Trading & Markets
Understanding crypto markets and trading
Plain English
The total amount of a cryptocurrency bought and sold in a specific time period (usually 24 hours). High volume means lots of trading activity and liquidity - easier to buy/sell without affecting price. Low volume means harder to trade and more price volatility.
Technical
Total value or quantity of an asset traded over a specified period. Volume indicators: spot volume (current asset trading), derivative volume, DEX vs CEX volume distribution. High volume relative to market cap indicates liquidity and price discovery efficiency. Wash trading and fake volume are concerns - track volume across multiple sources.
Plain English
A list showing all buy and sell orders at different prices. Buy orders (bids) on one side, sell orders (asks) on the other. When orders match, a trade happens. The "spread" is the gap between highest buy and lowest sell price. Tighter spread = more liquid market.
Technical
Real-time registry of limit orders organized by price level, showing market depth and liquidity. Bid side shows buy orders (demand), ask side shows sell orders (supply). Order book DEXs (Serum, Phoenix on Solana) match orders on-chain. Metrics: spread (best bid-ask difference), depth (liquidity at each price), order book imbalance (buy vs sell pressure).
Plain English
Market order: Buy/sell immediately at current price - you get instant execution but price isn’t guaranteed. Limit order: You set your desired price and wait - you might not get filled, but you control the price. Like shopping: market order is "I’ll pay whatever it costs," limit order is "I’ll only pay this specific price."
Technical
Market orders execute immediately at best available price, guaranteeing fill but not price. Acceptable for liquid markets with tight spreads. Limit orders specify exact price, only executing when market reaches that level. Provide price certainty but no execution guarantee. On-chain limit orders (Solana DEXs) persist until filled or cancelled. Advanced: stop-loss, stop-limit, iceberg orders.
Plain English
The difference between the highest buy price and lowest sell price. A $100 bid and $101 ask = $1 spread. Tighter spreads mean more liquid, efficient markets. Wide spreads mean less liquidity - you lose more money buying and immediately selling.
Technical
Bid-ask spread representing the difference between highest buy order (bid) and lowest sell order (ask). Indicates market liquidity and trading costs - tighter spreads reflect efficient price discovery and low transaction costs. Market makers profit from spread. Percentage spread calculated as: (Ask - Bid) / Midpoint. Critical for assessing DEX vs CEX competitiveness.
Plain English
How easily you can buy or sell an asset without significantly changing its price. High liquidity = lots of buyers and sellers, easy to trade. Low liquidity = few traders, your orders impact price heavily. Like selling a popular product (liquid) vs a rare antique (illiquid).
Technical
Measure of market depth and ability to execute large orders without substantial price impact. Quantified by: order book depth, bid-ask spread, volume, TVL in liquidity pools. Fragmented liquidity across DEXs/CEXs affects execution quality. Solana aggregators (Jupiter) route orders across venues for optimal liquidity. Illiquid markets vulnerable to manipulation and high slippage.
Plain English
Buying an asset where it’s cheap and immediately selling where it’s expensive, profiting from the price difference. Like buying gold in one city for $100 and selling in another for $105. Arbitrage traders keep prices similar across different exchanges.
Technical
Exploiting price discrepancies of identical assets across different markets/venues for risk-free profit. Types: spatial arbitrage (cross-exchange), triangular arbitrage (currency pairs), statistical arbitrage. Arbitrageurs provide efficient price discovery and cross-market liquidity. MEV bots on Solana execute arbitrage at millisecond speeds. High competition reduces arbitrage opportunities to microseconds.
Plain English
Bull market: Prices are generally going up, optimism is high, people are buying. Bear market: Prices are generally falling, pessimism dominates, people are selling. Named after how the animals attack - bulls thrust upward, bears swipe downward.
Technical
Bull market: sustained upward price trend characterized by increasing valuations, positive sentiment, high trading volumes, and capital inflows. Typically follows positive macroeconomic conditions or technological breakthroughs. Bear market: prolonged downward trend with declining prices, negative sentiment, reduced volumes, capital outflows. Crypto cycles often correlated with Bitcoin halving events and macro conditions.
Plain English
FOMO (Fear Of Missing Out): Anxiety that you’re missing profits, leading to impulsive buying. FUD (Fear, Uncertainty, Doubt): Spreading negative information (real or fake) to drive prices down. Both are psychological tactics that influence market behavior.
Technical
FOMO: Psychological phenomenon driving irrational buying during price surges, often creating bubbles. Amplified by social media, influencer marketing, and herd behavior. FUD: Strategic dissemination of negative information to manipulate sentiment and prices. Can be legitimate concerns or deliberate misinformation. Both exploit cognitive biases - successful traders recognize and resist emotional decision-making.
Plain English
Studying price charts and patterns to predict future movements. Uses indicators like moving averages, RSI, and support/resistance levels. Like reading weather patterns to forecast rain. Critics say past prices don’t predict future; supporters say patterns repeat due to human psychology.
Technical
Methodology analyzing statistical trends from trading activity: price, volume, historical patterns. Assumes all information is reflected in price and history repeats. Techniques: chart patterns (head & shoulders, triangles), indicators (RSI, MACD, Bollinger Bands), support/resistance levels. Behavioral finance underpins effectiveness. Limited by market efficiency hypothesis - especially relevant in crypto’s 24/7 algorithmic markets.
Plain English
Evaluating a cryptocurrency’s "true value" by examining the project itself - team, technology, adoption, tokenomics, competitors, roadmap. Like researching a company before buying stock. FA tries to find undervalued projects with strong fundamentals for long-term investment.
Technical
Valuation methodology assessing intrinsic project value through: technology innovation, developer activity (GitHub commits), network effects, token economics, team credentials, partnerships, competitive positioning, regulatory landscape, treasury management. Metrics: TVL, active addresses, transaction volume, revenue generation. Contrasts with TA by focusing on project fundamentals rather than price action.
Plain English
A chart showing price movements where each "candle" represents a time period. Green/white candles = price went up, red/black = price went down. The thick part shows opening and closing prices, thin lines show highest and lowest prices. Traders use patterns to predict movements.
Technical
Price visualization displaying open, high, low, close (OHLC) for each time period. Candle body: open-to-close range (green if close > open). Wicks: high/low extremes. Patterns indicate market psychology: doji (indecision), hammer (reversal), engulfing (momentum shift). Time frames: 1m, 15m, 1h, 4h, 1D. Essential for technical analysis and identifying support/resistance levels.