From the headline print, investors have every reason to be skeptical about SoundHound AI (SOUN). While the company recently posted strong sales, fundamental challenges in its core business have hurt investor sentiment. Combined with escalating concerns about overheated valuations in the technology sector — and especially in artificial intelligence — SOUN stock had nowhere to go but down. Still, amid the carnage lies an enticing opportunity for data-driven traders.
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At first glance, circumstances seemed auspicious. In Q3, SoundHound incurred a loss per share of 27 cents, which was much steeper than the anticipated loss of 9 cents. However, revenue reached $42.05 million, beating out the consensus target of $40.49 million. Notably, the company has already achieved a record year in revenue of $114 million, up 127% in the first three quarters.
Unfortunately, despite expanding into new markets and adopting enterprise AI, SoundHound’s automotive segment encountered challenges. What was most pressing to observers was the negative impact due to global tariffs and broader industry softness. Plus, as investors trimmed their exposure to high-risk, high-growth companies, SOUN stock took a beating.
So just how bad was it? In the trailing month, the security hemorrhaged more than 38%. Nevertheless, with the bad news now baked in, it’s time for the security to respond. My thesis is that SOUN stock is primed for a recovery, and I’ll lay out the quantitative reasoning for my bullishness.
Reversion to the Mean But with a Quant Twist
If you’re familiar with stock analysis, you’ll no doubt be familiar with the concept of reversion to the mean. In summary, publicly traded securities—especially popular ones like SOUN—don’t follow perfectly linear paths. Instead, there is an ebb and flow, with periods of excessive bullishness corrected by a downturn, and vice versa.
Under the principles of technical analysis, you can (apparently) read the chart to better determine when a reversal is about to occur. In essence, you buy the embattled security before the bullish wave comes in to drive shares back higher. As great as this game plan sounds, it might be complete garbage.
In the book Superforecasting: The Art and Science of Prediction, authors Philip E. Tetlock and Dan Gardner warned readers about how easy it is for humans to be tricked into believing that purely random data may offer predictive insight. Citing the seminal work of psychologist Ellen Langer, researchers have demonstrated that even the brightest of people can be duped into believing the impossible, such as skillfully predicting coin tosses.
The fundamental problem, according to Tetlock and Gardner, is that humans are not wired to correctly interpret data randomly distributed at the local level. In other words, it’s not that the equities market is random, a concept that I very much dispute. Instead, it’s that, up close in a sea of data, we humans lack an intuitive feel for distinguishing randomness from non-randomness.
Basically, we see what we want to see, which explains psychological concepts like pareidolia. This phenomenon also underscores the power of technical analysis: we are wired for narratives, not statistics.
That said, we can all become smarter traders by deploying empirical probabilistic thinking. To help move the finpub industry forward, I developed a Kolmogorov-Markov framework layered with kernel density estimations (KM-KDE) that computes a quantity known as the probability density. Rather than focusing on where a stock has been in the past, we can calculate where a security is likely to end up under certain stimuli or conditions.
Much of what makes KM-KDE powerful is non-linearity. Rather than view a stock as a journey across time, I view it as multiple trials across 10-week windows. The theory here is that, over many trials, the target security’s probabilistic structure will emerge. With this structure, we can make informed decisions.
Converting Theory into Action for SOUN Stock
While the KM-KDE approach is mathematically complex, the concept in practice is surprisingly intuitive. Using the process, the forward 10-week median returns for SOUN stock can be plotted as a distributional curve, with outcomes ranging from $10.80 to $12.20 (using Friday’s close of $11.22 as an anchor price). Further, price clustering would likely be predominant at $11.25, indicating a slightly bullish bias.
The above assessment aggregates all trials since SoundHound’s public market debut. However, we’re not interested in aggregating all data but only a specific subset. Specifically, in the last 10 weeks, SOUN stock printed a 3-7-D sequence: three up weeks, seven down weeks, with an overall downward slope.
Under this signal, the forward 10-week returns would be expected to range between approximately $10.60 and $13.70, with price clustering likely to be predominant at $12.65. Essentially, a 12.44% positive delta exists between the probability density expected under baseline conditions and that likely to materialize under the current signal. This is an informational arbitrage that traditional methodologies like technical analysis are blind to.
Given that we know the expected probabilistic structure of SOUN stock moving forward, traders can decide which options strategy makes the most sense. In my opinion, the most aggressive and still rational idea is the 12/13 bull call spread expiring January 16, 2026.
In this trade, you would make two simultaneous transactions under a single execution: buy the $12 call and simultaneously sell the $13 call, for a net debit paid of $32 (the maximum possible loss). Should SOUN stock rise through the second-leg strike of $13 at expiration, the maximum profit stands at $68, a payout of 212.5%.
What makes this trade so tempting is that the breakeven price is $12.32, which is near where the meatiest part of the distributional curve sits. Plus, the $13 strike is well within the expected range of outcomes. To be clear, you would be taking an ambitious risk. However, the risk is a realistic one based on expectations from past analogs.
Is SOUN Stock a Buy, Hold, or Sell?
Turning to Wall Street, SOUN stock carries a Moderate Buy consensus rating based on two Buys, four Holds, and zero Sell ratings over the past three months. The average SOUN price target is $17.20, implying ~47% upside potential over the coming 12 months.
Allowing Probability to Do the Heavy Lifting
Although SoundHound AI has been brutalized amid the broader tech-sector sell-off, the sea of red may actually reveal a compelling contrarian opportunity. At the moment, SOUN appears to be trading in a highly distributive technical state—one that, historically, often resolves to the upside once selling pressure exhausts itself.
Still, instead of merely assuming a reversion to the mean, a smarter approach is to quantify the setup. By using a data science framework—evaluating volatility regimes, dispersion, skew, and the probability-weighted payoff distribution—we can identify an options strategy that is both logical and empirically grounded. This transforms a speculative rebound thesis into a structured, evidence-based trade.