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The decision to scale (increase the traded lot size of a specific EA) should be based on statistical evidence that indicates your EA has the potential to perform to certain expectations. 

Equal weight should be given to the decision to scale, as to the initial decision to deploy an EA. This guide provides an indicative approach on how to put together and action your scaling plan.

Before You Start Your Scaling Plan

Important: this should be an individual plan that is consistent with your personal trading objectives, your EA portfolio, and your personal financial situation (including account size).

We are going to use a starting lot of 0.10 per trade in the examples in this document —you want to adjust this based on your own risk tolerance.

Whatever your chosen lot size start point, EA scaling should be a pre-planned incremental approach, scaling stepwise based on performance metrics you are seeing in your live trading account.

You should also have assessed the current margin usage of your EA portfolio exposure to ensure that any scaling and related increased margin requirements are appropriate to the size of your account. 

Suggested Scaling Baseline Requirements

Scaling should only be performed when your EA is performing to what you deem to be a good standard. To make this judgment, you need to set some minimum performance standards.

The past performance of your EA is not a guarantee of future performance. If market conditions change, you must remain vigilant and continue to measure performance on an ongoing basis for every live EA you have.

You need to define the key metrics that are important to you. 

Two important metrics to include are:

• The number of trades: to provide some evidence of reliability 
• The period of time: to have had exposure to at least some variation in market conditions

Example of how you may lay your metrics out in a table:

Some may choose to include proximity to original expectations of other metrics, such as minimum win rate, average profit in winning trades, and average loss in those that go against you. 

It should only be after your metrics are met that lot scaling begins on any specific EA.

Lot Size Scaling Ladder

Below is an example of a performance-based scaling plan assuming a 0.10-lot baseline.

Again, this is indicative. It provides a framework with clear review dates and an approach that illustrates incremental scaling. You must still define a regime that is right for your specific trading objectives. 

Risk Guardrails

It is vital to keep an eye on your general account risks and have limits in place that guide your EA use.

Such limits must be constant across all stages of scaling and referenced beyond the risk of a single EA, but to your portfolio as a whole.:

Per-Trade Risk (Nominal)

Trade risk for any one trade should be seen in the context of account size and the dollar risk based on the risk parameters you have set for your EA. 

Specify a maximum percentage of the account balance — a $200 loss is more impactful on a $1000 account compared to a $10,000 account. 

Stick to what is right for you in terms of your tolerable risk level based on your trading objectives and financial situation. A common suggestion is a 1-2% risk of account equity per trade. 

Total Open Exposure

Specifying maximum exposure in the number of EAs open at any time and those that use the same asset class is important for overall portfolio risk management. 

There are tools you can use to monitor exposure risk generally, as well as those that can be used to indicate single asset exposure.

Margin Usage

It is always desirable that your set exit approaches and parameter levels are what your exits are based on. It should not be because your margin usage has meant you have moved into a margin call situation. 

Specify a minimum level to adhere to and make sure that your account is sufficiently funded. If volatility or slippage rises (e.g., news events or illiquid sessions), reduce lot size temporarily.

Scaling Psychology – Managing “Big Numbers”

As lot sizes rise, your emotions may respond accordingly when you see the larger dollar amounts that your EA is generating. 

If you are used to seeing an average profit of $100 and average loss of $50, and suddenly you are seeing significantly bigger numbers, it creates an emotional challenge where you may be tempted to do a “discretionary override”. 

Although there are situations, such as major market events, overexposure in a specific asset, or VPS or account system problems, where such intervention may be considered, generally this would distort the actual performance evaluation of your EA and is not encouraged (unless it is pre-planned).

The table below presents some of the generally accepted challenges and offers suggestions on how to manage them. 

Your Plan Into Action…

In practical terms, your scaling plan should have two components:

1. The key parameters for action on your chosen key metrics
2. Specified periodic review times to make your next scaling decision

This is not a race. Having systems in place facilitates creating the opportunity that scaling brings while still mitigating the risks.

Markets retreated last week, pulling back about 2.5-3% from record levels. While the decline is modest, it is marked by several headwinds that could create further pressure this week.

Government Shutdown Reaches Historic Length

The ongoing shutdown has now reached record duration, and there's still no clear resolution in sight. Healthcare remains the primary sticking point between the two sides. Some reports suggest potential progress, but the jury's still out on whether any deal will materialise or gain bipartisan support before the Thanksgiving holiday season.

Key Economic Data May Be Delayed

The shutdown's impact extends to data releases. Market-influencing government reports, including jobs numbers and CPI data, may be delayed this week — CPI is still technically scheduled, but the shutdown could affect its release. This data delay will make it harder to gauge the economy's true direction and could inject further volatility into markets.

Earnings Season Continues to Impress

Despite these macro headwinds, corporate America is delivering exceptional results. We're seeing an 82% EPS beat rate and 77% of companies exceeding revenue expectations. While we're in the final 10% of S&P 500 reports, some important retail stocks are still due. These consumer-facing companies could provide valuable insights into spending patterns and economic health.

NVIDIA Tests Critical Support Level

AI stocks are facing pressure, with NVIDIA testing a key technical level around $180-$185. The stock experienced five consecutive days of losses before bouncing strongly on Friday with a major wick rejection. If support at $180 breaks, we could see a drop to $165. However, Friday's bounce suggests a possible retest of $193. This is a crucial moment for the AI sector leader, and its direction could influence broader tech sentiment.

Market Insights

‍Watch the latest video from Mike Smith for the week ahead in markets.

Key economic events

Keep up to date with the upcoming economic events for the week.

Artificial intelligence stocks have begun to waver slightly, experiencing a selloff period in the first week of this month. The Nasdaq has fallen approximately 2%, wiping out around $500 billion in market value from top technology companies.

Palantir Technologies dropped nearly 8% despite beating Wall Street estimates and issuing strong guidance, highlighting growing investor concerns about stretched valuations in the AI sector.

Nvidia shares also fell roughly 4%, while the broader selloff extended to Asian markets, which experienced some of their sharpest declines since April.

Wall Street executives, including Morgan Stanley CEO Ted Pick and Goldman Sachs CEO David Solomon, warned of potential 10-20% drawdowns in equity markets over the coming year.

And Michael Burry, famous for predicting the 2008 housing crisis, recently revealed his $1.1 billion bet against both Nvidia and Palantir, further pushing the narrative that the AI rally may be overextended.

As we near 2026, the sentiment around AI is seemingly starting to shift, with investors beginning to seek evidence of tangible returns on the massive investments flowing into AI, rather than simply betting on future potential.

However, despite the recent turbulence, many are simply characterising this pullback as "healthy" profit-taking rather than a fundamental reassessment of AI's value.

Supreme Court Raises Doubts About Trump’s Tariffs

The US Supreme Court heard arguments overnight on the legality of President Donald Trump's "liberation day" tariffs, with judges from both sides of the political spectrum expressing scepticism about the presidential authority being claimed.

Trump has relied on a 1970s-era emergency law, the International Emergency Economic Powers Act (IEEPA), to impose sweeping tariffs on goods imported into the US.

At the centre of the case are two core questions: whether the IEEPA authorises these sweeping tariffs, and if so, whether Trump’s implementation is constitutional.

Chief Justice John Roberts and Justice Amy Coney Barrett indicated they may be inclined to strike down or curb the majority of the tariffs, while Justice Brett Kavanaugh questioned why no president before Trump had used this authority.

Prediction markets saw the probability of the court upholding the tariffs drop from 40% to 25% after the hearing.

The US government has collected $151 billion from customs duties in the second half of 2025 alone, a nearly 300% increase over the same period in 2024.

Should the court rule against the tariffs, potential refunds could reach approximately $100 billion.

The court has not indicated a date on which it will issue its final ruling, though the Trump administration has requested an expedited decision.

Shutdown Becomes Longest in US History

The US government shutdown entered its 36th day today, officially becoming the longest in history. It surpasses the previous 35-day record set during Trump's first term from December 2018 to January 2019.

The Senate has failed 14 times to advance spending legislation, falling short of the 60-vote supermajority by five votes in the most recent vote.

So far, approximately 670,000 federal employees have been furloughed, and 730,000 are currently working without pay. Over 1.3 million active-duty military personnel and 750,000 National Guard and reserve personnel are also working unpaid.

SNAP food stamp benefits ran out of funding on November 1 — something 42 million Americans rely on weekly. However, the Trump administration has committed to partial payments to subsidise the benefits, though delivery could take several weeks.

Flight disruptions have affected 3.2 million passengers, with staffing shortages hitting more than half of the nation's 30 major airports. Nearly 80% of New York's air traffic controllers are absent.

From a market perspective, each week of shutdown reduces GDP by approximately 0.1%. The Congressional Budget Office estimates the total cost of the shutdown will be between $7 billion and $14 billion, with the higher figure assuming an eight-week duration.

Consumer spending could drop by $30 billion if the eight-week duration is reached, according to White House economists, with potential GDP impacts of up to 2 percentage points total.