Fundamental + Technical Analysis

It tells you what you should and should not own based on the fundamentals of the project, beyond short-term price moves. By researching the project's economics, execution, and adoption, you can size with conviction, hold through noise, and avoid shiny but empty narratives.

Trend describes the market's directional bias on your execution timeframe (and ideally the next future timeframe). You want the wind at your back. In uptrends, pullbacks to support levels offer potential buying opportunities. During downtrends, short term price increases to resistance level may result in a positive price reversal or simply fade while the longer term down trend continues.

Ask ten technical analysts for the "best" trend length and you'll likely get ten answers. What most will agree on is that longer time frames carry more statistical weight—they average more data and reduce noise—while recent data best reflects current price behavior. A quality trend model therefore blends long-term and short-term horizons.

Time-frame choice vs. volatility. Longer time frames work best for low-volatility assets; shorter time frames react faster for high-volatility assets. Since cryptocurrencies are more volatile than most equities, exponential moving averages (EMAs)—which weight recent prices more heavily—are preferred over simple moving averages (MAs), which have a longer lag time in detecting a change in trend.

Small moves often precede big ones. Research on volatility clustering shows that markets spend time in low-volatility "drift" before expanding into larger swings; brief, directional upticks frequently come before larger price moves.

True trend reversals are uncommon without a catalyst. Most counter-moves fade unless there's unexpected news or a clear shift (policy, liquidity, protocol change). Ahead of scheduled events—or even rumors—markets often show pre-positioning: rising volume and subtle trend changes as participants adjust before headlines.

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