Zscaler’s Stock Likely To Gain?

ZS: Zscaler logo
ZS
Zscaler

Zscaler Inc., (NASDAQ: ZS), a cloud-based information security company, saw its stock fall by 8.4% over the last five trading days. In comparison, the broader S&P500 was up 1% over the last five trading days. Will the company resume its upward trajectory over the coming weeks, or is a fall in the stock imminent? According to the Trefis Machine Learning Engine, which identifies trends in a company’s stock price using historical stock data, returns for Zscaler’s stock average around 8.6% in the next one-month (twenty-one trading days) period after experiencing an 8.4% fall in a week (five trading days). Further, the stock is likely to outperform S&P500 returns by 8.7% over the next month (twenty-one trading days).

But how would these numbers change if you are interested in holding Zscaler’s stock for a shorter or a longer time period? You can test the answer and many other combinations on the Trefis Machine Learning Engine to test Zscaler’s stock chances of a rise after a fall. You can test the chance of recovery over different time intervals of a quarter, month, or even just one day!

MACHINE LEARNING ENGINE – try it yourself:

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IF ZS stock moved by -5% over five trading days, THEN over the next twenty-one trading days, ZS stock moves an average of 7.1%, which implies an excess return of 6.3% compared to the S&P500.

More importantly, there is a 67% probability of a positive return over the next twenty-one trading days and a 63% probability of a positive excess return after a -5% change over five trading days.

Some Fun Scenarios, FAQs & Making Sense of Zscaler Stock Movements

Question 1: Is the average return for Zscaler stock higher after a drop?

Answer:

Case 1: Zscaler stock drops by -5% or more in a week

Case 2: Zscaler stock rises by 5% or more in a week

Is the average return for Zscaler stock higher over the subsequent month after Case 1 or Case 2?

ZS stock fares better after Case 1, with an average return of 7.1% over the next month (21 trading days) under Case 1 (where the stock has just suffered a 5% loss over the previous week), versus, an average return of 4.7% for Case 2.

In comparison, the S&P 500 has an average return of 3.1% over the next 21 trading days under Case 1, and an average return of just 0.5% for Case 2 as detailed in our dashboard that details the average return for the S&P 500 after a fall or rise.

Try the Trefis machine learning engine above to see for yourself how Zscaler’s stock is likely to behave after any specific gain or loss over a period.

Question 2: Does patience pay?

Answer:

If you buy and hold Zscaler stock, the expectation is over time the near term fluctuations will cancel out, and the long-term positive trend will favor you – at least if the company is otherwise strong.

Overall, according to data and Trefis machine learning engine’s calculations, patience absolutely pays for most stocks!

For ZS stock, the returns over the next N days after a -5% change over the last 5 trading days is detailed in the table below, along with the returns for the S&P500:

You can try the engine to see what this table looks like for Zscaler after a larger loss over the last week, month, or quarter.

Question 3: What about the average return after a rise if you wait for a while?

Answer:

The average return after a rise is understandably lower than after a fall as detailed in the previous question. Interestingly, though, if a stock has gained over the last few days, you would do better to avoid short-term bets for most stocks.

ZS’s returns over the next N days after a 5% change over the last 5 trading days is detailed in the table below, along with the returns for the S&P500:

It’s pretty powerful to test the trend for yourself for Zscaler stock by changing the inputs in the charts above.

While Zscaler stock may have moved, it is helpful to see how its peers stack up. Check out Zscaler Peer Comparisons to see how Zscaler compares against peers on metrics that matter. You can find more such useful comparisons on Peer Comparisons.

 

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