BFF2701 Chap.6 Market Making and Information
Market Making and Information
A market maker posts prices and absorbs temporary order imbalances, but earns the spread while facing inventory and information risk. A buy order can come from a noise trader with liquidity needs or an informed trader who believes value is higher. Because the dealer cannot observe type directly, order flow changes beliefs. Repeated buys can cause quotes to rise; repeated sells can cause them to fall.
This adverse-selection channel links trading to price discovery. In Kyle-style reasoning, order flow combines informed demand with noise, and lambda describes price sensitivity to net order flow. A larger lambda means a given imbalance produces a larger price change, which is consistent with lower depth or greater information content.
The informed trader balances expected profit against the price impact caused by trading more aggressively. Dealers also manage inventory by adjusting quotes to attract offsetting flow. A complete answer separates quote revision due to information from adjustment due to unwanted inventory, then explains how both affect spreads and execution.
What this chapter covers
- 01
Dealer quotes and spread revenue
- 02
Informed and noise traders
- 03
Adverse selection
- 04
Bayesian quote revision
- 05
Inventory control
- 06
Kyle lambda and market depth
- 07
Order flow and price discovery
Worked example · free
Use Kyle lambda to read order-flow impact
- +1Initial impact = 0.0004 times 7,500 = $3.00.
- +1Revised price = $18.00 + $3.00 = $21.00.
- +1With lambda $0.0007, impact = 0.0007 times 7,500 = $5.25.
- +1The second revised price is $18.00 + $5.25 = $23.25.
- +2Raising lambda from 0.0004 to 0.0007 increases the same order's impact by $2.25, or 75% of the first $3.00 impact.
- +1The higher lambda describes greater price sensitivity and lower market depth, not automatically better forecasting by the buyer.
Key terms
- Market maker
- A trader that quotes prices and stands ready to transact.
- Noise trader
- A trader whose order is driven by liquidity or motives unrelated to private value information.
- Informed trader
- A trader with information about value not yet fully reflected in price.
- Adverse selection
- Expected loss from trading with a better-informed counterparty.
- Kyle lambda
- A coefficient measuring price response to net order flow.
- Price discovery
- The incorporation of information into transaction prices and quotes.
Market Making and Information FAQ
Why does a dealer raise quotes after buy orders?
Buying pressure may signal that value is higher or leave the dealer short of desired inventory. Both channels can justify upward quote revision, although their predicted persistence can differ.
Does every buy order contain information?
No. Noise trading hides informed activity. The market maker updates probabilities from order flow rather than observing trader type directly, so a single buy never proves private information.
What does a high Kyle lambda mean?
The price changes substantially for a given net order flow. This is usually read as low depth or high information sensitivity, provided order size uses a consistent unit.
Why not trade the entire informed quantity immediately?
Aggressive size moves price against the informed trader. Optimal trading balances informational advantage against endogenous price impact, because revealing the signal too quickly erodes the profit opportunity.
How can I separate information from inventory effects?
Information-based quote revision should relate to inferred value and may persist. Inventory adjustment tries to attract orders that reduce an unwanted position and can reverse once inventory normalises. Observed quotes can reflect both, so use order history, persistence and dealer position evidence rather than claiming one cause from a single trade.
Exam move
Draw the information loop: private signal, informed order, mixed order flow, dealer inference, quote revision and new price. Then add a separate inventory loop. For calculations, write the linear price rule and units before substituting. For interpretation, connect a change in lambda to depth and price impact. Avoid claiming that every observed order is informed; the model depends on uncertainty about trader type.
Run a quote clinic with three diagnoses. If buys continue and the revised price persists, information is plausible. If a dealer with an unwanted short position raises both sides to attract sellers, inventory control is plausible. If costs are fixed and order flow is uninformed, order processing helps explain the baseline spread. Real observations can contain all three, so state what further evidence would separate them.
For Kyle calculations, create a unit line before arithmetic: prior price in dollars, net order flow in shares and lambda in dollars per share. Recalculate after changing order size, then after changing lambda. The first comparison isolates flow; the second isolates market depth or information sensitivity. Check that positive net buying increases price under the chosen sign convention. Link the model back to behaviour.
An informed trader cannot treat price as fixed because larger orders reveal more and create greater impact. Noise orders provide camouflage, while the market maker prices the probability of informed flow. This strategic feedback is the explanation behind the coefficient, not an optional add-on.
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