Using Crypto Market Data Across Investment and Trading Strategies
Summary
The article surveys how market and blockchain data may inform long-term crypto investing and short-term trading. For fundamental research, it lists measures such as market capitalization, supply, trading activity, network use, token holders, velocity, total value locked, risk-adjusted returns, network value relative to transactions, and token issuance. It connects these inputs to project selection for buy-and-hold and periodic-investment approaches, while noting that volatility and sentiment data can help frame risk and initial decisions.
For active trading, it describes using volatility, trends, RSI, moving averages, and OHLC levels in swing trading; real-time prices, volume, order books, market depth, candles, and technical indicators in day trading; and fast, multi-venue data plus historical data for arbitrage research and backtesting. The article is an introductory overview, not a tested strategy: it supplies no measured results, implementation rules, or treatment of fees, slippage, and execution risk. It cautions that holding strategies can incur large losses and that crypto is volatile.
Key ideas
- Crypto fundamental research can combine market measures with blockchain activity and token supply information.
- Volatility and sentiment measures can inform project selection and an investor’s expectations of risk.
- Swing traders may use price bands, RSI, moving averages, and OHLC levels to assess entries and exits.
- Day traders depend on timely prices, volume, order book and depth data, and technical indicators.
- Cross-market arbitrage research requires data from multiple venues, while historical data supports backtesting.
- The article provides a broad data overview rather than tested rules or evidence of profitability.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.