In this twelve-minute hands-on lab, learners set up an isolated paper-trading account, review multi-timeframe market research, create a simulated order, and monitor its lifecycle without connecting a real exchange. Learners calculate planned dollar and percentage risk, configure up to three take-profit legs, record decisions in a trading journal, and review outcomes using R-multiples, dashboard metrics, and trade history.

Lab Introduction: Build a Safe Paper-Trading Workspace

This lab moves from financial concepts to a practical simulated workflow. You will use a web-based paper-trading application to research a market, design a hypothetical trade, calculate its planned risk, and record your reasoning. The objective is not to earn money or produce an impressive performance chart. It is to understand how a financial decision moves from analysis into a structured order and how that decision can be reviewed afterward. Every activity uses simulated money.

Begin by opening the application's website and selecting Google sign-in. Complete the ordinary authentication process and enter the paper-trading workspace. Confirm that your account is isolated from real exchange accounts and displays a simulated starting balance. For the calculations throughout this lab, we will assume a starting balance of $10,000. If the application provides a different starting balance, use the stated example for the exercises and your actual simulated balance for account-specific calculations.

Key points

• The lab uses simulated money in an isolated paper account.
• Goal: research, plan, record and review without real capital.
• No exchange keys are needed, and none should be pasted anywhere.

Optional exchange API credentials and AI service keys are not required for this lab. Do not create, share, or paste private credentials, API keys, recovery phrases, or account secrets into chats, journals, screenshots, or assignments. A real exchange connection is outside the scope of this exercise. The paper account should remain a separate learning environment, and no real deposit, exchange account, or financial commitment is necessary.

Research a Market Before Creating an Order

After signing in, open the Research page and select a supported market symbol such as BTC or BTCUSDT. Review the available multi-timeframe analysis instead of relying on one isolated price movement. Depending on the application's output, you may see trend descriptions, technical indicators, support and resistance areas, price structure, or other market observations. These are research inputs rather than guarantees. The purpose is to practice reading information critically and developing a testable simulated hypothesis.

Compare shorter and longer timeframes. A market may show short-term recovery while maintaining a longer-term downward structure. Conversely, a temporary decline may occur inside an upward trend. Record the evidence that supports your proposed setup and any conflicting evidence. If the analysis is incomplete or unclear, acknowledge the uncertainty rather than inventing a confident conclusion. A strong journal entry explains what the learner actually observed and why a potential trade was considered.

Key points

• Sign in through the normal flow and confirm the starting balance.
• Read the multi-timeframe research for a symbol such as BTC.
• Timeframes can disagree: research is not a guarantee.

Before opening the Paper Trade workflow, describe the proposed direction, entry condition, stop level, and possible take-profit targets. A long position represents a hypothesis that the market will move upward after entry, while a short position represents a hypothesis that it will move downward. Neither direction is inherently safer or guaranteed to succeed. For this lab, the setup is an educational example used to practice risk calculation, order entry, and documentation.

Configure a Paper Trade: Side, Entry, Stop, and Targets

Turn the research setup into a Paper Trade. Select LONG or SHORT, then enter the proposed entry price and protective stop price. For a conventional long setup, the stop is below entry; for a conventional short setup, the stop is above entry. The application also supports up to three take-profit legs, each containing a target price and a percentage share of the original position. When multiple legs are used, their shares should total one hundred percent.

You may also provide an optional quantity and a note explaining the setup. The application checks that the entry remains within twenty percent of the current live market price. For example, when BTC is $65,000, the twenty-percent corridor runs from $52,000 to $78,000. An order that would fill immediately is rejected by this workflow, so the proposed price must also represent a valid pending entry. Passing the distance check alone does not guarantee acceptance.

Key points

• Pick one hypothesis: long (rise) or short (fall).
• Set a valid pending entry, a stop on the loss side, and up to three targets.
• Entry must be within 20% of the live price; an immediate fill is rejected.

After submission, the trade begins in PENDING_ENTRY. When the monitoring process detects the qualifying entry condition, the trade transitions to OPEN. Its entry price cannot be edited after creation, although the stop and take-profit settings can be modified through the supported workflow. A pending trade may be cancelled. Once a trade has filled, cancellation is no longer available; an open position must instead be closed at market. These rules encourage deliberate order planning.

Calculate Planned Maximum Loss Before Submission

The most important calculation in this lab is planned maximum loss at the protective stop. For a simple linear instrument with quantity expressed in units of the underlying asset, multiply the absolute difference between entry and stop by quantity. Consider a simulated BTCUSDT long with entry at $65,000, stop at $63,800, and quantity of 0.01 BTC. The stop distance is $1,200 per BTC. Multiplying $1,200 by 0.01 produces exactly $12 of planned loss.

To express this planned loss relative to a $10,000 simulated balance, divide $12 by $10,000 and multiply by one hundred. The result is exactly 0.12 percent. Now consider a simulated short with entry at $3,000, stop at $3,060, and quantity of two units. The adverse price distance is $60 per unit, so the planned loss is $120. Relative to the same $10,000 balance, that represents exactly 1.2 percent.

Key points

• Planned loss = stop distance × quantity.
• Divide by the balance to get the percent at risk.
• Planned loss is not guaranteed: gaps, costs and slippage can differ.

These calculations assume the order enters and exits at the specified prices, without commissions, financing costs, slippage, or other adjustments. They describe planned stop-loss exposure, not a guaranteed maximum realized loss. Real prices can gap, and this application's minute-based monitoring may detect an exit after the intended stop has already been crossed. A trading journal should clearly distinguish the planned risk amount from the loss that might actually occur under unfavorable execution conditions.

Take-Profit Legs, Reward-to-Risk Ratios, and Position Sizing

Return to the BTCUSDT long example with entry at $65,000, stop at $63,800, and quantity of 0.01 BTC. Suppose the first take-profit target is $66,500 for fifty percent of the position, and the second target is $68,000 for the remaining fifty percent. The first target offers $1,500 per BTC above entry. Dividing this distance by the $1,200 stop distance gives exactly 1.25R for that leg before applying its position share.

The second target offers a $3,000 price difference, corresponding to exactly 2.5R. If both legs execute at their planned targets, the weighted result is 0.50 multiplied by 1.25R plus 0.50 multiplied by 2.5R. This equals exactly 1.875R. In dollar terms, the first half earns $7.50 and the second half earns $15.00, creating a total gross profit of $22.50 against an initial planned risk of $12. Costs and execution differences are excluded.

Key points

• R = the planned initial risk, used as one unit.
• Weight each target leg by its share of the position.
• Risk-based sizing: risk budget ÷ stop distance = quantity.

You can also calculate quantity from a predefined simulated risk budget. Suppose the account contains $10,000 and the learner chooses an illustrative one-percent risk budget, equal to $100. If the proposed stop distance is $50 per unit, quantity equals $100 divided by $50, giving exactly two units. This is only a preliminary sizing calculation. Actual contract specifications, notional exposure, margin requirements, liquidity, minimum quantities, and transaction expenses must also be considered.

Monitor the Order Lifecycle and Read Performance Metrics

After submission, review the order's state. PENDING_ENTRY means the simulated order has not yet filled. OPEN means its entry condition has been detected and the position is active. Under the supported exit workflow, closing at configured take-profit or stop-loss conditions produces CLOSED_TP or CLOSED_SL. A pending order may also be cancelled, while an opened position can be manually closed at market. A manually closed position should be documented using its actual reported exit outcome rather than assuming a target was reached.

The application's background monitor checks market conditions approximately once per minute. Consequently, simulated fills and exits are minute-granular rather than tick-by-tick. Market prices may move beyond the configured entry, target, or stop between checks. The reported execution should be treated as the application's simulated result, not proof that a live exchange would fill at the same price. Do not repeatedly change orders simply because the monitor has not yet completed another scheduled check.

Key points

• PENDING_ENTRY, then OPEN, then CLOSED_TP or CLOSED_SL.
• Pending orders can be cancelled; filled ones are closed at market.
• The monitor runs about once a minute.

Open the dashboard to review the simulated account balance, win rate, average R, open trades, and equity curve. Win rate describes the proportion of closed trades classified as winners, while average R summarizes outcomes relative to their risk reference. These metrics need adequate observations and consistent definitions before they become meaningful. Visit the History page to examine closed trades. Compare the recorded results with the original plan, and identify differences caused by exits, partial targets, or execution assumptions.

Build a Trading Journal and Record Every Mock Order

A trading journal is the permanent learning record associated with your simulated account. For every mock order, record the date, symbol, trade side, intended entry, protective stop, take-profit prices, percentage shares, quantity, and starting account balance. Calculate the planned maximum loss in dollars and as a percentage of the account balance. Also record the reason for the setup, the research timeframes considered, and the assumptions supporting the position. Complete these fields before judging the outcome.

A useful journal record separates what was planned from what actually occurred. Before entry, document the expected reward-to-risk ratios and any position-sizing calculations. While the order is pending, record meaningful changes without rewriting the original reasoning. After closure, add the exit outcome, realized profit or loss, result in R, and relevant fees or simulation limitations. If the trade closes through multiple take-profit legs, calculate the weighted outcome using each leg's share of the original position.

Key points

• Plan fields go in before submitting; outcome and lesson after closing.
• Record R, realized dollars, costs and one specific lesson.
• Review the process, not a single win or loss.

Finally, write one lesson from the trade. The lesson might concern unclear research, an overly ambitious target, incorrect quantity, insufficient liquidity consideration, or a deviation from the planned stop. A profitable trade does not automatically prove that the process was good, and a losing trade does not automatically prove that the process was poor. Review the journal together with the dashboard and trade history to identify repeatable strengths, weaknesses, and calculation errors.

Final Lab Checkpoint: Submit a Mock Order and Explain Risk

Your final deliverable is a complete journal entry for one simulated order. Start with research from the application's Research page. Record your chosen symbol, proposed direction, entry, stop, take-profit levels, quantity, and setup reason. Calculate the planned stop-loss amount using the price distance multiplied by quantity, then express that loss as a percentage of the starting simulated balance. Verify that the entry satisfies the application's distance restriction and does not violate the pending-entry workflow.

Practice Lab: Record a Mock Order and Explain Maximum Planned Loss

Use simulated money only, with a hypothetical starting balance of $10,000 unless stated otherwise. Calculate planned stop-loss exposure as absolute entry-to-stop distance multiplied by quantity for the simple linear instruments in these examples. Express planned loss as a percentage of balance, explain order restrictions, and document the setup in a journal. Assume exact execution without costs only when performing the stated mathematical calculations. Never submit real orders or connect a real exchange.

• Decision 1: A simulated BTCUSDT long has entry $65,000, stop $63,800, quantity 0.01 BTC, and starting account balance $10,000. — Calculate the planned stop-loss amount and percentage of balance.
• Decision 2: The simulated BTCUSDT long uses entry $65,000, stop $63,800, quantity 0.01 BTC, TP1 $66,500 for 50%, and TP2 $68,000 for 50%. — Calculate each target's R-multiple, the weighted result if both targets fill, and the gross dollar profit.
• Decision 3: A simulated short position has entry $3,000, protective stop $3,060, quantity two units, and account balance $10,000. — What is the planned stop-loss amount and percentage of balance?
• Decision 4: A simulated account contains $10,000. The learner selects a hypothetical risk budget of 1% of balance and a planned stop distance of $50 per unit. — What quantity corresponds exactly to the selected dollar risk budget?
• Decision 5: The application's live reference price is $65,000. A learner proposes a pending entry at $80,000, then asks whether an already filled order can be cancelled. — Does the proposed entry satisfy the 20% price-distance guard, and can a filled position be cancelled?

Answer key

For the worked BTCUSDT example, the entry is $65,000, stop is $63,800, and quantity is 0.01 BTC. The planned loss is exactly $12, representing 0.12 percent of a $10,000 simulated balance. Targets at $66,500 and $68,000 with equal position shares correspond to 1.25R and 2.5R, respectively. If both targets execute as planned, the weighted result is 1.875R, or $22.50 gross profit before costs and slippage.

A valid pending order and completed journal are sufficient for the initial checkpoint; you do not need to wait for a fill. If the order eventually closes, update the journal with its recorded outcome and one lesson. Never connect a real exchange or share private credentials for this lab. Remember that a calculated stop-loss amount is only planned risk, not guaranteed loss protection. The purpose is to demonstrate accurate preparation, structured documentation, and responsible simulated decision-making.

Worked example at a glance

Key terms

• Paper trade: a simulated order that uses practice money.
• Paper account: an isolated simulated account with a starting balance.
• Entry: the price at which the order is meant to fill.
• Stop: the protective price that closes the trade at a loss.
• Take-profit leg: a target price with a share of the position.
• Planned loss: stop distance × quantity, in dollars.
• R-multiple: the planned initial risk, used as one unit.
• PENDING_ENTRY: the state of an order that has not filled yet.
• OPEN: the state of a filled, managed trade.
• Notional exposure: entry price × quantity, which is not the same as planned loss.
• Trading journal: a record of the plan before and the review after each order.

Multi Asset Trading Lab is an educational course and does not provide personalized investment, trading, financial, legal, or tax advice. All balances, trading orders, positions, prices, quantities, take-profit targets, stop-loss levels, risk percentages, R-multiples, and performance metrics in this lab are hypothetical or simulated. No real-money trading, investment, deposit, or exchange connection is required or encouraged. The paper-trading application is intended for educational research and simulated order management only. Optional exchange API credentials and AI service keys are not required and must never be shared in chats, journals, assignments, or screenshots. The application's monitoring process checks market conditions approximately once per minute, so simulated entries and exits may differ significantly from real-time exchange execution. Entry validation, stop-loss rules, take-profit settings, and order lifecycle behavior do not guarantee execution at a particular price. Calculated planned maximum loss refers to the estimated loss at the specified stop under simplified execution assumptions; actual or simulated realized losses may be greater because of price gaps, slippage, fees, liquidity limitations, execution timing, contract mechanics, or other factors. Partial take-profit outcomes and weighted R-multiples are mathematical illustrations, not guaranteed results. Risk-based position sizing must account for instrument specifications, notional exposure, minimum order quantities, financing, leverage, margin requirements, and potential liquidation where relevant. Paper-trading win rates, average R, equity curves, and historical results do not predict future performance and may not reflect real market conditions or emotional pressures. Learners should focus on accurate calculations, secure account practices, structured journaling, and disciplined simulated decision-making.