What will KALM (KALM) be valued at in 2024, 2025, 2025, and up to 2053? In this KALM price prediction, we will look more closely at KALM's current market position concerning trading volume, market capitalization, and past price movements to support investors set price targets and assess confidence levels. We will also break down expert analysis and technical indicators that give a better view of where KALM might head in the coming months & years.

We utilize one of the most common statistical approaches to time-series forecasting known as the ARIMA model for the price prediction of cryptocurrencies.
ARIMA-ARMA plus differencing to create a stationary time series. A stationary series is one whose statistical properties are constant over time. Differencing cancels out any trend or pattern this method might have, enabling the model to interpret data structure and provide a good forecast.

According to our current KALM price prediction, the value of KALM is expected to INCREASE by 5560%, reaching $0.7082 by mid 2026. As of now, there are 2 technical analysis indicators showing BULLISH signals, while 13 are indicating BEARISH signals. Additionally, 1 indicators suggest a NEUTRAL stance, makes the general sentiment BEARISH for KALM. Added to this is the fact that the Fear & Greed Index is reading 16, indicating that feelings around KALM are cautious or slightly bearish. The aforementioned data places KALM in Oversold state. Since October, KALM has DECREASED by 7%. Based on this trend, we anticipate a possible stabilization in the coming month. By the end of January, the value of KALM is projected to INCREASE by -74% and reach approximately $0.003366. At the moment, KALM is trading BELOW the 200-day moving average, which indicates a BEARISH trend. Besides that, the price is BELOW the 50-day simple moving average (SMA), giving DOWNWARD momentum for KALM. Currently, the RSI reads at 31.38, meaning therefore means that KALM is in the position of NEUTRAL. The Relative Strength Index (RSI) data shows whether cryptocurrency is oversold (less than 30) or overbought (above 70), using an RSI-momentum oscillator.

Mastering KALM technical analysis is the key to predicting its trends effectively. Our page will break down the essential components of KALM technical analysis to equip you with the cryptocurrency market's ups and downs.

The presence of bearish signals across multiple momentum indicators for KALM suggests a prevailing downward trend. Indicators like the Rate of Change, Awesome Oscillator, and Williams %R reflect declining momentum and a potential continuation of the downtrend. This alignment of bearish signals across various metrics reinforces the expectation of further price decreases.

• Relative Strength Index (RSI): The RSI for KALM is 31.38, indicating a bearish trend. The market is showing signs of being in a downward solid phase, with prices likely making lower lows and lower highs. This suggests that bearish pressure could continue.
• Commodity Channel Index (CCI): The CCI for KALM is -152.30, placing it in the neutral zone. This suggests that the market is balanced with no strong overbought or oversold conditions. Rate of Change (ROC): The ROC for KALM is -28.75, which indicates a bearish signal. This suggests that KALM is experiencing downward momentum, potentially leading to further price declines, and signaling a possible bearish trend.
• Awesome Oscillator (AO): AO for KALM is below the zero line, indicating that momentum is shifting downward. This suggests a bearish trend, meaning the market is experiencing downward pressure, and potential sell or short opportunities might arise.
• Williamson%R (14): The Williams %R for KALM is -96.41, indicating a bearish trend. This suggests downward momentum, with potential sell or short opportunities as prices continue to fall.
• Momentum: The momentum for KALM is above zero, suggesting a bullish trend. The price is rising, and the upward trend may continue.

Neutral trend indicators for KALM are evident when the MACD line is close to the signal line, ADX is between 20 and 25, or SAR dots are near the price level. These conditions suggest a lack of clear directional movement, with the market potentially consolidating or lacking a strong trend. Neutral signals imply that market conditions are indecisive, with no strong trend direction indicated.

• MACD (12,26,9): The MACD for KALM is 0.00, placing it in the bearish zone. Not only has the MACD line crossed below the signal line, signaling a potential downtrend, but it is also below zero, confirming the continuation of the bearish trend. Traders might consider selling or taking short positions based on this signal.
• Average Directional Index - ADX (14): The ADX for KALM is 20.05, placing it in the neutral zone. This suggests that the trend strength is uncertain at the moment, and the market does not show a clear directional bias. Traders may need to exercise caution, as the trend could shift either way.
• Parabolic SAR: The SAR for KALM dots are positioned below the price, signalling a bullish trend. This indicates that the price is on an upward trend and may continue.

Neutral oscillator readings for KALM are observed when the MFI is 50, the StochRSI is between 45 and 55, or the UO is between 45 and 55. These values imply a lack of strong momentum in either direction, suggesting that the market is in a consolidation phase or lacks a clear trend direction.

• Money Flow Index (MFI): The MFI for KALM is 23.58, indicating bearish conditions. This suggests weak buying pressure and a potential downtrend.
• StochRSI – Stochastic Relative Strength Index: The StochRSI for KALM is 0.00000000000007390, indicating bullish momentum. This suggests intense buying pressure, with potential for further upward movement.
• Ultimate Oscillator (UO): The UO for KALM is 66.93 neutral, showing no strong directional momentum, indicating the market is in a stable state without a clear trend.

The ARIMA model is defined by three parameters: p, d, and q.

• p: the number of past observations that the model will consider. This is the AR component which is expressed as below: $$ X_t = \phi_1 X_{t-1} + \phi_2 X_{t-2} + \cdots + \phi_p X_{t-p} + Z_t$$
  $$ X_t = \sum_{i=1}^{p} \phi_i X_{t-i} + Z_t $$
• d: the degree of differencing, which is the number of times needed to subtract the previous day’s price from today’s price to make the data consistent at all points in time. (The I component)
• q: the number of past errors in prediction. This is the MA component and is expressed as: $$ X_t = Z_t + \theta_1 Z_{t-1} + \theta_2 Z_{t-2} + \cdots + \theta_q Z_{t-q} $$
  $$ X_t = Z_t + \theta_1 Z_{t-1} + \theta_2 Z_{t-2} + \cdots + \theta_q Z_{t-q} $$

The ARIMA(p, d, q) model is the combination of the AR(p) and MA(q) and differencing: $$ \Delta dX_t = \sum_{i=1}^{p} \phi_i \Delta dX_{t-i} + Z_t + \sum_{i=1}^{q} \theta_i Z_{t-i} $$ Where:

• 𝑋𝑡: the time series X at a time t, and 𝑋𝑡−𝑖 is X at a previous point in time.
• 𝑍𝑡: the error terms or white noise, and 𝑍𝑡−𝑖 is Z at a previous point in time.
• 𝜙: the parameters of the autoregressive part of the model.
• 𝜃: the parameters of the moving average part of the model.
• ∇ 𝑑𝑋𝑡: the differenced time series (d times).