Skip to main content
Track System optimization
18 / 23
Search the archiveLibrary
Library

2006issue C031-5

Layered day-session automation from brackets to rules

Day-session automation can be stacked as replaceable order actions. Conditional tickets, front-end software, and a full mechanical procedure each turn live work into stated entry, scale, stop, or stand-aside rules, while a human still has to disable or repair the stack after a bad print or a lost connection.

  • Day-session automation can be built in layers: broker-side conditional orders, software that automates selected legs such as exits, or a full mechanical procedure that covers both entry and exit.
  • Grouped tickets such as order-cancels-order and order-sends-order can rest a range breakout or release a bracket-exit after the entry fills, but a partial fill still has to be resized by hand.
  • Front-end automation can place and resize related working orders from a price ladder without writing code, yet it depends on a running program and a live datafeed.
  • A mechanical trading system encodes rule-based entries and exits as one testable procedure, and still needs a human to disable or repair it when prints are wrong or the data connection is lost.
Entries in this reading3 entries
Current trackSystem optimization131 readingsRule-based entry292 readingsMechanical trading system322 readings

Build the session in replaceable layers

Day-session automation can be constructed in layers. The first layer is broker-side conditional orders. The next is software that automates selected legs such as exits. The last is a full mechanical procedure that covers both entry and exit.

A long that is split across two profit targets, with a protective stop later moved to the original entry after the first target fills, can require seven discrete actions: one buy, two sell limits, two sell stops, and two cancellations.

State each ticket as a condition or a group

A conditional order is a working instruction that is sent or withdrawn only after a stated fill or price condition is met. An order-cancels-order group withdraws the remaining members as soon as one member fills. It can admit a range breakout by resting opposing long and short orders, or exit an open position with a simultaneous stop and limit so the unfilled side is withdrawn when one side fills.

That paired protective stop and profit-limit is a bracket-exit. An order-sends-order instruction releases follow-on working orders only after the parent entry fills. It can release a protective stop and target bracket after the entry fills, and it can be joined to an order-cancels-order group so those exit legs are placed automatically at initiation.

Conditional orders still need manual resizing after a partial fill. Composing them by hand can be too slow when prices are moving quickly.

Front-end automation is order-management software on a direct-access connection. It can reduce placement to a single click on a price ladder, then recalculate related working orders as size changes, including multi-target, trailing-stop, and add-on constructions that do not require writing code.

Front-end exit logic depends on a continuously running program and a live datafeed. A computer or connectivity failure can leave an open position without its planned protective orders.

Encode entry, exit, and stand-aside as one procedure

A mechanical trading system is a complete pre-specified procedure that turns rule inputs and market state into entry, exit, and abstention signals without case-by-case discretion. A fully mechanical system encodes both rule-based entries and exits, from simple indicator conditions to custom-programmed strategies, so the same procedure can be attached to a chart and sent to the market automatically. A rule-based entry is an objective admission test that fires only when stated market conditions and execution constraints are met.

Because a mechanical system only reacts to the data it receives, incorrect prints or a lost data connection still require a human to disable or repair the procedure.

System construction that relies on historical tests treats entry, exit, and stand-aside decisions as one objective procedure. That is system optimization: evaluating and refining those rules together against historical market state so the procedure is one testable unit. Discretionary traders can still attach automated order-management layers, so the two styles can overlap.

Automated strategy P&L on December 2005 e-mini Russell 2000

Longs produced nearly all of the $8,340 net; shorts added only $220 after a profit factor just above one. The bars are the TradeStation performance-summary totals printed under the 144-tick strategy chart for 7 September through 25 October 2005.
Longs produced nearly all of the $8,340 net; shorts added only $220 after a profit factor just above one. The bars are the TradeStation performance-summary totals printed under the 144-tick strategy chart for 7 September through 25 October 2005.E-mini Russell 2000 Dec 2005 (ER2Z05) · 144-tick bars · 2005-09-07T00:00:00.000Z to 2005-10-25T00:00:00.000Z

The published test used 144-tick bars on ER2Z05 and reported zero open-position P&L at the end of the window. Profit factor is omitted here because it is a ratio, not a dollar amount.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
18 of 23 in the System optimization track
20061-1 pp.Next on System optimizationWhy mechanical rules must be retuned per securityWhether subjective crowd behavior can be reduced to objective systems, indicators, or chart patterns is left as an unresolved system-design question.
All readings on this track · 23 readings
  1. 1984Evaluating mechanical systems beyond net profit
  2. 1987Mechanical systems need more than pretty charts
  3. 1987Evaluating silver moving averages and RSI by scoring rule
  4. 1988Simple systems over optimized complexity
  5. 1988Cycle rule inputs until the parameter search stops
  6. 1990Split-sample tests for stochastic parameter grids
  7. 1993Four-subsystem trading system construction
  8. 1993Randomized price paths for stock system parameters
  9. 1994Mechanical timing with out-of-sample and filter checks
  10. 1995Evaluating asymmetric percent-reversal trading rules
  11. 1996Evaluating a daily volume-strength and new-high new-low timing procedure
  12. 1997Rule-based intraday system design with genetic search
  13. 1997Evolving three-rule systems with genetic templates
  14. 1997Audit the holdout and the exposure before the fitted entries
  15. 2001Inner weights are part of the candlestick signal
  16. 2003Mechanical short-term rules for news-sensitive rallies
  17. 2004Band construction as a testable trading procedure
  18. 2006Layered day-session automation from brackets to rules
  19. 2006Why mechanical rules must be retuned per security
  20. 2006A linear-regression next-bar forecast needs a searchable cutoff
  21. 2015Construct if-then rules, then backtest and optimize
  22. 2015Mechanical system design as a critique of discretion
  23. 2025Joint channel design with a trend filter and stop-loss orders
By fieldSystem design203 readingsBy year2006150 readings
All 131 readings tagged System optimization
Also on System optimization5 readings
1995Evaluating asymmetric percent-reversal trading rules1997Evolving three-rule systems with genetic templates1997Rule-based intraday system design with genetic search2003Mechanical short-term rules for news-sensitive rallies1992Building TRIX crossover and momentum entries on a period grid