#Earnings whisperings full
That's not surprising because of the beat-the-estimates game that was played.ĭuring a sample period drawn from the latest third-quarter reporting season, when the bear was in full growl, whispers were closer to actual earnings 65% of the time versus 35% by official consensus estimates. co-founder Paul Hauck says that in the three years since whisper estimates became popular, they have on average been closer to actual earnings than the Wall Street consensus. But even though the fourth-quarter reporting season is barely a week old, tallies 33 whispers lower than the consensus estimates versus 71 during the entire two months of last year's fourth-quarter reporting season.Īre investors on target or overly pessimistic? Whisper numbers usually don't surface in force until a week or so before scheduled earnings announcements. Today, in the wake of warnings by dozens of companies that their fourth-quarter earnings won't meet the official consensus, whisper numbers are taking unprecedented dives below the consensus estimates that Wall Street analysts have already lowered. That compares to just 36 instances in the same period of 1999, and 54 in 1998 during the market tumble provoked by the Asian financial crisis. In the reporting period for third-quarter earnings, Belle Mead, N.J.-based tallied whispers estimates lower than consensus estimates for 98 companies. Then the whisper numbers themselves began to deteriorate. The disappointment exacerbated the slide of tech stocks. Some companies unexpectedly met rather than exceeded whisper numbers. The game worked spectacularly until March 2000 quarter reports. In fact, "beating the whisper" became essential to moving a stock higher. So, when earnings were reported, they "beat the consensus" and validated the whisper numbers.Īs the market rise became more frantic, consensus and whisper numbers were pegged to enable actual earnings to hurdle both. But the valuation extremes of recent years have made a penny a very big deal to investors.ĭuring the bull market, whisper numbers became so popular for tech stocks that the companies and Wall Street choreographed official consensus estimates lower than actual earnings. That's a mirror image of the situation in previous quarters.Īs with Yahoo!, the difference in many cases is just a penny. Some whisper numbers for fourth-quarter earnings of well-known companies such as Intel, Cisco Systems, Motorola and eBay are lower than the consensus. Now that's begun to work in reverse, moving into uncharted territory. Usually higher than the official Wall Street consensus, they justified pushing stock prices ever higher. This indicates that analysts’ forecast errors can still be improved by employing the instrumental variables technique.Whisper estimates flowered in the bull market. Finally, we observe that analysts’ forecast errors seasoned with the signs of various time-series forecast errors (as well as the signs of their own forecast errors) outperform those without seasoning. The paper provides evidence that the instrumental variables approach performs better for small-firm samples than for large-firm samples. It produces not only a smaller magnitude but also a narrower dispersion of earnings forecast errors. The results show that the instrumental variables approach is effective for reducing measurement errors inherent in various proxies for earnings forecast errors. We use signs of various proxies for earnings forecast errors obtained from different time-series forecasting models as multiple instruments.
The key aspect of the approach is to extract information from alternative proxies for the same underlying variable, namely a portion of realized earnings signals unexpected by the market. This paper develops an instrumental variables framework to form a better proxy for earnings forecast errors.
They are only a fair predictor of stock prices’ movement and do not represent the market’s true earnings expectations. In summary, whispers are not as accurate as generally portrayed. In fact, I find that a strategy of shorting stocks for which whispers forecasts predict that stocks will outperform is profitable. There is mixed evidence that the market partially reflects the whispers information into price. I find that whispers, while unbiased, are not more accurate than the analysts’ consensus. Gathering my sample from an on-line source of whisper information, I compare the whispers performance to that of traditional investment analyst forecasts. I examine the accuracy, the predictive performance and the informational value of these whispers. They have heightened the drama of companies’ earnings releases and have been played up as explanations for stock prices’ reactions to actual earnings announcement. Whisper numbers have captured the attention of both the investment community and the financial media.
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