The trader of each wikifolio can be limited to specific assets of the wikifolio investment universe in their trading. The investment universe is set during the emission process and cannot be changed afterwards.

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Stocks DAX

Stocks SDAX

Stocks TECDAX

Stocks Other

Stocks MDAX

Stocks Europe Select

Stocks Dow Jones

Stocks USA Select

Stocks NASDAQ 100 Select

Stocks Hot Stocks

Stocks Eastern Europe Select

Stocks Japan Select

Stocks International

ETFs Latin & South America

ETFs emerging markets

ETFs countries Europe

ETFs North America

ETFs other bonds

ETFs world

ETFs raw materials ETCs

ETFs Germany

ETFs other countries

ETFs DAX

ETFs sectors

ETFs EuroStoxx

ETFs Asia

ETFs Europe bonds

ETFs Europe overall

ETFs basic resources

Other ETFs

Funds real estate

Funds bonds

Funds Stocks

Funds money market

Funds

Funds mixed

Discount certificates

Bonus certificates

other investment certificates

Knock-out products

Subscription warrants

other leverage products

Beta shows how sensitively the price of a wikifolio reacts to movements in a reference index.

Volatility measures the intensity of the fluctuation of the daily returns of a wikifolio around their mean value. It is a mathematical quantity (standard deviation) for the risk of an investment.

To make wikifolios more comparable with each other, each published wikifolio receives a score based on 13 different criteria.
According to this score the wikifolios are sorted and are given a place in the wikifolio ranking.

The liquidation indicator makes wikifolio certificates comparable according to their liquidity.

The highest difference in the respective period between a price low and the previously reached high of the wikifolio. Calculation: (price low x 100 / previously reached high) - 100.

Shows the ratio of performance to volatility and thus the return per unit of risk taken. The two components are annualized.

The ratio of the mean of daily returns to their standard deviation. The higher the Sharpe Ratio, the better the performance over the specified period relative to the risk taken. This value is recalculated once a day.

The Sortino Ratio is a variation of the Sharpe Ratio. Instead of looking at total volatility, it looks only at negative excess returns, i.e. downside risk. The higher the Sortino Ratio, the better the performance in relation to the downside risk taken.

The invested capital corresponds to the value of all currently sold index certificates based on the displayed wikifolio.

Sum of all buy and sell orders within the last 30 days of the displayed wikifolio-certificate.

Day of creation of this wikifolio by the wikifolio trader.

The high watermark highlights the currently highest level of the wikifolio within a calendar year and is used to calculate the performance fee.

The symbol is a short description that is assigned by the wikifolio trader to a wikifolio, consists of alphanumeric characters (A-Z, 0-9), and always starts with WF.

The wikifolio certificate fee is calculated daily pro-rata. Calculations are based on the components of the wikifolio:
<ul>
<li>the virtual cash assets and</li>
<li>the virtual securites in the wikifolio at daily closing prices of Lang &amp; Schwarz (bid price, ca. 11 p.m.)</li>
</ul>

The prices shown have been converted and may differ from the actual price to be paid.

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The wikifolio performance fee usually amounts to between 5 and 30 percent of the returns generated in the wikifolio and is only charged when a new high watermark (new annual high) is reached in the wikifolio.
The amount is proposed by the wikifolio trader and agreed upon by wikifolio and Lang &amp; Schwarz.

In Germany, Austria, and Switzerland, investors can buy wikifolio certificates at the stock exchange. These open-ended index certificates track the performance of a wikifolio 1:1.
 The displayed data is a preview only – additional details for investable wikifolio certificates are available exclusively in the German version of wikifolio.com.

Using AI to trade sector futures with a mid-frequency strategy (MFT) involves detecting large mutual fund flows before they fully impact prices. AI models analyze historical fund allocation patterns, news sentiment, and market microstructure to predict impending moves. By positioning ahead of these shifts, traders can capture alpha efficiently. Unlike HFT, this approach balances speed with predictive power, leveraging machine learning for smarter execution rather than sheer velocity.

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This wikifolio has reached a new annual high with the price of %PRICEWITHCURRENCY%.

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The wikifolio AI Allocator has existed since 2025 and trades ETFs. Learn more about AI Allocator here!