# Beginner Guided Practice Lab Apply the beginner material in a repeatable demo routine. Use this workbook alongside the course. Write your answers before opening the solutions. Practical work is self-reviewed; scored knowledge checks are in the Academy. ## 1. Preparation ### Instrument checklist Begin with a product fact sheet: symbol, provider, price units, multiplier, minimum size and relevant schedule. Use the actual demo instrument's specification. This prevents a technically successful click from representing an unintended quantity. ### Session plan Set a hypothetical practice budget and calculate ordinary and adverse-execution scenarios. The budget is an exercise constraint, not a recommendation for live funds. If the minimum size exceeds it, document that the planned order is unsuitable. ### Event awareness Choose one observable setup and a defined observation window. Record qualifying cases even when they are unattractive or lose. A practice log that selects only pleasing examples cannot evaluate whether the rule was followed consistently. ### Risk worksheet Prepare a journal template before the first order. Include planned and actual values, timestamps, costs, reasons and screenshots where useful. Distinguish simulated fills from executable live evidence in every exported report. ### Worked example A hypothetical practice rule allows one contract only when estimated loss is at most 30. An instrument with estimated loss of 45 at its minimum size fails the rule even if the platform allows the order. ### Independent exercise Prepare a go/no-go sheet for that case. Include the arithmetic, the platform's minimum size and the decision that follows the exercise constraint. My inputs and assumptions: My calculation or decision: Evidence that would change my conclusion: ## 2. Practice ### Planned entries Practise placing and cancelling an order while reading acknowledgements and remaining quantity. The objective is correct state interpretation, not obtaining a favorable price. Include an unfilled order so cancellation behavior is actually observed. ### Stop handling Practise a partial-fill scenario if the environment supports it, or use a written simulation otherwise. Requested quantity, filled quantity and remaining quantity must reconcile. Do not claim that a platform produced partial fills if the exercise was only a worksheet. ### Planned exits Practise a protected position and distinguish its trigger condition from its eventual fill. A chart may use a different price stream from the trigger. Record the provider's convention and the observed result without assuming universal behavior. ### No-trade decisions Practise a no-trade decision caused by missing data or an unmet rule. Record the reason with the same care as an executed order. This demonstrates that the plan controls eligibility rather than merely justifying activity after the fact. ### Worked example In a written scenario, an order requests four units, fills one and leaves three working. The learner must identify both current exposure and possible additional exposure before deciding whether to cancel the remainder. ### Independent exercise Reconcile that order and describe the state after a confirmed cancellation of the remaining three units, assuming no intervening fill. My inputs and assumptions: My calculation or decision: Evidence that would change my conclusion: ## 3. Review ### Journal completeness Reconcile journal entries with the demo account's order and execution history. Match identifiers, direction, size and costs. Resolve mismatches before calculating statistics; otherwise the performance report may describe an incomplete or duplicated sample. ### Execution versus intention Review process quality separately from P&L. Classify whether the setup was eligible, size was correct and order state was understood. A losing trade can follow the plan, and a winning trade can reveal a serious violation. ### Rule adherence Summarize the complete defined sample, including no-trade cases and execution problems. Avoid claiming an edge from a short practice run. The educational objective is to demonstrate a reliable process and identify limitations. ### Readiness gaps Choose one improvement with an observable acceptance criterion. Examples include eliminating missing timestamps or preventing uncertain retries. Record the next review window so the change can be evaluated rather than merely announced. ### Worked example The demo statement contains twelve fills, but the journal contains thirteen because one execution was imported twice. Performance should not be interpreted until the duplicate is identified and the reconciliation is complete. ### Independent exercise Describe a duplicate check and explain how a repeated import can be distinguished from two genuinely separate fills at the same price. My inputs and assumptions: My calculation or decision: Evidence that would change my conclusion: ## 4. Beginner practical assessment ### Submit an instrument specification Submit the instrument specification and identify the fields that control quantity and price risk. Explain the source of each field. The reviewer should be able to reconstruct what the order represented without guessing from the symbol name. ### Explain a position-size calculation Show a worked position-size calculation with costs and an adverse fill scenario. Explain rounding and why an invalid input blocks an output. The arithmetic matters more than choosing a particular percentage budget. ### Demonstrate cancel and replace Demonstrate cancel and replace using acknowledgements or a clearly labelled written simulation. Show how intervening fills change the remaining requirement. A clean final screen alone does not prove the transition was handled correctly. ### Defend a no-trade decision Defend a no-trade decision using the information available at the time. Later price movement does not determine whether that decision followed the rule. The assessment asks for process evidence, not retrospective perfection. ### Worked example A learner stays out because the required quote is stale; price later moves favorably. The missed gain does not invalidate the data-quality rule. Rewriting the decision based on the later outcome would introduce hindsight. ### Independent exercise Prepare a final practice portfolio containing a fact sheet, sizing worksheet, order-state trace and no-trade explanation. Identify one limitation of each item. My inputs and assumptions: My calculation or decision: Evidence that would change my conclusion: ## Course project Submit a demo decision log with a no-trade decision and a loss review. ### Self-review rubric - Concepts and reasoning: 25% - Calculations, data and evidence: 30% - Process and risk controls: 25% - Limitations and communication: 20% Record one correction and one next practice task. This rubric is not automatically graded. ## Worked solutions ### Exercise 1 The sheet should show that minimum-size loss 45 exceeds budget 30 and therefore mark no trade for that instrument under that plan. Platform acceptance would not make the order fit the budget. ### Exercise 2 Before cancellation there is one filled unit and three working. After confirmed cancellation with no intervening fill, one unit remains as exposure and zero remains working. Cancelling an unfilled remainder does not close the existing unit. ### Exercise 3 Use stable execution identifiers and account identity where available. Matching price alone is insufficient because different fills can share a price. Preserve original records and document the reconciliation instead of deleting arbitrary rows. ### Exercise 4 A complete portfolio exposes assumptions: specifications can change, planned fills can slip, a written trace may not represent live behavior, and a no-trade rule may need evaluation across many cases. Naming limitations strengthens rather than weakens the submission. ## Further reading - https://www.metatrader5.com/en/terminal/help/trading - https://www.investor.gov/introduction-investing