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# How to Predict Market Reversals with Z-Scores

## Learn to use the laws of statistics to predict the markets →

## Hey there 👋🏼

**Today in less than 5 minutes:**

**1) **Why do you invest at the top & end up losing**2) **Using 8th-grade maths to predict market reversals**3)** How you could have predicted the latest correction

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Most of us buy when the rally is almost over

Most market rallies are started by ‘smart money’, i.e. one or more institutional investors betting on the long-term prospects of a stock or country. This usually creates what we call a ‘breakout’.

Next, other investors start jumping in, each paying more than the group before them. The last ones to join are usually regular folks like us, the everyday investors. By the time we get in, the smart groups are usually cashing out, and others follow suit. This triggers a market correction, and suddenly, it feels like we got played 😳

If only there was a way to predict reversals… 😪

Well, there is a way… and it has its roots in a simple mathematics concept that we learned in 8th grade!

Using Z-Scores to Predict Market Reversals

You must recollect something about the concept of ‘normal distribution’, a simple statistics concept taught in the 8th grade.

The principle of normal distribution is based on the concept that data near the mean are more frequent in occurrence than data far from the mean. And the standard deviation (SD) helps us measure how far a data point is from the mean.

Another term used in this context is the z-score, which we will look at for our analysis today.

**A z-score helps us quantify how far a particular value is from its mean over a defined period.** The z-score of a stock’s price can convey a lot about its behavior. For example, a z-score of 2 indicates that a stock’s price is trading 2 standard deviations above the mean while a z-score of -2 indicates that it is trading 2 standard deviations below the mean.

The confidence interval pertaining to a z-score represents the percentage of data expected to fall within a certain range around the mean. A higher z-score corresponds to a wider range and a higher confidence level.

This score can be used smartly to gauge overbought and oversold conditions in the market 🧮

By the way, you can learn to analyze long-term market trends & invest at the right valuations in Upsurge.club’s **Stock Market Valuations Course****.**

Assume we set a z-score threshold of 1.96, representing a 95% confidence interval, to analyze a stock's price behavior over the past 22 trading days (1 month).

**When a stock's price surpasses this threshold, its price movement is considered extreme, indicating a potential market reversal.** This is because the z-score of 1.96 corresponds to the range within which the stock's price would typically fall about 95% of the time based on the historical data of the past 22 days. And a score beyond that signals something unusual!

We used the same threshold (z-score of 1.96) to study the price chart of RELIANCE, and were able to time its rallies/corrections most of the time since January 2020:

RELIANCE (1W)

Note that z-scores are backward looking, and using them as a strategy for generating buy/sell signals has its pitfalls.

Can we use this method of analysis to predict the fate of the markets? Read on to find out how we actually used this method to predict the ongoing correction in Nifty!

Learn to use various chart types, indicators, and techniques to identify and profit from market trends in Ms. Jyoti Budhia’s comprehensive **Technical Analysis Course****.** Use **STOCK10** for a 10% discount & get the course for just **₹****359**.

You Could Have Predicted this Correction

Now that you've understood the concept of z-scores and using them to guess when the market might turn around, let's try it out on Nifty 50, and figure out what's up with the markets lately.

NIFTY50 (1D)

As highlighted in the chart above, Nifty touched an all-time high of 22,124 recently. At the same time, its **z-score came in at 2.39, **which means the market was 2.39 standard deviations above (away) from its 22-day mean value.

A z-score of 2.39 gives us a confidence interval of 99.16%, saying that the market has been **below this level for about 99.16% of the past 22 days**.

This translates to only a 0.84% chance of Nifty staying at or above 22,124, so it looked like a turnaround was on the way. And guess what? It happened!

As of January 20, 2024, Nifty's z-score is -0.35, comfortably within its 95% confidence interval.

Learn to identify and profit from market trends in Ms. Jyoti Budhia’s comprehensive **Technical Analysis Course****.** Use **STOCK10** for a 10% discount & get the course for just **₹****359**.

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