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 |

'Total return is the amount of value an investor earns from a security over a specific period, typically one year, when all distributions are reinvested. Total return is expressed as a percentage of the amount invested. For example, a total return of 20% means the security increased by 20% of its original value due to a price increase, distribution of dividends (if a stock), coupons (if a bond) or capital gains (if a fund). Total return is a strong measure of an investment’s overall performance.'

Applying this definition to our asset in some examples:- The total return, or increase in value over 5 years of US Sector Rotation Strategy is 108.5%, which is higher, thus better compared to the benchmark SPY (99.9%) in the same period.
- Compared with SPY (35%) in the period of the last 3 years, the total return, or increase in value of 34.4% is lower, 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 15.9%, which is higher, thus better compared to the benchmark SPY (14.9%) in the same period.
- During the last 3 years, the annual performance (CAGR) is 10.4%, which is lower, thus worse than the value of 10.5% from the benchmark.

'Volatility is a statistical measure of the dispersion of returns for a given security or market index. Volatility can either be measured by using the standard deviation or variance between returns from that same security or market index. Commonly, the higher the volatility, the riskier the security. In the securities markets, volatility is often associated with big swings in either direction. For example, when the stock market rises and falls more than one percent over a sustained period of time, it is called a 'volatile' market.'

Which means for our asset as example:- Looking at the volatility of 12.7% in the last 5 years of US Sector Rotation Strategy, we see it is relatively lower, thus better in comparison to the benchmark SPY (20.9%)
- During the last 3 years, the volatility is 12.5%, which is smaller, thus better than the value of 17.3% from the benchmark.

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

Applying this definition to our asset in some examples:- The downside volatility over 5 years of US Sector Rotation Strategy is 9.2%, which is lower, thus better compared to the benchmark SPY (15%) in the same period.
- Looking at downside volatility in of 9.1% in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (12%).

'The Sharpe ratio is the measure of risk-adjusted return of a financial portfolio. Sharpe ratio is a measure of excess portfolio return over the risk-free rate relative to its standard deviation. Normally, the 90-day Treasury bill rate is taken as the proxy for risk-free rate. A portfolio with a higher Sharpe ratio is considered superior relative to its peers. The measure was named after William F Sharpe, a Nobel laureate and professor of finance, emeritus at Stanford University.'

Which means for our asset as example:- The risk / return profile (Sharpe) over 5 years of US Sector Rotation Strategy is 1.05, which is greater, thus better compared to the benchmark SPY (0.59) in the same period.
- Compared with SPY (0.47) in the period of the last 3 years, the risk / return profile (Sharpe) of 0.63 is larger, thus better.

'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.'

Which means for our asset as example:- Looking at the excess return divided by the downside deviation of 1.46 in the last 5 years of US Sector Rotation Strategy, we see it is relatively higher, thus better in comparison to the benchmark SPY (0.83)
- During the last 3 years, the excess return divided by the downside deviation is 0.87, which is greater, thus better than the value of 0.67 from the benchmark.

'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.'

Which means for our asset as example:- Compared with the benchmark SPY (9.32 ) in the period of the last 5 years, the Ulcer Index of 6.01 of US Sector Rotation Strategy is lower, thus better.
- During the last 3 years, the Downside risk index is 7.32 , which is smaller, thus better than the value of 10 from the benchmark.

'A maximum drawdown is the maximum loss from a peak to a trough of a portfolio, before a new peak is attained. Maximum Drawdown is an indicator of downside risk over a specified time period. It can be used both as a stand-alone measure or as an input into other metrics such as 'Return over Maximum Drawdown' and the Calmar Ratio. Maximum Drawdown is expressed in percentage terms.'

Using this definition on our asset we see for example:- The maximum drop from peak to valley over 5 years of US Sector Rotation Strategy is -16.4 days, which is higher, thus better compared to the benchmark SPY (-33.7 days) in the same period.
- During the last 3 years, the maximum DrawDown is -16.4 days, which is greater, thus better than the value of -24.5 days from the benchmark.

'The Maximum 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. It is the length of time the account was in the Max Drawdown. A Max Drawdown measures a retrenchment from when an equity curve reaches a new high. It’s the maximum an account lost during that retrenchment. This method is applied because a valley can’t be measured until a new high occurs. Once the new high is reached, the percentage change from the old high to the bottom of the largest trough is recorded.'

Applying this definition to our asset in some examples:- The maximum days under water over 5 years of US Sector Rotation Strategy is 507 days, which is larger, thus worse compared to the benchmark SPY (488 days) in the same period.
- Compared with SPY (488 days) in the period of the last 3 years, the maximum days below previous high of 507 days is higher, thus worse.

'The Drawdown Duration is the length of any peak to peak period, or the time between new equity highs. 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.'

Which means for our asset as example:- The average time in days below previous high water mark over 5 years of US Sector Rotation Strategy is 131 days, which is greater, thus worse compared to the benchmark SPY (124 days) in the same period.
- Looking at average days below previous high in of 190 days in the period of the last 3 years, we see it is relatively higher, thus worse in comparison to SPY (181 days).

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