To explain the influence of order flow on asset prices, economists tend to focus on three things:

  1. Trading is not cost-free:
    Dealers generally charge a bid-ask spread. In the presence of such spreads, aggressive buying/selling automatically move the price up to the ask and down to the bid on average.

  2. Limits to arbitrage:
    Trading is never unlimited, as dealers are constrained by position and loss limits, while asset managers and retail traders are constrained by funding constraints and risk aversion influences their psychological biases. If investors were risk neutral and could trade unlimited amounts of an asset, its price will only move in response to the arrival of new information. But rigorous evidence shows that asset prices move in response to non-informative shocks. Daily price moves are driven by the net demand shock from one set of customers and the supply elasticity of another. Moreover, these shocks come frequently from exogenous influences, like private information about future returns (cash flows), changed perceptions of risk (discount rates), or pure liquidity needs such as end-of-month inflows to retirement funds. Exogenous influences on corporate currency trading include domestic and foreign GDP, inflation, and barriers to trade. Exogenous influences on retail traders include private information (or perceived information, as discussed below) and pure liquidity needs.

  3. Asymmetric information:
    Private information is gathered by armies of analysts who pore over financial reports, meet management, and visit competitors. They also methodically track macroeconomic variables, such as prices, interest rates, and output, that are publicly announced, yet necessarily reported with a lag. o motivated traders might combine publicly available data about past macroeconomic conditions with their own insights to derive private estimates of current values.

But more recently, academics suggest that private fundamental information is naturally dispersed among customers and that dealers can infer this information by observing patterns in order flow.

Better business conditions and expanding internal demand, for example, automatically generate rising currency demand from manufacturing firms. A dealer could infer the economy’s underlying change in strength by observing that currency demand is consistently rising among importing firms. And because trades between dealers and customers are not revealed publicly, that dealer’s information would be private.

Whether customers aggressively seek information or passively reveal information through trading motivated by other factors, this perspective implies that customer order flow (in particular, speculative customers like hedge funds and CTAs) has predictive power for macro fundamentals and for future exchange rates.

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Reuters Dealing Screenshot (Source: Reuters)

How can we use Order Flow in our trading?

In equity markets, private information relates to the fundamental value of equities, with tons of analysts bearing CFA certifications and in love with their spreadsheets doing the work.

With this centralized order flow and disclosure, private information about order imbalance is often quickly revealed, thus becoming public information and therefore no longer price sensitive.

There is a well-recognized information hierarchy from corporate insiders to institutional investors to individuals.

Such an information hierarchy is critical to the standard models of price discovery where market makers don’t have private information and instead learn from trading against insiders.

Order flow is technically defined as the cumulative flow of signedtransactions but it is important to note that order flow is not the same as demand or supply. Order flow measures actual transactions, whereas textbook supply and demand does not need any transactions whatsoever. In demand/supply models, shifts in macro fundamentals cause shifts in demand and thus price, but without any transactions taking place, or needing to take place, in order for the price change to occur.

What makes this important is that traditional economics is at odds with the actual functioning of the marketplace. Textbook models are unable to account for the strong positive correlations between signed order flow and the direction of price changes found in the data because they assume that all demand shifts are driven by changes in public information. So by developing an order flow based view of market asset pricing, one can unlock exploitable arbitrage opportunities.

It is also worth pointing out that Order flow can and does reveal the intentions of private information because if the information is available and seen as valid, it will be acted upon. And when it is acted upon, it shows up in the flow.

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Order Flow Price Action. Source: Bloomberg

To sum up: The existence of private, dispersed information, makes order flow very important because it’s only through the price discovery mechanism, i.e., through trading between informed and non-informed participants, that information is disseminated.

Aggressive one-way flows from a non-quoting counterparty (large speculators) contain private information that can and does influence future asset prices because participants trade based on their expectations for future developments.

That’s why it’s imperative to trade in the direction of clear sentiment and flow. By learning to “read” the flows correctly, you will be trading in line with the informed players and, in a fashion, becoming an informed participant yourself.


References:

Bjønnes, G., and D. Rime, 2002, Volume, order flow and the FX market: Does it matter who you are?
working paper
, Stockholm Institute for Financial Research.

Cheung, Y., M. Chinn, and I. Marsh, 2000, How do UK-based foreign exchange dealers think their market operates,
NBER working paper 7524
, February

Evans, M., and R. Lyons, 2000, The Price Impact of Currency Trades: Implications for Intervention,
working paper
, U.C. Berkeley.

Evans, M., and R. Lyons, 2002a, Order Flow and Exchange Rate Dynamics,
Journal of Political Economy
110: 170 – 180.

Evans, M., and R. Lyons, 2002b, Are Different-Currency Assets Imperfect Substitutes?
working paper
, U.C. Berkeley.

Evans, M., and R. Lyons, 2003, How Is Macro News Transmitted into Exchange Rates,
NBER working paper 9433
.

Goodhart, C., T. Ito, and R. Payne, 1996, One day in June 1993: A study of the working of the Reuters 2000-2 electronic foreign exchange trading system. In
The microstructure of foreign exchange markets
, edited by J. Frankel, G. Galli & A. Giovannini. Chicago: University of Chicago Press

Osler CL. 2000. Support for resistance. FRBNY Econ. Policy Rev. 6(2):53–68

Osler CL. 2003. Currency orders and exchange-rate dynamics: an explanation for the predictive success of technical analysis. J. Finance 58:1791–819

Osler CL. 2005. Stop-loss orders and price cascades in currency markets. J. Int. Money Finance 24:219–41

Osler CL. 2009. Foreign exchange microstructure: a survey. In Encyclopedia of Complexity and System Science, ed. RA Meyers. New York: Springer

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