A Complete Walkthrough

The previous lessons taught the tools one at a time. This one plays the whole game: take a single strategy from a raw export file to a portfolio seat — or to the reject pile — making an explicit decision at every stage. Follow along with one of your own strategies, or run it with a sample.

The numbers below are illustrative examples, chosen to show how decisions get made. Your strategy will produce its own.

The candidate

Say you've got a daily S&P futures strategy from your platform: 7 years of backtest, 412 trades, and a backtest report that looks great. The question AlgoChef answers is not "did it make money?" — your platform already told you that. The question is: would you bet real capital that it keeps doing this?

Stage 1 — Import (Lessons 3–4)

Strategy Hub → Add Strategies → Import Strategy Data. Map the columns, then the settings that matter: Initial Capital that matches your intended allocation, the correct contract so point values convert properly, realistic costs (database costs if your file is cost-free), and the exchange timezone.

Sanity check after import: net profit within costs-explained distance of your platform's figure, 412 trades, dates matching the backtest window. ✓

Decision made: none yet — but the numbers are now trustworthy, which every later stage depends on.

Stage 2 — The scores (Lessons 2, 5)

Open the Quality Report. Suppose it comes back:

Read in order: CSI says "worth taking seriously." Health says "not degrading." The weak leg is Confidence at 55 — decent trade count, but consistency across the history is shakier than the headline suggests. Scroll the report with that lens: the equity curve shows a flat stretch through one year; Top Drawdowns shows the worst period took 14 months to recover. Could you have sat through that without turning it off? Be honest — this question kills more live strategies than math does.

Decision: proceed, with a flag — "watch the consistency evidence, mind the long recovery."

Stage 3 — Monte Carlo (Lesson 6)

Monte Carlo → Robustness Test → Run Simulation. Suppose the Robustness Grade comes back solid, score ranges reasonably tight, but the equity fan shows the 5th-percentile paths hitting a drawdown half again deeper than the backtest's worst.

That last part is not a failure — it's the honest price tag. The backtest's max drawdown is one draw from a distribution; the fan shows the distribution.

Decision: the edge survives resequencing. Capital planning must use the simulated drawdown range, not the backtest's single number.

Stage 4 — Health check (Lesson 7)

Health Monitor. Health was 78 — but check where the strategy is drifting anyway. Suppose the IS/OOS tables show win rate holding, average trade slightly down, drawdowns in line with baseline. Rolling Sharpe flat, not sliding.

Decision: healthy today. Set the weekly traffic-light habit from day one — degradation is a when-not-if risk for every strategy.

Stage 5 — Is the edge actually yours?

Two quick reference checks before the portfolio (both work on any strategy):

• Strategy vs Benchmark — if the strategy just rides the index, buying the index is cheaper. You want alpha, not disguised beta.
• Crisis Dependency — if most of the profit came from a few panic windows (2008, 2020...), the edge is "owning chaos insurance," which pays rarely and by luck of timing.

Suppose both come back clean: modest correlation to the S&P, profits spread across regimes.

Decision: the edge is real and independently earned. This strategy is a legitimate portfolio ingredient.

Stage 6 — Into a portfolio (Lesson 8)

Portfolios Hub → Compose → Quick Build, this strategy plus your other validated ones, Auto allocation, build, inspect, save. Then Portfolio Studio → Robustness tab → Run Robustness Check — walk-forward, Monte Carlo resampling, and stress scenarios in one integrated run. The Capital Sizing result tells you what the portfolio actually needs to meet your risk targets; run it with Size Capital On: Out-of-Sample for the conservative answer.

Decision: trade the portfolio at the capital the robustness check demands — not the capital the backtest makes look comfortable.

The pattern to keep

Every stage asked one question and produced one decision:

1. Import — can I trust the numbers?
2. Scores — is it worth my attention, and where's the weak leg?
3. Monte Carlo — does the edge survive shuffled history, and what's the honest drawdown range?
4. Health — is it still itself?
5. Benchmark & Crisis — is the edge real and mine?
6. Portfolio & Robustness — what does it need to survive the future?

A strategy that passes all six has earned real capital. A strategy that fails one has told you exactly why — before the market charged you for the lesson.