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    Kvadrat Black

    Algorithmic Strategies for Trading in US Stocks
    Strategy pack
    Low risk

    The fund's performance since its incorporation

    Invest in Kvadrat Black

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    Historical Performance
    Annual returns
    with reinvested profits
    Annual returns
    with reinvested profits
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2019
    3,36%
    0,26 
    0,51 
    −0,8 
    3,4 
    . .
    . .
    . .
    . .
    . .
    . .
    . .
    . .
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2018
    9,28%
    2,60 
    4,47 
    0,26 
    0,6 
    −0,87
    −0,51
    −0,54
    0,9
    1,08
    −0,13
    0,32
    0,85
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2017
    16,01%
    0
    0,76
    2,85
    0,39
    −2,25
    1,54
    2,02
    1,57
    1,53
    2,08
    2,47
    2,09
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2016
    4,7%
    −0,74
    3,52
    2,31
    1,49
    1,88
    1,88
    −0,05
    0,11
    −1,1
    −1,4
    −1,79
    −1,79
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2015
    35,83%
    1,25
    0,91
    4,33
    0,81
    0,01
    −1,63
    5,01
    10,86
    0,93
    6,54
    3,57
    −0,9
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2014
    24,21%
    −2,64
    1,87
    −0,28
    −0,38
    2,6
    1,03
    1,12
    3,6
    0,45
    6,94
    5,03
    2,9
    Jan
    Feb
    Mar
    Apr
    May
    Jun
    Jul
    Aug
    Sep
    Oct
    Nov
    Dec
    2013
    0,93%
    . .
    . .
    . .
    . .
    . .
    . .
    . .
    0,0
    −0,02
    −0,02
    4,18
    −2,74
    Hedge Fund’s Strategy Selection Principles
    ALGORITHMIC STRATEGIES

    Only algo strategies are used in managing fund’s assets. These strategies are more stable in generating returns than manual strategies as robots experience neither emotions nor feelings. This way the core risk, a human error, is eliminated.

    MULTI-LEVEL TESTING

    Before employing a new strategy for managing fund’s assets we test it on proprietary accounts of United Traders for at least 6 months.

    RISK CONTROL

    Even after the massive work done when developing and selecting strategies, we still keep in mind that there are risks we might have missed. Therefore, a risk-managing robot tracks the strategies’ performance as well as a human risk manager. Working together, they are capable of identifying emergencies and timely terminating operation of a particular strategy. None of the strategies can cause a loss exceeding 3% of the fund’s equity. As a result, the risk of loss when investing into the hedge fund is similar to the probability of Apple, Google, Gazprom, or Sberbank, for example, going bankrupt within an hour. The probability of technical failures stemming from the fact that robots manage the fund is many times lower than human error risks.

    Why invest with United Traders?
    PROPRIETARY FUNDS

    Members of the Board of Directors and fund managers invest their own money in Kvadrat Black together with other investors. As of summer 2015, funds of fund’s employees account for over 30% of the assets.

    MONEY NEVER SLEEPS

    You money is always at work during both stock market growth and decline stages.

    FAIR FEES

    We charge a success fee every week and only if your investment portfolio has increased in value using High-Water Mark rule.

    MULTIPLE STRATEGIES

    As there are many trading strategies available at United Traders, we can pick the best ones for the hedge fund. Owing to the above, Kvadrat Black hedge fund enjoys all the benefits that funds provide.

    HISTORY OF KVADRAT BLACK

    In 2013-2016, the fund's strategies managed Kvadrat Black SPC hedge fund.

    Auditor: KPMG
    Administrator: Trinity Fund Administration
    Servicing Bank: Deutsche Bank
    Primary Broker: Wedbush Securities.
    In the above period, the fund generated a return of 59.22% without substantial drawdowns.

    AWARDS

    Kvadrat Black SPC was recognized by two awards:

    BEST EQUITY FUND (GLOBAL)

    The prize is awarded to the best global equities fund.

    BEST RISK ADJUSTED RETURN

    The prize is awarded to funds demonstrating the best risk/return ratio (with a 2.0 Sharpe ratio). The above means that in addition to high returns, Kvadrat Black’s performance was also very consistent demonstrating high efficiency of the employed trading strategies.

    Developing a Successful Strategy

    Behind each of our strategies is a team of professionals. To implement any trading strategy a trader, a mathematician, and a programmer are required.

    1. In a joint brainstorming session, an idea is born.
    2. A mathematician builds a math model for the trading strategy and analysis its performance on historic prices.
    3. A trader is responsible for the applicability of mathematical models to the actual market environment. The trader answers the following question: Is it possible to buy or sell the instrument at a specific time and in the required amount as set forth in the mathematical model?
    4. If the answer is positive, the programmer codes this strategy, and then the strategy goes «live».
    ARTIFICIAL INTELLIGENCE

    Every strategy can change its properties depending on the phase of the market. We equip our strategies with AI features for them to be as consistent as possible.

    At least once a day, each strategy analyzes the market phase by 150 parameters and is optimized using new historic data; then, a decision to adjust internal parameters is made.

    All our strategies employ machine learning algorithms. Different strategy types have no effect on each other, and therefore, we manage to generate consistent returns even in an unfavorable environment for some of the strategies.

    MARKET NEUTRAL ALGORITHMS

    Market-neutral strategies imply independence of returns from the overall market environment. Portfolios employing these strategies always comprise 50% long positions and 50% short positions. The total number of stocks in the portfolio is up to 2000. The portfolio is being continuously rebalanced. Stocks with an upside potential are added to the portfolio as longs, and those with a downside potential are sold short.

    DIRECTIONAL
    STRATEGIES

    These strategies seek extended stock price movements in a particular direction. As soon as the direction is identified, the strategy signals a trade entry.

    Positions are held from 15 minutes to 5 days. Applying the strategies on multiple timeframes and instruments ensures consistent performance.

    In addition to profiting from long-lasting movements (trend trading), these strategies also profit from short-term deviations from such movements (counter-trend trading).

    Invest in Kvadrat Black

    Please, log in or sign up to invest in Kvadrat Black