Description of the Algotoria Trading Strategy on TradeLink Marketplace

Information taken from an AMA session with the founders of the Algotoria fund: Evgeny Voronchikhin and Nikolai Ptitsyn.

You can watch the full AMA session in Russian on our YouTube channel:

Algotoria Algo-Trading Team / Fund

Strategy Page on TradeLink Marketplace:
https://tradelink.pro/strategy/8b49f81b-865e-4ff1-870f-45ff23d88395

⁃ AUM: $1M – Crypto assets

⁃ AUM: $20M – Stock market (USA, CIS)

Trading Strategy Idea:

⁃ Initially, in 2021, the team’s successful strategies with 10 years of experience in traditional markets were tested on crypto, where they showed better risk-adjusted returns than on classic assets. Based on the successful testing results, the decision was made to scale up, leading to the founding of Algotoria.

⁃ 14 selected trading strategies

⁃ Most strategies are trend-following: 12 out of 14

⁃ Trend-following strategies rely on the cyclical volatility of Bitcoin and Ethereum. In practice, trend-following strategies profit during strong market movements.

⁃ The majority of trend-following strategies trade long positions, with some trading both long and short. Two strategies are counter-trend.

⁃ There are strategies that are always in the market and those that enter and exit based on signals. On average, since their entries and exits are summed, the portfolio is always in a position.

⁃ Entry signals are mainly based on market structure breakouts, volatility, etc.

⁃ Trend-following strategies enter positions with full volume at once and exit with full volume without averaging or partial exits.

Rules:

The strategy trades on the most liquid Binance Futures pairs:

⁃ 7 strategies trade only BTCUSDT

⁃ 7 strategies trade only ETHUSDT

Management Type of All Strategies: Algorithmic

⁃ Funds are allocated among trading strategies inversely proportional to their risk level. Rebalancing of funds between strategies occurs quarterly.

In practice: more funds are allocated to less risky strategies than to more risky ones.

Two-Level Capital Management Method:

The position size is calculated based on the current capital size. If the capital grows, the position size increases, and vice versa.
The position size changes depending on the volatility of the trading instrument. When volatility is low, algorithms increase the position size; when volatility is high, they decrease it. In practice: If the market remains stagnant for a long time, strategies increase the position size to capitalize on the anticipated big move. After big moves, the position size is reduced to preserve the earned profits.

⁃ To maintain stable profitability and increase the risk-to-reward ratio, the majority of the selected strategies have low correlation with each other.

History:

Check the historical track record of the Algotoria portfolio on TradeLink.pro:

https://tradelink.pro/portfolio/8d78b017-b2aa-47f1-8c92-ece97c3d7a82

⁃ Track record length: 19 months.

⁃ Due to a recent technical failure and rebalancing of strategies in the portfolio, the maximum drawdown on the tracking account increased by 7% to 40%.

⁃ In backtesting, the portfolio of strategies survived the COVID crash.

⁃ The portfolio’s performance dynamics generally align with the core idea of the strategy and its type. Historical track records show profits during trending Bitcoin’s movements and drawdowns.

Risk:

Recommended risk set by Algotoria: 50%

The relatively high risk of the strategy is justified by several factors:

– Clients and Algotoria themselves do not keep all their funds on centralized exchanges due to associated risks, so strategies take on more risk to earn more.

⁃ The risk was recently increased to 50% as it is expected that the second half of 2023 will be much more volatile than the first, allowing for greater profits from high volatility.

⁃ The expected drawdown-to-annual-return ratio that Algotoria aims for is 1:2. That is, with a recommended strategy risk of 50%, one should expect an annual return of 50% to 100%.

⁃ The average leverage used by the strategy: 0.68 (Ratio of open positions to account size)

⁃ The maximum recorded leverage used by the strategy: 7.02

Team Experience:

⁃ Nikolai Ptitsyn: Data scientist – mathematician, serial entrepreneur in AI and blockchain. Expert in computer vision. Nikolai believes his team’s experience in machine vision can be well applied to crypto algo-trading.

⁃ Evgeny Voronchikhin: Portfolio manager, trader with 16+ years of experience. Holds two higher degrees in brokerage accounting, finance, and credit. Creator of successful trading algorithms for stock markets with a 12+ year history. Actively involved in crypto algo-trading since 2021.

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