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The Kairi Relative Index (KRI): Definition, How It Works, and Practical Application

Last updated 04/17/2024 by

Abi Bus

Edited by

Fact checked by

The Kairi relative index (KRI) is a valuable tool in technical analysis, aiding traders in making buy or sell decisions based on price deviations from a simple moving average (SMA). This comprehensive guide explores the calculation, interpretation, application, examples, and limitations of the KRI, providing traders with a deep understanding of its nuances.

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What is the kairi relative index (KRI)? Example & how it’s used

The Kairi relative index (KRI) serves as a technical analysis metric employed by traders to discern opportune moments for asset transactions. Derived from the Japanese term “Kairi,” meaning relative, this index measures the discrepancy between an asset’s current price and its simple moving average (SMA) over a specified period, commonly ranging from 10 to 20 days.

How to calculate the kairi relative index

To compute the KRI:

Calculate a simple moving average

Begin by determining the simple moving average (SMA) using the latest closing prices over a designated timeframe, typically 10 to 20 days.

Subtract the SMA from the most recent closing price

Subtract the computed SMA value from the most recent closing price of the asset.

Divide the result by the SMA

Divide the obtained difference by the SMA.

Multiply by 100

Multiply the quotient by 100 to express the KRI as a percentage.

Repeat the process with each period’s closure

As each period concludes, repeat the aforementioned steps to continually update the KRI.

What does the kairi relative index tell you?

Initially introduced by a Japanese investor, the KRI gained prominence in the mid-20th century before yielding to more sophisticated metrics like the Relative Strength Index (RSI) by the 1970s. It primarily quantifies the deviation between an asset’s price and its moving average, with greater fluctuations in volatile assets yielding more pronounced KRI values.
When the KRI plunges to exceptionally low levels, indicating oversold conditions, it suggests a potential price rebound, prompting traders to contemplate buying opportunities. Conversely, soaring KRI values signaling overbought scenarios hint at potential price corrections, prompting traders to consider selling.

Example of how to use the kairi relative index

In the depicted scenario involving a weekly chart of Apple Inc. (AAPL), the KRI is superimposed to offer insights into buy and sell signals. Over a span exceeding seven years, the KRI’s extreme readings typically surpassed 15 on the upside and dipped below -10 at the downside.
While some signals proved beneficial due to Apple’s overall uptrend during the period, others resulted in suboptimal entry and exit points, especially when relying solely on the KRI. Waiting for confirmation of price reversals post-extreme KRI levels could mitigate premature trading actions.

Difference between the KRI and the MACD

Distinct from the Moving Average Convergence Divergence (MACD), which measures the disparity between two exponential moving averages, the KRI solely assesses the gap between closing prices and the SMA. While the MACD incorporates a signal line to facilitate trade signal generation, the KRI offers a more direct assessment of price deviations.

Limitations of using the kairi relative index

Despite its utility, the KRI bears certain limitations:
  • The KRI’s efficacy diminishes during rapidly changing market conditions, necessitating additional confirmation signals.
  • Asset prices may continue moving in their current direction despite KRI fluctuations, highlighting the indicator’s inherent lag.
  • Relying solely on historical moving averages may fail to accurately predict future price movements, warranting supplementary analytical tools.
Here is a list of the benefits and drawbacks to consider.
  • Provides insights into price deviations from moving averages.
  • Offers potential buy or sell signals based on extreme readings.
  • Customizable timeframe for calculating the KRI.
  • May yield false signals during rapid market fluctuations.
  • Relies on historical moving averages, which may not accurately predict future price movements.
  • Requires supplementary confirmation signals for optimal trading decisions.

Frequently asked questions

What timeframes are typically used when calculating the kairi relative index?

The Kairi relative index is commonly computed over periods ranging from 10 to 20 days, though traders may customize the timeframe based on their preferences and trading strategies.

Can the KRI be utilized as a standalone indicator for trading decisions?

While the KRI offers valuable insights into price deviations from moving averages, it is advisable to supplement its signals with other technical analysis tools to enhance trade accuracy and mitigate potential risks.

How does the KRI differ from the Relative Strength Index (RSI)?

Unlike the KRI, which focuses on price differentials from moving averages, the Relative Strength Index (RSI) quantifies the magnitude of recent price changes to assess overbought or oversold conditions. Each indicator offers distinct perspectives on market dynamics.

Key takeaways

  • The Kairi Relative Index (KRI) measures the deviation of an asset’s price from its simple moving average (SMA) over a specified period, aiding traders in identifying potential buy or sell signals.
  • Extreme readings in the KRI can indicate oversold or overbought conditions, prompting traders to consider contrarian trading strategies or wait for confirmation signals.
  • While the KRI offers valuable insights into price differentials, it should be complemented with other technical indicators and fundamental analysis for comprehensive trading decisions.
  • Traders should be mindful of the limitations of the KRI, including its lagging nature, susceptibility to false signals during rapid market fluctuations, and reliance on historical moving averages.
  • To optimize the use of the KRI, traders can experiment with different parameter settings, combine it with other indicators, conduct thorough backtesting, and adapt their strategies to changing market conditions.

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