Smart Order Routing (SOR) helps you trade ETFs more effectively by scanning multiple trading venues to find the best prices. This is especially useful in Singapore, where liquidity can be fragmented. By considering factors like bid-ask spreads, order book depth, and imbalance ratios, you can reduce costs and improve trade execution. Here’s what you need to know:

• Check Liquidity: Spread your trades across multiple venues (e.g., SGX, dark pools) and focus on metrics like bid-ask spreads and order book depth.
• Monitor Bid-Ask Spreads: Real-time tracking of spreads helps you time your trades better, especially during periods of high liquidity.
• Use Combined Data: Aggregating data from different venues ensures better visibility and decision-making for large trades.
• Customise Routing Rules: Adjust SOR settings to prioritise speed, cost, or market impact based on your trading goals.
• Manage Large Orders: Break up large trades, use VWAP or TWAP strategies, and avoid volatile trading periods.

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1. Check Liquidity Across Multiple Trading Venues

ETF liquidity isn’t confined to a single exchange. It spreads across lit exchanges, dark pools, and internalisers, meaning what you see on one platform only reflects a portion of the total liquidity. For traders in Singapore, this is especially relevant when dealing with global ETFs through the Singapore Exchange (SGX), OTC markets, or international platforms like Bloomberg RFQ and Tradeweb. This fragmented nature of liquidity can significantly influence both the cost and quality of trade execution.

By examining multiple trading venues, you can pinpoint where the tightest spreads and the deepest liquidity are available at any given moment. For active systematic traders or institutions handling larger trades, this can lead to substantial cost savings and better execution.

To make informed decisions, focus on three key metrics:

• Bid-ask spread: This represents your immediate transaction cost. Narrower spreads mean lower costs.
• Order book depth: Look at the depth at the National Best Bid and Offer (NBBO) to determine if your trade size can be executed without causing significant price movement.
• Imbalance ratio: Calculate the total bid size divided by the total ask size at the best price. A ratio above 1.0 indicates buying pressure, while a ratio below 1.0 suggests selling pressure.

Using these metrics can guide you to the trading venue best suited to your needs. For instance, in a 2025 case study, splitting a 100,000-share iShares MSCI Emerging Markets ETF order across three venues – each selected based on bid-ask spread, NBBO depth, and imbalance ratio – helped minimise both price drift and market impact.

Timing also plays a crucial role. Liquidity for ETFs tends to peak around the market’s opening and closing hours. However, it’s wise to avoid trading during the first and last 10–15 minutes of the session, as these periods can be particularly volatile. For ETFs holding foreign securities, aim to execute trades when the underlying markets are open. This ensures more accurate pricing and tighter spreads.

2. Track Bid-Ask Spreads in Real Time

Once you’ve pinpointed the best trading venues, keeping an eye on live bid-ask spreads can fine-tune your timing for trade execution. The bid-ask spread is essentially the cost of entering a trade – the gap between what buyers are willing to pay and sellers are willing to accept. This gap isn’t fixed; it can shift significantly during periods of market volatility or when liquidity is low. Over time, even small variations in spreads can add up, affecting your overall trading costs.

This is where Smart Order Routers (SORs) come into play. These automated systems scan various venues – lit exchanges, dark pools, and electronic communication networks – to identify the tightest spreads available at any given moment. By using this data, you can time your trades more effectively, pairing it with liquidity analysis to achieve better execution outcomes.

Timing is key when it comes to spread optimisation. According to Morningstar: “The opening auction and shortly thereafter is a time for price discovery… Market makers play it safe during this time: The more volatile the market, the wider their spreads”. Because of this, many seasoned traders wait for about 15 minutes after the market opens to avoid these volatile periods and secure narrower spreads.

For international ETFs listed on SGX or other global platforms, spreads tend to narrow when the underlying securities are actively trading in their home markets. This allows market makers to price the ETFs more accurately based on real-time movements in the underlying assets. Advanced routing systems also monitor venue latency – the time it takes to execute an order. During volatile periods, it’s best to avoid venues with latency exceeding 150 milliseconds, as this could lead to trades being executed against outdated quotes, effectively increasing your spread.

Additionally, setting protective measures within your routing logic is a smart move. Many professional trading systems are programmed to cancel orders if projected slippage – the difference between the expected execution price and the mid-price – exceeds 5 basis points. Similarly, they may re-route orders if the fill price deviates by more than 0.2% from the mid-quote. These safeguards are essential for avoiding costly errors, especially when spreads widen unexpectedly.

3. Use Combined Market Data for Better Execution

Real-time spread tracking is just the starting point. To make sharper execution decisions using systematic trading strategies, you need a broader view of the market. Relying on data from a single exchange only gives you part of the picture. Smart Order Routers (SORs) take this further by scanning across lit exchanges, dark pools, and ECNs simultaneously. This approach aggregates real-time liquidity data, offering a clearer view of market depth and identifying the best prices across fragmented venues.

One useful tool in this process is the order book imbalance ratio, calculated by dividing the total bid size by the total ask size. A ratio above 1.0 indicates buying pressure, while a ratio below 1.0 points to selling pressure. For example, in January 2026, a SOR managing a 100,000-share order for the iShares MSCI Emerging Markets ETF analysed three venues: Venue A (40,000 shares, 1.3 ratio), Venue B (35,000 shares, 0.9 ratio), and Venue C (30,000 shares, 1.0 ratio with the lowest latency). By splitting the order across these venues, the SOR minimised slippage to just 5 basis points.

“Because market makers… typically display only a fraction of the volume they are willing to trade, investors may find that secondary market liquidity is actually much higher than on-screen indicators suggest.” – J.P. Morgan Asset Management

This aggregated data is especially valuable for large block trades – orders exceeding 5,000 or 10,000 shares – that could disrupt the market if executed on public order books. By combining data from both lit and dark venues, traders can access hidden liquidity, execute orders discreetly, and reduce market impact while still securing competitive pricing.

Another benefit of combined market data is avoiding costly errors. For instance, monitoring venue latency is crucial. Excluding sources with latency above 150 ms during volatile periods prevents trades from executing on outdated quotes, which could widen spreads and increase slippage. This integrated approach not only improves trade accuracy but also lays the groundwork for more tailored routing strategies.

4. Set Up Custom Routing Rules for Your Strategy

Fine-tune your Smart Order Router (SOR) by setting custom rules that align with your trading objectives. These rules let you decide whether to prioritise speed, cost, or market impact, and each choice directly influences how your ETF orders are executed. Essentially, these tailored settings combine market data insights with execution strategies, ensuring your trades match current market conditions.

If your primary goal is cost reduction, consider targeting dark pools and internalisers while setting slippage limits below 5 basis points. This way, your orders are automatically aborted if costs exceed your pre-set thresholds. This strategy is particularly helpful for traders handling large positions who want to avoid the additional cost of immediate execution.

For traders prioritising speed, focus on lit exchanges with latency between 1–2 milliseconds, while steering clear of venues with delays exceeding 150 milliseconds during volatile periods. A real-world example: In December 2025, Interactive Brokers‘ SmartRouting system managed 20.66 million orders worth US$467 billion. By dynamically re-routing orders across eight dark pools and multiple exchanges, it achieved an impressively low net expense of just 0.030% of the trade value.

“IB SmartRoutingSM never routes and forgets about your order. It continuously evaluates fast changing market conditions and dynamically re-routes all or parts of your order seeking to achieve optimal execution.” – Interactive Brokers

For large block trades, setting participation caps is critical. Limiting your participation to 10% of the ETF’s average daily volume helps prevent market disruption. Additionally, you can configure execution-price stop-losses to automatically cancel and re-route orders if the fill price deviates more than 0.2% from the mid-quote. These measures are key to balancing risk while minimising market impact, allowing you to access hidden liquidity across fragmented trading venues without exceeding your risk tolerance.

5. Manage Speed and Market Impact for Large ETF Orders

When handling large ETF orders, it’s crucial to break them up smartly across different trading venues. This approach helps you maintain a balance between execution speed and minimising market disruption. Keep hidden order sizes below 10% of the average daily volume to prevent driving prices against your position. Once orders are split, you can leverage algorithmic tools to further limit their market impact, a core component of systematic trading.

For large-cap ETFs like SPY and QQQ, using VWAP (Volume-Weighted Average Price) over 10-minute intervals can help you achieve better execution prices. For ETFs with lower trading volumes, TWAP (Time-Weighted Average Price) is a better choice as it spreads out trades evenly, reducing the risk of noticeable market impact.

Another key tactic is to avoid trading during periods of high volatility. By timing your trades during calmer market conditions, you can benefit from tighter spreads. It’s also advantageous to trade when the underlying securities of your ETF are actively moving, as this typically provides deeper liquidity.

Set strict controls to manage execution risks. For example, use a stop-loss mechanism that cancels or re-routes orders if the fill price deviates by more than 0.2% from the mid-quote. Additionally, configure your Smart Order Router to halt trades if projected slippage exceeds 5 basis points.

Keep an eye on your order-to-trade ratio, which measures the number of orders sent versus those executed. A rising ratio may indicate thinning liquidity. Even a small spread difference – like 0.01% – between venues could cost about S$13.50 on a S$135,000 trade, and these costs can quickly add up with large orders. Monitoring this metric ensures your strategy stays efficient and responsive to changing liquidity across venues.

Conclusion

Smart order routing blends tactical precision with advanced technology to optimise ETF execution while safeguarding capital. By assessing liquidity, monitoring spreads, aggregating market data, customising routing rules, and managing execution speed, traders can significantly cut costs and reduce slippage on ETF trades.

These approaches not only improve trade outcomes but also remove emotional biases, helping you stay focused on measurable goals like keeping execution costs under 0.03% of the total trade value. For instance, improving a trade spread by just 0.01% translates to saving S$10 on a S$100,000 trade – a small change that adds up over time. Together, these methods form the foundation for effective ETF trading.

Smart order routers also dynamically analyse market data to minimise volatility and slippage. When paired with strategies like using limit orders and avoiding the first and last 10 minutes of trading sessions, traders can limit exposure to wider spreads. Additionally, automated safeguards – such as halting orders if slippage exceeds 5 basis points – help ensure trades stay within acceptable risk thresholds.

For those keen to deepen their knowledge of systematic trading and risk management, the Collin Seow Trading Academy offers the Systematic Trader Programme (SMT). With over 1,400 5-star reviews on Seedly, this programme equips traders with tools like maximum participation rates and execution-price stop-losses, ensuring compliance with best-execution practices. It’s an excellent resource to complement the strategies discussed here.

Success in ETF trading comes down to consistency. Implement these strategies with discipline, track your performance metrics, and refine your approach based on real-world data.

FAQs

How does Smart Order Routing enhance ETF trading in Singapore’s fragmented market?

Smart Order Routing improves ETF trading in Singapore by automatically navigating multiple trading venues, such as lit markets and dark pools. It intelligently divides orders to tap into the most favourable liquidity sources, which helps narrow spreads and reduce slippage.

By doing so, it ensures best execution and lowers transaction costs, making it an effective solution for handling ETF trades in a market with diverse trading platforms.

What key factors should you consider when evaluating ETF liquidity across different trading venues?

When evaluating ETF liquidity, a few key metrics can significantly influence trading efficiency. Start with the bid-ask spread – this represents the transaction costs you’ll face. A narrower spread generally means lower costs. Next, look at the average daily trading volume, which provides insight into how frequently the ETF is traded. Higher volumes often indicate better liquidity.

It’s also worth examining the order book depth, which reveals the level of market interest at different price points, and the imbalance ratio, a metric that can hint at potential price shifts.

Beyond these, keep an eye on factors like venue latency – how quickly orders are processed, your participation rate – the proportion of market volume your trade represents, and projected slippage – the gap between the expected price and the actual execution price. By carefully analysing these metrics, you can fine-tune your trades and keep costs in check.

How can I adjust Smart Order Routing (SOR) settings to meet my trading goals?

To make Smart Order Routing (SOR) work for your trading goals, you can tweak several settings to get the most out of your ETF trades. Start by identifying your top priorities – do you care more about cutting costs, getting faster executions, or minimising market impact? For example, if avoiding slippage is a big concern, you could set limits to ensure your trades stay within a small percentage of the ETF’s average daily volume, like 5%. You can also set price controls, such as stop-loss thresholds, to avoid trades when prices stray too far from your target.

For smoother execution, it’s a good idea to avoid venues with high latency during volatile periods. Instead, focus on exchanges or liquidity pools that consistently offer good depth and tighter spreads. Keeping an eye on real-time data, like order-book depth and market imbalances, can help you spread trades more effectively, reducing slippage while keeping execution on point.

If you want to sharpen your skills in systematic trading strategies, Collin Seow Trading Academy provides courses and resources that can help you refine your methods and work towards your financial goals.