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Tracking error is one of the metrics investors look at to measure fund performance. It gauges an investment’s consistency against its benchmark. A large tracking error, especially combined with suboptimal returns, will often cause investors to seek different solutions.
A good portfolio manager will ensure that tracking error is minimal. Here are steps portfolio managers can take to mitigate tracking error and stay competitive.
There are several factors that can generate tracking error. Understanding what they are can give portfolio managers several levers for reducing them.
Before fund managers and portfolio managers make decisions about expense ratios, they need to understand what the fees are. Performance analysts measuring the impact of fees on returns also need to understand all of the fees and costs associated with a product. Funds have fees and indices that they do not track. Transaction costs, trading costs, and expense ratios all impact tracking error frequency. High expense ratios in particular can impact overall performance and eat away at investor returns. Reducing expense ratios and minimizing fees can help.
Indices do not have cash reserves, which many funds do. Cash reserves that are not in play can diminish returns because they are not invested, they are sitting on the sidelines. This can further deviate a fund’s net asset value (NAV) from its underlying index, as the index is tracking the performance of various securities while the fund will have a pool of cash that is not invested in any security. Traders and operational analysts will note that cash drag is most visible at redemption and settlement. Minimizing cash holdings will mitigate tracking error resulting from cash drag.
When a fund tracks an index that includes stocks that don’t trade a lot, ETF issuers can’t buy those stocks without pushing prices up. Sampling and optimization involves using more liquid stocks as proxies, but that can create performance variations and generate tracking error. Portfolio managers face a challenge in how they approach replicating an index’s performance through its more liquid holdings.
If market makers, authorized participants, and fund managers can’t easily buy or sell a stock, that creates a host of issues that impact tracking error. Risk managers and traders need to navigate liquidity all the time, as constraints can lead to transaction delays, which can cause cash drag. Additionally, perfectly representing a benchmark will become more daunting if many of the underlying securities are illiquid.
Dividends inherently create cash, which in turn becomes short-term cash drag until the proceeds are reinvested. Of particular note to operation analysts measuring cash flow and portfolio managers making reinvestment decisions, if the timing isn’t right, a fund could end up with more cash sitting outside of the market, which can create tracking error.
Rebalances are done to reduce tracking error by keeping the fund aligned with index changes. However, they often involve broker commissions and transaction fees. Portfolio managers need to strike the right balance between accuracy and keeping fees low.
If the markets are more volatile, tracking error tends to rise. Volatility widens bid-ask spreads, and can be particularly concerning for risk managers and traders. Volatile markets can also cause an ETF to trade at a premium to its NAV, further complicating efforts to keep tracking error in check.
Less volatile markets create lower tracking error, as bid-ask spreads are generally tighter and more consistent, making it easier to match to the underlying index. Risk managers and performance analysts should pay attention to when tracking errors spike relative to historical averages, this could be the result of market volatility.
The key to properly navigating tracking error is to measure and monitor, then adjust as needed. Monitoring how your ETFs track indexes as part of overall fund performance can help you react in real time and make necessary adjustments.
Performance analysts and risk managers will want to have a full understanding of tracking error over multiple periods and specific periods (such as 1 year, 3 years, etc.). This understanding can create practical guidance and strategies and ensure a fund’s NAV tracks closely with its underlying index.
There are a few techniques asset managers can use to minimize tracking error during portfolio construction and with ongoing management. These include:
Sampling usually creates higher tracking error because it involves swapping in more liquid proxies in place of actual securities, a challenge that ETFs face more acutely than mutual funds, which have more flexibility in how they manage redemptions. Those proxies will naturally perform differently.
Full replication, however, can reduce tracking error. Portfolio managers should note there are trade-offs to doing full replication. As noted earlier, securities with low liquidity could end up having their prices affected by trades. There could also be delays in transactions, leading to cash drag. Portfolio managers need to be judicious with where they deploy sampling and where they stick to full replication.
Operations and compliance staff managing rebalancing schedules and fund administration should note that optimizing the operations of an exchange-traded fund can minimize overhead, which reduces fees and tracking error. A regular and efficient rebalance combined with minimized transaction costs and reduced portfolio management fees will result in fees eating away less at returns, keeping a fund in line with its benchmark.
One tool that portfolio managers have at their disposal to generate more revenue and mitigate potential tracking error is securities lending. Loaning out securities to other financial institutions in exchange for a fee and some collateral can generate additional revenue and make up some of the performance gap caused by expense ratios.
Active risk modeling can also generate additional revenue. Active risk happens when portfolio management decisions deviate from the benchmark. This lean into risk can sometimes lead to additional performance and revenue boosts.
Tracking error expectations will vary greatly between products. Passive products in general will want to maintain a low tracking error, as close to zero as possible. For some active products, the goal is to beat a benchmark, so a tracking error rate over the index is more normalized.
Your asset class, investment objectives, and investment strategy will play a huge factor in determining what the ideal range of your tracking error will be. Less volatile sectors and investment styles will be easier to maintain lower tracking error in than more volatile securities. For example, a fund built on passive fixed income will have less tracking error than an active fund centered on alternatives.
Regardless, the general goal will be to mitigate tracking error as much as possible given the constraints of whatever part of the market your fund is invested in.
ETF tracking error measures how consistently an ETF replicates the performance of its underlying benchmark index. It is calculated as the standard deviation between the ETF’s returns and the benchmark’s returns over a given period. A higher tracking error indicates greater inconsistency, while a lower tracking error suggests the ETF is closely following its index. Tracking error is distinct from tracking difference, which measures the total performance gap rather than consistency.
ETF tracking error can be caused by several factors, including:
Tracking difference and tracking error both measure how closely an ETF follows its benchmark index, but they measure different things. Tracking difference looks at magnitude, or the total performance gap between an ETF’s return and its benchmark index return over a specific period. Tracking error looks at consistency, or the standard deviation of that performance gap over time. A fund can have a low tracking difference but a high tracking error if its returns vary significantly from period to period, even if the overall gap is small.
Tracking error affects ETF risk in several ways. A high tracking error introduces performance unpredictability, making it harder for investors to rely on the ETF to replicate its benchmark consistently. This unpredictability can signal hidden costs, like high expense ratios or excessive transaction fees, that erode returns over time. For risk managers, a rising tracking error can also be an early warning sign of liquidity problems or structural issues within the fund that need to be addressed before they affect investor returns more significantly.
There is no universal standard for a good tracking error. Some asset classes, investment styles, sectors, and products will inherently have higher tracking error potential than others. Index funds tend to have lower tracking error than active funds. Less volatile products will likewise be easier to keep in line with the benchmark.
Tracking error is one of the metrics investors look at to measure fund performance. It gauges an investment’s consistency against its benchmark. A large tracking error, especially combined with suboptimal returns, will often cause investors to seek different solutions.
A good portfolio manager will ensure that tracking error is minimal. Here are steps portfolio managers can take to mitigate tracking error and stay competitive.
There are several factors that can generate tracking error. Understanding what they are can give portfolio managers several levers for reducing them.
Before fund managers and portfolio managers make decisions about expense ratios, they need to understand what the fees are. Performance analysts measuring the impact of fees on returns also need to understand all of the fees and costs associated with a product. Funds have fees and indices that they do not track. Transaction costs, trading costs, and expense ratios all impact tracking error frequency. High expense ratios in particular can impact overall performance and eat away at investor returns. Reducing expense ratios and minimizing fees can help.
Indices do not have cash reserves, which many funds do. Cash reserves that are not in play can diminish returns because they are not invested, they are sitting on the sidelines. This can further deviate a fund’s net asset value (NAV) from its underlying index, as the index is tracking the performance of various securities while the fund will have a pool of cash that is not invested in any security. Traders and operational analysts will note that cash drag is most visible at redemption and settlement. Minimizing cash holdings will mitigate tracking error resulting from cash drag.
When a fund tracks an index that includes stocks that don’t trade a lot, ETF issuers can’t buy those stocks without pushing prices up. Sampling and optimization involves using more liquid stocks as proxies, but that can create performance variations and generate tracking error. Portfolio managers face a challenge in how they approach replicating an index’s performance through its more liquid holdings.
If market makers, authorized participants, and fund managers can’t easily buy or sell a stock, that creates a host of issues that impact tracking error. Risk managers and traders need to navigate liquidity all the time, as constraints can lead to transaction delays, which can cause cash drag. Additionally, perfectly representing a benchmark will become more daunting if many of the underlying securities are illiquid.
Dividends inherently create cash, which in turn becomes short-term cash drag until the proceeds are reinvested. Of particular note to operation analysts measuring cash flow and portfolio managers making reinvestment decisions, if the timing isn’t right, a fund could end up with more cash sitting outside of the market, which can create tracking error.
Rebalances are done to reduce tracking error by keeping the fund aligned with index changes. However, they often involve broker commissions and transaction fees. Portfolio managers need to strike the right balance between accuracy and keeping fees low.
If the markets are more volatile, tracking error tends to rise. Volatility widens bid-ask spreads, and can be particularly concerning for risk managers and traders. Volatile markets can also cause an ETF to trade at a premium to its NAV, further complicating efforts to keep tracking error in check.
Less volatile markets create lower tracking error, as bid-ask spreads are generally tighter and more consistent, making it easier to match to the underlying index. Risk managers and performance analysts should pay attention to when tracking errors spike relative to historical averages, this could be the result of market volatility.
The key to properly navigating tracking error is to measure and monitor, then adjust as needed. Monitoring how your ETFs track indexes as part of overall fund performance can help you react in real time and make necessary adjustments.
Performance analysts and risk managers will want to have a full understanding of tracking error over multiple periods and specific periods (such as 1 year, 3 years, etc.). This understanding can create practical guidance and strategies and ensure a fund’s NAV tracks closely with its underlying index.
There are a few techniques asset managers can use to minimize tracking error during portfolio construction and with ongoing management. These include:
Sampling usually creates higher tracking error because it involves swapping in more liquid proxies in place of actual securities, a challenge that ETFs face more acutely than mutual funds, which have more flexibility in how they manage redemptions. Those proxies will naturally perform differently.
Full replication, however, can reduce tracking error. Portfolio managers should note there are trade-offs to doing full replication. As noted earlier, securities with low liquidity could end up having their prices affected by trades. There could also be delays in transactions, leading to cash drag. Portfolio managers need to be judicious with where they deploy sampling and where they stick to full replication.
Operations and compliance staff managing rebalancing schedules and fund administration should note that optimizing the operations of an exchange-traded fund can minimize overhead, which reduces fees and tracking error. A regular and efficient rebalance combined with minimized transaction costs and reduced portfolio management fees will result in fees eating away less at returns, keeping a fund in line with its benchmark.
One tool that portfolio managers have at their disposal to generate more revenue and mitigate potential tracking error is securities lending. Loaning out securities to other financial institutions in exchange for a fee and some collateral can generate additional revenue and make up some of the performance gap caused by expense ratios.
Active risk modeling can also generate additional revenue. Active risk happens when portfolio management decisions deviate from the benchmark. This lean into risk can sometimes lead to additional performance and revenue boosts.
Tracking error expectations will vary greatly between products. Passive products in general will want to maintain a low tracking error, as close to zero as possible. For some active products, the goal is to beat a benchmark, so a tracking error rate over the index is more normalized.
Your asset class, investment objectives, and investment strategy will play a huge factor in determining what the ideal range of your tracking error will be. Less volatile sectors and investment styles will be easier to maintain lower tracking error in than more volatile securities. For example, a fund built on passive fixed income will have less tracking error than an active fund centered on alternatives.
Regardless, the general goal will be to mitigate tracking error as much as possible given the constraints of whatever part of the market your fund is invested in.
ETF tracking error measures how consistently an ETF replicates the performance of its underlying benchmark index. It is calculated as the standard deviation between the ETF’s returns and the benchmark’s returns over a given period. A higher tracking error indicates greater inconsistency, while a lower tracking error suggests the ETF is closely following its index. Tracking error is distinct from tracking difference, which measures the total performance gap rather than consistency.
ETF tracking error can be caused by several factors, including:
Tracking difference and tracking error both measure how closely an ETF follows its benchmark index, but they measure different things. Tracking difference looks at magnitude, or the total performance gap between an ETF’s return and its benchmark index return over a specific period. Tracking error looks at consistency, or the standard deviation of that performance gap over time. A fund can have a low tracking difference but a high tracking error if its returns vary significantly from period to period, even if the overall gap is small.
Tracking error affects ETF risk in several ways. A high tracking error introduces performance unpredictability, making it harder for investors to rely on the ETF to replicate its benchmark consistently. This unpredictability can signal hidden costs, like high expense ratios or excessive transaction fees, that erode returns over time. For risk managers, a rising tracking error can also be an early warning sign of liquidity problems or structural issues within the fund that need to be addressed before they affect investor returns more significantly.
There is no universal standard for a good tracking error. Some asset classes, investment styles, sectors, and products will inherently have higher tracking error potential than others. Index funds tend to have lower tracking error than active funds. Less volatile products will likewise be easier to keep in line with the benchmark.
