How to Build a Balanced EA Portfolio

A market bubble occurs when asset prices rise far beyond any reasonable valuation.

It is driven by speculation, emotion, and the belief that prices will continue rising indefinitely. 

For traders, the challenge is more about finding a way to manage a bubble, rather than just identifying that one exists.

By their very nature, bubbles can persist far longer than any logical analysis suggests. There are opportunities as they develop, but timing their peak is virtually impossible. 

Understanding their characteristics and having a systematic way of managing bubbles in your trading strategy is worth considering for any trader.

What is a Bubble?

Market bubbles have distinct features that separate them from normal bull markets or even overvalued conditions for a particular asset:

Dramatic Price Appreciation Disconnected From Fundamentals

In a bubble, traditional valuation metrics become meaningless. 

Company or asset fundamentals that usually matter to market participants are ignored in the hope of what might be.

Cash flow, profit margins, competitive positioning, and (in some cases) producing revenue may be dismissed. 

Widespread Participation And "This Time Is Different" Narratives

Bubbles require mass market participation. 

When every headline you see or article you read references "this time is different," or "the old rules don't apply anymore," it is a sign that the collective psychology has shifted from normal caution.

Social media may begin to explode with ever more frequent success stories, and for the individual trader, the fear of missing out becomes increasingly overwhelming.

Credit and Leverage Fuelling Demand

Bubbles are typically accompanied by easier credit conditions. 

When interest rates are lowered and investors are confident in general economic conditions, any spare cash is put to work.

In stock or other market bubbles, you may see retail traders maxing out credit cards to buy call options, with the put/call ratio becoming increasingly distorted.

This leverage often amplifies the rise and the eventual fall, making the risk even more acute and potentially damaging to trader capital.

Vertical Price Charts in Final Stages

One of the telltale signs of a bubble's final phase is a parabolic price chart.

Prices seem to go up daily, and every minor pullback is short-lived (creating more buying pressure). 

This is the euphoria stage. It is where the greatest danger is.

The fear of missing out on further moves is at its highest, and a logical willingness to take profit off the table diminishes in the minds of ever more excited traders.

New participants may continue to enter solely for the way the price is appreciating. Entering into the move only understanding that what they are buying is going up, so they want to join in too.

Bubble vs. Overvalued: Key Differences

Not every expensive market is a bubble. Several characteristics distinguish a bubble from a simpler and far less dangerous overvaluation:

Elevated Valuations With Reasoned Fundamental Justification

An overvalued market has stretched valuations, but can point to real supporting factors (at least to some degree). 

Examples include strong earnings growth, low interest rates, disruption in service or productivity, and providing genuine temporary value.

Even if prices respond to less obvious immediate influencing factors, such as international events, policy changes, and supply issues, the fact that some factors justify continued positive sentiment (even if somewhat unfulfilled) is a positive sign.

Linear or Steady Uptrend

Overvalued markets tend to grind higher with a more sustainable trend rather than a vertical spike. There are normal corrections along the way, even if the highs and lows of a fluctuation are higher. 

Reasonable Participation Levels

There is evidence of institutional investors buying on any dips, but common retracements last days or even weeks.

Retail participation exists but isn't frenzied and plastered all over social media every day or referenced in mainstream media consistently.

Some Scepticism Still Exists

There will be some legitimate and contrary opinions about valuations. Major financial media will present both bearish and bullish cases when a stock is discussed.

Trading Strategies for Potential Bubble Management

Here is the scenario: You bought early in the up move, you are now in profit, but some of the bubble signs are beginning to show up in your thinking.

Tiered Profit-Taking Strategies

Don't try to pick the top. As an alternative approach, begin to scale out systematically with partial closes. This will alleviate the potential for FOMO creeping in. 

You could stage this with set points, e.g. sell 30% when you've doubled, another 30% when you've tripled, 20% when conditions clearly show evidence of entering bubble territory and, having banked a substantial profit already, you keep the final 20% with a trailing stop for the final run if it happens.

Trailing Stops With Wider Bands to Accommodate Volatility

Let’s assume you see the merit in some form of trial stop. In bubble conditions, normal stop distances will get you whipsawed out. Use percentage-based trailing stops or ATR multiples with enough room to accommodate bigger intraday moves.

For example, if your norm is to trail your stop 1.5 x ATR behind price at the end of every candle, then in increasingly volatile conditions during a parabolic move, consider 2,5 x ATR to allow room to move while still offering protection against price collapse.

Reduce Position Sizing and Leverage

The temptation in bubbles is to maximise gains by increasing your margin and entering more and more positions in one asset. 

High leverage and significant single asset exposure in bubble conditions is a potential death sentence to trading capital. 

Recognising the added risks you are contemplating before entry is critical. Combining this with an approach that reduces position sizing and increases margin requirements is consistent with good trading practice as risk increases.

Planned and Rigid Exits

Before buying, you should have already made decisions on what exit approaches you should take and the parameters at which they will be executed, 

Having the exit plan as you enter can limit the chance of getting trapped by greed. Neglecting this and focusing on the opportunity alone can be disastrous.

Never Assume You Can Time the Top

It is usually a big mistake if you believe you will recognise the exact top and exit perfectly. Let’s be frank, even if you hit it lucky once, you won't be able to every time — no one does.

Recognise Behavioural Biases That May Affect Your Judgment

Bubbles can create powerful psychological forces.

Anchoring bias may mean that you fixate on peak prices. Confirmation bias makes you seek information supporting your bullish view and ignore opposing evidence. Recency bias makes you believe the recent trend will continue indefinitely. 

The indisputable key to any bias management is awareness and honesty that some markets may just not be for you (or if they are, to proceed with extreme and continuous caution).

Psychological Preparation for Rapid Reversals

Mentally rehearse the worst scenario and clarity of planned action, e.g., “if it drops 10% in three days, I will ….”.

Having thought through your response and armed with unambiguous exits in advance will make execution easier when emotions run high and begin to dominate. 

Final Thoughts

Extreme valuations, little fundamental underpinning, parabolic price action, and universal bullishness should be part of your bubble identification checklist and flag that your bubble action plan should be implemented.

If you are already in, or tempted to be so, then approach bubbles with honesty, awareness of your trading self and extraordinary discipline to follow through, as predicting what and when things may dramatically turn is close to impossible. 

Never forget you are not smarter than the market, but you can (potentially) be smarter than many traders by planning and doing the right thing.

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.

You've been using a 30-pip trailing stop for as long as you can remember. It feels professional, manageable and relatively safe. 

But during volatile sessions, you see your winners get stopped out prematurely, while low-volatility winners drift back and hit stops that are relatively too tight. 

Same 30 pips, different market contexts, but inconsistent in the protection of profit and overall results.

The Fixed-Pip Fallacy?

Traders gravitate toward fixed pip trailing stops because they feel concrete and calculable. The approach is easy to execute, readily automated through platforms like MetaTrader, and aligns with how most people naturally think about profit and loss. 

But this simplicity masks a fundamental problem. 

A twenty-five pip move in EURUSD during the London open represents an entirely different market event than the same move during the Asian session. The context matters, yet the fixed-pip approach treats them identically. 

This becomes even more problematic when you consider different currency pairs. GBPJPY might have an average true range of thirty pips on an hourly chart, while EURGBP shows only ten. The same trailing stop applied to both instruments ignores the reality that volatility varies dramatically across pairs.

Timeframe introduces yet another layer of complexity. Take AUDUSD as an example: a ten-pip move on a four-hour chart barely registers as meaningful price action, but on a five-minute chart it represents a significant swing. The fixed-pip method treats these scenarios as equivalent.

The natural response might be to use something more sophisticated, like an ATR multiple. This accounts for your chosen timeframe, the instrument's normal volatility, and even session differences. But it brings its own complications. 

When do you measure the ATR? Do you use the value at entry, knowing it might be distorted by sessional effects? Or do you make it dynamic, which becomes far more complex to implement in practice?

Perhaps there's another way forward that doesn't rely on abstract measures of volatility but instead responds directly to the movement of price in relation to the trade you're actually in—accounting for your lot size and the profit you've already captured. 

Maximum Give Back: The Percentage Approach

Instead of asking "how do I protect profit after fifty pips," ask "how do I protect profit after giving back a certain percentage of open gains." 

Consider a maximum give-back threshold of 40%. When your trade is up one hundred pips, the trailing stop activates if price retraces forty pips from peak, locking in a minimum of sixty pips. 

But when that same trade reaches two hundred fifty pips of profit, the stop adjusts, and now it activates at a one-hundred-pip pullback, securing at least one hundred fifty pips. The stop distance scales naturally with the magnitude of the win you're sitting on.

This creates a logical asymmetry that fixed pip approaches miss entirely. Small winners receive tighter protection. Big winners get room to breathe.

The approach adapts automatically to what the market is actually giving you in real time, without requiring you to predict anything in advance. 

You don't need to maintain a reference table where EURUSD gets thirty pips and GBPJPY gets sixty. You don't need different standards for different instruments at all. 

The same 40% logic works whether the average true range is high or low, whether volatility is expanding or contracting. It is designed to be more adaptive to regime changes than fixed-pip stops, potentially requiring less manual recalibration as it's responding to the trade itself rather than to abstract measures of what the instrument normally does.

The market tells you how much it's willing to move in your direction, and you protect that information proportionally. Nothing more complicated than that.

Key Parameters to Specify in Your System:

• Maximum Give Back Percent: 30-50% is typical, but is dependent on how much profit retracement you can tolerate. 
• Minimum Profit to Activate: In dollar amount or an ATR multiple form entry. This prevents premature exits on tiny winners, e.g., if it has moved 5 pips at 40% that would mean you are only locking in a 3-pip profit.
• Update Frequency: Potentially every bar. More frequent, but there may be issues if there is a limited ability to look at the market (if using some sort of automation, this could be programmed).

Is Maximum Giveback Always the Optimum Trail?

As with many approaches, results can be highly dependent on underlying market conditions. It is important to be balanced. 

The table below summarises some observations when maximum giveback has been used as part of automated exits.

The major difference isn’t likely to be an increased win rate. It is about keeping more of your runners during high-volatility price moves rather than donating them back to the market.

It may not always be the best approach, as different strategies often merit different exit approaches.  

There are two obvious scenarios where fixed pips may still be worth consideration.

• Very short-term scalping (sub-20 pip targets)
• News trading, where you want instant hard stops

Integrating Maximum Giveback With Your System 

You may have other complementary exit filters in place that you already use. Remember, the ideal is often a combination of exits, with whichever is triggered first.

There is no reason why this approach will not work well with approaches such as set stops, take profits and partial closes (where you simply use maximum Giveback in the remainder as well as time-based exits.

Final Thoughts

To use fixed-pip trailing stops irrespective of instrument pricing, volatility, timeframe, and sessional considerations is the trading equivalent of wearing the same jacket in summer and winter. 

Maximum Give Back trailing adjusts to the ‘market weather’. It won't make bad trades good, but it could help stop you from cutting your best trades short just because your stop was designed for average conditions. 

The market doesn't trade in averages but has specific likely moves dependent on context. Your exits should not be average either.