Market Close


Market Close Strategy, just like an Adaptive Shortfall is designed to reduce cost of executing large orders by minimizing market impact. Its aim is to operate until End Time, which is originally the market close session phase and achieve same or better price than instrument’s one at the end of strategy’s trading.

Market Close Strategy workflow is similar to Implementation Shortfall Strategy. It can be even implemented similar to mentioned above adaptive one. Algorithm divides trading horizon into intervals of length Interval Length in each keeping market volume participation essential to achieve declared traded volume at the End Time. Decision concerning how much of volume should be traded in particular interval is made with regard to some historical data and information about market volume changes in the past. Internal execution of trades in each period can be done according to any other algorithm, like TWAP or POV.

Some part of volume to be traded can be kept for Market-On-Close order. In order to prevent enormous market impact during auction, this amount can be limited by user.

Market Close, similarly to Adaptive Shortfall is cost-reductive strategy. Therefore, as well as in Adaptive Shortfall, average trade price comparision to benchmark execution price marks its effectiveness. If arbitrary benchmark is not provided, price at the end of strategy’s trading is taken as a benchmark. The less is the gap between obtained price and Price Banchmark – the more efficient is an algorithm’s execution.

Finally, like all casual Shortfall strategies, Market Close Startegy can be tilted. Tilt impels market participation to decrease slightly with time. By Risk Aversion management user is able to decide to devote algorithm’s execution evectiveness in order to reduce time risk – strategy trades then more rapidly. Also, stop loss mechanism can be implemented to automatically prevent strategy from executing inappropriate trades during critical market conditions.

Market Data

  • Last trade
  • Order book (full depth – to calculate market volume)
  • Historical market data


End Time Indicates time in which strategy has to finish (by default: Market Close) No
Volume Required strategy’s overall traded volume Yes
Price Banchmark Price for determining strategy’s effectiveness No
Limits Absolute limits of orders’ prices No
Interval Length Length of the single trading interval Yes
Risk Aversion Defines how rapidly the algorithm will be executed biasing between time/price risk Yes
Tilt Indicates whether strategy should be more active in the beginning or not No
Auction Participation Allow to limit (from above and below) prticipation in close auction No


Open position

Side Buy or Sell
Amount Part of Volume adequate to current interval market participation
Price Last market price
Type Price limit / Market order

Market Close strategy’s opened positions strongly depend on subalgorithm used in implementation. It keeps calculated market participation in each interval but this participation can be approached by other algorithm, designed for it.

Side Buy or Sell
Amount Constricted by Auction Participation relative to market volume on close
Price Last market price / Price Banchmark
Type Market order

Strategy can also place Market On Close order in the market, which will be executed in auction at market close phase.

Close position

In general, strategy does not open more position than it should execute in total. So, if the stop loss mechanism does not have to be used, there is no need to close any in other way than executing them.


Strategy terminates at End Time, after execution all of demanded Volume.

Time frame

Strategy bases on some trade horizon between moment of its start and End Time. Its main aim is to reduce market impact during quick, until time executions of very large orders. It is originally designed to work before and during market close session phase, so is considered as daily trading algorithm.

Further information & source

  • Barry Johnson, Algorithmic Trading & DMA: An introduction to direct access trading strategies, 4Myeloma Press, 2010.