Original author: Cred

Original translation: Saoirse, Foresight News

As a discretionary trader, it is useful to categorize your trades.

Systematic trading and autonomous trading are not binary opposites or mutually exclusive.

At one extreme, there is a fully automated trading system—one that is always “on” and manages every step of the trading process—and at the other, completely instinctive speculation—with no rules or fixed trading strategies.

Technically speaking, any degree of autonomous decision-making (such as shutting down automated systems or manually adjusting position balances) can be classified as "autonomous decision-making behavior," but such a definition is too broad and lacks practical reference value.

In fact, my definition of a discretionary trader probably applies to most readers, and its core characteristics include:

• Execute trades primarily manually;
• The analysis revolves around technical analysis (including key price levels, charts, order flow, news catalysts, etc.);
• Subjectively judge whether a trading strategy is effective and worth participating in;
• Have independent decision-making power over the core elements of trading: risk control, position size, entry point, stop-loss conditions, target price, and trade management.

It is important to note that “autonomous decision-making” should not be equated with “laziness”.

Some traders will say, "Look, man, no two trading strategies are exactly alike, so testing is pointless because every situation is different anyway."

But good independent traders usually have detailed data on the markets they trade, develop trading strategy manuals, set market status filters, keep trading logs to optimize their performance, and so on.

When exercising their autonomous decision-making power, they will at least follow a general set of rules and regulations; as experience accumulates, the rules will become more flexible, and the proportion of autonomous decision-making in the transaction process will also increase accordingly.

But this flexible decision-making power is acquired through accumulation, not just out of thin air.

Regardless, based on my experience and observations, most discretionary trading strategies with positive expected value (+EV) fall into three distinct categories (these categories are my own creation):

• Incremental
• Convex
• Specialist

There are three core differentiating dimensions for each category:

• Risk-Reward Ratio (R:R)
• Probability of success
• Frequency

(Note: Combining the risk-reward ratio with the probability of success can roughly estimate the expected value of a transaction, but this will not be expanded here. We will only simplify the understanding through three dimensions.)

Below we analyze these three types of transactions one by one.

Incremental transactions

Core characteristics: low risk-reward ratio, high probability of success, medium frequency of occurrence

These types of trades are key to keeping your account functioning and your market agility high.

They may not be eye-catching enough or suitable for showing off on social media, but they are the "basic plate" of traders - as long as there is a certain market advantage, the profits from such transactions can achieve considerable compound growth.

Typical cases include: market microstructure trading, order flow trading, intraday mean reversion trading, trading based on statistical laws (such as intraday time effect, weekend effect, post-news release effect), range trading during low volatility periods, etc.

The main risks faced by this type of transaction are "fading advantages" and "sudden changes in market conditions".

However, these two risks can be considered "necessary costs of trading": intraday trading opportunities are intermittent, and if you stand on the wrong side when the market conditions suddenly change, the cost is often extremely high (you can refer to the case of the fall of the Gaddafi regime to understand the "risks of going against the trend when the trend reverses").

Incremental trades are a valuable category: they typically generate consistent profits and occur frequently enough to smooth out the profit and loss curve while providing traders with valuable information about the market and potential trends.

Convexity Trading

Core characteristics: high risk-reward ratio, medium success probability, low occurrence frequency

Most trades based on higher timeframes (such as daily and weekly) - especially those around rising volatility or sudden changes in market trends - fall into this category.

As the name suggests, these trades don’t occur very often, but when they do, they can yield strong returns if you can capture some of the gains from the large swings.

Typical cases include: high timeframe breakout trading, reversal trading after a high timeframe breakout failure, high timeframe trend continuation trading, major catalyst/news-driven trading, extreme trading of funds and open interest, and breakout trading after volatility compression.

The main risks of this type of trading include: false breakouts, long intervals between trading opportunities, and difficulty in managing trades.

Likewise, these risks are “necessary costs of trading.”

Typically, traders may need to try the same strategy multiple times, experiencing several small losses, before it works (or perhaps never works at all). Furthermore, these trades are often more volatile and difficult to manage, making them more prone to errors – but this is precisely what makes them so rewarding.

In the cryptocurrency world, convex trading is often the primary contributor to a trader's long-term profits and losses. Proper position management, capturing major trends, and capitalizing on breakouts or trend reversals are key to freeing your asset balance from fee erosion.

It can be said that the profits from convex transactions can cover the transaction fee losses, frequent transaction costs and volatility risks generated in incremental transactions.

Generally speaking, this type of transaction is what we often call a "hot deal."

Professional Trading

Core features: high risk-reward ratio, high probability of success, low frequency of occurrence

This is a type of "once-in-a-lifetime" high-quality trading opportunity, such as the recent chain liquidation events in the perpetual contract market, stablecoin decoupling events, key tariff policy news (during periods of greater policy influence), major catalyst-driven transactions, and market conditions with significantly increased volatility.

Typical cases include: capturing low-timeframe entry points and expanding them into high-timeframe swing trading, arbitrage when spot and derivative prices deviate significantly, arbitrage across large price spreads across exchanges, "cold quotes" executed at extremely low discount prices, providing liquidity in a market with thin orders to generate profits, etc.

Participation in such transactions generally requires one of two conditions:

• Abnormal market fluctuations or "breaks" (such as price crashes, liquidity drying up)
• Perfectly combine high-time cycle trading logic with low-time cycle execution strategy to form a "snowball-like" profit

The difficulty of the first condition lies in the fact that opportunities are extremely rare; and when opportunities arise, most traders are often busy responding to margin calls and managing existing positions, and have no time to consider new opportunities. In addition, the stability of the exchange system is usually poor at this time, which further increases the difficulty of operation.

The difficulty with the second condition lies in the fact that higher timeframe price trends often exhibit high volatility and noise on lower timeframe charts. This requires traders to accurately grasp entry points and stop-loss conditions, as well as the ability to adhere to lower timeframe trading strategies and properly manage positions as higher timeframe trends expand.

The main risks of this type of trading include: extremely high skill requirements for traders, extremely low frequency of opportunities, the possibility that traders may miss opportunities when they arise because they are "too busy to survive", execution risks (such as slippage in a thin order book market and facing liquidation risks), etc.

These trades are extremely difficult to pull off, but once nailed, they can completely change a trader's career.

It is worth noting that the source of the attractiveness of such transactions is also the source of their risks.

Therefore, it is very wise to recommend that traders set aside a portion of the "crisis fund pool" - that is, stablecoin funds that are not easily used, specifically for capturing such rare opportunities.

Conclusion

I recommend going through your trading journal or strategy book and trying to categorize your past trades into the three categories above. If you don’t have a trading journal or strategy book yet, this framework can provide a starting point.

Another valuable revelation (through the process of elimination) is that many types of trades are actually not worth investing time in. For example, "boring trades"—these trades clearly fall into the "low risk-reward ratio, low probability of success, high frequency" category, and are an ineffective waste of time and money.

If you are a growing trader, it is recommended that you devote most of your energy to incremental trading: through this type of trading, accumulate market data, build a trading system, optimize operating strategies, and then accumulate sufficient funds and experience, and then gradually try other types of trading.

You don't have to limit yourself to one type of trading forever.

A more valuable approach is to develop a strategy playbook that takes into account all three types of transactions. More importantly, it is to set reasonable expectations for the risk-reward ratio, success probability, frequency, potential risks and strategy form of each type of transaction.

For example, it would be a mistake to use a convex trading strategy but manage it using incremental trading. Similarly, it would be a mistake to use a convex trading strategy but set the position size according to the standards of incremental trading (this is also my biggest weakness as a trader).

Therefore, it is important to understand the type of transaction you are involved in and adjust accordingly.

I haven't set specific numerical standards for risk-reward ratios, success rates, or frequency of occurrence, as these metrics are highly influenced by market conditions and can vary significantly. For example, in a bull market, convex trading opportunities may appear weekly, while in a down market, even incremental trading opportunities are cause for celebration.