Who Tessera is for

What it is

Tessera is a performance and review platform for traders who want to understand their results from real trade history - not just a spreadsheet or a broker statement. It connects to your accounts (or imports CSVs), surfaces statistics and reports, and optionally helps you test ideas on past trades with the simulator or export rules to TradingView.

Different trading styles get different value from Tessera. This article helps you see where you fit, what to lean on, and what to treat with scepticism.

This is not financial advice. Nothing in Tessera certifies an edge, guarantees future results, or replaces your own judgement. Treat every insight as a hypothesis - then validate with discipline, small size, and forward testing.

What you can do

• See which of the four profile branches fits you - `profile-a-manual`, `profile-a-systematic`, `profile-b`, or `profile-c` - and which Tessera features match
• Use the right tools: deep policies for stable rules; statistics, Trade Review, and notes for flexible styles
• Export policy indicators to TradingView as chart accessories - even if you never merge them into a strategy
• Merge policies into Pine quickly if you develop strategies on TradingView
• Set realistic expectations before you run reports or change live rules

How it works

The problem Tessera addresses

Many traders hit the same walls:

• Journals that die after two weeks - too many fields, no review habit, or only PnL with no structure
• Memory replacing data - after a loss or a win streak, recall of “what I actually did” is unreliable
• Backtests that look perfect, live that disappoints - overfitting, missing costs, or rules that change in real time
• No bridge between “what happened” and “what should I try next” - data sits in a log; improvement stays vague

Tessera focuses on closed trades you actually took, enriched with market context where relevant, so you can review, narrate, and test one change at a time on a fixed history - not pretend the past predicts the future blindly.

Four profiles

Tessera recognises four profile branches. Pick the one that matches how you trade:

Profile A (manual + systematic) is the strongest fit today. Profile B and Profile C both keep execution discretionary - see Choosing between profile B and profile C if unsure.

Profile A - Rules-based traders (best fit today)

Who this includes

• Manual traders with strict entry and exit parameters - same session every time, written playbook, clear invalidation (`profile-a-manual`)
• TradingView strategy developers and algorithmic traders - Pine `strategy()` or own-code execution; Tessera is review + policy source of truth while you place trades (`profile-a-systematic`)

Intraday or swing does not matter as long as your rules stay recognisably the same across the period you analyse. A scalper with a fixed checklist and a swing trader with a fixed setup sheet both fit here.

profile-a-manual - written playbook, manual execution

You trade from a documented playbook and click entries yourself. Tessera validates ideas before you edit the doc.

• Sync or import on a fixed cadence - weekly for API brokers, after each session for CSV prop firms
• Workflow: reports → one simulator hypothesis → edit playbook version → forward journal → compare to frozen benchmark
• Export to TradingView as confirmation (standalone indicator or composed script) - not as an auto-trader Tessera runs for you

profile-a-systematic - Pine / TradingView workflow

You develop or run rules in Pine `strategy()` or your own execution stack. Tessera is especially aligned with reports, policy inject/merge, and cohort-based testing.

• Name accounts so future-you knows the story: `[strategy] + [symbol] + [purpose]`; use separate demo accounts per variant for forward A/B
• Workflow: report → segment simulate → publish policy versions → combine bundle → full-bundle sim → compose Pine → forward demo → promote or revert
• TradingView Strategy Tester shows what your code would do; Tessera shows what you (or your bot) actually did in the broker account

Fastest path for TV developers

1. Save your strategy in Tessera
2. Run Regime Analysis or Exit Placement on imported or synced live history (not only TV’s in-sample backtest)
3. Build policies from slices → simulate on that real cohort
4. Merge policies into your script or download a separate indicator

TV backtests can overfit when parameters are tuned until the equity curve looks perfect. Tessera does not remove that risk for Pine - but grounding review in real executions and testing one rule change at a time on that history is a saner improvement loop than endless parameter scraping.

Where Tessera helps most

The critical caveat - rules must stay the same

Insights from reports and the simulator assume your playbook was stable over the cohort you selected. Tessera answers: *“Given the trades I actually took under roughly the same approach, what patterns appear?”*

If you change entries, sizing, or discretion often, the cohort mixes different versions of you. A filter that “fixes” last month’s trades may not apply to next month because you will not take the same sequence of trades. Read Understanding when results change before treating simulator output as a forecast.

Healthy workflow for Profile A

*Manual (`profile-a-manual`):* import/sync → report → one sim → edit playbook → forward journal → compare to frozen benchmark playbook.

*Systematic (`profile-a-systematic`):* import/sync → report → segment sim → publish → combine → full-bundle sim → compose Pine → forward demo → promote or revert.

Shared steps:

1. Import/sync history → check Statistics
2. Run a focused report on a stable period
3. Form a hypothesis (e.g. “I lose in range regimes”)
4. Test with the simulator on that same period - one change at a time
5. Optional: export to Pine or paper-trade forward before size
6. Journal decisions in notes - what you will test live and how you will know if it failed

Profile B - Discretionary and multi-style traders (`profile-b`, partial fit)

Who this includes

• Traders who use several setups or switch approach with context
• Subjective entries - “felt right,” partial discretion, frequent rule tweaks
• Mix of intraday and swing without one written playbook
• Traders optimising for process and awareness more than mechanical rule extraction

Where Tessera helps

Where Tessera is less optimised

• [Policies](03-strategies-and-policies.md) and [simulator](05-simulator-overview.md) entry filters assume repeatable conditions at entry. If your rules shift trade to trade, “remove trades like X” on past data is weak evidence for the future.
• Exit Placement replay still works on fixed past trades, but if your live exits are discretionary, simulated stops/targets are hypothetical - useful for exploration, not proof.
• Pine merge is most valuable when you already code a stable `strategy()` - discretionary traders may prefer standalone indicators only (see below).

Healthy workflow for Profile B

1. Lean on statistics and visuals - find when and where you trade best, not just total PnL
2. Use reports for narrative - “what does the data suggest?” - then decide in your own words
3. Journal after sessions: notes, short tags on trades, weekly review habit (same day each week beats heroic 30-field logs)
4. Use simulator lightly - e.g. exit distance on a single setup you can name, not whole-account rule trees
5. Avoid optimising until you can name one setup and stick to it for enough trades to matter

Benchmark for forward compare: prior ~20 trades’ expectancy for that named setup, not whole-account policy trees.

Profile C - Review layer before live (`profile-c`, partial fit)

Who this includes

• Traders who want Tessera as a review and context layer before funding live accounts or importing large histories
• Chart-first traders who may keep execution discretionary - pre-live, returning after a break, or learning the platform
• Anyone building a demo cohort first and deferring heavy policies / bundle work until trade count supports it

Where Tessera helps

Where Tessera is less optimised

• Deep Regime Analysis and policy bundles need stable rules and sufficient N - defer until a single-symbol demo cohort reaches roughly 40+ closes on a fixed playbook
• Simulator entry filters and full Pine merge workflows are Profile A territory - profile C treats Remove, exit replay, and cohort concepts as learning goals while execution stays discretionary
• Pre-live demo psychology may not match funded trading - expect statistics to shift when you go live

Healthy workflow for Profile C

1. Connect demo sync or import a minimal CSV - verify entries, exits, and timezones
2. Build statistics and report literacy before spending report quota
3. Accumulate demo trades on one simple setup - avoid changing rules every few days
4. Run Performance Review around 20+ demo trades; defer Regime Analysis until N and rule stability support it
5. Export standalone indicators only when ready - skip full bundle compose until you pick a long-term branch (often A or B)
6. When live at minimum size: distinct account label, sync after every session, update your pre-live report plan

Choosing between profile B and profile C

Both profiles keep execution discretionary and favour statistics, narrative, and chart review over full policy automation.

If you later stabilise one written playbook or move to Pine `strategy()`, graduate toward profile-a-manual or profile-a-systematic.

For all traders - policy indicators on TradingView

You do not have to merge policies into a full strategy to benefit from report work.

From Policy Pine, you can export a standalone indicator that plots entry-filter or context labels on your chart - an accessory to your existing process:

• Highlight sessions or regimes where your historical edge was stronger or weaker
• Keep your execution discretionary while seeing Tessera-derived context on TradingView
• Share one policy version as an indicator without changing your master script

Think of it as a review layer on the chart, not automatic trading. Especially relevant for profile-b and profile-c traders who do not want full strategy merge.

Mindset: hypothesis, validation, grain of salt

Community and industry experience (journals, algo forums, backtesting guides) repeat the same lesson: documentation without review does not improve performance; backtests without out-of-sample discipline fail live. Tessera gives you structured review and counterfactual tools - you still own discipline and validation.

Limitations

• Tessera is not a signal service, trade copier, or guaranteed edge finder
• Simulator does not replay entry logic or predict live results after rule changes
• AI analysis can mis-emphasise patterns - always check the underlying tables
• Market data and imports must be complete enough to trust cohorts
• Discretionary traders (profile-b, profile-c) should not expect policy automation to match how they actually trade
• Requires an active subscription