Application Flow AI Trading App for STOCKS.pdf

Prepared for: Jipu Miah, Founder, AI-Powered Trading Automation Mobile Application

1. Introduction

This document maps the complete Application Flow for the AI-Powered Trading Automation Mobile Application against every strategy element taught in the source YouTube training. It covers not only the core scan-signal-execute loop, but also the candlestick pattern library, the beginner-to-advanced share-size progression, the sim-to-live onboarding path, the daily consistency and profit-cushion routine, performance diagnostics, strategy diversification, the community/broadcast layer, and the educational resource library referenced in the video. The platform consists of a Trader Mobile App, an AI Signal Engine, live brokerage/market data integrations, a Learning Center, a Community layer, and an Admin Panel.

2. Platform Overview

2.1 Trader Mobile App (iOS & Android)

Authentication and profile management

Live trading dashboard

AI Signal Engine (stock scanner, candlestick pattern detection, audio alerts)

Chart analysis with technical indicators

Trade execution against a connected broker

Auto Trading (algorithmic mode)

Position sizing and risk management tools, including a guided share-size progression path

Portfolio, trade history, and performance diagnostics

Market watch, economic calendar, and notifications

Community / Live Broadcast layer

Learning Center (strategy guide, downloadable resources, recap videos)

Subscription and billing

2.2 Admin Panel

User and subscription management

Signal creation, review, and publishing controls

Market and asset configuration

Broadcast notifications

Learning Center content management

Community/broadcast moderation

Platform analytics and reporting

3. User Roles

Trader (User) — connects a brokerage account, receives AI-generated signals, executes live trades, and progresses through the guided onboarding path.

AI Signal Engine (System) — scans the live market against the five-criteria filter, detects candlestick patterns, computes entries/stops/targets, and fires alerts.

Admin — oversees platform operations, signal quality, Learning Center content, community broadcasts, and reporting.

4. Trader Mobile App Flow

4.1 Registration & Login

Trader opens the app to the Splash Screen, then the Welcome Screen.

Trader selects Sign Up or Login.

Registration collects Name, Email, Phone, Password, Confirm Password, and Terms Acceptance.

System sends OTP via SMS or Email for verification.

Forgot Password supports Email Recovery, OTP, and Reset Password.

After verification, trader lands on the Onboarding Path (Section 4.2) before the live Dashboard.

4.2 Guided Onboarding Path (Learn → Simulate → Fund → Scale)

The app walks every new trader through the four-step path taught in the video before unlocking full live trading, so that account growth mirrors the instructor's own recommended progression.

Step 1 — Learn the Strategy

Trader completes the in-app Strategy Course (see Learning Center, Section 4.13) covering risk management, the five-criteria stock selection filter, and the candlestick entry/exit patterns.

Step 2 — Simulate for 90 Days

Trader trades in a Simulator Mode using the same AI Signal Engine, live-delayed or live pricing, and no real money.

The app tracks a 90-day simulator clock and a running Accuracy % and Profit/Loss Ratio against the trader's sim trades.

If accuracy or profit/loss ratio has not improved after 30 days, the app surfaces a diagnostic prompt asking the trader to review entries, exits, and hold time versus the strategy rules.

Trader must demonstrate a track record of simulated profitability before the app unlocks live funding.

Step 3 — Fund a Live Account

Trader chooses an account type: a Cash Account (no minimum, but funds must settle before reuse), a Margin Account with a US broker-dealer ($25,000 minimum, no Pattern Day Trader restriction issue), or a Margin Account with an international/offshore broker-dealer (lower minimum, leverage such as 4x-6x, no PDT enforcement). The app displays the buying power implications of each choice.

Step 4 — Scale Position Size Across the First 3,000 Trades

The app enforces a share-size ramp so the trader scales up only as a track record is built, exactly as demonstrated in the video's own rebuild-from-$600 example:

Batch 1 (first ~1,000 trades): start at 10 shares on day one, then step up week over week — 10 → 20 → 30 → 40 → 50 → 70 → 100 → 150 → 160 shares. Target: approximately $10,000 of cumulative profit by the end of the batch.

Batch 2 (second ~1,000 trades): scale from 160 shares up through 250 → 500 → 750 → 1,000 → 1,500 → 1,600 shares. Target: approximately $100,000 of cumulative profit.

Batch 3 (third ~1,000 trades): trade at approximately 16,000 shares average size, mirroring the instructor's own 936-trade, $1M+ run. Target: continued compounding toward six- and seven-figure account growth.

The app also models the compounding leverage path for undercapitalized accounts (e.g., starting near $600 with 6x broker leverage), reinvesting each day's gain into the next day's buying power rather than jumping straight to large size.

At every step, the Position Sizing module (4.8) blocks size increases until the account's live metrics (accuracy, profit/loss ratio, and cumulative profit) are consistent with the current batch's target.

4.3 User Dashboard

Central trading hub. Displays: Portfolio value, current balance, Daily/Weekly Profit/Loss, Active Trades, Pending Signals, Today's Market Status, AI Trade Recommendations, Account Health, Onboarding Path progress, and Daily Goal progress.

Quick Actions: Start Auto Trading, Manual Trade, Trading History, Risk Settings, Notifications, Learning Center, Community.

4.4 AI Signal Engine — Five-Criteria Stock Selection

The engine scans the entire listed market continuously and scores every mover against five weighted criteria. A stock meeting all five is A-quality; four of five is B-quality; three of five is C-quality. Only A- and B-quality candidates are surfaced by default; the trader can manually lower the quality threshold, with an in-app warning that doing so historically reduces accuracy, matching the instructor's own caution against trading C-quality setups.

Relative volume — the stock is trading at 5x or more of its 50-day average volume.

Gap / rate of change — the stock is up at least 2% versus prior close, with 10%+ treated as the strongest signal.

Price range — the stock is priced between $2 and $20.

Float — shares available to trade (float) is under 10 million; lower floats score higher, since a low float versus high volume signals a heavy supply/demand imbalance.

News catalyst — a detectable news event (earnings, clinical trial results, FDA action, contract win, etc.) is present and is treated as the reason the other four criteria exist.

When a candidate crosses the enabled thresholds, the engine fires a configurable Audio Alert (ding-style, matching the scanner software referenced in the video) plus a push notification, and opens the candidate on the Chart Analysis Screen (4.10).

4.5 AI Signal Engine — Candlestick Pattern Library

Beyond the bull flag entry pattern, the engine reads and labels the individual candlestick signals described in the video, since the instructor treats these as the alphabet the bull flag pattern is built from.

Large green candle — strong buying sentiment; contributes to squeeze detection.

Large red candle — strong selling sentiment; used to invalidate a pullback (a further red candle after the first pullback candle means do not enter yet).

Long-wick / tug-of-war candle — opened, dipped, rallied, and closed near the open; flagged by the engine as a possible trend-exhaustion warning and surfaced as an exit consideration on open positions.

Dragonfly doji — a specific bottoming candle shape; when it appears at the pullback low, the engine treats it as a bullish confirmation candidate for the entry trigger.

Bottoming tail (lower wick on a red candle) — the stock sold off intraday but buyers rallied it back; the engine treats this as bullish even though the candle itself still closed red.

Each detected candle shape is labeled on the Chart Analysis Screen so the trader can see which signal the engine is reading, not just the resulting buy/sell decision.

4.6 AI Signal Engine — Bull Flag Entry/Exit Pattern

Once a qualifying stock is alerted, the engine applies the bull flag pattern logic to compute entry, stop, and target:

Detect the initial squeeze — a run of five to seven consecutive green candles on the news catalyst, with volume increasing as price rises.

Detect the pullback — price retraces on lighter volume but holds at or above 50% of the initial move (still net bullish). A pullback that breaks below 50% invalidates the setup.

Entry trigger — the first candle to make a new high above the pullback high (optionally confirmed by a dragonfly doji or bottoming tail per 4.5). The engine computes the exact breakout price to the cent from the prior candle's high.

Stop-loss — set at the low of the pullback (the point that invalidates the pattern).

Profit target — the retest of the high of day, or the next resistance level, whichever the engine judges reachable; the engine will not publish a signal whose target sits too close to resistance to clear the 2:1 minimum.

Trade validity check — the engine only publishes the signal if the implied profit-to-loss ratio is at least 2:1. Historical examples from the strategy range from roughly 2:1 up to 10:1 on the strongest setups; sub-2:1 setups are discarded or flagged sub-quality.

First-pullback preference — the engine weights the first and second pullbacks of a fresh move higher than a third pullback, since the strategy treats early pullbacks as the strongest opportunities and flags "overstaying" past a third pullback as lower quality.

Multi-timeframe support — the pattern can be evaluated on 10-second, 1-minute, 5-minute, or 15-minute charts, selectable by the trader.

Confidence score, trend strength, and expected reward are attached to and shown with the signal.

Signals move through states: Waiting, Executed, Cancelled, Completed. From a signal card the trader can View Signal, Accept Signal, Ignore Signal, Execute Trade, or Save Trade.

4.7 Live Trade Execution

Trader (or Auto Trading, see 4.9) accepts a signal and opens the Trade Execution Screen.

Screen pre-fills Buy/Sell, Lot Size, Stop Loss, and Take Profit from the signal.

Risk Calculator shows dollar risk = (entry price minus stop price) times share quantity, computed live against the connected account's buying power, and separately displays total capital deployed versus actual dollars at risk (mirroring the instructor's distinction between position size and true risk).

Trader confirms via a confirmation popup; the order routes live to the connected brokerage.

Filled orders appear immediately in Active Trades on the dashboard with live P/L, cents-per-share, and dollars-per-share metrics.

Exit is triggered automatically at the stop-loss or take-profit level, or manually by the trader at any time.

4.8 Position Sizing & Risk Management Module

This module encodes the position-management rules from the strategy so that share size is never static and risk is always defined before entry:

Position Size Calculator — converts account risk tolerance and stop distance into a share quantity.

Lot Calculator and Maximum Risk per trade (defaults to a 2:1 minimum profit-to-loss ratio).

Drawdown Monitor and Daily Exposure tracking against the trader's daily loss limit.

Risk Score per open position.

Onboarding-batch size cap tied to the progression in Section 4.2, Step 4.

Add-to-winners logic: when an open position moves favorably, the trader (or Auto Trading) can scale in — typically doubling the position — while the module automatically recalculates the blended average cost and can move the stop to break-even on the combined position. Add-to-losers is explicitly disabled: the module will not let a trader increase size on a position that has moved against the original stop, matching the strategy's rule to cut losers rather than average down.

4.9 Auto Trading & the Daily Profit Cushion Routine

Auto Trading Settings let the trader hand execution to the AI Signal Engine within guardrails: Enable Auto Trading, Trading Hours, Risk Level, Maximum Daily Trades, Maximum Daily Loss, Preferred Markets, AI Aggressiveness, and Capital Allocation.

Whether trading manually or on Auto Trading, the app enforces the full consistency routine described in the strategy:

Session start — every new trading day begins at quarter position size (25% of the trader's configured full size).

Building the cushion — the trader stays at quarter size until cumulative daily profit reaches one quarter of the trader's daily profit goal, typically achieved in one to two winning trades.

Scale to full size — once the cushion threshold is hit, the app unlocks full configured position size for the remainder of the session and increases willingness to add to winners.

Give-back protection — if the account gives back the cushion after reaching it, size automatically steps back down to quarter size, or the app prompts the trader to stop for the day.

Time-based stand-down — if no qualifying trade has been taken in a rolling 30-minute window, the app prompts the trader (or auto-halts Auto Trading) that conditions are not favorable and the day should likely be called.

Daily max-loss cutoff — the session hard-stops once the configured Maximum Daily Loss is reached; the strategy sets this equal to the trader's daily profit goal, so the app defaults max daily loss to the same figure as the daily goal, editable by the trader.

Hot-market override — on days where the trader is hitting the daily goal quickly, the app does not force a stop; it continues surfacing A-quality signals and lets the trader keep compounding, reflecting the instructor's own $475,000-in-a-day outcome versus his $20,000 baseline goal.

This routine is what the module surfaces on the dashboard as "Account Health" and daily goal progress.

4.10 Chart Analysis Screen

Candlestick charts across selectable time frames (10-second, 1-minute, 5-minute, 15-minute, daily)

Indicators: EMA, SMA, RSI, MACD, Volume

Trend lines and Fibonacci levels

Overlaid entry zone, stop-loss line, and take-profit line from the active signal

Labeled candlestick pattern callouts from the library in Section 4.5

Gesture controls: zoom, scroll, drawing tools

4.11 Market Watch

Trader opens Market Watch to view a live-scanned list across Forex, Crypto, Commodities, Stocks, and Indices.

Trader can favorite assets, search assets, and monitor prices in real time.

Assets meeting the five-criteria filter are visually flagged and ranked by quality grade (A/B/C), matching the scanner behavior in the strategy.

4.12 Portfolio, Trade History & Performance Diagnostics

Portfolio Screen displays Balance, Equity, Margin, Free Margin, Daily/Weekly/Monthly Profit, ROI, Win Rate, and Open Positions.

Trade History logs Entry Time, Exit Time, Profit/Loss, Duration, Instrument, Screenshot, and Notes for every trade, filterable by Today, Weekly, Monthly, or Custom range.

Performance Diagnostics reproduces the metrics review the instructor demonstrates on his own trading software, so the trader can self-diagnose exactly as shown in the video:

Filter trade history by price range (e.g., isolate only $2–$10 trades) to see accuracy and profit by price band.

Filter and compare accuracy and profit/loss ratio on winning days versus losing (red) days.

Filter by day of week or time of day to spot recurring weak windows.

Side-by-side month comparison (e.g., a lower-accuracy month versus the following month after a filter adjustment), so the trader can see the effect of narrowing their own quality criteria.

Average winner/loser in both cents-per-share and dollars, plus average share size on winners versus losers, so the trader can see whether they are sizing up into strength (the instructor's own pattern of ~16,000-share winners versus ~9,500-share losers).

4.13 Learning Center

An in-app resource library reproducing the educational materials referenced in the video:

In-app Strategy Course covering risk management, stock selection, and chart pattern reading (required for onboarding Step 1).

Downloadable Trading Plan (PDF).

Downloadable Stock Selection Criteria sheet (the five-criteria filter as a printable reference).

Downloadable Small Account Growth Worksheet.

Full candlestick-chart and technical-analysis training module.

Daily Recap Library — auto-generated or admin-published end-of-day recap entries (green-day and red-day) with linked trade history, mirroring the instructor's practice of publishing a recap every trading day.

Recommended Reading list (trading psychology and decision-making titles) with optional audiobook links.

4.14 Community / Live Broadcast Layer

Reproduces the community trading-room element referenced in the video:

Live Broadcast Room — traders can optionally watch a live or admin-hosted trading session, viewing a shared position window and real-time commentary while a session is active.

Community Chat — text discussion tied to the live session or to specific tickers on Market Watch.

Community Leaderboard / shared recap feed of anonymized or opt-in trade results for social accountability.

4.15 Strategy Diversification

Once a trader's Performance Diagnostics show they have scaled a single strategy to the point of diminishing returns (larger size producing lower marginal profit, matching the liquidity ceiling described in the video), the app surfaces a Diversification prompt suggesting the trader enable a second configured strategy profile within Auto Trading Settings rather than continuing to oversize the first.

4.16 Notifications

New job-equivalent alerts: Buy Signal, Sell Signal

Take Profit Hit

Stop Loss Hit

Trade Closed

Market News

Price Alerts

Daily cushion / max-loss status changes

30-minute no-trade stand-down prompts

Onboarding batch milestones (e.g., cleared for next share-size step)

Community broadcast session starting

4.17 Economic Calendar

Displays Upcoming News, High/Medium/Low Impact Events, and Market Holidays so the trader can anticipate volatility around scheduled catalysts, and cross-references entries in Market Watch that already carry a news catalyst per the five-criteria filter.

4.18 Subscription Module

Plans: Free, Premium, Professional. Features: Upgrade, Billing History, Payment Method, Subscription Status. Premium/Professional tiers gate Auto Trading, full Learning Center downloads, and Live Broadcast access, consistent with the video's own paid-community upsell.

5. Admin Panel Flow

5.1 Admin Login & Dashboard

Admin logs into the internal management system.

Dashboard shows Total Users, Active Traders, Daily Signals, Revenue, Subscription Reports, Trade Statistics, AI Performance, and Server Health.

5.2 User Management

View Users

Suspend / Activate accounts

Edit Profiles

Subscription Management

View a user's Onboarding Path progress (sim-trading stage, funding stage, current share-size batch)

5.3 Signal Management

Create, Edit, Delete Signals

Publish Signals

Schedule Signals

Override or manually flag a signal's quality grade (A/B/C)

5.4 Market Management

Manage Assets, Symbols, Categories, and Trading Sessions

5.5 Notification & Content Management

Broadcast Push Notifications, Market Updates, Promotions, and Emergency Alerts

Publish Daily Recap entries to the Learning Center

Manage Learning Center course content and downloadable resources

Schedule and moderate Live Broadcast / Community sessions

5.6 Subscription & Analytics

Manage Pricing, Plans, Discounts, and User Purchases

Analytics Dashboard: Trade Success Rate, User Growth, Revenue, Signal Performance, Engagement Analytics

6. System-Level Flow (End-to-End)

Trader registers, verifies via OTP, and enters the Guided Onboarding Path.

Trader completes the Strategy Course, then simulates for 90 days while the app tracks accuracy and profit/loss ratio.

Trader funds a live account (cash, US margin, or international margin broker) and connects it to the platform.

AI Signal Engine scans the market continuously against the five-criteria filter and the candlestick pattern library.

A qualifying stock forms a bull flag pattern; the engine computes entry, stop, and target, checks the 2:1 minimum, and pushes a signal with an audio alert.

Trader accepts the signal (or Auto Trading executes automatically) and the order routes live to the broker.

Position sizing follows the onboarding share-size batch and the daily quarter-size-to-full-size cushion routine; winners may be scaled in, losers are cut at the stop.

Trade closes at stop-loss, take-profit, or manual exit; portfolio and trade history update in real time.

Session halts automatically on Maximum Daily Loss, on a 30-minute no-trade window, or continues uncapped on a hot-market day.

Trader reviews Performance Diagnostics, reads the Daily Recap, and optionally joins the Live Broadcast / Community layer.

As diagnostics show diminishing returns on size, the app prompts Strategy Diversification.

Admin monitors signal quality, trading activity, Learning Center engagement, community activity, and platform revenue across all users.

7. Conclusion

This Application Flow defines the complete interaction between the Trader, the AI Signal Engine, the connected brokerage, the Learning Center, the Community layer, and the Admin within the AI-Powered Trading Automation Mobile Application. It reproduces the stock-selection criteria, candlestick pattern library, bull flag entry/exit logic, position-sizing and profit-cushion rules, onboarding and share-size progression, performance diagnostics, diversification guidance, and educational/community elements described in the source training material, and provides a complete foundation for UI/UX design, development, testing, and deployment.