A sub-strategy for the U.S. Sector strategy. It goes long the worst performing U.S. sectors assuming they may rebound.

See the main US Sector strategy for a detailed asset description.

'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.'

Which means for our asset as example:- The total return over 5 years of US sectors worst US sectors is 119.3%, which is greater, thus better compared to the benchmark SPY (60.9%) in the same period.
- Compared with SPY (34.2%) in the period of the last 3 years, the total return, or increase in value of 47.4% is higher, thus better.

'The compound annual growth rate isn't a true return rate, but rather a representational figure. It is essentially a number that describes the rate at which an investment would have grown if it had grown the same rate every year and the profits were reinvested at the end of each year. In reality, this sort of performance is unlikely. However, CAGR can be used to smooth returns so that they may be more easily understood when compared to alternative investments.'

Using this definition on our asset we see for example:- Looking at the compounded annual growth rate (CAGR) of 17% in the last 5 years of US sectors worst US sectors, we see it is relatively higher, thus better in comparison to the benchmark SPY (10%)
- Looking at compounded annual growth rate (CAGR) in of 13.8% in the period of the last 3 years, we see it is relatively higher, thus better in comparison to SPY (10.3%).

'In finance, volatility (symbol σ) is the degree of variation of a trading price series over time as measured by the standard deviation of logarithmic returns. Historic volatility measures a time series of past market prices. Implied volatility looks forward in time, being derived from the market price of a market-traded derivative (in particular, an option). Commonly, the higher the volatility, the riskier the security.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (18.7%) in the period of the last 5 years, the historical 30 days volatility of 19% of US sectors worst US sectors is greater, thus worse.
- Compared with SPY (21.5%) in the period of the last 3 years, the historical 30 days volatility of 21.3% is smaller, thus better.

'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:- The downside deviation over 5 years of US sectors worst US sectors is 12.9%, which is lower, thus better compared to the benchmark SPY (13.6%) in the same period.
- Compared with SPY (15.7%) in the period of the last 3 years, the downside risk of 14.6% is lower, thus better.

'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.'

Applying this definition to our asset in some examples:- Looking at the ratio of return and volatility (Sharpe) of 0.76 in the last 5 years of US sectors worst US sectors, we see it is relatively greater, thus better in comparison to the benchmark SPY (0.4)
- Compared with SPY (0.36) in the period of the last 3 years, the Sharpe Ratio of 0.53 is greater, 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:- The excess return divided by the downside deviation over 5 years of US sectors worst US sectors is 1.13, which is higher, thus better compared to the benchmark SPY (0.55) in the same period.
- Looking at ratio of annual return and downside deviation in of 0.78 in the period of the last 3 years, we see it is relatively larger, thus better in comparison to SPY (0.5).

'The Ulcer Index is a technical indicator that measures downside risk, in terms of both the depth and duration of price declines. The index increases in value as the price moves farther away from a recent high and falls as the price rises to new highs. The indicator is usually calculated over a 14-day period, with the Ulcer Index showing the percentage drawdown a trader can expect from the high over that period. The greater the value of the Ulcer Index, the longer it takes for a stock to get back to the former high.'

Using this definition on our asset we see for example:- The Ulcer Ratio over 5 years of US sectors worst US sectors is 6.57 , which is higher, thus worse compared to the benchmark SPY (5.82 ) in the same period.
- During the last 3 years, the Ulcer Index is 7.94 , which is greater, thus worse than the value of 6.86 from the benchmark.

'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:- Compared with the benchmark SPY (-33.7 days) in the period of the last 5 years, the maximum DrawDown of -37.3 days of US sectors worst US sectors is lower, thus worse.
- Looking at maximum reduction from previous high in of -37.3 days in the period of the last 3 years, we see it is relatively smaller, thus worse in comparison to SPY (-33.7 days).

'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) in days.'

Which means for our asset as example:- The maximum days below previous high over 5 years of US sectors worst US sectors is 129 days, which is smaller, thus better compared to the benchmark SPY (187 days) in the same period.
- Looking at maximum days below previous high in of 124 days in the period of the last 3 years, we see it is relatively lower, thus better in comparison to SPY (139 days).

'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.'

Applying this definition to our asset in some examples:- Compared with the benchmark SPY (43 days) in the period of the last 5 years, the average days below previous high of 30 days of US sectors worst US sectors is smaller, thus better.
- During the last 3 years, the average time in days below previous high water mark is 32 days, which is smaller, thus better than the value of 39 days from the benchmark.

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 sectors worst US sectors 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.