Trading · iOS & Android · Fintech
A mobile trading journal built around discipline, session structure and the behavioural side of trading, rather than just recording wins and losses.
Live on iOS and Android.
Product Designer
Pocket Pixels
Product strategy, UX, UI, interaction design, design system, app-store design and ongoing iteration
iOS · Android
The problem
Traditional trading journals are very good at recording what happened. They are much less useful in the moment when a trader is tired, emotional, over-confident or about to ignore the rules they set before the session.
Trading Journal was designed around that gap.
Instead of focusing only on entries, exits and P&L, the product helps structure the session before trading starts, keeps the trader accountable while the market is live and creates a clearer review once the session is over.
The design challenge was making that discipline useful without turning the app into another complicated trading dashboard.
The product is structured around the trading session itself, from setting rules before the market opens through to reviewing behaviour afterwards.
What I did
The app starts before the first position is opened.
Traders can define their session rules, lock in a maximum loss and check their mindset before they start. That creates a reference point for the rest of the session instead of asking someone to decide what their rules were after they have already broken them.
The design keeps that setup short enough to use every day while still making the commitment feel meaningful.
Emotional trading rarely feels dramatic while it is happening. It is usually a sequence of small decisions: moving a stop, increasing size, revenge trading or ignoring the plan.
The live-session experience focuses on keeping the trader aware of those decisions while they are still actionable.
SOS anti-tilt tools, mindset context and session accountability sit close to the main journey without turning the app into another source of noise during an already intense trading session.
A journal only becomes useful when the trader can see patterns across sessions rather than treating every bad day as an isolated event.
The post-session experience supports text, voice and video reflections, discipline streaks, session history and performance insights.
Later iterations added AI weekly summaries to surface recurring behavioural patterns and give the trader something specific to work on the following week. Apple Watch can add heart-rate context during a live trading session as an additional signal for moments of increased stress.
The finished product turns journaling into a full trading-session loop, helping traders set rules before they trade, stay accountable during the session and review behaviour once the market closes.
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Send the Figma, live product, deck or even a rough message. I’ll tell you what I think it needs, whether I’m the right fit and roughly what it’ll cost.
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