Trading - Execution Strategy and Order Management

By EC Assets Research Team, Trading Strategy · Published 19 May 2026 · Updated 16 October 2026

Trading: Trading is the discipline of executing investment decisions in markets. For institutions, trading determines the difference between theoretical strategy returns and realised returns; the gap often exceeds 100 basis points annually for active strategies.

What Trading Is

Trading is the step that turns an investment decision into a position. A portfolio manager decides what to own; the trading desk decides how, when and where to buy or sell it, choosing the instrument, the venue, the algorithm and the pace. The quality of that step shows up as the gap between the returns a strategy earns on paper and the returns it earns in practice.

Costs come in several layers. Commissions and fees are visible. The bid-ask spread, the market impact of the order itself, price drift while the order waits or is worked, and the cost of orders that are never completed are less visible but usually larger. For high-turnover strategies, such as many factor investing approaches, these costs decide whether a paper return survives.

How It Works

Perold (1988) proposed measuring all of these at once. The implementation shortfall compares the real portfolio with a paper portfolio that trades instantly, at no cost, at the price when the decision is made. Anything that makes the real portfolio worse, including shares that were never bought, counts as cost.

Market impact depends on how much of the market's liquidity an order consumes. A widely used rule of thumb is that cost per share grows with the square root of the order's share of daily volume, scaled by the stock's daily volatility. Tóth and co-authors (2011) find this square-root shape across markets, and Almgren, Thum, Hauptmann and Li (2005), using large US equity orders, estimate an exponent of about 0.6, close to it. For a stock with 2 percent daily volatility, 1 million shares of daily volume and a price of 50:

Square-root rule with Y = 1; a rough guide that varies by market, stock and conditions.

Because the cost per share rises with size, the total cost of an order rises faster than its size. Working the order over time lowers impact but exposes it to price moves in the meantime. Almgren and Chriss (2001) formalised this trade-off, and implementation-shortfall algorithms are built on it: they trade faster when risk aversion is high and more slowly when impact dominates. Schedule algorithms such as VWAP and TWAP spread orders evenly through the day; liquidity-seeking algorithms search displayed and non-displayed venues, a subject covered under market microstructure.

Instrument choice matters too. Exposure can sometimes be gained more cheaply through futures or ETFs than through the underlying securities, at least for an initial position.

Worked Example

A portfolio manager decides to buy 100,000 shares when the price is 50.00, a paper portfolio of 5 million dollars. The order reaches the market when the price is 50.10. The desk buys 90,000 shares at an average of 50.25, pays commissions of 1 cent a share and cancels the remaining 10,000 shares when the price reaches 50.60.

Basis points of the 5 million dollar paper portfolio; delay and execution apply to the 90,000 shares bought, opportunity cost to the 10,000 not bought.

The check is simple: at 50.60 the paper portfolio gains 60,000 and the real one 30,600, a difference of 29,400. If the day's VWAP was 50.20, the same fill is about 10 basis points worse than VWAP, a figure that hides the delay and the missed shares entirely. Commissions, the most visible cost, are the smallest part.

When It Applies (and Limitations)

Impact estimates are rough. The square-root rule describes averages; real costs depend on volatility, news, time of day and what other traders are doing.

Opportunity cost needs a cut-off. The measured cost of unfilled shares depends on when the order is considered over, which should be set in advance.

Benchmarks can be gamed. A trader judged against VWAP or arrival price can choose behaviour that looks good on that measure while raising the true cost.

Cross-asset differences. Bonds, over-the-counter derivatives and private assets trade through dealers or negotiation, where costs are less transparent and measurement relies on dealer quotes or evaluated prices.

Why It Matters for Institutional Investors

Net returns. Measuring implementation shortfall on every order shows how much of a strategy's paper return is lost in execution, and whether capacity limits are near.

Manager due diligence. Asking managers how they measure and control trading costs, and comparing turnover with expected edge, separates strategies that work on paper from those that work in practice; this applies to hedge funds and long-only managers alike.

Best execution. In the US, FINRA Rule 5310 requires broker-dealers to use reasonable diligence to find the best market for client orders, and SEC Rule 605 requires published execution-quality statistics. In the EU, MiFID II requires firms to take all sufficient steps to obtain the best possible result. Regular cost analysis is how firms show they meet these duties.

Policy and oversight. A written execution policy, reviews of broker and algorithm performance, and pre-trade cost estimates for large orders turn trading from a back-office task into a managed source of return.

References

1. Perold, A. F. (1988). The Implementation Shortfall: Paper Versus Reality. Journal of Portfolio Management, 14(3), 4-9.
2. Almgren, R., & Chriss, N. (2001). Optimal Execution of Portfolio Transactions. Journal of Risk, 3(2), 5-39.
3. Tóth, B., Lempérière, Y., Deremble, C., de Lataillade, J., Kockelkoren, J., & Bouchaud, J.-P. (2011). Anomalous Price Impact and the Critical Nature of Liquidity in Financial Markets. Physical Review X, 1(2), 021006.
4. Almgren, R., Thum, C., Hauptmann, E., & Li, H. (2005). Direct Estimation of Equity Market Impact. Risk, 18, 57-62.
5. Harris, L. (2003). Trading and Exchanges: Market Microstructure for Practitioners. Oxford University Press.