US Sector Climber
Sharpe Ratio
Volatility Target
Max. LeverageThe US Sector Climber aims to outperform S&P 500 on a sharpe ratio basis by changing allocations to sectors more dynamicly and based on the sector's recent trend.
It takes correlations into account to minimize volatility; therefore it is expected the have better returns in down markets while tracking S&P closely in bullish markets.
The portfolio is rebalanced at multiple times daily, particularly when the underlying assets experience sharpe changes in expected returns, volatility, or correlations. The strategy targets at most 10% volatility. Access to the strategy is available through 1 delta or structured products replication.
Real Time Strategy Performance1
| Name | Allocation | 1 Month P&L | Last Trade | Expected Return | Expected Vol |
|---|---|---|---|---|---|
| Technology | 10% | -$1,314.35 | 12/2, 15:00:00 | 10% | 11% |
| Basic Materials | 2% | -$57.12 | 12/2, 15:00:00 | 33% | 9% |
| Consumer Staples | 28% | -$11.53 | 12/2, 15:00:00 | 63% | 8% |
| Consumer Discretionary | 4% | -$396.86 | 12/2, 15:00:00 | 51% | 10% |
| Industrials | 1% | -$48.54 | 12/2, 15:00:00 | 42% | 6% |
| Communication | 0% | -$5.16 | 11/26, 14:00:00 | 17% | 8% |
| Health Care | 18% | $4,030.49 | 12/2, 15:00:00 | 27% | 7% |
| Financials | 5% | -$206.04 | 12/2, 15:00:00 | 42% | 8% |
| Energy | 17% | $568.54 | 12/2, 15:00:00 | 54% | 12% |
| Utilities | 2% | -$54.41 | 12/2, 15:00:00 | -65% | 8% |
| Real Estate | 6% | $73.55 | 12/2, 15:00:00 | 49% | 7% |
| Gold | 7% | $441.05 | 12/2, 15:00:00 | 13% | 9% |
Strategy Access
Strategy Construction
The U.S. Sector Climber quantitative investment strategy (the Strategy) invests into 11 U.S. sector ETFs, and a gold ETF. To allocate between these investments, the Strategy performs a mean-variance optimization (MVO) at several points during the day using short term expected returns and volatilities, and longer term correlation estimates. Resulting weights are smoothed before they are translated into share numbers.
1. Expected Return and Covariance Estimation
For each asset, returns are estimated using exponentially decaying log returns of VWAP prices over a 10 minute window, every 10 minutes during the trading day which typically starts at 9:30am and ends at 4pm. To avoid fitting to outliers, two averages are used; the decay factors λi are set to λ1=0.97 and λ2=0.94. The two averages are then combined using weights proportional to 1/σi where σi is the standard deviation of the return, calculated using the same decay factors.
To calculate the covariance matrix we first estimate an exponentially decaying covariance matrix and back out the correlation matrix. We then use a slow decay factor of λcov=0.99987148154578 to update the previous correlation matrix with the new one. In a second step we estimate variances of the returns using a fast decay factor of λvar=0.97 and calculate the final covariance matrix using the correlation matrix and the variance.
This approach is more robust as correlations are typically slower moving, while variances can change quickly. Moreover, by separating correlations and variances we can more easily deal with missing values.
2. Optimization
At specified points in time throughout the trading day the Strategy runs a MVO using the covariances and expected returns as above. The MVO aims to find a fully invested portfolio with the highest return for a 10% volatility target. The result of the MVO is weighted against the previous weights using
αMVO=0.1 for the new target weights.
3. Volatility Targeting
Every 10 minutes the Strategy checks its ex-ante volatility using the covariance matrix estimated above. If the ex-ante volatility is larger than 10%, it will scale down all weights to reach an estimated volatility of 10%. If volatility is estimated to be below 10% it will scale up weights up to a maximum total of 1.0: the strategy leverage should never exceed 1.
Volatility targeting happens after the MVO in case a MVO is performed at the same instant.
4. Smoothing
To avoid high turnover, weight changes have to be at least 2% of the total Strategy level. Any change to weights below that threshold will be ignored, and the old value is used instead.
5. Implementation and Trading
The resulting weights are translated into share quantities using the previous strategy level, calculated from last trading prices. If current trading prices are missing, the last known value is used. After share quantities are calculated, the central hedging facility is notified of the change, at which point it will update client portfolios by trading to the new quantities.
Strategy construction as of 3/30/2023. To adapt to structural changes in the market, GLR Investment Advisory may tweak certain parameters at any time. If the situation allows, GLR Investment Advisory will inform clients ahead of any changes. For a major update GLR will typically create a new version of the strategy, at which point clients can switch their allocations to the new version if desired.
FAQFrequently Asked Questions
For general questions please consult this page.
Questions specific to this strategy are answered here;
if you have additional Questions please email us at pm@glrtec.com
Why do allocations not add up to 100%?
The strategy will put your money into cash if markets are too risky. If the ex-ante volatility exceeds 10%, all weights are scaled down proportionally to arrive at a volatility estimte of 10%. Please note that "cash" may in reality be a ultra short term money market ETF if such ETF earns higher interest than keeping the money as cash in your account.
What's the difference between Communications and Technology?
Is correlation accounted for?