Sifting through the noise
As data volume increase by the day, the noise level is tremendous. By noise, we mean the same data in different wording or even duplication of the same content. In the financial markets, data is key factor for outperforming the benchmarks. However, nowdays, it becomes impossible to track all major events for relevant companies as the news volume are at pick and continue to raise.
One good example of the “noise” is found during earnings session as companies files their 10-Q and 10-K, the amount of duplication of the same key events is tremendous with an average of 10 news items per corporate event (revenue, earnings, guidance), and for large-cap companies up to 30 news items per event
Here are a few examples of the same events distributed via multipole news sources:
Lyft $LYFT got 130 mentions in the global press and financial related social media before and during the quarterly financial announcement date. 3 key events: 1. Raises outlook 2. Q2 earnings Beat 3. Q2 revenue Beat.
Apple $AAPL got 314 mentions in the global press and financial related social media before and during the quarterly financial announcement date. 3 key events: 1. Slowing revenue growth 2. Q3 Earnings Beat 3. Q3 EPS Beat.
Beyond Meat $BYND got 114 mentions in the global press and financial related social media before and during the quarterly financial announcement date. 4 key events: 1. Common stock offering 2. sales growth 3. Earnings miss 4. Raised forecast.
Now think about a typical PM which covers 50-70 companies in his portfolio, need to read between 500-1500 news items during earnings session just to keep up. Or think about a quant strategy that relay on a clean dataset and being constantly overloaded by duplications of the same event over and over.
The “noise” is inefficient no matter if a fund uses fundamental or quant strategy, it must be solved. Contact us and see if our dataset can help you fund the sifting through the news.