What Is the Kairi Relative Index (KRI)?
Let me explain the Kairi Relative Index directly: it's a technical analysis metric that you, as a trader, can use to determine when to buy or sell an asset. It measures how much the price deviates from the simple moving average (SMA) of that asset's price over a set period, usually 10 to 20 days.
If the asset's price is significantly higher than the SMA for your chosen period, the KRI suggests it's time to sell. Conversely, if the price is much lower than the SMA, the index indicates a buying opportunity.
Key Takeaways
The KRI focuses on the distance between closing prices and a simple moving average. You need to watch for extreme readings, as they signal potential buys or sells. Keep in mind that these extremes vary by asset—volatile ones hit higher and lower levels than stable ones. Remember, the KRI isn't a perfect timing tool, so combine it with other analyses for reliable trade signals.
The Formula for the Kairi Relative Index (KRI)
Here's the formula you use for the KRI: it's (Close - SMA_n) / SMA_n multiplied by 100, where SMA is the simple moving average and n is the number of periods in that average. This calculation gives you the percentage deviation directly.
How to Calculate the Kairi Relative Index
- Calculate a simple moving average using the most recent closing prices for your specified number of periods, say 10 (n).
- Subtract the n-period SMA from the most recent close price.
- Divide that result by the SMA.
- Multiply by 100.
- Repeat this as each new period closes.
What Does the Kairi Relative Index Tell You?
The KRI was developed by a Japanese investor and gained popularity in the mid-20th century, but by the 1970s, more advanced metrics like the Relative Strength Index (RSI) took over. Essentially, it shows you how far the price has strayed from its moving average. Assets with high volatility will produce larger KRI values than those with low movement.
For instance, on the SPDR S&P 500 ETF (SPY), extreme lows might be between -7 and -15, with highs from 4 to 10. A volatile stock could reach -40 or +50. When applying the KRI to any asset, check its historical extremes—those are the levels to monitor going forward.
If the indicator drops to an extreme low for that asset, it signals the price is oversold and might bounce back. Wait for confirmation, like the price starting to rise, before you buy. On the other hand, an extreme high means the price is overbought and could drop—wait for the price to start falling before selling.
Example of How to Use the Kairi Relative Index
Take a look at the KRI applied to an Apple Inc. (AAPL) weekly chart over more than seven years. Extreme upside readings typically hit 15 or above, while lows go below -10. I've marked some of these with vertical lines: green for buy signals and red for sells.
While some trades would have panned out, especially during Apple's uptrend, many signals were off if relying solely on the KRI. Buy signals often came while the price was still dropping, and sell signals appeared too early as the price kept climbing. Waiting for price reversal confirmation after a KRI extreme would avoid these mistakes.
Difference Between the KRI and the MACD
The KRI measures the distance from closing prices to the SMA, but the Moving Average Convergence Divergence (MACD) looks at the gap between two exponential moving averages. MACD usually includes a signal line for trade triggers, making it different in approach.
Limitations of Using the Kairi Relative Index
The KRI simply tracks how far an asset's price is from its moving average, with extremes as buy or sell signals. But note that extreme readings often mean a strong trend is underway—prices move fast to deviate that much from the average. Jumping in to short a rising market or buy a falling one based on KRI alone can be risky, like stepping in front of a train.
Always wait for verification that the price is turning, using other indicators or price action. The KRI might shift without the price changing direction if the gap to the SMA narrows while the trend continues. Since the SMA is based on historical data, it doesn't predict the future reliably.
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