Market impact

In financial markets, market impact is the effect that a market participant has when it buys or sells an asset. It is the extent to which the buying or selling moves the price against the buyer or seller, i.e., upward when buying and downward when selling. It is closely related to market liquidity; in many cases "liquidity" and "market impact" are synonymous.

Especially for large investors, e.g., financial institutions, market impact is a key consideration that needs to be considered before any decision to move money within or between financial markets. If the amount of money being moved is large (relative to the turnover of the asset(s) in question), then the market impact can be several percentage points and needs to be assessed alongside other transaction costs (costs of buying and selling).

Market impact can arise because the price needs to move to tempt other investors to buy or sell assets (as counterparties), but also because professional investors may position themselves to profit from knowledge that a large investor (or group of investors) is active one way or the other. Some financial intermediaries have such low transaction costs that they can profit from price movements that are too small to be of relevance to the majority of investors.

The financial institution that is seeking to manage its market impact needs to limit the pace of its activity (e.g., keeping its activity below one-third of daily turnover) so as to avoid disrupting the price.

Several statistical measures exist. The most common and simplest is Kyle's Lambda, defined as the slope from regressing absolute returns to volume over some time window (often as short as 15 minutes). For very short periods, this reduces to simply

Volume is typically measured as turn-over or the value of shares traded, not the number. Under this measure, a highly liquid stock is one that experiences a small price change for a given level of trading volume.

Kyle's lambda is named from Albert Kyle's famous paper on market microstructure.

Chart to Scalar Theory, a purely theoretical result, says there is a correspondence between discrete buy and sell orders in the stock market volume and stock market geometry on the boundary. The boundary represents the charts which we can see. If you peel it back, there are buy and sell orders. The idea of the scalar is to encode the properties of the stock market into a scalar which represents a constraint of a hypothetical stock chart constrained by boundary conditions.

${\displaystyle \Lambda _{R_{0}}=s_{o}+\Lambda _{L_{1}}}$ valid for ${\displaystyle p_{1}\leq p_{2}}$

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