An asset that rises by 8% in a few weeks often attracts attention too late, when euphoria has already replaced analysis. This example of a momentum strategy shows how to turn a simple idea—buying established momentum and selling when it fades—into a concrete decision-making framework. Momentum does not predict the future. It seeks to exploit an observation seen in many markets: strong assets sometimes tend to remain strong for a while.
This approach suits individual traders who prefer to follow measurable rules rather than react to every alarming headline or social media post. But it also requires discipline: a trend can reverse abruptly, especially in cryptocurrencies and the most volatile stocks.
What is a momentum strategy?
A momentum strategy involves selecting assets whose price has already shown positive performance over a given period, then holding them as long as this relative strength persists. Conversely, it avoids or sells assets that are losing momentum.
The idea may seem counterintuitive to investors used to “buying low.” Momentum does not seek the bottom. It accepts paying more for an asset if the data suggests sustained demand remains. It is a trend-following strategy, not an attempt to guess a reversal.
The signal can be based on three, six, or twelve-month performance, on crossing a moving average, or a combination of these elements. The simpler and more clearly defined the rules are before entering a position, the easier they are to apply consistently.
Momentum strategy example: a simple framework
Let’s take a hypothetical portfolio of 10,000 euros split between equity ETFs or liquid cryptocurrencies. The goal is not to recommend a specific asset, but to illustrate a method that any investor can adapt to their risk profile.
On the first Monday of each month, the investor analyzes a list of ten assets. They calculate their six-month performance and only keep those trading above their 200-day moving average. This second condition helps avoid confusing a simple technical rebound with a more solid underlying trend.
Eligible assets are then ranked, and the top three are selected. The portfolio is equally divided among them, about 3,333 euros per position. The other assets remain outside the portfolio, even if they are popular. This rule is useful: it limits decisions based on popularity rather than chosen criteria.
At the monthly review, a position is sold if it drops out of the top three, if its price falls below its 200-day moving average, or if a pre-defined protection rule is triggered. Freed-up capital is allocated to an asset that meets the criteria. The portfolio is thus rebalanced at a fixed frequency, not based on emotion.
Numerical illustration
Suppose the three selected assets show six-month performances of 32%, 25%, and 18%. A fourth asset, widely discussed, gains only 4% and remains below its 200-day moving average. It is not bought, even if its story seems appealing.
A month later, the first asset maintains its momentum. The second drops by 12% and falls below its moving average. The third remains stable, while another asset in the list climbs the ranking with a 21% six-month gain. The method leads to selling the second and replacing it with the new entrant. This choice can be uncomfortable, as selling after a drop means accepting a loss. Yet, that is precisely the rule’s purpose: to prevent a small mistake from turning into a long-term burden.
The parameters that really change the outcome
A momentum strategy is not just about picking the top performers. Its results depend heavily on the chosen parameters.
The observation period is the first lever. A three-month period reacts faster to market changes but produces more false signals and rotations. A twelve-month period is more stable but may exit a reversing trend too late. For beginners, six months is often a reasonable compromise to test, without assuming it is universally superior.
Rebalancing frequency also matters. Weekly reviews may seem more responsive but increase costs, monitoring time, and the risk of overreacting to market noise. Monthly or quarterly reviews generally reduce these frictions. The right pace depends on asset volatility, investment size, and broker fees.
Finally, the number of positions affects concentration. Three holdings make the logic clear but expose the portfolio more to individual asset risk. Holding eight to ten positions reduces this specific risk but dilutes the impact of the best trends. There is no magic number: the investor should be able to explain each rule and withstand the associated fluctuations.
Why momentum can fail
Momentum works best when trends last. But markets are not always directional. In a hesitant market, assets may break out upwards only to fall back immediately. These sequences, often called false signals, lead to repeated buying and selling with limited but cumulative losses.
Sharp reversals are another risk. A macroeconomic announcement, unexpected regulation, or a liquidity crisis can cause top-performing assets to plunge. Cryptocurrencies especially illustrate this risk: their momentum can be strong, but their volatility can make a tight stop ineffective or trigger an exit at a price far from the expected level.
Past performance is not enough. You must factor in transaction fees, bid-ask spreads, taxes, and correlation risk. Three different assets may all depend on the same general market movement. Apparent diversification is not always real diversification.
Build risk rules before your first purchase
The capital committed to a position should remain compatible with a significant temporary drop. Before buying, ask yourself a simple question: what will I do if this asset loses 15%, 25%, or more? If the answer depends on your mood that day, the rule is not precise enough.
You can set a maximum loss per position, a maximum exposure to an asset class, and an amount of cash kept out of the market. These limits do not guarantee perfect protection, especially during a sharp move, but they frame the risk. They also prevent concentrating the entire portfolio on the most spectacular trend of the moment.
It is wise to test the method on historical data, then observe it in a virtual portfolio for several months. This test does not prove it will be profitable in the future. It mainly helps verify if the rules are applicable, if the rotations are reasonable, and if you can stick to them during unfavorable phases.
Turning data into clearer decisions
A momentum strategy requires tracking performance, moving averages, rankings, and risk thresholds without being distracted by daily noise. An automated tool or AI agent can centralize this data, signal trend changes, compare assets using consistent criteria, and remind you of the defined rules. Solutions like Ya.puka Trader can thus reduce monitoring time and mental load. AI helps analyze faster and decide more clearly, but it does not replace your risk management or judgment, and never guarantees profits.