How EAs and Automated Trading Systems Stack Up Against Human Traders

Trading the financial markets is a complex endeavor that requires knowledge, skill, and emotional control. In recent years, technological advancements have led to the development of automated trading systems that aim to match or even surpass the performance of human traders. In this comprehensive guide, we’ll examine how Expert Advisors (EAs) and algorithmic trading platforms compare to discretionary trading by humans.

Introduction

Automated trading systems, also referred to as algorithmic trading or algo trading, utilize computer programs and mathematical models to automate the process of buying and selling financial assets. The programs are designed to follow a defined set of rules and take action based on market data and technical indicators. The goal is to identify trading opportunities and execute orders faster and more efficiently than a human trader could.

EAs, short for Expert Advisors, are one of the most popular forms of automated trading software utilized in the forex market. EAs are programs developed for the MetaTrader trading platform that allow for automation of trading strategies. When attached to a trading chart, the EA will monitor the market and place buy or sell orders according to its programming without any manual intervention.

So how exactly do these technological trading tools stack up against human discretionary traders? In this comprehensive guide, we will compare EAs and automated trading to manual trading in terms of:

• Speed and efficiency
• Emotionless trading
• Backtesting capabilities
• Optimization and adaptability
• Risk management
• Costs and setup requirements

By the end, you’ll have a solid understanding of the key differences, pros and cons, and be able to determine if algorithmic trading strategies are a viable option for your needs and trading style. Let’s get started!

The Benefits of Algorithmic Trading Systems

There are some clear advantages automated trading platforms have over manual traders. Let’s take a look at some of the key benefits of EAs and algo trading software:

Speed and Efficiency

One of the biggest advantages of algorithmic trading is the ability to scan the markets and execute orders extremely quickly. EAs and trading bots can monitor hundreds of assets simultaneously and react within milliseconds when opportunities arise. This gives them a significant edge over human traders who are much slower to analyze information and enter orders.

The speed allows algo traders to capitalize on even the smallest, short-lived price movements and market inefficiencies. Strategies like arbitrage, news playing, and scalping that exploit small price changes become more viable. For breakout and trend following strategies, getting in earlier allows larger position sizes and profit potential.

In today’s volatile and technology-driven markets, the enhanced speed and efficiency gives algorithmic trading software an advantage over manual trading. Humans simply can’t match the processing power and reaction time of a well-programmed EA.

Emotionless Trading

One of the biggest challenges facing human traders is controlling fear and greed. Algorithmic trading systems eliminate emotions from the trading process altogether by mechanically executing trades based on programmed strategy rules and parameters.

EAs don’t experience the same mental obstacles that cause traders to second guess, hesitate on pulling the trigger, choke up losses, or prematurely take profits. Without emotions clouding their judgment, trading bots can stick steadfast to the strategy rules and trade with consistency.

Removing the influence of emotions is a major benefit of automated trading. By strictly adhering to backtested rules and mechanics, algorithmic trading systems can potentially achieve higher, more stable returns long-term compared to discretionary traders impacted by psychological biases.

Backtesting Capabilities

A key advantage of EAs and trading algorithms is the ability to accurately backtest strategies against historical data. Backtesting refers to applying the trading rules and logic retrospectively to chart data to evaluate their hypothetical past performance.

Since the EA adheres to the programmed logic with precision, backtesting provides an accurate depiction of how the strategy would have performed through previous market conditions. This allows traders to fine-tune strategies by adjusting inputs and settings to optimize returns before putting real money at risk.

For discretionary traders, it’s difficult to know if a trading system would have been profitable in the past. Human-executed trades will always have some level of subjectivity and influence of emotions/biases. This makes precise backtesting of manual trading systems nearly impossible. The accuracy of backtesting gives algorithmic trading an edge.

Optimization and Adaptability

With their coding, algorithms are more adaptable than manual trading systems. Program parameters can be adjusted and optimized to improve performance or adapt to evolving market conditions.

EAs allow traders to run multiple backtests to find the ideal strategy settings. The code can also be edited to programmatically optimize inputs based on performance metrics. For example, phases of market volatility can trigger changes in position sizes or stop loss levels.

Manual trading systems are largely static and lack the systematic optimization of algo trading. Humans can certainly adjust their trading rules over time, but lack the precision, speed, and consistency of algorithm modifications. The built-in optimization gives trading bots an advantage.

How Human Traders Counter the Algorithms

While automated trading boasts some clear advantages, human discretionary traders have their own strengths and ways to counter the rise of algorithms:

Understanding Context and Intent

Humans have a unique ability to discern contextual market drivers, events, and participant intent that algorithms simply can’t replicate. Reading news headlines, press conferences, earnings calls, investor presentations, expert opinions, and regulatory changes provides insight into the meaning behind price action.

Unless explicitly programmed to do so, trading bots lack a true comprehension of context and intent behind market moves crucial for discretionary traders to gain an edge. They can only react to price action patterns, technical indicators, and statistics, not broader market forces.

Adapting to Changing Market Conditions

In dynamic, ever-evolving markets, the rigid trading rules of EAs leave them susceptible to periods of underperformance. Discretionary traders remain flexible, able to utilize different strategies and adjust position sizes based on changing volatility, trends, and risk environments.

Automated systems follow static rules optimized for past market conditions. When those conditions inevitability change, the strategies are slower to adapt and their edge deteriorates. Humans have the innate ability to quickly modify their approach, giving them the upper hand in fluid market regimes.

Identifying Opportunities Outside the Code

Even the most sophisticated trading algorithms miss opportunities simply not identified within their coded rules. Discretionary traders are adept at spotting irregular price action, chart patterns, sentiment shifts, and events that algorithms routinely overlook.

Humans can take advantage of news events, technical levels, seasonality, momentum surges, and mispricings due to fear/greed dislocations. Their subjective interpretation of the markets allows profiting from opportunities unavailable to rigid EAs. This gives human traders an advantage computers lack.

Risk Management and Survival

In extremely volatile markets, most automated trading systems struggle to adapt their risk management. Pre-programmed stop losses and position sizing often remain static despite surges in volatility that require reduction of risk parameters.

Human traders have the ability to actively adjust their risk in real-time to account for heightening volatility and uncertainty. By quickly reducing position sizes, tightening stops, and managing leverage, they can ensure survival during periods of deep drawdowns that would paralyze most EAs.

Key Differences Between Algorithmic and Discretionary Trading

Now that we’ve covered the distinguishing benefits of automated trading systems versus human discretionary traders, let’s summarize some of the key differences between the two trading approaches:

| Algorithmic Trading | Discretionary Trading | |-|-| |Executes orders in milliseconds|Slower manual order execution| |Emotionless trading|Subject to psychological biases| |Rigid strategy rules|Flexible trading approach| |Limited understanding of context|Interprets news/events for insight| |Code-based backtesting|Imprecise hypothetical modeling| |Automated optimization|Manual strategy adjustments| |Static risk management|Adaptable real-time risk controls| |Setup requires programming skills|No special skills needed| |Higher upfront costs|Lower cost for starting trading|

As shown in the comparison table, there are clear trade-offs between utilizing automated trading platforms versus a manual discretionary approach. Algo trading provides speed, consistency, and backtesting capabilities that human traders lack. But human traders maintain advantages in interpreting market conditions, flexibility, and active risk management that computers struggle to match.

Neither approach is necessarily superior in all market conditions. In fact, many successful traders find the optimal results by combining automated trading with human oversight and discretionary trading. The strengths of each can complement the weaknesses of the other.

6 Key Questions to Consider Before Trading Algorithms

If you’re considering venturing into algorithmic trading, there are some important factors to weigh before getting started:

1. Does algorithmic trading match your personality and skills?

Programming skills or hiring a qualified developer are a prerequisite for building and implementing auto trading systems. For non-technical traders focused on analysis and discretionary order execution, algo trading may not be the best fit despite its advantages.

2. Do you prefer codified or discretionary trading strategies?

If you gravitate toward rule-based strategies with definitive entry/exit criteria, algorithmic trading aligns well with a systematic approach. For discretionary price action or macro traders, the absence of flexibility and real-time human oversight in algo trading may be a downside.

3. What regulatory requirements will impact your algorithms?

Depending on the assets traded and account size, regulations like the European Union’s MiFID II and warnings from the SEC on unchecked algo trading require consideration. Developing compliant systems involves extensive additional programming and ongoing monitoring.

4. Does your strategy benefit from speed and efficiency?

For strategies dependent on fast execution like scalping and high frequency trading, the speed advantages of algorithmic trading make it a clear fit. But for swing or position trading, manual order entry likely doesn’t carry significant drawbacks.

5. How will you backtest and optimize your algorithms?

Robust backtesting and optimization requires clean, accurate historical data along with coding skills to run iterations and tweak inputs. If you lack the data or programming ability, it will be challenging to develop consistently profitable EAs.

6. Are you prepared to actively manage system risks?

Since algorithms lack human judgement, ongoing monitoring of trading activity and risk parameters is crucial. Without prudent oversight and controls, unchecked automated strategies can spiral out of control during volatile markets.

Carefully weighing these key considerations will help determine if algorithmic trading aligns with your skills, personality, strategies, and risk tolerance. The pros and cons compared to manual trading should drive your implementation decisions.

Combining Algo Trading with Manual Discretion

For many traders, the optimal approach is to find ways to combine the benefits of algorithmic trading with their own human judgement and discretionary adjustments. Some examples include:

• Using EAs for trade execution but manually identifying opportunities and determining position size based on risk
• Coding algorithms to monitor and recommend trades but making final entry/exit decisions discretionarily
• Reducing EA position sizes or tightening stops during volatile periods identified by human traders
• Letting algorithms identify potential setups and“alert” human traders to evaluate and confirm trades
• Employing automated strategies for short term scalping while manually executing swing trades

Instead of being an all-or-nothing proposition, savvy traders are finding ways to harness the strengths of both automated trading systems and human discretionary management. The future is likely increased integration of coding, algorithms, data, and technology with human judgement and oversight.

The Bottom Line – Humans Still Maintain an Edge

In summary, while EAs and algorithmic trading platforms offer enticing advantages like speed, emotionless execution, and backtesting capabilities, human discretionary traders still maintain an edge in today’s dynamic markets. The innate human abilities to interpret contextual market drivers, adapt to changing conditions, spot unprogrammed opportunities, and manage risk give them capabilities no algorithm can duplicate.

For the foreseeable future, combining automated processes with human creativity, flexibility and judgement appears to offer the best of both worlds. We may eventually reach a point where true artificial intelligence matches or exceeds a top trader’s abilities, but for now discretionary trading remains vital – even in the age of algorithms.

The key is to objectively assess your own skills, preferred trading style and strategies to determine if elements of algorithmic trading could complement your approach. With prudent implementation and ongoing human oversight, EAs and trading algorithms can be a useful tool but are unlikely to fully replace discretionary traders anytime soon.

Frequently Asked Questions

What are the main advantages of algorithmic trading over manual trading?

The biggest advantages of algorithmic trading are speed and efficiency in scanning markets and executing orders, emotionless adherence to strategy rules, backtesting capabilities, built-in optimization mechanisms, and cost efficiencies from automating the trading process.

What capabilities do human traders have that automated systems lack?

Humans possess innate abilities to discern context and intent behind market moves, adapt strategies to evolving conditions, identify opportunities outside programmed code, and actively manage risk based on experience and judgement.

Is algorithmic trading suitable for discretionary price action traders?

For heavily discretionary traders who base decisions on real-time price action analysis, algorithmic trading is likely not the best fit. The lack of flexibility and human oversight in algo trading systems limits their usefulness for discretionary styles.

What should you consider before implementing automated trading strategies?

It’s important to realistically assess your personality fit, skills required, regulatory impacts, strategy match, backtesting capabilities, and risk management needs before committing to algorithmic trading. Having a solid understanding of the pros and cons is key.

How can traders combine the benefits of algorithms and manual trading?

Ways to integrate the two approaches include using EAs for execution but manual trade identification and sizing, implementing human override functions, and combining algo and discretionary strategies across different timeframes or assets.

Will artificial intelligence ever fully replace human traders?

While AI and machine learning are rapidly advancing, human traits like creativity, pattern recognition, and risk judgement maintain an edge over today’s algorithms. But the future outlook is uncertain as AI capabilities accelerate.

Conclusion

Algorithmic trading platforms provide enticing advantages but still lack integral human skills and judgement that give discretionary traders an edge. The most successful approach is likely integrating automation with human creativity and oversight. Carefully assess your own personality fit, skills, strategies and risk tolerance when weighing the pros and cons of EAs and trading algorithms against manual trading. Use the strengths of each to your advantage.