The U.S. Sector strategy allocates dynamically between four long U.S. sector sub-strategies. Each of the four long sub-strategies use different momentum and mean reversion criteria

Due to the low correlation of these strategies, the combination creates a strategy with a considerably higher Sharpe Ratio than a simple sector rotation.

The strategy uses SPDR sector ETFs, but you can replace these with the corresponding sector ETFs or futures from other issuers.

US sectors have historically been good for trend following systems because each sector usually over or under performs for long periods at a time due to longer lasting economic cycles and not just short-term market fluctuations.

The economy itself is not a linear stable system, but swings between periods of expansion (growth) and contraction (recession). This results in a series of market cycles which are visualized in the following picture.

Source: http://www.nowandfutures.com (Global Business Cycles)

Each market cycle favors different industry sectors. The goal of a good working strategy is to choose the best performing sectors while avoiding or even shorting the worst performing sectors.

You can read the original strategy whitepaper for more details.

U.S. industry sectors ETFs, their corresponding inverse or short sector ETFs and optional futures:

U.S. Sector |
ETF |
Inverse (leverage) |
Globex Futures |

Materials | XLB | SMN (-2x) | IXB |

Energy | XLE | ERY (-3x) | IXEe |

Financial | XLF | SKF (-2x) | IXM |

Industrials | XLI | SIJ (-2x) | IXI |

Technology | XLK | REW (-2x) | IXT |

Consumer Staples | XLP | SZK (-2x) | IXR |

Real Estate | XLRE | SRS (-2x) | - |

Utilities | XLU | SDP (-2x) | IXU |

Health Care | XLV | RXD (-2x) | IXV |

Consumer Discretionary | XLY | SCC (-2x) | IXY |

'The total return on a portfolio of investments takes into account not only the capital appreciation on the portfolio, but also the income received on the portfolio. The income typically consists of interest, dividends, and securities lending fees. This contrasts with the price return, which takes into account only the capital gain on an investment.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (64%) in the period of the last 5 years, the total return of 81.2% of US Sector Rotation Strategy is larger, thus better.
- Compared with SPY (51.6%) in the period of the last 3 years, the total return of 35% is smaller, thus worse.

'The compound annual growth rate (CAGR) is a useful measure of growth over multiple time periods. It can be thought of as the growth rate that gets you from the initial investment value to the ending investment value if you assume that the investment has been compounding over the time period.'

Applying this definition to our asset in some examples:- The annual performance (CAGR) over 5 years of US Sector Rotation Strategy is 12.6%, which is greater, thus better compared to the benchmark SPY (10.4%) in the same period.
- Looking at compounded annual growth rate (CAGR) in of 10.5% in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (14.9%).

'Volatility is a rate at which the price of a security increases or decreases for a given set of returns. Volatility is measured by calculating the standard deviation of the annualized returns over a given period of time. It shows the range to which the price of a security may increase or decrease. Volatility measures the risk of a security. It is used in option pricing formula to gauge the fluctuations in the returns of the underlying assets. Volatility indicates the pricing behavior of the security and helps estimate the fluctuations that may happen in a short period of time.'

Which means for our asset as example:- Looking at the volatility of 8.2% in the last 5 years of US Sector Rotation Strategy, we see it is relatively lower, thus better in comparison to the benchmark SPY (13.4%)
- During the last 3 years, the 30 days standard deviation is 7.6%, which is lower, thus better than the value of 12.5% from the benchmark.

'The downside volatility is similar to the volatility, or standard deviation, but only takes losing/negative periods into account.'

Using this definition on our asset we see for example:- Compared with the benchmark SPY (14.6%) in the period of the last 5 years, the downside risk of 8.8% of US Sector Rotation Strategy is smaller, thus better.
- Looking at downside risk in of 8.3% in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (14%).

'The Sharpe ratio (also known as the Sharpe index, the Sharpe measure, and the reward-to-variability ratio) is a way to examine the performance of an investment by adjusting for its risk. The ratio measures the excess return (or risk premium) per unit of deviation in an investment asset or a trading strategy, typically referred to as risk, named after William F. Sharpe.'

Which means for our asset as example:- Looking at the Sharpe Ratio of 1.24 in the last 5 years of US Sector Rotation Strategy, we see it is relatively larger, thus better in comparison to the benchmark SPY (0.59)
- Looking at Sharpe Ratio in of 1.05 in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (1).

'The Sortino ratio improves upon the Sharpe ratio by isolating downside volatility from total volatility by dividing excess return by the downside deviation. The Sortino ratio is a variation of the Sharpe ratio that differentiates harmful volatility from total overall volatility by using the asset's standard deviation of negative asset returns, called downside deviation. The Sortino ratio takes the asset's return and subtracts the risk-free rate, and then divides that amount by the asset's downside deviation. The ratio was named after Frank A. Sortino.'

Applying this definition to our asset in some examples:- Looking at the downside risk / excess return profile of 1.16 in the last 5 years of US Sector Rotation Strategy, we see it is relatively higher, thus better in comparison to the benchmark SPY (0.54)
- Looking at downside risk / excess return profile in of 0.97 in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (0.89).

'The ulcer index is a stock market risk measure or technical analysis indicator devised by Peter Martin in 1987, and published by him and Byron McCann in their 1989 book The Investors Guide to Fidelity Funds. It's designed as a measure of volatility, but only volatility in the downward direction, i.e. the amount of drawdown or retracement occurring over a period. Other volatility measures like standard deviation treat up and down movement equally, but a trader doesn't mind upward movement, it's the downside that causes stress and stomach ulcers that the index's name suggests.'

Using this definition on our asset we see for example:- Looking at the Ulcer Ratio of 1.92 in the last 5 years of US Sector Rotation Strategy, we see it is relatively smaller, thus better in comparison to the benchmark SPY (3.99 )
- Compared with SPY (4.04 ) in the period of the last 3 years, the Ulcer Ratio of 2.14 is lower, thus better.

'Maximum drawdown is defined as the peak-to-trough decline of an investment during a specific period. It is usually quoted as a percentage of the peak value. The maximum drawdown can be calculated based on absolute returns, in order to identify strategies that suffer less during market downturns, such as low-volatility strategies. However, the maximum drawdown can also be calculated based on returns relative to a benchmark index, for identifying strategies that show steady outperformance over time.'

Applying this definition to our asset in some examples:- Looking at the maximum drop from peak to valley of -8.6 days in the last 5 years of US Sector Rotation Strategy, we see it is relatively larger, thus better in comparison to the benchmark SPY (-19.3 days)
- During the last 3 years, the maximum reduction from previous high is -8.6 days, which is larger, thus better than the value of -19.3 days from the benchmark.

'The Drawdown Duration is the length of any peak to peak period, or the time between new equity highs. The Max Drawdown Duration is the worst (the maximum/longest) amount of time an investment has seen between peaks (equity highs). Many assume Max DD Duration is the length of time between new highs during which the Max DD (magnitude) occurred. But that isn’t always the case. The Max DD duration is the longest time between peaks, period. So it could be the time when the program also had its biggest peak to valley loss (and usually is, because the program needs a long time to recover from the largest loss), but it doesn’t have to be'

Which means for our asset as example:- Compared with the benchmark SPY (187 days) in the period of the last 5 years, the maximum days under water of 135 days of US Sector Rotation Strategy is lower, thus better.
- Compared with SPY (139 days) in the period of the last 3 years, the maximum days under water of 135 days is smaller, thus better.

'The Average Drawdown Duration is an extension of the Maximum Drawdown. However, this metric does not explain the drawdown in dollars or percentages, rather in days, weeks, or months. The Avg Drawdown Duration is the average amount of time an investment has seen between peaks (equity highs), or in other terms the average of time under water of all drawdowns. So in contrast to the Maximum duration it does not measure only one drawdown event but calculates the average of all.'

Applying this definition to our asset in some examples:- The average days below previous high over 5 years of US Sector Rotation Strategy is 26 days, which is smaller, thus better compared to the benchmark SPY (41 days) in the same period.
- During the last 3 years, the average days under water is 36 days, which is larger, thus worse than the value of 36 days from the benchmark.

Historical returns have been extended using synthetic data.
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- "Year" returns in the table above are not equal to the sum of monthly returns due to compounding.
- Performance results of US Sector Rotation Strategy are hypothetical, do not account for slippage, fees or taxes, and are based on backtesting, which has many inherent limitations, some of which are described in our Terms of Use.