Zilliqa Price Prediction: Potential Pullback Hints 25% Discount On ZIL Price

CoingapeОпубліковано о 2022-04-03Востаннє оновлено о 2022-04-03

Анотація

The Zilliqa(ZIL) technical chart shows multiple higher price rejection candles at $0.211 resistance. This constant rejection from above may trigger a bearish reversal and plunge the altcoin to the $0.136…

The Zilliqa(ZIL) technical chart shows multiple higher price rejection candles at $0.211 resistance. This constant rejection from above may trigger a bearish reversal and plunge the altcoin to the $0.136 mark. Is its safe to hold during the correction?
Key points

  • ZIL chart shows several high-tail rejection candles at $0.221 resistance
  • The ZIL price could correct till the 0.5 Fibonacci retrenchment level
  • The intraday trading volume in the Zilliqa coin is $3.4 Billion, indicating a 32% loss.
TradingView Chart

Source-Tradingview
The sudden pump in the ZIL/USDT pair after the launch of the ZIL metaverse, ‘Metapolis,’ and recent partnership with other firms registered a 371% gain in just six days. As a result, the altcoin reached a high of $0.231 on 1st April, Its highest in the last eleven months.
However, the coin chart displays a long rejection candle at $0.231 resistance, indicating the sellers are restricting any further growth from this point. These failed attempts from buyers suggest they are exhausted, and a minor correction is needed to renew the bullish momentum.
As per the Fibonacci retracement level, the traders can expect the pullback support to $0.157(0.326 FIB) or $0.136(0.5 FIB). 
Technical indicator
The Relative Strength Index(54) slopes have surged straight to the overbought territory, indicating overvaluation of the coin rice. This bolsters the possibility of a minor retracement to stabilize the aggressive buyers.
The perpendicular rally has surged the ZIL price high above the exponential moving average(20, 50, 100, and 200). However, the coin price should keep a reasonable distance from its moving average to maintain a healthy bull run, which also signals a potential pullback.

  • Resistance levels- $0.221, and $0.256
  • Support levels are $0.157 and $0.136

Пов'язані матеріали

Probability in the Price: How World Cup Odds Are Calculated

**The Probability in the Price: How World Cup Odds Are Calculated** Two major systems released their "championship probabilities" before the 2026 World Cup, and they disagreed on the favorite. Prediction market aggregators listed France at around **17%**, while the Opta supercomputer gave European champion Spain **16.1%**. These numbers look similar, but their production methods are fundamentally different. The market's **17%** is the **price** that clears after hundreds of millions of dollars in trading across platforms like Polymarket and Kalshi, where contracts trade between 0 and 100 cents, directly representing implied probability. This liquidity is provided by crypto-native market makers like Wintermute, though the market still has "the liquidity profile of an early-stage" asset class. In contrast, Opta's **16.1%** is a **simulated frequency**. Its model uses team data (including betting market odds as an input) to estimate match probabilities, then runs **10,000 full tournament simulations**, counting how often each team wins. Which is more accurate? There is **no rigorous, cross-tournament academic study** directly comparing their track records. However, a persistent **longshot bias**—where low-probability outcomes are systematically overvalued—observed in traditional betting for nearly a century, has also been found in modern crypto prediction markets. Research shows low-price contracts on Kalshi/Polymer less likely to pay out than their implied odds suggest. Unlike traditional bookmakers, prediction markets operate on **public blockchain ledgers**, making every transaction auditable and enabling such research. However, price formation is also influenced by **regulatory uncertainty**, as seen in recent US state-level bans and legal battles over jurisdiction. In summary, the "probability" you see is either a **market-clearing price** subject to behavioral biases and liquidity constraints, or a **model-simulated frequency** that partially incorporates market data. The question of which method is more reliable remains open, highlighting the importance of asking: **How was this number produced?**

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Probability in the Price: How World Cup Odds Are Calculated

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