Global Developed Outperformers
Last Login: 2022-01-23
Performance
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-6.4 %since 2019-11-22
-
-0.9 %1 Year
-
-3.0 %Ø-Performance per year
Risk
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-16.7 %Maximum loss (to date)
-
0.00×Risk factor
Trading Idea
The constituents of this portfolio are found through a variety of proprietary Python algorithms that scan SP500 stocks.
The portfolio is updated every two to four weeks, given that the models forecast stock price changes for this duration of time.
The algorithms are mostly the standard ones with performance-oriented tweaks. Given that using constituents of one index only leads to a high correlation in the stocks' prices, i.e. less diversification and thus higher risk, the portfolio will soon be updated to include a variety of asset types spread out over multiple international indices.
Return is engineered to be at 39%/annum at a risk of 14%. show more
The portfolio is updated every two to four weeks, given that the models forecast stock price changes for this duration of time.
The algorithms are mostly the standard ones with performance-oriented tweaks. Given that using constituents of one index only leads to a high correlation in the stocks' prices, i.e. less diversification and thus higher risk, the portfolio will soon be updated to include a variety of asset types spread out over multiple international indices.
Return is engineered to be at 39%/annum at a risk of 14%. show more
Master data
|
Symbol
|
WF0JKL2019 |
|
Date created
|
2019-11-22 |
| Index level | |
|
High watermark
|
93.5 |
Rules
Investment Universe
Trader
Registered since 2019-11-22
Decision making
- Technical analysis