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How ATS Changed the Retail Trading Ecosystem

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ATS: Transforming Retail Trading


The retail trading landscape has evolved dramatically over the past decade. Amid these changes, ATS (which stands for AlgoTrading Trading Systems or a similarly named entity) has emerged as a major innovator. By combining technology, education, and market access, ATS has helped retail traders achieve better results with fewer emotional pitfalls. Here is how ATS has transformed the way trading is approached in the retail space:

1. Pioneering Hybrid Trading Systems and Methods

  • Max Profit, Min Drawdown, Least Emotion One of the core breakthroughs of ATS CEO Tom Leeson is the development of hybrid trading systems from 2006 that blend traditional discretionary analysis with algorithmic precision. The overarching goal: maximize potential profit, minimize drawdown, and reduce the emotional stress that often derails traders.
  • Decades of Hands-On Experience These systems did not spring up overnight. Instead, ATS’s approach is the result of years of iterative learning, constant feedback, and real-world testing. By synthesizing proven methods with modern technology, ATS provides traders with robust tools that adapt well to fluctuating market conditions.
  • Real-Time Adaptability Hybrid trading systems stand out for their ability to rapidly incorporate new data and evolve. This dynamic capability ensures that strategies remain relevant in both trending and volatile markets.

2. Providing Access for All Traders

  • Free, Long-Term Trials with a “Zero to Hero” Program A significant barrier to entry for retail traders is often the cost of professional tools and training. ATS disrupts this model by offering extended, free trials so that aspiring and intermediate traders can test the platform risk-free. This “zero to hero” initiative democratizes trading and helps participants build confidence before committing financially.
  • Lowering the Entry Barriers By eliminating high initial fees and providing sophisticated tools at no cost for a trial period, ATS lowers the financial bar for new traders to develop skills, practice strategies, and see results in real-time market conditions.
  • Focus on Skill Development The structured training programs emphasize both theoretical and practical knowledge. Rather than merely handing traders a set of tools, ATS guides them toward proficiency, helping them understand how strategies work and how to adapt as markets shift.

3. 360-Degree Trading: Systems, Education, Support, and AI

  • All-In-One Ecosystem ATS offers a full suite of resources: trading systems, ongoing education, technical and emotional support, plus community engagement. By weaving these pillars into a single platform, ATS ensures that traders have everything they need—no more piecemeal solutions or juggling multiple vendors.
  • AI Copilot for Enhanced Insights One of the most forward-thinking aspects of ATS is its AI Copilot feature, which uses artificial intelligence to assist traders with real-time market analysis, risk assessment, and even personalized strategy suggestions. This AI-driven guidance helps keep human bias in check and allows for more informed decision-making.
  • Building a High Trading IQ Community Central to ATS’s vision is cultivating a network of knowledgeable, well-equipped traders. Through online forums, webinars, and mentorship, traders can continually enhance their skills, share insights, and tap into a supportive environment geared toward collective success.

Why It Matters

By integrating technology, education, and a community-driven ethos, ATS has effectively shifted retail trading practices from a “lone-wolf” approach to a collaborative, data-driven experience. The result is a new generation of traders who are not just skilled with market techniques but also supported by cutting-edge tools and a like-minded community.

Key Takeaways

  1. Hybrid System Innovation – ATS bridges the gap between discretionary and algorithmic trading with an emphasis on stable growth and minimal emotional interference.
  2. Open Access – Free, long-term trials and structured mentorship lower the entry barrier for new traders.
  3. Comprehensive Support – Education, AI-powered tools, and a supportive community create a holistic environment for sustainable success.

Conclusion

ATS’s multifaceted approach—encompassing cutting-edge trading systems, robust education programs, and AI-based co-pilot features—has set a new standard in retail trading. By focusing on accessibility and continuous improvement, ATS helps traders of all levels develop the skills and confidence needed to succeed in today’s rapidly evolving markets.


Prop Firm Trader Get Funded Accelerator

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Prop Firm Trading Benefits and Get Funded Accelerator

Prop Firms: Key Resources and Benefits

Proprietary trading firms provide traders with several key resources and benefits designed to support trading activity and maximize potential profitability. Here’s what they typically offer:

  1. Trading Capital: Prop firms fund traders with significant amounts of capital, allowing them to trade larger positions than they could with their own funds.
  2. Profit Sharing: Traders earn a percentage of the profits they generate, often between 70% and 90%, while the prop firm keeps a smaller cut.
  3. Risk Management Rules: To protect their capital, prop firms set clear rules regarding maximum daily loss, drawdowns, and position sizing. Traders must adhere to these rules to remain funded.
  4. Access to Technology: Many prop firms provide advanced trading platforms, proprietary tools, and software to help traders execute and manage trades efficiently.
  5. Training and Resources: Some firms offer training programs, mentorship, or access to educational materials for new traders to develop their skills.
  6. Evaluation Programs: To qualify for funding, traders often participate in evaluation phases where they must meet specific performance targets while adhering to risk parameters.
  7. Leverage: Prop firms offer high leverage, allowing traders to control larger positions with smaller amounts of initial capital.
  8. Community and Networking: Traders gain access to a network of professionals and peers for collaboration, sharing strategies, and gaining insights.
  9. Performance Feedback: Many firms provide analytics and feedback on a trader’s performance to help them improve over time.
  10. No Personal Risk: Traders use the firm’s capital, so they don’t risk their own money. However, they may need to pay for evaluations or monthly platform fees.

Getting Funded Prop Firm Trading

Getting capital from a prop firm is a huge step—but it’s only the beginning. Passing the evaluation can be a challenge in itself, and many traders who do get funded end up losing their accounts soon after. Without a clear strategy, every trade feels like a gamble.

Prop firms provide the capital, but not a roadmap. If this sounds familiar, the Get Funded Accelerator is here to bridge that gap.

What’s Holding Traders Back?

  • ❌ Struggling to pass tough evaluations without guidance
  • ❌ Losing funding soon after they get it
  • ❌ Trading without a proven strategy to maintain a funded account
  • ❌ Feeling stuck under pressure, unsure of the best moves

How the Get Funded Accelerator Solves It:

  • ✅ 100% Free trial for eval/live trading prop firms
  • ✅ 100% Free trading reviews and prop firm discovery
  • ✅ Proven methods to pass evaluations and get paid!
  • ✅ Long-term strategies to protect and grow your funding
  • ✅ Step-by-step guidance on risk management and smart trading decisions
  • ✅ A roadmap to consistent results and regular payouts
  • ✅ Turnkey trading systems tuned to prop firm trading

Ready to break the cycle and trade with clarity and confidence? Click here to learn more about the Get Funded Accelerator and take the next big step in your trading journey!


Why Don’t You Just Trade Fully Automated Trading Systems?

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In the modern trading landscape, the allure of fully automated trading systems is strong. With promises of hands-free profits and sophisticated algorithms, it’s easy to understand why traders might gravitate toward this approach. However, the reality of fully automated trading systems (ATS) is more complex. Let’s explore why traders often favor hybrid automated trading systems, such as those leveraging AFT (Algo Futures Trading) and AWT (AlphaWebTrader), for a more robust, adaptable trading strategy.

The Reality of Fully Automated Trading Systems

Lack of Market Adaptability

Fully automated systems rely on preprogrammed rules and historical data. While these rules can be effective in specific market conditions, they often fail to adapt to unforeseen changes, such as major economic events, news catalysts, or shifts in market sentiment. Markets are dynamic, and rigid systems can struggle to keep up.

Prop Firm Constraints

Prop firms, which offer traders access to funded accounts, typically prohibit 100% automated trading. This restriction exists because fully automated systems can quickly breach drawdown limits due to their inability to pause or recalibrate during volatile phases. Hybrid systems provide a manual override capability, aligning better with these rules.

The Drawback of Black Box Systems

Many fully automated systems are “black boxes,” offering no transparency into their logic. Traders using these systems are left to trust algorithms they don’t understand, making it challenging to diagnose issues or improve performance during losing streaks.

Risk of Over-Optimization

Fully automated systems often fall victim to over-optimization, tailoring their strategies to fit historical data too precisely. This can lead to poor performance in live markets where conditions deviate from the backtested scenarios.

Why Hybrid Automated Trading Systems Are Superior

Dynamic Decision-Making

Hybrid systems empower traders to leverage automated signals for consistency while retaining the ability to intervene based on market context. For instance, with AFT and AWT, traders can follow algo signals while using their judgment to adjust trades during pivotal moments.

Enhanced Control

Hybrid trading blends the precision of automation with the control of manual trading. Systems like AFT + AWT allow traders to configure algo signals, filters, and exits or even inject their own logic into the framework. This flexibility makes hybrid systems adaptable to diverse trading styles and market conditions.

Compliance with Prop Firm Rules

Hybrid trading aligns well with prop firm guidelines. A trader can combine systematic signals with manual execution, reducing the risk of breaching drawdown limits and ensuring compliance with firm regulations.

Improved Risk Management

Hybrid systems enable traders to manage risks more effectively by manually overriding or modifying trades in response to unforeseen events. Automation handles repetitive tasks, while traders focus on high-level decision-making.

Scalability and Growth

Hybrid systems, like those powered by AFT and AWT, provide a pathway for traders to evolve. Beginners can start with semi-automated setups, manually taking systematic signals, and progressively transition to fully automated strategies for specific markets or sessions.

How AFT + AWT Combine the Best of Both Worlds

  • Algo Signals + Human Insight: AFT provides systematic trading signals, while AWT offers tools like TradeViewPoint and Trendo to monitor market conditions and correlations.
  • Customizable Automation: Traders can build and refine their strategies by adding filters, adjusting parameters, or incorporating custom logic into the baseline settings.
  • Learning Through Execution: Hybrid trading encourages traders to learn market behavior through hands-on experience, fostering a deeper understanding of when to trade and when to step aside.

Conclusion

While fully automated trading systems may seem like the ultimate solution, their limitations in adaptability, transparency, and risk management often make them unsuitable for long-term success. 80% of traders lose at day trading manually, and up to 95% of day traders lose at fully automated trading!

Hybrid automated trading systems, such as those utilizing AFT + AWT, provide the perfect balance of automation and human intelligence, offering flexibility, control, and scalability. Our VIP Trading group can surpass 66% winners versus losers, compared to the standard retail world of 20% wins. Need we say more? AFT + AWT were purpose-built for hybrid trading specifically as we want the maximum profit with the least drawdown systems.

By combining the best of both worlds, traders can harness the power of automation while retaining the discretion to navigate the complexities of modern markets. Whether you’re seeking consistency, compliance, or growth, a hybrid approach paves the way for sustainable trading success.

Book list reading list on trading systems performance

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Books on Trading System Analysis and Improvement


Books on Trading System Analysis and Improvement

Here’s a curated list of books on system expectancy, trading performance measurement, and related concepts to deepen your understanding of trading system analysis and improvement:

Trading System Development and Expectancy

  1. “Trade Your Way to Financial Freedom” by Van K. Tharp
    • A comprehensive guide to system development, expectancy, and position sizing.
    • Focuses on creating systems tailored to your trading psychology and goals.
  2. “Building Winning Algorithmic Trading Systems” by Kevin Davey
    • Offers practical advice on designing, testing, and optimizing trading systems.
    • Emphasizes risk management and long-term profitability.
  3. “Design, Testing, and Optimization of Trading Systems” by Robert Pardo
    • A detailed guide on developing and validating trading systems.
    • Introduces robust testing techniques and optimization strategies.

Risk and Money Management

  1. “The Mathematics of Money Management” by Ralph Vince
    • A deep dive into money management strategies and their impact on trading expectancy.
    • Explores concepts like optimal bet sizing and drawdown control.
  2. “The New Trading for a Living” by Dr. Alexander Elder
    • Covers trading psychology, system design, and risk management.
    • Includes practical tools for measuring and improving system performance.
  3. “Position Sizing: The Key to Maximum Returns” by Van K. Tharp
    • Explains how position sizing impacts trading system expectancy and overall results.

Performance Measurement and Trading Metrics

  1. “Beyond Technical Analysis” by Tushar S. Chande
    • A focus on system development and performance measurement metrics.
    • Introduces innovative methods for evaluating trading systems.
  2. “Systematic Trading” by Robert Carver
    • Covers quantitative approaches to trading and performance evaluation.
    • Explains how to test, measure, and refine trading systems.
  3. “Quantitative Trading Systems” by Howard B. Bandy
    • Discusses the mathematics and analysis behind trading systems.
    • Provides actionable advice on evaluating system performance.

General Trading and Market Analysis

  1. “The Art of Trading: A Complete Guide to Trading the Markets” by Christopher Tate
    • Combines trading psychology, technical analysis, and system evaluation.
    • Great for beginners looking to understand expectancy and performance metrics.
  2. “Trading Systems and Methods” by Perry J. Kaufman
    • A classic, comprehensive resource on trading system development and analysis.
    • Covers tools, metrics, and strategies for system evaluation.
  3. “Thinking in Bets” by Annie Duke
    • Focuses on decision-making under uncertainty, relevant to trading expectancy.
    • Explains how to approach probability and outcomes objectively.

Trading Psychology and Long-Term Performance

  1. “The Disciplined Trader” by Mark Douglas
    • Explores the psychological aspects of trading and their impact on performance.
    • Includes methods to build consistency and discipline in trading.
  2. “Trading in the Zone” by Mark Douglas
    • Focuses on mindset and emotional control to enhance system performance.
    • Complements expectancy by addressing trader behavior.
  3. “The Mental Game of Trading” by Jared Tendler
    • Explores the psychological challenges of trading and how to overcome them.
    • Offers tools for improving discipline and maintaining focus.

These books cover a mix of technical, quantitative, and psychological aspects of trading, offering a well-rounded approach to improving your systems and understanding expectancy.


Trading System Win Rates: Ranges, Realities, and Refinements

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Algo Trading Insights


I was recently asked, “What win percentage do your algos achieve?” This is a broad and open-ended question—and a good one but not a great one. It would not be a question a pro trader or a fund manager would ask me. They would ask about NAV, % profit, drawdown, etc., or better, what expectancy your systems have, then dive into preferences of win ratio and RR, etc. Let’s take a moment to put it into perspective.

Note to self: I need to get the baseline algo stats website online again, as they’re a helpful guide. However, that’s just the starting point—there’s much more to the story. While baselines are useful to understand, let’s dive deeper into the possibilities.

AFT (Algo Trading Framework) is a comprehensive tool designed with preconfigured turnkey systems, giving traders a ready-made solution to start trading effectively. However, it also offers the flexibility for traders to invent, configure, or even code their own algo rules. With its vast range of off-the-shelf features, there isn’t just one answer to what a system can achieve—it’s simply too expansive. The permutations are nearly endless, allowing traders to experiment and refine their setups for years if they choose.

For many, the journey begins with our turnkey systems, offering a solid foundation to start trading. As traders master the basics, they can then optimize, experiment, and create unique combinations to suit their style. Some prefer to stick with the turnkey setups, live trading, and fine-tuning them to achieve consistent results. Whatever the approach, AFT adapts to the trader’s needs and skill level.

Trading system win rates can vary widely, ranging from 35% to 95%, depending on the trader’s preference, the type of trading system, and their style. While high win rates may seem appealing, it’s important to understand what truly defines a successful trading system.

Baselines and Real-World Performance

At Algo Trading Systems (ATS), baseline systems typically achieve win rates between 50% and 65%. However, live traders in the VIP Group often average 66% to 80% win rates by leveraging a combination of strategies and tools, such as the Hybrid Trading Approach.

Why Win Percentage Alone Is Misleading

While win percentage is an essential metric, it cannot determine profitability on its own. For instance, a trading system with a 95% win rate could still lose money after factoring in commissions and costs if its losses are disproportionately large compared to its wins.

A more meaningful metric combines win ratio and risk-reward into a measure of expectancy. For example:

  • A 65% win rate with a 1:1 risk-reward ratio is excellent.
  • A 50% win rate with a 1:2 risk-reward ratio would be exceptional.
  • A 50% win rate with a 1:1.25 risk-reward ratio is more typical and sustainable.

Example: High Win Ratio Scalper System (ES Futures)

Consider a scalping system with the following parameters:

  • Stop: 24 ticks
  • Target: 8 ticks

If we assume random price movement without any edge or strategy, the likelihood of hitting the target or stop is inversely proportional to their respective distances from the entry point. The shorter distance (the target) has a higher probability of being hit.

Probabilities:

  • Target Being Hit: 75%
  • Stop Being Hit: 25%

This means the win percentage could be 75% based purely on chance, assuming equal price movement probabilities.

Adjusted Example: Smaller Target

Now, consider a system with:

  • Stop: 28 ticks
  • Target: 6 ticks
  • Total Distance: 34 ticks

Probabilities:

  • Target Being Hit: 82.35%
  • Stop Being Hit: 17.65%

The target is 82.35% likely to be hit because it is much closer to the entry point than the stop. The stop, on the other hand, has a 17.65% probability of being hit.

Caveats of High Win Ratios

While such systems heavily favor hitting the target, they require a very high win rate (>82.35%) to overcome their poor risk-reward ratio (approximately 4.6:1). For every 1 loss, you would need at least 5 wins to break even.

Is This Tradeable?

For me, no. I prefer baseline systems designed around a 65% average win ratio, with targets that start at 1:1, 1:2, or even 1:5 risk-reward ratios, and potentially 1:10 for runners.

Improving the System

To improve such systems, align trading with high-probability times to increase the win ratio without compromising the risk-reward ratio. For example:

  • Stop: 20 ticks
  • Targets: 20, 40, 100 far runner

With trading skill and careful selection of high-probability conditions, it’s possible to move the win ratio from 50% to 65%, or even 85%, over time.

Introduction to Expectancy: Combining Win Percentage and Risk-Reward

Expectancy is the cornerstone of any successful trading system. It combines two critical metrics—Win Percentage and Risk-Reward Ratio—to provide a complete picture of a strategy’s profitability over time. While Win Percentage reflects how often a trade is successful, it doesn’t account for the size of wins versus losses. Similarly, Risk-Reward Ratio quantifies the relationship between potential profits and losses but says nothing about how frequently those profits occur. Expectancy bridges this gap by calculating the average profit or loss per trade, considering both the probability of winning and the magnitude of gains and losses. A balanced approach, such as a moderate Win Percentage paired with a favorable Risk-Reward Ratio, often leads to consistent and sustainable trading outcomes. This metric allows traders to evaluate whether their system can generate profits over the long term, regardless of occasional losing streaks.

Example of Expectancy for a System Trading ES E-mini Futures with the Given Parameters:

System Parameters:

  • Average Loss (Stop): 24 ticks
  • Average Reward (Target): 12 ticks
  • Win Percentage (Win %): 66% (0.66)
  • Loss Percentage (Loss %): 34% (0.34)

Step-by-Step Calculation:

  1. Win Component: 0.66 × 12 = 7.92
  2. Loss Component: 0.34 × 24 = 8.16
  3. Expectancy: 7.92 – 8.16 = -0.24

Expectancy Result:

The system has an expectancy of -0.24 ticks per trade, meaning that over time, you lose 0.24 ticks on average for each trade.

Interpretation:

This system, with a 66% win rate and a risk-reward ratio of 2:1 (24 ticks risk vs. 12 ticks reward), is not profitable over the long term because the losses outweigh the gains despite a high win percentage.

To make this system profitable:

  1. Increase the Reward: Aim for a reward of at least 16 ticks (closer to a 1:1.5 risk-reward ratio).
  2. Increase the Win Rate: Improve the win rate beyond 66% to compensate for the current risk-reward imbalance.
  3. Reduce the Stop Loss: Tighten the stop loss to 18 ticks to align better with the 12-tick reward.

System 2 Parameters:

  • Average Loss (Stop): 24 ticks
  • Average Reward (Target): 20 ticks
  • Win Percentage (Win %): 66% (0.66)
  • Loss Percentage (Loss %): 34% (0.34)

Expectancy = (0.66 × 20) − (0.34 × 24)

Expectancy Result:

The system has an expectancy of +5.04 ticks per trade, meaning that over time, you gain 5.04 ticks on average for each trade.

Interpretation:

This system is profitable over the long term. Despite risking slightly more (24 ticks) than the potential reward (20 ticks), the 66% win rate compensates for the slightly unfavorable risk-reward ratio.

Why It Works:

  • The win percentage (66%) is high enough to offset the imbalance in the risk-reward ratio.
  • The average reward (20 ticks) is close to the stop loss (24 ticks), meaning the system doesn’t rely too heavily on an extreme win rate to stay profitable.

Performance Insights:

This system has a positive expectancy, which makes it viable for consistent trading. To enhance it further:

  • Improve the Reward: Target closer to 24 ticks for a 1:1 risk-reward ratio.
  • Optimize the Win Rate: A slight increase in win percentage (e.g., 70%) would boost profitability significantly.

Combining Systems for Success

Using AWT alongside AFT has allowed traders to achieve win rates of 85% to 100% during certain trading periods, even when the system itself averages around 65%. Some traders have consistently averaged 87% win rates over extended periods, but this level of performance requires skill, practice, and time.

Achievably, realistically for day trading if you are hauling in 66% on average and your RR is around 1:1 and find that to be sustainable you are definitely on the right track to excellence—way above 80% to 90%+ of the rest of the herd!

By combining classic trading systems theory with the hybrid edge, traders can achieve maximum profit, minimum drawdown, and reduced emotional strain. This is the approach we teach, coach, and provide the tools and systems to implement.

Conclusion

With Hybrid—high probability trading methods and tools. Why do we beat traditional algo traders into dust? We can do what classic trading automated trading and systematic traders are unable to do—increase the win % without changing the system profile. For example, they would change the RR to increase the Win % or keep looking for the next holy grail settings and optimizing to get them through the next phase never settling, etc. But we use adaptive systems and one setting and instead nail the bullseye with far more consistency than any other method—with time, skill, and commitment. “Bruce Lee” trading if you will—economy of thought and action practicing the same way 10,000 times, not practicing 1,000 ways.

A Simple Analogy

Think of it as a Tesla driving around a racetrack on autopilot, achieving an okay lap time. With man and machine mode, a skilled driver at the wheel, navigating the nuances of S-bends and traffic, the performance could be far superior. Trading isn’t a Route 66 cruise; it’s more like a Swiss Alps rally. Anyone who believes a robot alone can outtrade a hybrid trader has yet to experience the real rewards and success that VIP traders achieve. To get funded and to trade, our approach allows a trader the maximum control on the smallest targets so as not to fall foul of the prop firm trading rules. ATS Traders share their stories and stats, straight from the horse’s mouth in the VIP Trading Group.


How to perform Network testing for a trading server?

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Network testing for a trading server requires a rigorous approach to ensure the lowest latency and highest reliability. Here’s a breakdown of the gold standard in testing methodologies and tools:

1. Key Performance Indicators (KPIs)

  • Latency: This is the most critical metric. Measure round-trip time (RTT) in microseconds (”s) for order submission and market data updates. Aim for consistently low latency with minimal jitter (variation in latency).
  • Jitter: Variations in latency can disrupt order execution timing. Measure jitter to identify inconsistencies in network performance.
  • Packet Loss: Lost packets can lead to missed orders or inaccurate market data. Measure packet loss as a percentage of total packets sent.
  • Throughput: Ensure sufficient bandwidth for peak trading volumes. Measure throughput in megabits or gigabits per second (Mbps or Gbps).
  • Error Rate: Monitor for network errors that can disrupt trading activity. Measure errors per second or as a percentage of total traffic.

2. Testing Tools & Techniques

  • Network Simulation Tools:
    • Hardware Simulators: Expensive but offer the most realistic testing environment. Examples include Spirent TestCenter and Ixia IxNetwork.
    • Software Simulators: More affordable and flexible. Examples include Packet Tracer, GNS3, and OPNET Modeler.
  • Dedicated Testing Environment: Replicate your production environment as closely as possible for accurate results. This includes network hardware, server configurations, and market data feeds.
  • Load Testing: Simulate peak trading conditions with high message rates and order volumes. Tools like LoadRunner or JMeter can be used.
  • Stress Testing: Push the network beyond its limits to identify breaking points and bottlenecks.
  • Failover Testing: Simulate network failures (e.g., link or switch failure) to verify redundancy and failover mechanisms.
  • Monitoring Tools: Use real-time network monitoring tools to identify performance issues during testing. Examples include SolarWinds Network Performance Monitor and PRTG Network Monitor.

3. Best Practices

  • Baseline Testing: Establish a performance baseline in a controlled environment.
  • Continuous Monitoring: Continuously monitor network performance during testing and in production.
  • Automated Testing: Automate tests to ensure consistency and repeatability.
  • Documentation: Thoroughly document test procedures, results, and analysis.

4. Specialized Considerations for Trading Servers

  • Co-location: If your server is co-located with an exchange, focus on testing connectivity to the exchange’s network.
  • Market Data Feeds: Test the performance of your market data feeds with tools like those from Vela Trading Technologies or Refinitiv.
  • Order Routing: Test the entire order routing path, from your trading application to the exchange and back.
  • Time Synchronization: Ensure accurate time synchronization using NTP (Network Time Protocol) servers.

5. Example Test Scenarios:

  • Latency under peak load: Simulate high message rates and order volumes to measure latency under stress.
  • Packet loss during market volatility: Simulate a period of high market volatility with rapidly changing prices to measure packet loss.
  • Failover to backup network link: Simulate a primary network link failure to verify failover to a backup link.

By following these guidelines, you can establish a gold standard for network testing your trading server, ensuring optimal performance, reliability, and successful trading outcomes.

Note: We performed many of the above tests when selecting QuantVPS as our preferred Trading Server providers.

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