The bid-ask spread is the difference between the highest price a buyer will pay (bid) and the lowest price a seller will accept (ask). Market makers — who post both bid and ask quotes simultaneously, providing liquidity — profit from this spread when they buy at the bid and sell at the ask. The spread compensates market makers for two costs: inventory risk (holding positions in securities whose prices can move against them) and adverse selection risk (the risk that a counterparty knows the stock's true value better than the market maker does).

Kyle's Lambda (1985) models price impact: the change in price per unit of order flow, capturing how quickly the market's price adjusts to buying or selling pressure. For highly liquid large-cap stocks, Lambda is very small — a $10 million buy order moves the price by a few basis points. For illiquid small-cap stocks, Lambda is large — the same order might move the price by 1-2%. Understanding Lambda is critical for institutional execution: orders that represent a large fraction of average daily volume have substantial price impact, and execution algorithms are calibrated to Kyle's model to minimize this impact.

Market orders execute immediately at the best available price — they consume liquidity provided by resting limit orders. Limit orders specify a maximum buy price or minimum sell price — they add liquidity to the order book, waiting for counterparties. The decision between market and limit orders depends on urgency: urgent execution (liquidity-demanding) uses market orders; patient execution (liquidity-providing) uses limit orders that can capture part of the bid-ask spread. Stop-limit orders combine a trigger price (stop) with a limit price — providing price protection but risking non-execution in fast markets.

Dark pools, crossing networks, and multilateral trading facilities (MTFs in Europe, ATSs in the US) provide venues for large block trades to execute without pre-trade transparency. These venues reduce information leakage — institutional buyers and sellers can match without revealing their intentions to high-frequency traders who might otherwise trade in front of large orders on lit exchanges. The fragmentation of trading across multiple venues creates complexity: smart order routing technology is required to find the best execution across the entire market ecosystem simultaneously.

High-frequency trading (HFT) uses co-located servers, sophisticated algorithms, and microsecond execution to exploit tiny pricing inefficiencies across venues. HFT provides significant market benefits: tighter bid-ask spreads (HFT market makers compete aggressively, compressing spreads from the levels of the specialist era), more continuous price discovery, and higher overall market liquidity. The SEC's academic research and independent market microstructure economists broadly conclude that HFT improved retail execution quality through tighter spreads, even while generating controversy around fairness.

The 2010 Flash Crash — when the Dow Jones dropped 1,000 points in minutes and recovered almost as quickly — exposed HFT's role in liquidity withdrawal during stress. HFT algorithms that normally provide liquidity by posting bid/ask quotes withdrew simultaneously during the volatility spike, removing market depth and amplifying the move. Subsequent regulatory changes (limit-up/limit-down circuit breakers, single-stock trading halts) were designed to prevent HFT liquidity withdrawal from amplifying isolated volatility events into cascade failures.