Telegaon is a popular website for its price predictions of cryptocurrencies. Many world-renowned financial institutions have mentioned the work of Telegaon. Before making price predictions of a cryptocurrency, we use this methodology.
1. Market Data Collection
We gather live and historical data from trusted sources, including cryptocurrency exchanges, coin-tracking websites, financial news, and trading volume insights. This data provides us with an accurate view of each cryptocurrency’s price trends.
Our data pipeline ingests real-time order book data, trade execution records, and on-chain metrics from major centralized exchanges (Binance, Coinbase, Kraken) and decentralized sources (DEX aggregators, blockchain explorers). Data is normalized across exchanges to account for varying trading pair conventions and timestamp offsets.
2. Technical Analysis
Our system analyzes price patterns using popular technical indicators like moving averages, RSI (Relative Strength Index), and MACD (Moving Average Convergence Divergence). These indicators help identify trends, potential turning points, and momentum shifts.
Beyond standard indicators, we incorporate crypto-specific metrics:
- On-chain activity: Active addresses, transaction volume, gas fees (for EVM chains), and network hash rate provide insight into actual network utilization beyond price.
- Exchange flow data: Net inflows/outflows to exchanges serve as a proxy for potential selling pressure.
- Funding rates (perpetual futures): Tracking funding rate divergence across exchanges reveals leverage positioning and potential squeeze scenarios.
3. Sentiment Analysis
We monitor social media, news sources, and forums to gauge public sentiment around major cryptocurrencies. By understanding general investor confidence or doubt, we can estimate price movement influenced by hype or panic.
Sentiment signals are quantified through:
- Social volume indices: Tracking mention frequency and emotional valence across Twitter/X, Reddit (r/cryptocurrency, r/Bitcoin), Telegram groups, and Discord channels.
- Google Trends data: Search interest scores provide a macro sentiment thermometer.
- Whale alert feeds: Large wallet movements on-chain serve as a leading indicator of institutional or significant retail activity.
4. AI and Machine Learning Models
Using machine learning, we analyze trends and predict future movements based on past behavior and real-time data. These models improve accuracy as they learn from previous predictions and market changes.
Our ML pipeline employs ensemble methods combining:
- LSTM networks: For capturing long-range temporal dependencies in price sequences.
- Gradient-boosted trees: For integrating heterogeneous feature sets (on-chain metrics, macro indicators, sentiment scores).
- Transformer-based attention models: For identifying regime shifts in volatile market conditions.
Predictions are output as probabilistic ranges (10th–90th percentile) rather than point estimates to reflect genuine uncertainty in crypto markets.
5. Risk Assessment
Cryptocurrencies are extremely volatile digital assets. Each prediction includes a risk warning to highlight the level of uncertainty, helping users understand possible fluctuations and make more informed decisions.
Risk factors explicitly modelled include:
- Volatility scaling: Annualized volatility (calculated from 252-day log returns) directly widens the prediction band. High-volatility assets carry substantially wider confidence intervals.
- Liquidity risk: Assets with lower market depth receive wider spreads and greater slippage assumptions.
- Regulatory risk: Qualitative scoring based on jurisdictional clarity and recent enforcement actions.
- Smart contract risk: Code audit status, TVL (Total Value Locked), and exploit history for DeFi assets.
6. Regular Updates
Cryptocurrencies change their performance every second. All price predictions are updated regularly to reflect any sudden changes in the market, economic shifts, or major news events impacting cryptocurrency prices.
Our update cadence:
- Daily: Technical indicator refresh, sentiment score updates.
- Weekly: Full model re-inference, on-chain metric refresh.
- Event-driven: Immediate re-scoring triggered by material events (hard forks, protocol upgrades, regulatory announcements, exchange listings).
Limitations and Important Disclosures
No predictive model can account for all variables that influence cryptocurrency prices. Past price behaviour is not a reliable indicator of future results. Our predictions are speculative estimates, not financial advice. Users should treat these figures as one input among many in their own research process, not as a recommendation to buy, hold, or sell any crypto. We update our cryptocurrency price predictions periodically as new financial data, analyst revisions, and material corporate events become available.
