Behind every trading system, whether automated or manual, lies execution logic: the rules that translate analysis into action. Understanding how these decision processes work helps traders design better systems, diagnose problems, and improve performance. This applies whether you're building algorithms or following a manual trading plan.
The Signal Generation Process
Execution begins with signal generation: identifying conditions that suggest a trading opportunity exists. Signals can come from technical indicators, fundamental data, statistical models, or combinations thereof.
Technical Signals
Technical signals derive from price and volume data. Moving average crossovers, momentum indicator thresholds, pattern recognition, and support resistance tests all generate signals that suggest potential trade entries. The specific indicators matter less than their consistent application and validation through testing.
Filter Conditions
Raw signals typically require filtering to improve quality. A trend filter might prevent taking mean reversion signals during strong trends. A volatility filter might pause trading during unusual market conditions. Time filters might restrict trading to certain hours or days. These filters transform raw signals into actionable opportunities.
Confirmation Requirements
Many systems require multiple conditions before acting. A breakout signal might require both price exceeding a level and volume exceeding average. A momentum signal might need confirmation from a related indicator. These confirmation requirements reduce signal frequency but typically improve quality.
Position Sizing Logic
Once a signal passes filters and confirmations, the system must determine how much to trade. Position sizing logic converts signals into specific quantities.
Fixed Sizing
The simplest approach uses fixed position sizes regardless of conditions. Every trade is the same size. This approach offers simplicity and consistency but doesn't adapt to varying opportunity quality or account changes.
Percent Risk Sizing
More sophisticated systems size positions based on risk. If you're risking one percent of capital per trade and your stop loss is five percent from entry, position size equals twenty percent of capital. This approach adapts to stop loss distance and account size automatically.
Volatility-Adjusted Sizing
Some systems adjust size based on current volatility. During high volatility periods, position sizes decrease to maintain consistent dollar risk despite wider price swings. During calm periods, sizes can increase since smaller moves are needed to generate the same risk.
Conviction Scaling
Advanced systems might scale size based on signal strength or quality metrics. Higher-conviction setups receive larger allocations. This approach requires robust measures of conviction and discipline to prevent rationalized oversizing.
Order Execution Logic
Determining what to trade and how much leads to order execution: actually placing orders in the market.
Market Orders
Market orders execute immediately at the best available price. They guarantee execution but not price. For time-sensitive signals or liquid markets, market orders ensure you capture opportunities without delay. The tradeoff is potential slippage during volatile conditions.
Limit Orders
Limit orders specify a maximum buy price or minimum sell price. They guarantee price but not execution. Limit orders provide price certainty but risk missing opportunities if the market doesn't reach your limit. They work well for patient entries but poorly for urgent signals.
Stop Orders
Stop orders become market orders when price reaches a specified level. They're commonly used for entries on breakouts or for stop loss exits. The conversion to market order means execution is guaranteed once triggered, but the execution price may differ from the trigger price during fast-moving markets.
Complex Order Types
Many exchanges offer sophisticated order types that combine multiple conditions. Stop limit orders trigger at one price but then execute as limits. One-cancels-other orders allow multiple contingent orders where filling one cancels the rest. These tools enable more nuanced execution strategies.
Position Management Logic
After entering a position, management logic handles ongoing decisions until exit.
Stop Loss Management
Systems must handle stop loss orders: where to place them initially, whether and how to trail them, and how to execute when triggered. Automatic stop placement ensures every position has defined risk. Trailing logic can lock in profits as positions move favorably.
Profit Target Management
Profit targets define levels where some or all of the position exits at a profit. Systems might take partial profits at initial targets while letting remaining size run. Target management logic determines these levels and handles the scaling out process.
Time-Based Rules
Some systems include time-based management rules. A position might close if it hasn't moved significantly after a certain period. Weekend closures might be mandatory to avoid gap risk. These time-based rules add another dimension to position management.
Scaling Logic
Sophisticated systems might add to winning positions or reduce losing ones based on defined criteria. Scaling in allows building positions as they prove successful. Scaling out allows locking in partial profits while maintaining exposure. This logic must be carefully designed to avoid the common error of averaging into losers.
Exception Handling
Real trading encounters situations that standard logic doesn't anticipate. Exception handling addresses these edge cases.
Partial Fills
Orders don't always fill completely. Systems must handle partially filled orders appropriately, deciding whether to pursue remaining size, accept the partial fill, or cancel the unfilled portion.
Failed Orders
Orders can fail for various reasons: insufficient funds, exchange errors, or connectivity issues. Systems need logic to detect failures and respond appropriately, whether retrying, alerting, or adapting the strategy.
Extreme Market Conditions
During flash crashes, extreme volatility, or liquidity crises, normal logic may produce bad outcomes. Circuit breakers that pause trading during extreme conditions can prevent damage when markets behave abnormally.
Execution logic is where trading theory meets market reality. The best analysis means nothing without execution that translates ideas into positions effectively.
Whether you trade manually or use automation, thinking through your execution logic systematically improves results. Document your process from signal to exit. Identify where decisions occur and what criteria drive each decision. Test whether your execution matches your intentions. Platforms like SkiaPaper provide environments where you can refine execution logic without financial consequences, preparing you for consistent execution when real capital is at stake.