Tracking error формула - Исправление ошибок и поиск оптимальных решений проблем

Formula for Tracking Error (Definition)

Tracking Error Formula is used in order to measure the divergence arising between the price behavior of portfolio and price behavior of the respective benchmark and according to the formula Tracking Error calculation is done by calculating the standard deviation of the difference in return of the portfolio and the benchmark over the period of time.

Tracking error is simply a measure to gauge how much the return of a portfolio or a mutual fund deviates from the return of an index it is trying to replicate in terms of the components of an index and also in the term of the return of that index. There are several mutual funds where the fund managers of that fund aim to construct the fund by closely replicating the stocks of a particular index, by trying to add stocks in his fund with the same proportion. There are two formulas to calculate the tracking error for a portfolio.

The first method is to simply make the difference between the portfolio return and the return from the index it is trying to replicate.

Tracking Error = Rp-Ri

Rp= Return from the portfolio
Ri= Return from the index

You are free to use this image on your website, templates, etc., Please provide us with an attribution linkArticle Link to be Hyperlinked
For eg:
Source: Tracking Error Formula (wallstreetmojo.com)

There is another method to calculate the tracking error of a portfolio with respect to the return from the index the portfolio is tracking.

The second method takes the standard deviation of the return of the portfolio and the benchmark.

The only difference is in this method; it is like calculating the standard deviation of return of the portfolio and that of the index the portfolio is trying to replicate. The second method is the more popular one and is used when the time series of data has a long history; in other words, when the historical data for the return of two variables are available for a longer period of time.

Formula for Tracking Error (Definition)
- Explanation
- Examples
- Use of Tracking Error Formula
- Recommended Articles

Explanation

Tracking error is a measure to find out how much the return of a portfolio or a mutual fund deviates from the return of an index it is trying to replicate in terms of the components of an index and also in the term of the return of that index. But most of the time, it doesn’t get replicated exactly in terms of the return, due to various factors like the timing of buying the stocks, the personal judgment of the fund manager to alter the proportion depending on his style of investment.

Other than these, the volatilities of the stocks in the portfolio and the various charges that are attached for an investor when they invest in a mutual fund also result in deviation of the returns of a portfolio and the index the portfolio tracks.

Examples

You can download this Common Stock Formula Excel Template here – Common Stock Formula Excel Template

Example #1

Let us try to do the calculation of the tracking error with the help of an arbitrary example, say for mutual fund A, which is tracking the oil and gas index. It is calculated by the difference in the return of the two variables.

Tracking Error calculation = Ra – Ro&G

Ra= Return from the portfolio
Ro&g= return from the oil and gas index

Suppose the return from the portfolio is 7%, and the return from the benchmark is 6%. The calculation will be as follows,

In this case, the tracking errors for the portfolio will be 1%.

Example #2

There is a mutual fund managed by a fund manager in SBI. The name of the fund in question is SBI- ETF Nifty Bank. This particular fund is constructed by taking the components of bank nifty closely in the proportion by which the banking stocks are in the bank nifty index.

Tracking Error = Rp-Ri

One year return from the portfolio is 8.9%, and the one-year return from the Nifty benchmark index is 8.6%.

In this case, the tracking errors for the portfolio will be 0.3%.

Example #3

There is a mutual fund managed by a fund manager in Axis Bank. The name of the fund in question is Axis Nifty ETF. This particular fund is constructed by taking the components of the nifty 50 closely in the proportion by which the index stocks are in the Nifty index.

One year return from the portfolio is 5.4%, and the one-year return from the Nifty benchmark index is 3.9%.

In this case, the tracking errors for the portfolio will be 1.5%.

Use of Tracking Error Formula

It helps the investors of a fund to understand whether the fund is closely tracking and replicating the components of the index it is putting up as a benchmark. It showcases whether the fund manager is trying to actively track the benchmark or he is putting his style in order to modify it. It also helps the investors to find out whether the charges are high enough for the fund to impact the return of the fund.

Definition[edit]

If tracking error is measured historically, it is called ‘realized’ or ‘ex post’ tracking error. If a model is used to predict tracking error, it is called ‘ex ante’ tracking error. Ex-post tracking error is more useful for reporting performance, whereas ex-ante tracking error is generally used by portfolio managers to control risk. Various types of ex-ante tracking error models exist, from simple equity models which use beta as a primary determinant to more complicated multi-factor fixed income models. In a factor model of a portfolio, the non-systematic risk (i.e., the standard deviation of the residuals) is called «tracking error» in the investment field. The latter way to compute the tracking error complements the formulas below but results can vary (sometimes by a factor of 2).

Formulas[edit]

The ex-post tracking error formula is the standard deviation of the active returns, given by:

${displaystyle TE=omega ={sqrt {operatorname {Var} (r_{p}-r_{b})}}={sqrt {{E}[(r_{p}-r_{b})^{2}]-({E}[r_{p}-r_{b}])^{2}}}={sqrt {(w_{p}-w_{b})^{T}Sigma (w_{p}-w_{b})}}}$

where ${displaystyle r_{p}-r_{b}}$ is the active return, i.e., the difference between the portfolio return and the benchmark return.^[1] The optimization problem of maximizing the return, subject to tracking error and linear constraints, may be solved using second-order cone programming:

${displaystyle max _{w};mu ^{T}(w-w_{b}),quad {text{s.t.}};(w-w_{b})^{T}Sigma (w-w_{b})leq omega ^{2},;Axleq b,;Cx=d}$

Interpretation[edit]

Under the assumption of normality of returns, an active risk of x per cent would mean that approximately 2/3 of the portfolio’s active returns (one standard deviation from the mean) can be expected to fall between +x and -x per cent of the mean excess return and about 95% of the portfolio’s active returns (two standard deviations from the mean) can be expected to fall between +2x and -2x per cent of the mean excess return.

Examples[edit]

Index funds are expected to have minimal tracking errors.
Inverse exchange-traded funds are designed to perform as the inverse of an index or other benchmark, and thus reflect tracking errors relative to short positions in the underlying index or benchmark.

Index fund creation[edit]

Index funds are expected to minimize the tracking error with respect to the index they are attempting to replicate, and this problem may be solved using standard optimization techniques. To begin, define $omega ^{2}$ to be:

${displaystyle omega ^{2}=(w-w_{b})^{T}Sigma (w-w_{b})}$

where ${displaystyle w_{b}}$ is the benchmark return and Sigma is the covariance matrix of assets in an index. While creating an index fund could involve holding all investable assets in the index, it is sometimes better practice to only invest in a subset of the assets. These considerations lead to the following mixed-integer quadratic programming (MIQP) problem:

${displaystyle {begin{aligned}min _{w}&quad omega ^{2}\{text{s.t.}}&quad w_{j}leq y_{j},quad sum _{j=1}^{N}y_{j}leq K\&quad ell _{j}y_{j}leq w_{j}leq u_{j}y_{j},quad y_{j}in {0,1},quad ell _{j},;u_{j}geq 0end{aligned}}}$

where $y_{j}$ is the logical condition of whether or not an asset is included in the index fund, and is defined as:

${displaystyle y_{j}={begin{cases}1,quad &w_{j}>0\0,quad &{text{otherwise}}end{cases}}}$

References[edit]

^ Cornuejols, Gerard; Tütüncü, Reha (2007). Optimization Methods in Finance. Mathematics, Finance and Risk. Cambridge University Press. pp. 178–180. ISBN 978-0521861700.

External links[edit]

Tracking Error — YouTube
Tracking error: A hidden cost of passive investing
Tracking error
What is the Tracking Error?

Источник

What Is a Tracking Error?

Tracking error is the divergence between the price behavior of a position or a portfolio and the price behavior of a benchmark. This is often in the context of a hedge fund, mutual fund, or exchange-traded fund (ETF) that did not work as effectively as intended, creating an unexpected profit or loss.

Tracking error is reported as a standard deviation percentage difference, which reports the difference between the return an investor receives and that of the benchmark they were attempting to imitate.

Key Takeaways

Tracking error is the difference in actual performance between a position (usually an entire portfolio) and its corresponding benchmark.
The tracking error can be viewed as an indicator of how actively a fund is managed and its corresponding risk level.
Evaluating a past tracking error of a portfolio manager may provide insight into the level of benchmark risk control the manager may demonstrate in the future.

Tracking Error

Understanding a Tracking Error

Since portfolio risk is often measured against a benchmark, tracking error is a commonly used metric to gauge how well an investment is performing. Tracking error shows an investment’s consistency versus a benchmark over a given period of time. Even portfolios that are perfectly indexed against a benchmark behave differently than the benchmark, even though this difference on a day-to-day, quarter-to-quarter, or year-to-year basis may be ever so slight. The measure of tracking error is used to quantify this difference.

Tracking error is the standard deviation of the difference between the returns of an investment and its benchmark. Given a sequence of returns for an investment or portfolio and its benchmark, tracking error is calculated as follows:

Tracking Error = Standard Deviation of (P — B)

Where P is portfolio return and B is benchmark return.

From an investor’s point of view, tracking error can be used to evaluate portfolio managers. If a manager is realizing low average returns and has a large tracking error, it is a sign that there is something significantly wrong with that investment and that the investor should most likely find a replacement.

It may also be used to forecast performance, particularly for quantitative portfolio managers who construct risk models that include the likely factors that influence price changes. The managers then construct a portfolio that uses the type of constituents of a benchmark (such as style, leverage, momentum, or market cap) to create a portfolio that will have a tracking error that closely adheres to the benchmark.

Special Considerations

Factors That Can Affect a Tracking Error

The net asset value (NAV) of an index fund is naturally inclined toward being lower than its benchmark because funds have fees, whereas an index does not. A high expense ratio for a fund can have a significantly negative impact on the fund’s performance. However, it is possible for fund managers to overcome the negative impact of fund fees and outperform the underlying index by doing an above-average job of portfolio rebalancing, managing dividends or interest payments, or securities lending.

Beyond fund fees, a number of other factors can affect a fund’s tracking error. One important factor is the extent to which a fund’s holdings match the holdings of the underlying index or benchmark. Many funds are made up of just the fund manager’s idea of a representative sample of the securities that make up the actual index. There are frequently also differences in weighting between a fund’s assets and the assets of the index.

Illiquid or thinly-traded securities can also increase the chance of a tracking error, since this often leads to prices differing significantly from market price when the fund buys or sells such securities as a result of larger bid-ask spreads. Finally, the level of volatility for an index can also affect the tracking error.

Sector, international, and dividend ETFs tend to have higher absolute tracking errors; broad-based equity and bond ETFs tend to have lower ones. Management expense ratios (MER) are the most prominent cause of tracking error and there tends to be a direct correlation between the size of the MER and tracking error. But other factors can intercede and be more significant at times.

Premiums and Discounts to Net Asset Value

Premiums or discounts to NAV may occur when investors bid the market price of an ETF above or below the NAV of its basket of securities. Such divergences are usually rare. In the case of a premium, the authorized participant typically arbitrages it away by purchasing securities in the ETF basket, exchanging them for ETF units, and selling the units on the stock market to earn a profit (until the premium is gone). Premiums and discounts as high as 5% have been known to occur, particularly for thinly traded ETFs.

Optimization

When there are thinly traded stocks in the benchmark index, the ETF provider can’t buy them without pushing their prices up substantially, so it uses a sample containing the more liquid stocks to proxy the index. This is called portfolio optimization.

Diversification Constraints

ETFs are registered with regulators as mutual funds and need to abide by the applicable regulations. Of note are two diversification requirements: 75% of its assets must be invested in cash, government securities, and securities of other investment companies, and no more than 5% of the total assets can be invested in any one security. This can create problems for ETFs tracking the performance of a sector where there are a lot of dominant companies.

Cash Drag

Indexes don’t have cash holdings, but ETFs do. Cash can accumulate at intervals due to dividend payments, overnight balances, and trading activity. The lag between receiving and reinvesting the cash can lead to a decline in performance known as drag. Dividend funds with high payout yields are most susceptible.

Index Changes

ETFs track indexes and when the indexes are updated, the ETFs have to follow suit. Updating the ETF portfolio incurs transaction costs. And it may not always be possible to do it the same way as the index. For example, a stock added to the ETF may be at a different price than what the index maker selected.

Capital-Gains Distributions

ETFs are more tax-efficient than mutual funds but have nevertheless been known to distribute capital gains that are taxable in the hands of unitholders. Although it may not be immediately apparent, these distributions create a different performance than the index on an after-tax basis. Indexes with a high level of turnover in companies (e.g., mergers, acquisitions, and spin-offs) are one source of capital-gains distributions. The higher the turnover rate, the higher the likelihood the ETF will be compelled to sell securities at a profit.

Securities Lending

Some ETF companies may offset tracking errors through security lending, which is the practice of lending out holdings in the ETF portfolio to hedge funds for short selling. The lending fees collected from this practice can be used to lower tracking error if so desired.

Currency Hedging

International ETFs with currency hedging may not follow a benchmark index due to the costs of currency hedging, which are not always embodied in the MER. Factors affecting hedging costs include market volatility and interest-rate differentials, which impact the pricing and performance of forward contracts.

Futures Roll

Commodity ETFs, in many cases, track the price of a commodity through the futures markets, buying the contract closest to expiry. As the weeks pass and the contract nears expiration, the ETF provider will sell it (to avoid taking delivery) and buy the next month’s contract. This operation, known as the «roll,» is repeated every month. If contracts further from expiration have higher prices (contango), the roll into the next month will be at a higher price, which incurs a loss. Thus, even if the spot price of the commodity stays the same or rises slightly, the ETF could still show a decline. Vice versa, if futures further away from expiration have lower prices (backwardation), the ETF will have an upward bias.

Maintaining Constant Leverage

Leveraged and inverse ETFs use swaps, forwards, and futures to replicate on a daily basis two or three times the direct or inverse return of a benchmark index. This requires rebalancing the basket of derivatives daily to ensure they deliver the specified multiple of the index’s change each day.

Example of a Tracking Error

For example, assume that there is a large-cap mutual fund benchmarked to the S&P 500 index. Next, assume that the mutual fund and the index realized the following returns over a given five-year period:

Mutual Fund: 11%, 3%, 12%, 14% and 8%.
S&P 500 index: 12%, 5%, 13%, 9% and 7%.

Given this data, the series of differences is then (11% — 12%), (3% — 5%), (12% — 13%), (14% — 9%) and (8% — 7%). These differences equal -1%, -2%, -1%, 5%, and 1%. The standard deviation of this series of differences, the tracking error, is 2.50%.

Источник

A measure of the difference between the return fluctuations of an investment portfolio and the return fluctuations of a chosen benchmark

What is Tracking Error?

Tracking error is a measure of financial performance that determines the difference between the return fluctuations of an investment portfolio and the return fluctuations of a chosen benchmark. The return fluctuations are primarily measured by standard deviations.

Generally, a benchmark is a diversified market index that represents part of the total market. The most common benchmarks for equity portfolios are the S&P 500 and the Dow Jones Industrial Average (DJIA) for portfolios with large-cap stocks, and the Russell 2000 for small-cap portfolios.

Importance of Tracking Error

Tracking error is one of the most important measures used to assess the performance of a portfolio, as well as the ability of a portfolio manager to generate excessive returns and beat the market or the benchmark. Due to the abovementioned reasons, it is used as an input to calculate the information ratio.

Tracking error is frequently categorized by the way it is calculated. A realized (also known as “ex post”) tracking error is calculated using historical returns. A tracking error whose calculations are based on some forecasting model is called an “ex ante” tracking error.

Low errors indicate that the performance of the portfolio is close to the performance of the benchmark. Low errors are common with index funds and ETFs that replicate the composition of major stock market indices.

High errors reveal that the portfolio’s performance is significantly different from the performance of the benchmark. The high errors can indicate that the portfolio substantially beat the benchmark, or signal that the portfolio significantly underperforms the benchmark.

Formula for Tracking

Tracking efficiency is calculated using the following formula:

Where:

Var – the variance
r_p– the return of a portfolio
r_b– the return of a benchmark

Example of Tracking Error

Five years ago, Sam invested $100,000 in Fund A. The fund primarily invests in large-cap US equities. During the five-year period, the fund showed positive returns. Also, the economy also grew during the period and equity markets rose.

In order to assess how successful his investment was, Sam decides to compare the returns of Fund A against the returns of a benchmark. In such a case, the most appropriate benchmark is the S&P 500 because it tracks the performance of the biggest large-cap companies.

The comparison of the fund against the benchmark can be measured using the tracking error.

The following data is available for the yearly returns for both Fund A and the S&P 500:

We can plug this data into the formula to calculate the tracking error:

In the scenario above, the small tracking error indicates that Fund A does not significantly outperform the benchmark. Therefore, Sam may consider withdrawing his money from the fund and putting it into other, more promising investment opportunities. Alternatively, he may be satisfied with the fact that his portfolio is keeping pace with the gains of the overall market.

Что это такое:

Ошибка отслеживания — это разница между доходами портфеля и эталоном или индексом предназначенный для имитации или избиения. Ошибка отслеживания иногда называется активным риском.

Существует два способа измерения ошибки отслеживания. Первый заключается в вычитании суммарной доходности контрольного показателя из возвратов портфеля, как показано ниже:

Возврат _p — Возврат _i = Ошибка отслеживания

Где:

p = портфель

i = индекс или ориентир

Тем не менее, второй путь более распространен, что заключается в вычислении стандартного отклонения разницы в портфеле и повторных результатов с течением времени. Формула такова:

Как это работает (пример):

Предположим, вы инвестируете в взаимный фонд компании XYZ, который существует для тиражирования индекса Russell 2000 как по составу, так и по доходности. Если взаимный фонд компании XYZ возвращает 5,5% в год, а Russell 2000 (эталон) возвращает 5,0%, то, используя первую формулу выше, мы бы сказали, что у взаимного фонда компании XYZ была ошибка отслеживания 0,5%.

Со временем будет больше периодов, в течение которых мы можем сравнивать доходность. Здесь вторая формула становится более полезной. Консистенция (или несогласованность) «спредов» между доходами портфеля и доходностью эталона позволяет аналитикам попытаться предсказать будущую производительность портфеля. Если, например, мы знали, что годовая доходность портфеля на 0,4% выше, чем в контрольном контроле 67% времени за последние пять лет, мы бы знали, что это, вероятно, произойдет в будущем (предполагая, что управляющий портфелем не сделал никаких крупных изменения). Прогностическая ценность этих вычислений становится еще лучше, когда есть больше точек данных, и когда аналитик объясняет, как ценные бумаги портфеля перемещаются относительно друг друга (это называется со-дисперсией).

Несколько факторов обычно определяют ошибку отслеживания портфеля:

1. Степень, в которой портфель и контрольный показатель имеют общие ценные бумаги

2. Различия в рыночной капитализации, сроках, стиле инвестиций и других фундаментальных характеристиках портфеля и эталонных показателях

3. Различия в взвешивании активов между портфелем и эталоном

4. Плата за управление, сборы за хранение, брокерские расходы и другие расходы, влияющие на портфель, который не влияет на эталонный показатель

5. Волатильность эталона

6. Бета-версия портфеля

Кроме того, портфельные менеджеры должны учитывать приток и отток денежных средств от инвесторов, что заставляет их время от времени перестраивать свои портфели. Это также связано с прямыми и косвенными затратами.

800×600

Почему это имеет значение:

Низкая ошибка отслеживания означает, что портфель внимательно следит за своим эталоном. Высокие ошибки отслеживания указывают на противоположное. Таким образом, ошибка отслеживания дает инвесторам представление о том, как «жесткий» портфель, о котором идет речь, находится вокруг его контрольного показателя или насколько изменчивый портфель по сравнению с его эталоном. Важно отметить, что некоторые контрольные портфели допускают большую ошибку отслеживания, чем другие, поэтому инвесторы должны понять, предназначены ли их ориентированные на портфель портфели, чтобы либо скопировать контрольный показатель, либо инвестировать таким образом, который отражает дух эталона, либо просто попытаться чтобы статистически воссоздать поведение эталона.

Хотя некоторые инвесторы могут быть счастливы, что портфель в нашем примере превысил контрольный показатель, ошибка отслеживания на самом деле свидетельствует о том, что менеджер фонда взял на себя больший риск. Это не всегда то, что хотят инвесторы фонда, и именно поэтому ошибка отслеживания в какой-то мере является показателем избыточного риска.

Хотя эталонный показатель представляет собой возможную альтернативу рассматриваемому портфелю, вычисление ошибки отслеживания не означает разумного инвестор должен ограничивать сравнение только с эталоном; он или она будет также оценивать ошибки отслеживания других портфелей с той же целью.

В конечном счете, ошибка отслеживания является показателем мастерства менеджера и отражает то, насколько активно или пассивно управляется портфель. Активно управляемые портфели стремятся предоставить вышезадачные результаты, и они обычно требуют дополнительного риска и опыта для этого. В этих случаях инвестор стремится максимизировать ошибку отслеживания. С другой стороны, пассивно управляемые портфели стремятся тиражировать доходность индекса, поэтому большая ошибка отслеживания обычно считается нежелательной для этих инвесторов. Вот почему ошибка отслеживания может использоваться для установки допустимых диапазонов производительности для менеджеров портфеля.

Источник

Содержание

Ошибка слежения в биржевых и ETF-фондах: что это такое и почему ее надо учитывать
Содержание статьи
Что такое биржевые и ETF-фонды
Что такое ошибка слежения и зачем на нее смотреть
Факторы, которые могут повлиять на ошибку отслеживания
Tracking Error
What Is a Tracking Error?
Key Takeaways
Tracking Error
Understanding a Tracking Error
Special Considerations
Factors That Can Affect a Tracking Error
Premiums and Discounts to Net Asset Value
Optimization
Diversification Constraints
Cash Drag
Index Changes
Capital-Gains Distributions
Securities Lending
Currency Hedging
Futures Roll
Maintaining Constant Leverage
Example of a Tracking Error
Tracking Error
What is Tracking Error?
Importance of Tracking Error
Formula for Tracking
Example of Tracking Error
Related Readings

Ошибка слежения в биржевых и ETF-фондах: что это такое и почему ее надо учитывать

Содержание статьи

Разбираемся, что значит данный показатель, как он рассчитывается и почему его важно знать.

Что такое биржевые и ETF-фонды

ETF (exchange-traded fund) дословно переводится как торгуемый на бирже фонд. Это фонд, паи (акции) которого обращаются на бирже. ETF может повторять структуру какого-либо индекса, например индекса S&P 500, а может быть собран из акций или облигаций компаний из конкретного сектора экономики, например, технологического или энергетического.

Суть инструмента в том, чтобы сделать доступными инвестиции розничным инвесторам, которым не по карману покупать много различных акций или облигаций по отдельности. Покупая пай ETF-фонда, который состоит из десятков ценных бумаг, инвестор тоже приобретает их, но опосредованно.

Аналогом ETF-фондов в России выступают биржевые паевые инвестиционные фонды (БПИФы). ETF и БПИФы могут включать самые разные активы, имеют высокую диверсификацию, низкую цену входа и существенно меньшую комиссию, чем другие виды паевых фондов. Чтобы их купить или продать, не нужно обращаться в управляющую компанию, сделку можно совершить самостоятельно, этим ETF и БПИФы схожи с акциями. Принципиальная разница между ETF и БПИФами лежит в юридической плоскости: ETF регистрируются за рубежом (США, Европа, Ирландия), БПИФы — в России.

Что такое ошибка слежения и зачем на нее смотреть

Суть ETF и БПИФов предполагает, что они должны максимально точно повторять динамику выбранного индекса или динамику собранной корзины ценных бумаг (базового актива).

Возьмем БПИФ «Тинькофф — Вечный портфель RUB». Фонд инвестирует в акции, долгосрочные и краткосрочные облигации, а также физическое золото в равных долях по 25%. Изменение стоимости пая всего фонда будет в большей или меньшей степени следовать за теми инструментами, доля которых наиболее велика в его структуре.

Однако именно из-за того, как сформирован фонд и доля каких инструментов в нем выше, а также какие комиссии предусмотрены, может возникнуть ошибка слежения (tracking error).

Ошибка слежения или ошибка отслеживания — это показатель отклонения дневных доходностей фонда от индекса или корзины ценных бумаг в пересчете на год. Простыми словами это разница между доходностью фонда и базового актива с учетом статистической погрешности. Она исчисляется в процентах. Ошибка слежения в инвестициях демонстрирует, насколько точно фонд повторяет динамику выбранного инструмента.

Низкая ошибка слежения показывает, что ETF или БПИФ максимально точно повторяет динамику индекса или корзину ценных бумаг, а значит, и доходность будет схожей. Высокая ошибка слежения, напротив, говорит о том, что фонд не в полной мере следует за изменением стоимости базового актива и, скорее всего, управляется малоэффективно.

Факторы, которые могут повлиять на ошибку отслеживания

В первую очередь на ошибку слежения влияет комиссия управляющей компании (УК) фонда за свои услуги. Чем выше комиссия УК, тем сильнее негативное влияние на результаты фонда, а следовательно, на размер ошибки слежения.

Источник

Tracking Error

James Chen, CMT is an expert trader, investment adviser, and global market strategist. He has authored books on technical analysis and foreign exchange trading.

Gordon Scott has been an active investor and technical analyst of securities, futures, forex, and penny stocks for 20+ years. He is a member of the Investopedia Financial Review Board and is a Chartered Market Technician (CMT).