 different emotions can evidently be detected from brief vocal statements and comments.

In this sense, vocal cues can inadvertently leak a speaker’s emotional state, so that, when the content is related to financial results, analysing vocal cues may yield otherwise hidden and implicit insights into real perceptions and valuations of both past and future firm performance. They can even evidently help prevent financial fraud and improve financial risk prediction.