Three Major Mainstream Trading Paradigms and Corresponding Strategies: A Must-Read Guide for Crypto Traders

Author: Cred

Translation: Saoirse, Foresight News

Original Title: Three Major Trading Categories and Strategies Every Crypto Trader Should Know

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

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

In extreme cases, on one end is a fully automated trading system—always "on," managing every aspect of the trading process; on the other end is pure gut-feel speculation—no rules, no fixed trading strategy.

Technically, as long as you exercise any degree of discretion (such as turning off an automated system or manually adjusting position balances), it can be classified as "discretionary behavior," but such a definition is too broad and lacks practical reference value.

In reality, my definition of a "discretionary trader" may apply to most readers, with core characteristics including:

• Mainly executes trades manually;

• Analysis revolves around technicals (including key price levels, charts, order flow, news catalysts, etc.);

• Subjectively judges whether a trading strategy is effective and worth participating in;

• Has discretionary control over core trading elements: risk management, position sizing, entry points, stop-loss conditions, target prices, and trade management.

It is important to note that "discretion" should not be equated with "laziness."

Some traders might say: "Bro, look, no two trading strategies are exactly the same, so testing is useless—every situation is different anyway."

But excellent discretionary traders usually master detailed data of the markets they trade, create trading strategy manuals, set market state filters, and keep trading logs to optimize performance, among other practices.

When exercising discretion, they at least follow a rough set of rules; as experience accumulates, the rules become more flexible, and the proportion of discretion in the trading process increases accordingly.

But this flexible discretion is earned through accumulation, not possessed out of thin air.

In any case, based on my experience and observation, most positive expected value (+EV) discretionary trading strategies can be classified into the following three clear categories (category names are self-defined):

• Incremental

• Convex

• Specialist

Each category is mainly distinguished by three dimensions:

• Risk-Reward Ratio (R:R)

• Probability of Success

• Frequency

(Note: Combining risk-reward ratio and probability of success can roughly estimate the expected value of a trade, but for simplicity, we’ll just use these three dimensions here.)

Let’s analyze these three types of trades one by one.

Incremental Trades

Core features: Low risk-reward ratio, high probability of success, medium frequency

These trades are key to keeping your account running smoothly and maintaining market sensitivity.

They may not be "eye-catching," nor suitable for showing off on social media, but they are the trader’s "foundation"—as long as you have some market edge, the returns from these trades can achieve considerable compound growth.

Typical examples include: microstructure trading, order flow trading, intraday mean reversion trading, statistically-based trades (such as intraday time-of-day effects, weekend effects, post-news release effects), and range trading during low volatility periods.

The main risks faced by these trades are "edge decay" and "sudden market regime shifts."

But these two risks can be seen as "necessary costs of trading": intraday trading opportunities are inherently sporadic, and if you’re on the wrong side during a regime shift, the cost is often very high (refer to the fall of the Gaddafi regime for an understanding of the risks of counter-trend trading during reversals).

Incremental trades are highly practical: they usually deliver stable profits and occur frequently enough—not only smoothing the P&L curve but also providing traders with effective information about the market and potential trends.

Convex Trades

Core features: High risk-reward ratio, medium probability of success, low frequency

Most trades based on higher timeframes (such as daily or weekly charts)—especially those centered around volatility expansion or sudden market regime shifts—fall into this category.

As the name suggests, these trades don’t occur often, but when they do, as long as you can capture part of the move during major volatility, you can reap substantial rewards.

Typical examples include: high timeframe breakout trades, reversals after failed high timeframe breakouts, high timeframe trend continuation trades, major catalyst/news-driven trades, trades based on extreme funding or open interest, and breakouts after volatility compression.

Main risks for these trades include: false breakouts, long intervals between opportunities, and high trade management difficulty.

Again, these risks are "necessary costs of trading."

Usually, when participating in these trades, traders may need to attempt the same strategy multiple times, endure several small losses before the strategy pays off (or it may never pay off at all). In addition, these trades usually have higher volatility and are harder to manage, so traders are more likely to make mistakes in execution—which is precisely why they offer high returns.

In the crypto trading world, convex trades are often the main contributors to a trader’s long-term P&L. Proper position sizing, capturing major trends, and seizing breakout or reversal opportunities are key to keeping your equity curve from being eroded by fees.

In other words, the returns from convex trades can cover the fee losses, frequent trading costs, and volatility risks incurred in incremental trades.

Put simply, these are the so-called "blockbuster trades."

Specialist Trades

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

This is a category of "once-in-a-lifetime" high-quality trading opportunities, such as the recent chain liquidations in the perpetual futures market, stablecoin depegging events, key tariff policy news (during periods of significant policy impact), major catalyst-driven trades, and markets with sharply increased volatility.

Typical examples include: capturing low timeframe entries and expanding them into high timeframe swing trades, arbitrage when spot and derivatives prices diverge significantly, cross-exchange arbitrage with large price differences, "off-market" quotes executed at extremely low discounts, and providing liquidity in thin markets for profit.

Participating in these trades usually requires meeting one of the following two conditions:

• The market experiences abnormal volatility or a "break" (such as a price crash or liquidity drought)

• Perfectly combining high timeframe trading logic with low timeframe execution strategies to achieve "snowballing" returns

The challenge with the first condition is that opportunities are extremely rare; and when they do arise, most traders are busy dealing with margin calls or managing existing positions, leaving no time to seize new opportunities. Additionally, exchange system stability is often poor at these times, making execution even harder.

The challenge with the second condition is that high timeframe price action often appears highly volatile and noisy on low timeframe charts. This requires traders to precisely time entries and stop-losses, and to have the ability to stick to low timeframe strategies and manage positions well as the high timeframe trend unfolds.

Main risks for these trades include: extremely high skill requirements, extremely low frequency of opportunities, missing out due to being "busy surviving" when opportunities arise, and execution risks (such as slippage in thin markets or liquidation risk).

These trades are extremely difficult, but catching just one can completely change a trader’s career.

It is worth noting that the appeal of these trades is precisely the source of their risk.

Therefore, it is recommended that traders set aside a "crisis fund"—stablecoin capital that is not easily touched, specifically reserved for capturing these rare opportunities, which is a very wise move.

Conclusion

I suggest you review your trading logs or strategy manuals and try to categorize your past trades according to the three types above. If you don’t have a trading log or strategy manual yet, this classification framework can also provide a starting point.

Another valuable insight (derived by "elimination") is: many types of trades are actually not worth your time. For example, "boredom trades"—these clearly fall into the category of "low risk-reward ratio, low probability of success, high frequency," and are an ineffective waste of time and capital.

If you are a developing trader, it is recommended to devote most of your energy to incremental trades: use these trades to accumulate market data, build trading systems, optimize strategies, and gradually accumulate enough capital and experience before trying other types of trades.

You don’t have to be limited to just one type of trade forever.

A more valuable approach is to develop a strategy manual that covers all three types of trades. More importantly, set reasonable expectations for each type’s risk-reward ratio, probability of success, frequency, potential risks, and strategy form.

For example, using a convex trading strategy but managing it as if it were incremental is a mistake; likewise, using a convex strategy but sizing positions as if it were incremental is also wrong (this is also my biggest weakness as a trader).

Therefore, it is very important to clarify the type of trade you are participating in and make corresponding adjustments.

I have not set specific numerical standards for risk-reward ratio, probability of success, or frequency, because these metrics are highly dependent on market conditions and can vary significantly. For example, in a hot bull market, convex trading opportunities may arise every week; while in a sluggish market, even incremental trading opportunities are something to be grateful for.