Portfolio

Index basket backtest

A basket backtest with configurable weights, correlation measurement, and drawdown evaluated at basket level rather than per symbol.

MT5 Team / company Navid Investment Team Investment team

Project specifications

Project specifications

Market
US30 / NAS100
TF
M15
Platform
MT5
Client type
Team / company
Delivery window
9 weeks
Stack
MQL5, analysis scripts, a basket report
Strategy
Basket testing + correlation
Modules
Weight allocation + exposure control
Testing
Three basket weightings

Who this was for

Navid Investment Team

Role
Investment team
City
Tehran
Project reference
TBT-1410-35
Trade flow

The client's idea

Navid Investment Team works US30 / NAS100 on M15; the opening brief was: I have single-symbol results; I want to see how a two-index basket actually behaves.

Initial challenge

The team had tested each index alone; combining them could either worsen drawdown or make it look artificially small.

Solution

A basket backtest with configurable weights, correlation measurement, and drawdown evaluated at basket level rather than per symbol.

Why this design

The headline number in the report is basket-level drawdown: single-symbol figures were misleading. It matches how US30 / NAS100 is actually traded and can be tested against the data already available.

Safeguards and risk control

No parameter was optimized on the whole set: part of the data was held back for out-of-sample testing.

Our next-step proposal

The next step is running the selected build on demo and reviewing weekly deviation from the test.

Portfolio

Measured results

These are the figures the test produced — not a promise about future performance.

  • 4 years Test window
  • 13.9 % Max drawdown in test
  • 2 Symbols covered
  • 10 scenarios Scenario test coverage

Portfolio

How the delivery ran

Every project moves through these five phases, with the window for each agreed in the specification.

  1. Discovery and problem framing

    Completed

    Reviewing the client's current test method and the quality of the available US30 / NAS100 data.

    Day 3–7

  2. Written specification

    Completed

    Fixing the assumptions: spread, commission, slippage and the tick model used.

    Day 8–19

  3. Implementation

    Completed

    Preparing the test environment, the run scripts and results that can be compared.

    Day 20–43

  4. Testing and validation

    Completed

    Controlled optimization, out-of-sample testing and forward testing on fresh data.

    Day 44–57

  5. Handover and support

    Completed

    A report separating the optimized part from the robust part, plus the remaining risks.

    Day 58–61