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Most traders understand EA portfolio balance through the lens of traditional risk management — controlling position sizes, diversifying currency pairs, or limiting exposure per trade.
But in automated trading, balance is about deliberately constructing a portfolio where different strategies complement each other, measuring their collective performance, and actively managing the mix based on those measurements.
The goal is to create a “book” of EAs that can help diversify performance over time, even when individual strategies hit rough patches.
A diversified mix of EAs across timeframes and assets can, in some cases, reduce reliance on any single strategy. This approach reduces dependency on any single EA’s performance, smooths your overall equity curve, and builds resilience across changing market conditions.
It’s about running the right mix, identifying gaps in your coverage, and viewing your automated trading operation as an integrated whole rather than a collection of independent systems.
Basic Evaluation Metrics – Your Start Point

Temporal (timeframe) Balancing
When combined, a timeframe balance (even on the same model and instrument) can help flatten equity swings.
For example, a losing phase in a fast-acting M15 EA can often coincide with a profitable run in an H4 trend model.
Combining this with some market regime and sessional analysis can be beneficial.

Asset Balance: Managing Systemic Correlation Risk
Running five different EAs on USDJPY might feel diversified if each uses different entry logic, even though they share the same systemic market driver.
But in an EA context, correlation measurement is not necessarily between prices, but between EA returns (equity changes) relating to specific strategies in specific market conditions.
Two EAs on the same symbol might use completely different logic and thus have near-zero correlation.
Conversely, two EAs on a different symbol may feel as though they should offer some balance, but if highly correlated in specific market conditions may not achieve your balancing aim.

In practical terms, the next step is to take this measurement and map it to potential actionable interventions.

For example, if you have a EURUSD Trend EA and a GBPUSD Breakout EA with a correlation of 0.85, they are behaving like twins in performance related to specific market circumstances. And so you may want to limit exposure to some degree if you are finding that there are many relationships like this.
However, if your gold mean reversion EA correlates 0.25 compared to the rest of your book, this may offer some balance through reducing portfolio drawdown overlap.
Directional and Sentiment Balance
Markets are commonly described as risk-on or risk-off. This bias at any particular time is very likely to impact EA performance, dependent on how well balanced you are to deal with each scenario.
You may have heard the old market cliché of “up the staircase and down the elevator shaft” to describe how prices may move in alternative directions. It does appear that optimisation for each direction, rather than EAs that trade long and short, may offer better outcomes as two separate EAs rather than one catch-all.

Market Regime and Volatility Balance
Trend and volatility states can have a profound impact on price action, whether as part of a discretionary or EA trading system. Much of this has a direct relationship to time of day, including the nature of individual sessions.
We have a market regime filter that incorporates trend and volatility factors in many EAs to account for this. This can be mapped and tested on a backtest and in a live environment to give evidence of strategy suitability for specific market conditions.
For example, mean reversion strategies may work well in the Asian session but less so in strongly trending markets and the higher volatility of the early part of the US session.
As part of balancing, you are asking questions as to whether you actually have EA strategies suited to different market regimes in place, or are you using these together to optimise book performance?
The table below summarises such an approach of regime vs market mapping:

Multi-Level Analysis: From Composition to Interaction
Once your book is structured, the challenge is to turn it into something workable. An additional layer of refinement that turns theory and measurement into something meaningful in action is where any difference will be made.
This “closing the circle” is based on evidence and a true understanding of how your EAs are behaving together. It is the step that takes you to the point where automation can begin to move to the next level.
Mapping relationships with robust and detailed performance evaluation will take time to provide evidence that these are actually making a difference in meeting balancing aims.
To really excel, you should have systems in place that allow ongoing evaluation of the approaches you are using and advise of refinements that may improve things over time.

What Next? – Implementing Balance in Practice
Theory must ultimately translate into an executable EA book. A plan of action with landmarks to show progress and maintain motivation is crucial in this approach.
Defining classification tags, setting risk weights, and building monitoring dashboards are all worth consideration.
Advanced EA traders could also consider a supervisory ‘Sentinel’ EA, or ‘mothership’ approach, to enable or disable EAs dynamically based on underlying market metrics and external information integrated into EA coding decision-making.
Final Thoughts
A balanced EA portfolio is not generated by accident; it is well-thought-out, evidence-based and a continuously developing architecture. It is designed to offer improved risk management across your EA portfolio and improved trading outcomes.
Your process begins with mapping your existing strategies by number, asset, and timeframe, then expands into analysing correlations, directional bias, and volatility regimes.
When you reach the stage where one EA’s drawdown is another’s opportunity, you are no longer simply trading models but managing a system of EA systems. To finish, ask yourself the question, “Could this approach contribute to improved outcomes over time?”. If your answer is “yes,” then your mission is clear.
If you are interested in learning more about adding EAs to your trading toolbox, join the new GO EA Programme (coming soon) by contacting [email protected].


Why you need to understand this market concept to improve your trading: Market Correlation For new traders and experienced traders, it can be daunting trying to find the best assets to trade. Whether it be equities, foreign exchange or indices, traders should be trying to have as many factors pointing in their favour as possible when entering a trade. These factors can include, the general trend of the individual asset, the price action at the time of entering the trade, candlestick patterns, use of technical indicators, among many others.
However, one thing that all traders should know about and understand is correlation. What is Correlation? Correlation is the pattern or relationship of how one asset performs relative to another asset.
In statistics, there are mathematical measures of correlation including covariance, correlation coefficients and other terms to describe the relationship of one asset to another. These methods can also be used to quantify asset correlations. A correlation between assets can be positive negative or uncorrelated.
Understanding which relationship between different assets can help provide some indication of the way in which an assets price will go. Below is a diagram that shows how the return of assets can be plotted against each other and the potential relationship. For example, imagine that there are two gold companies Gold company A Gold company B Assume that the price of their shares is perfectly, positively, correlated.
This means that when gold company A’s share price rises by 1% company B’s share price will also rise by 1%. This same price action will occur in reverse if the price of company A falls by 1%. Now in practice no two assets are perfectly correlated.
However, two or more assets may be very strongly correlated. Therefore, identifying how correlated certain assets are and how the price of one impact on the other can be a powerful tool. What creates correlation?
Strong correlation between assets usually occurs because the price of the different assets is material impacted by very similar factors. For instance, two companies in Australia may be more correlated than one company in Australia and one company in the USA. This is because geographically the Australian companies will be affected the local economic conditions.
This may include things such as inflation, taxation policies and other geographical specific conditions. Other factors that can influence the correlation include similarity of the assets or a company’s business operations, being in the same sector or a range of other factors. For example, see the correlation between the ‘Big 4’ banks in Australia below.
It can be seen due to how similar the businesses are and the conditions of which they operate in the pattern on returns are almost identical. Index correlation An important phenomenon to understand is the law of averages and big numbers. Essentially, if large companies are grouped together then they act as a good proxy for the overall market or a specific sector.
This essentially is what an ETF or and Index is. Therefore, as it represents how most individual companies are performing, most companies will be to a degree correlated to the overall market index or relevant sector index or ETF. Size matters Another important thing to understand about how correlation works is that smaller assets or companies will tend to correlate towards the performance of the major players within the sector.
For instance, in the technology sector, smaller technology company’s such as zoom will likely be correlated to larger companies such as Apple and Microsoft by virtue of being in the same sector. Correlations do not just occur in equities and are prevalent in FOREX and commodities. Correlation can be found between growth assets such as the Nasdaq Index which is a technology heavy Index and growth currencies such as the AUD or NZD.
Similarly, more stable assets such as the Dow Jones will likely be more correlated to commodities such as oil, they represent more stable industry and manufacturing sectors. How does it improve your trading? By simply being aware of the direction of the correlated assets, a trader is better able to trade with underlying trend and momentum.
This is vital when trying to optimise edge and improve trading accuracy. It can also equally show when a stock is underperforming or overperforming. For instance, if the general trend of a sector leader is trading 5% higher over a certain period, and a smaller company in the sector is trading at 10% higher it is outperforming the ‘sector’ and understanding why this occurs is an important step into deciphering what is driving price action.
Having a good understanding of how assets correlate can also help find potential trading opportunities earlier than others. This is because by following a sector it becomes easier to see which assets still may have room to shift their price. Ultimately, if a trader can develop their identification of patterns of correlation and the reasons for the relationships between different assets it can provide a trader with a much stronger and accurate edge.

Entries for longer-term stock investment approaches can be based on either long-term technical trends or more commonly, fundamental data related to a company’s current and projected performance. Despite the plethora of such suggestions, there is often a lack of clear guidance, or even a complete absence, of instructions on determining the timing of an exit from a long-term position. Logically, whether it’s a short-term technical entry or long-term fundamental entry, many of the “rules of the game” are similar, including the need for clear and unambiguous exit strategies seems paramount for consistently positive investment outcomes.
The approach originally used to make an entry decision can serve as a good starting point but there are other considerations that can potentially benefit outcomes. This article aims to briefly describe six potential exit approaches you could consider, providing some detail and examples as to how to action your chosen approach. Target Price Exit Strategy Setting Targets: Determine a fair value (and thus exit price target) by conducting in-depth fundamental analysis, utilizing metrics like Price-to-Earnings ratio (P/E), Cash flow, debt levels, book value, or longer-term technical levels.
On-going monitoring: Regularly track the price against this target. For example, if you calculate a fair value for a stock at $50, and it’s currently trading at $45, you might decide to sell once it reaches or exceeds $50. Other Considerations: Regularly review and adjust the target price, taking into account changes in fundamental factors impacting the relevant sector or market as a whole.
Ongoing Fundamental Awareness Ongoing Analysis: Continuously evaluate underlying fundamentals, such as earnings, balance sheets, cash flow, and management quality. Be vigilant not only when next company reporting dates are due but also for the often-unpredictable release of operational updates or changes in guidance. Trigger Points: Identify specific company indicators or information that would prompt an exit.
An example of this may be a sustained decline in revenue or mounting debt levels, particularly when beyond what was originally expected. Other Considerations: Implementing this strategy requires consistent research and a nuanced understanding of the particular business and industry factors influencing the investment. Having the optimum resources in place to be able to do this is vital and identifying these should be a primary goal of any fundamental investor.
Economic & Sector Changes On-going Analysis: Regularly review broader economic indicators like GDP growth, inflation, interest rates, or industry trends. Understand how such changes in these key data points may correlate with the asset price and establish exit criteria accordingly.For example, you may reconsider a position in a technology stock if there’s a widespread shift away from tech spending or growth concerns or regulatory changes that detrimentally affect the sector. Other Considerations: This strategy necessitates a broad understanding of economic cycles, industry dynamics, and how these elements interact with your particular investment holdings.
Additionally, it’s worth noting that appropriate resources should be in place to ascertain this as proactively as possible, or at worst in a timely manner. This may assist in preventing excess depreciation in asset price to the point where action is delayed and major capital damage has occurred. Dividend Targeted Approaches On-going Analysis: If part of your entry criteria and anticipated return from fundamental analysis-oriented trades is based on dividend yield to some degree, it is worthwhile to not only look at what is current but also perform ongoing evaluation of the reliability and/or growth of dividends.
Exit Criteria: Having established an expected return, it logically makes sense to have criteria in place to help decision making. For example a decrease in dividend yield below a certain threshold or a cut in dividends could be part of your potential exit plan for a specific investment. Other Considerations: As well as vigilance for the timing of company announcements where dividend changes are often announced, awareness of the yield of your current investment compared to others, and industry trends is required, as they could influence the sector and the market as a whole.
Time-Based Exits On-going Analysis: Often with time-based exits, there is alignment with a particular impending event. Examples of this type of event include a shift to EVs from petrol-fuelled cars or the impact on assets in the lead-up to an election. Either way, your investment time horizon needs to be reviewed should there be a change in circumstances and the rationale behind your initial thinking on entry.
Other Considerations: There is a discipline involved in exiting from a stock position that remains strong even after an event, or the impact of such, has passed. With a systematic approach to fundamental entries in place, it is legitimate to review whether other fundamental approach criteria are met and perhaps consider continuing to hold. Without this in place, or if no match with other approaches exists, logic would dictate that a planned exit is an exit, and you should action it as such, no matter how well this specific position has served you to date.
Portfolio Rebalancing On-going Analysis: Although not based on a specific entry approach, periodically evaluate your overall portfolio asset allocation is prudent. Reviewing whether the current holdings are still a fit with long-term investment aims and risk tolerance in current and ongoing market circumstances are appropriate rebalancing considerations. Rebalancing Exit Approach: Criteria for rebalancing should be pre-planned and clearly defined.
These may require consideration of multiple factors, such as an asset becoming an excessive portion of the portfolio on good performance, or changes in market or economic circumstances that threaten specific portions of the portfolio. Other Considerations: Continuous monitoring of the portfolio is required, and checking continuing congruence with desired asset allocation and your risk profile is vital. Rather than based on a specific entry approach, just to reinforce that the concept of rebalancing is one that is important across all of the approaches described above.
Summary Although they receive little “airplay” in comparison to technical approaches and exits, the exit strategies within a portfolio based on fundamental analysis entries are multifaceted, frequently interconnected, and equally important to master. Crafting a proficient exit system demands a comprehensive knowledge of each specific investment holding, and wider market and economic dynamics, in the context of your personal investment objectives, and risk tolerance. The need for a set of written system criteria for all actions, regular monitoring, thorough analysis, and disciplined adherence to predetermined exit criteria are essential.

Ideally, as traders, our aim is often to identify potential entries at the start of a new trend (so “first in the queue”) and exit at the end of that trend. Of course, we often will identify a price move where a trend may already be established and are therefore faced with the decision as to “join in” mid-trend (we hope) with the aim of catching the rest of a trend move. The concern of this approach is of course the fear of potentially entering just prior to that trend changing.
There are “clues” we can use, such as candle body/wick size and volume which may help, but also there is a group of indicators termed ‘oscillators’ which work on the idea that there are points in a price move which the underlying asset (be it a Forex pair or CFD) may be overbought (and hence a long trade could be deemed riskier), and oversold (where a short trade may be termed riskier). Although the Relative Strength Index (RSI) which we covered previous in an article (review "Adding the RSI to your entry or exit trading plan? "), is possibly a more commonly used oscillator for determining oversold and overbought situations, the stochastic although possibly seen as being slightly more complex, does appear to be frequently used by more experienced traders. This article aims to shed some light on how this indicator is used and what it may be showing you relative to price movement.
What is the stochastic trying to tell us? As with the RSI the Stochastic is an oscillator (whose value can theoretically lie between 0-100) which has identified key levels which may indicate whether a particular asset is overbought or oversold. A move into either of these two “zones” may suggest a trend change is more likely to be imminent.
The key levels are below 20 (oversold) and above 80 (overbought). See below a 30-minute chart for GBP/USD with the stochastic added using the default system settings (we have added horizontal lines from the drawing tools to make the key levels clearer. We will discuss settings later and the additional line but at a simple level, taking the blue line on the stochastic if it moves below 20, then you would be cautious and perhaps avoid entering a short trade (examples A and B), and perhaps avoid entering a long trade if it moves above 80 (see example C).
And the other dotted line? There are two lines that form the stochastic namely: %K (usually a solid line) – In this case blue as previously referenced above. %D (usually a dotted line) and is a moving average of %K (often set as an exponential) Slowing periods may also be set (default is 3). As a rule, the slower (bigger number the less “noisy” i.e. you will see less overbought and oversold conditions).
And how can it be used? a. As an additional entry criteria “tick” As referenced earlier, for entry, traders may use this as an additional tick (when other indicators may suggest entry) to make sure they do not enter a long trade on an overbought currency pair/CFD, or short trade on an oversold currency pair/CFD. b. As a warning to prepare for exit action in an open trade Though less commonly discussed, it would appear logical that if in a long trade for example and the Stochastic moves into an over-bought position this could be a warning to consider exit (more commonly used as a signal to tighten a trailing stop loss) c.
As a primary reversal signal Additionally, some traders may look to buy when moving out of an oversold situation when the EMA dotted line crosses the solid blue line. (and of course, the reverse when overbought). It would be rare to use this in isolation with no other indicators, using increasing volume, and candle change recognition would often be used also. The relatively fast default settings (5,3,3) may merit some review anyway but particularly in this case.
Which settings? As with any indicator you are in control of the settings and what you use for you is of course your choice. With the chart below, we have used the default 5,3,3 and added a 21,7, 7 to illustrate the difference of a less noisy set of perimeters.
In Summary Ultimately, and to finish, it is of course your choice as to which criteria you use for entry and exit. Remember, whatever these are for you, the key lessons of: a. specifically identifying how you are to use the criteria within your plan, b. the importance of forward-testing (as well as back-testing) of any system change, c. and of course, the discipline of following through are ALL critical whether you use the Stochastic, RSI or neither.

The Volatility Contraction Pattern, (VCP) is a famous trading pattern identified and dissected by Market Wizard, Mark Minervini. The premise of the pattern is that stocks in long term up trends will pause and consolidate as some holders exit their positions and the stock is accumulated again by buyers in the market. The chart pattern can provide opportunities for powerful break outs and can be used across any time frame.
This allows traders to jump in on potential moves before they explode. Mechanics of the pattern The background of the pattern is relatively simple. The stock has been previously rising in an uptrend and has found some resistance.
It then moves into a period of consolidation categorised by 2-6 retracements with each one being smaller than the previous one. The volume should usually be decreasing as the chart moves to the right. The pattern culminates in a powerful break out that can often be long lasting.
The key for this pattern is that there needs to be a contraction of volatility as the chart moves from the left to the right. This highlights that the volume available is decreasing and becoming scarce. In addition, the more dramatic in volume, the more likely that the move will be explosive.
Below the breakout is accompanied by an increase in the relative volume. In the chart below for Natural Gas, the decrease in volume can be associated with the contracting candlestick pattern. This occurs prior to the break of the long-term resistance.
The breakthrough was also associated with a large amount of buying volume. The VCP can manifest itself in other patterns such as a cup and handle patterns. The key is that the candlesticks must be decreasing volatility.


A resistance level is a key tool in technical analysis, indicating when an asset has reached a price level that market participants are unwilling to surpass. Resistance levels are often used in conjunction with support levels, or the point at which traders are unwilling to let an asset's price drop much lower. To understand this fully, it’s important to understand how support and resistance works in general.
A support line is when a price hits a low point (on the selling side) and resistance is when the price hits a high (on the buying side). If the prices rebound back to this price or continue to hit this price without surpassing it, it then starts to become a key resistance or support level. As a rule of thumb when using technical analysis, these tools become very important for some traders.
This is due to those points offering various outcomes. Whether they are a Bounce or a Break, essentially meaning, does the price hit the support/resistance and comes back (Bounce) or does it go through the support/resistance lines (Breaks). It is important to also use other indicators to accompany your technical analysis, as these movements could also easily become reversals or break outs, meaning, instead of them following your prognosis the price does the opposite.
When a price has been rejected various times, it builds an even stronger key resistance. Trading volume and sentiment can help to propel a price past this point and some of the biggest movements come after a price breaks a key resistance. Using a current trend (Fig 1) and a hypothetical trend (Fig 2), let’s take the daily timeframe for BTCUSD as an example (below).
The daily candle has broken through a key resistance of $41,000 as shown on figure 1. If a trader identifies this, they can do one of two things; trade it aggressively and place a trade as it breaks through or trade it conservatively and wait for the former resistance line to become the new support line before placing a trade (so wait for the price to bounce off as outlined on the drawn projection and circled on figure 2). Figure 1.
Figure 2. This technical analysis can be used for any asset you wish to trade: it’s transferrable and key in identifying entry or exit points of trades. By learning to spot the patterns and combining this with knowledge of trading volume and sentiment, you can start to understand the markets better.
Sources: Babypips, Investopedia, @sell9000 Twitter.


Please find below the video recording from this weeks Inner circle session "Share CFDs" where we explored how this trading vehicle could be of benefit to many traders. We dispelled some of the myths surrounding Share CFDs and presented some ideas for alternative ways to use these as part of your trading toolbox. Please send any comments or questions to [email protected] Please note the disclaimer at the beginning of the video.
Mike Smith Educator GO Markets Disclaimer The articles are from GO Markets analysts based on their independent analysis. Views expressed are of their own and of a ‘general’ nature. Advice (if any) are not based on the reader’s personal objectives, financial situation or needs.
Readers should, therefore, consider how appropriate the advice (if any) is to their objectives, financial situation and needs, before acting on the advice.