Highlights From AMA with the Founder of the Syndicate Crypto Hedge Fund

Syndicate Strategy on TradeLink Marketplace:
https://tradelink.pro/strategy/bf9b8a98-7beb-43c8-9773-2a0f629cc3d0

Detailed analytics of Syndicate’s strategy efficiency on TradeLink Passport:
https://tradelink.pro/portfolio/bf9b8a98-7beb-43c8-9773-2a0f629cc3d0

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

Vyacheslav Konovalenko is the CEO of the Syndicate cryptocurrency fund, co-founder of the Cash Code trading platform, and a professional trader who began his trading journey in 2008. Vyacheslav worked in brokerage companies, traded on the stock market, including the American and Russian markets, and traded derivatives. Since 2018, he has been deeply studying the cryptocurrency market and its opportunities, as well as trying his hand in it.

The Story of Syndicate’s Founding

According to Vyacheslav, the company was named “Syndicate” for fairly simple reasons, primarily due to the meaning of the word. A syndicate is a community of people united by common values, ideas, and principles. It so happened that during his journey, a small team of close friends who were also interested in financial markets and trading gathered around Vyacheslav.

“We moved together for a long time, and at some point, we just realized that we agreed on many things: in terms of risk approach, in terms of trading approach, in terms of analysis, and in general, in our understanding of markets and market situations. Thus, we wanted to bring it all together and give it a name. So, the idea came up — why not call it a syndicate.”

How They Came to Create Trading Algorithms

Vyacheslav traded manually for a long time. In his words, manual trading is a complex and exhausting process. He believes that trading should be approached as a personal business; treating trading as a hobby will only lead to expenses, while a serious business approach will discipline you in trading, lead to stable results, and allow you to grow your capital year by year. However, manual trading requires constant monitoring, which is exhausting. A way had to be found to make money work and grow capital by applying market knowledge. Eventually, the team agreed to shift their focus entirely to earning through trading algorithms, largely because several good developers in the team were already immersed in financial markets and had been trading for a long time. A regular programmer won’t simply create a trading robot based on a technical task; it’s crucial that the person creating the algorithm understands what they’re doing and how it should work.

Attitude to Risk

The core idea of Syndicate’s approach to trading algorithms is minimizing risks, in contrast to maximizing short-term profits. The priority is the survival of trading algorithms over time and their adaptability to extreme market situations.

Firstly, a trading system should be built with a focus on risk. Vyacheslav mentions a well-known golden rule often neglected: the market favors the patient. Many people come to the market with unrealistic expectations, inspired by stories of someone making thousands of percent profit. This is a survivorship bias. With experience comes the understanding that such things happen everywhere, even on the stock market, where out of 1,000 instruments, something is always shooting up. However, the chances of catching that opportunity are extremely low, yet people continue to strive to be that lucky one and make a fortune at once.

“This all leads to situations where people create an algorithm focused primarily on profitability. Typically, these stories end when the market throws a curveball: if it’s a spot system, it might get stuck for a long time; if it’s a futures system, it could lead to significant losses or even liquidation, meaning the loss of the entire deposit.”

Secondly, there’s the approach to building a trading system. Syndicate focuses on risks and their own understanding of acceptable risks for themselves and most of their clients.

“If our trading system survives for a year, 2, 3, 5, 10 years, then it doesn’t matter if it earns a little more or less at times. It will earn.”

Ultimately, you can’t promise stable, fixed returns monthly due to changing market conditions. A professional trader with a good trading system and risk management can only promise not to lose investor money beyond a certain threshold, like 30% of the deposit.

Trading and Investments

Vyacheslav clearly distinguishes between trading and investing — two completely different concepts often mixed up by people.

“I’ll probably say something unpleasant for many, but based on my experience: trading will not lead you to financial independence. Financial independence comes from investments. Trading will bring you lots of stress, sleepless nights, and so on. It’s a very challenging job.”

Vyacheslav knows many good traders, including those working abroad in large U.S. funds. This profession quickly drains people. That’s how the financial world works — traders are on a conveyor belt; when one burns out, they replace them with another.

Trading is 80% about working on yourself because a trader is fighting not with the chart but with himself. To grow from a gambler to a good trader capable of making a living from the market, one must realize this and do a lot of work on himself, especially on his emotions, feelings, and discipline.

Trader Emotional Burnout

Trading is an exhausting process, especially for those who have been in the field for a long time. Many traders with 10-20 years of experience feel tired and can’t see themselves in this line of work for the rest of their lives. When someone is young, they can dedicate themselves to trading, immersing in all available tools, systems, and indicators. However, as they age, many feel the need to shift direction and do something else.

An important stage for any trader is to diversify the earned capital, including investing in real estate, stocks, bonds, and cryptocurrencies. Failing or refusing to do this in time can leave a trader without means of support when burnout occurs.

It’s also important to consider that markets constantly change. New algorithms, liquidity changes, increased volatility — all these can lead to losses even for the most disciplined traders with refined strategies. Flexibility and the ability to adapt quickly to new market conditions are crucial. Otherwise, failing to adjust, a trader could lose all their funds, regardless of experience and skills.

The Principle Behind Syndicate’s Trading System

Any automated trading strategy is based on a set of rules that the robot follows. Most existing market strategies are based on indicators, which is not always the best approach since indicators work inconsistently depending on the market cycle and may not work at all. It can be said that the vast majority of indicators are just a form of chart visualization. They can be helpful in this regard, but they are not always relevant for real trading.

Syndicate took a different path and uses market data instead of charts. The structure of this approach includes:

The Core or Analytical Machine, which receives various market data (volumes, limit orders and their characteristics, deltas, etc.).
The analytical machine analyzes this information, identifying trading situations where trades can be made.
If such a situation is detected, the data is passed to the trading robot, which performs the corresponding trading operation.

The fund has its own scoring system responsible for selecting coins for trading. The main aspects of this system are:

Selection Criteria: The fund does not trade random or little-known coins. The focus is on coins with sufficient trading volume.
Main Coins: Conservative strategies primarily trade Bitcoin and Ethereum. For more dynamic strategies, coins in the top 30 of CoinMarketCap are considered.
Market Adaptability: If a coin stands out in the market by volume, it doesn’t automatically become a trading target. The robot doesn’t change its list of traded coins every day; changes occur roughly every quarter or month, depending on market dynamics and current scoring.
Regular Analysis: Based on the scoring, a pool of coins for upcoming trades is formed.

Flexibility in Algo Trading

All major exchanges actively use trading algorithms, adapting them to current market conditions. Key points:

Constant Changes: Exchanges regularly perform technical updates, during which trading algorithms are rebooted or modified. This allows for adaptation to changing market conditions.
Market Dynamics Response: Algorithm changes can happen with varying frequency—from once every six months to once a quarter, depending on market dynamics.
Trading Stimulation: Sometimes exchanges hold competitions, attracting traders with large prizes. During such times, the exchange adapts its algorithms to increase profits.
Algorithm Updates: It’s impossible to create a universal algorithm that will work effectively for years. Markets change, and algorithms must evolve with them.
Risk Management: In high market volatility, particular attention is paid to risk management in trading systems to ensure the safety of clients’ funds.
Flexibility is Key: Flexibility is important for both manual traders and algorithmic funds. It’s more effective to regulate and adapt existing trading systems than to create numerous new ones. Syndicate has only 5 trading algorithms.

In conclusion, flexibility in algo trading means the ability to adapt to constantly changing markets, responding to its dynamics and ensuring optimal performance with minimal risk.

A Rational Approach to Creating Trading Algorithms

In trading, the key is understanding that any system can work, but not always. Beginner traders often mistakenly believe that the secret to success lies in having a perfect trading system. In practice, even a simple algorithm, like a moving average indicator, can be profitable with proper automation and risk management. The value of an algorithm is determined not so much by the trading system itself but by its implementation and consideration of all risks and nuances. When creating trading algorithms, it is important to consider real market conditions, not just rely on backtesting, as it doesn’t always give a complete picture of the algorithm’s real performance.

When creating trading algorithms, it’s important to consider the difference between backtesting and real trading. At Syndicate, before trading algorithms are used in the real market or offered to clients, they are tested in real-world conditions for six months to a year. This approach makes the development process more complex, but it results in more reliable and effective algorithms. Backtesting does not always account for unforeseen market conditions, such as high volatility or order execution delays, which can significantly impact the system’s performance. Syndicate emphasizes long-term stability and reliability of algorithms because the company’s reputation and client trust are paramount. The algorithms are tested under increased risks to determine their breaking points and to better understand how they will perform in extreme market situations.

Answers to Questions:

– When and how do strategies undergo changes in risk management?

Changes in risk management strategies occur when the market experiences unclear or extreme situations. There is a standard risk pattern for normal market conditions. However, if the market behaves unusually, risks are reduced. Decisions are made based on experience and understanding of macroeconomic factors, not automatically. Despite the automation of trading, the team constantly monitors the market situation and the global economy. If negative events are forecasted in the market, measures are taken to reduce risks, even if it might reduce profitability. The primary goal is survival. The company’s risk management strategies are based on expert analysis, particularly from the in-house experienced risk manager. When potentially challenging market situations arise, the team holds meetings to analyze and discuss the situation. The main philosophy is that it’s better to be over-cautious than to face unexpected losses. While it is impossible to predict market behavior accurately, the team relies on macroeconomic indicators, understanding the cyclicality of markets. Market growth is not infinite, and certain economic signals can serve as harbingers of changes. If deviations are observed in the market or macroeconomic situation, the team becomes more cautious, relying on their experience and past crises. The main goal is to protect investments and always be prepared for changing conditions.

– You mentioned that you don’t conduct backtesting; how then do you check the stability of a strategy in extreme market situations, such as in March 2020 when the market dropped by 70%?

Backtests are not used as the primary testing tool but rather to initially understand the viability of a strategy. When a new idea or set of rules emerges, they are first visualized and then implemented by developers. A backtest is then conducted to determine the potential effectiveness of this idea. If the strategy does not show viability in the backtest, it is discarded. If there are particular nuances or complexities, the question of their elimination is addressed. After a successful backtest, the strategy is placed on a live account on the exchange, where it must prove its resilience under aggressive settings for six months to a year without manual intervention. This helps understand how stable the system is in real market conditions.

– At what drawdown level will the algorithms be stopped? Specifically, what is the maximum amount of capital a strategy can lose?

At a 30% capital drawdown, the algorithms automatically stop thanks to a built-in “emergency stop” mechanism. This is the maximum loss threshold set for all futures algorithms.

– A more specific question about the strategy. We understand that this is a grid averaging algorithm, presumably widely diversified across different pairs. We would like to ask about futures. How many averaging levels are there, and what is the maximum margin percentage that can be utilized?

In futures, the maximum margin usage is 50%. That is, the system cannot load the deposit by more than half. Each algorithm has unique mathematics that sets us apart and makes us strong in the market. However, we cannot disclose the detailed nuances as they are our competitive advantage. For example, if you have a $1,000 deposit, the maximum margin usage would be $500, with the remaining $500 always remaining free. This reduces profitability, but it is the price for reduced risk.

– There are two types of markets: trend and flat. How do you determine when the market type changes?

You can’t. Determining a market type change is difficult and not obvious. Most often, a trend becomes noticeable only after it has already started. A trend is a sequential price movement, and to assert a market reversal, sufficient time and data are needed. Catching market reversals can be risky and lead to losses.

However, you can monitor certain indicators, such as trading volumes or analyze reports from major banks and hedge funds. By studying their risk appetite, conclusions can be drawn about the current state of the market. If major players do not show interest in risky assets, the market may not be in the best condition.

The cyclicality of risk appetite among large investors correlates with market changes. And while the exact moment of trend reversal is impossible to predict, it is possible to monitor current changes, adapt strategies accordingly, and thereby minimize risks.

Algorithmic Trading vs. Manual Trading

In the long run, algorithmic trading undoubtedly outperforms manual trading. The main reason is the absence of emotions, which play a key role in the decisions of human traders. In manual trading, investors face FOMO — the fear of missing out. Vyacheslav recalls staying awake for two days, monitoring trades involving large sums, fearing he might miss any changes. Robots do not experience fatigue or emotions: they can wait for the right moment indefinitely and won’t miss it.

“This is a huge thrill, I think, knowing that you can sleep soundly, and if Bitcoin is going to the moon, you won’t miss that moment.”

Looking at the stock market from 2010-2012, it was less filled with trading algorithms. However, technology advances every year. Now, when large investors and funds enter the market, they face a choice between assembling a team of manual traders or algorithmic trading; the latter appears more attractive, efficient, and cost-effective in the long run.

Algorithms will continue to improve, just as the markets will. Although the cryptocurrency market is relatively young, and many exchanges are not yet technically advanced enough, progress does not stand still.

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