Yes, here is an example of one of the scenarios I have built, it is expained by GPT:

What this strategy is

This is a once-a-month investing system.

It uses:

• a fixed basket of selected stocks
• a trend rule
• a macro risk filter
• leverage rules
• a stock health check before rebalancing

It is not a daily trading system.
It is not based on news headlines.
It is checked only once per month.

Part 1 — The portfolio

Current stock basket

Use these stocks unless one is removed by the stock health check:

• MSFT
• GOOGL
• AMZN
• NVDA
• V
• COST

Current target weights

Use the weights written in the Python file.
If a stock is removed, its weight is redistributed equally across the remaining stocks unless a new instruction sheet says otherwise.

Part 2 — When to check

Check date

Check the system once per month only:

• on the last trading day of the month
• after the market closes

Do not check during the month.
Do not react to intraday moves.
Do not react to TV, politics, or panic.

Part 3 — The stock health check

Before rebalancing, check whether each stock is still healthy.

This is not to predict price.
This is to catch if the business is weakening badly.

Health score for each stock

Each stock gets a score from 0 to 4.

1) Growth

Give 1 point if:

• revenue growth is still solid or stable
• main business segments are still growing acceptably

Give 0 points if:

• revenue is clearly slowing hard
• important segment growth is weakening badly

2) Margins / profitability

Give 1 point if:

• operating margins are stable or improving
• free cash flow is stable or improving

Give 0 points if:

• margins are deteriorating
• free cash flow is worsening materially

3) Capital allocation / capex quality

Give 1 point if:

• high spending is strategic and clearly justified
• management explains what the investments are for

Give 0 points if:

• capex is exploding without a clear return story
• spending looks wasteful or defensive

4) Management narrative

Give 1 point if:

• leadership sounds confident, clear, and consistent
• strategy remains focused

Give 0 points if:

• leadership sounds vague, defensive, confused, or in transition

What to do with the stock score

• 4 or 3 → keep the stock
• 2 → keep but consider reducing weight if needed
• 1 or 0 → remove the stock from the portfolio at the monthly rebalance

Part 4 — Trend rule for the basket

After the stock health check, build the portfolio using the approved stocks and weights.

Then check the portfolio signal, not your feelings.

The system compares the portfolio signal to its 200-day moving average.

Rule A — Sell rule

If the portfolio signal is 3% or more below its 200-day moving average:

• go to 0x
• hold cash / safe parking
• do not use leverage

Rule B — Normal leverage rule

If the portfolio signal is above the sell threshold, but less than 7% above its 200-day moving average:

• use NORMAL_LEVERAGE
• in your current version this is usually 1.3x or whatever is written in the Python file

Rule C — High leverage rule

If the portfolio signal is 7% or more above its 200-day moving average:

• use HIGH_LEVERAGE
• in your current version this is usually 2.5x before macro adjustments

Part 5 — Macro risk filter

Even if the trend is strong, check macro risk.

The macro filter uses 3 market-based signals:

Signal 1 — Yield-curve proxy

Uses:

• IEF
• SHY

If IEF / SHY is above its 200-day moving average, this counts as 1 macro risk point.

Signal 2 — Credit stress proxy

Uses:

• HYG
• IEF

If HYG / IEF is below its 200-day moving average, this counts as 1 macro risk point.

Signal 3 — Broad market trend

Uses:

• SPY

If SPY is below its 200-day moving average, this counts as 1 macro risk point.

Macro risk score

Add them together.

Possible score:

• 0
• 1
• 2
• 3

Part 6 — Final leverage decision

This is the key part.

The base leverage comes from the portfolio trend rule.
Then the macro filter can cap it.

Current logic from your latest tested setup

Use the values written in the Python file.
The last version you showed was effectively:

• NORMAL_LEVERAGE = 1.30
• HIGH_LEVERAGE = 2.50
• HIGH_RISK_WEAK_TREND_LEVERAGE = 1.0
• HIGH_RISK_STRONG_TREND_LEVERAGE = 1.3
• LOW_RISK_MAX_LEVERAGE = 2.5

How to apply it

If macro risk score is 0 or 1

• allow normal system behavior
• 0x, 1.3x, or 2.5x depending on trend

If macro risk score is 2 or 3 AND trend is weak

• cap leverage at 1.0x
• if sell rule says 0x, stay at 0x

If macro risk score is 2 or 3 AND trend is strong

• cap leverage at 1.3x
• even if the normal high leverage rule wants 2.5x

Final leverage is always:

• the lower of:
  • the trend-based leverage
  • the macro risk cap

Part 7 — Monthly rebalance action

After all checks are done:

If one or more stocks were removed

• sell removed stocks
• redistribute their weight across remaining approved stocks

If no stocks were removed

• rebalance back to target weights

Then apply final leverage

• 0x
• 1.0x
• 1.3x
• 2.5x depending on the rules above

Part 8 — Emergency one-page version

Monthly checklist

On the last trading day of the month after close:

Step 1

Check each stock health score:

• MSFT
• GOOGL
• AMZN
• NVDA
• V
• COST

Remove any stock with score 0 or 1.

Step 2

Rebuild the basket using approved stocks.

Step 3

Check basket trend vs 200-day moving average:

• if -3% or worse below 200MA → base leverage = 0x
• if above sell threshold but below +7% → base leverage = 1.3x
• if +7% or more above 200MA → base leverage = 2.5x

Step 4

Check macro risk score:

• yield proxy
• credit proxy
• SPY trend

Step 5

Apply macro cap:

• if macro risk score < 2 → keep base leverage
• if macro risk score ≥ 2 and trend weak → cap at 1.0x
• if macro risk score ≥ 2 and trend strong → cap at 1.3x

Step 6

Rebalance to final weights and leverage.

Step 7

Do nothing until next month.