Gate Institute: Application and Backtesting of Momentum Indicators in the Cryptocurrency Market

Summary

• Momentum investing is based on the hypothesis of price trend persistence and is widely used in traditional finance and crypto markets; this report focuses on BTC, systematically reviewing the theoretical foundations, behavioral drivers, and potential risks of momentum strategies, and providing a framework for empirical analysis.
• Momentum can be understood as the “inertia” of prices, commonly quantified by the difference between the current price and historical prices; in the BTC market, short-term momentum indicators (such as 10-day momentum) can effectively characterize phased trend directions.
• The momentum effect is closely related to behavioral finance; herd behavior, conformity psychology, and underreaction can reinforce trend continuation, but sudden events and emotional reversals may quickly invalidate momentum signals, leading to significant drawdowns.
• This report selects MACD, Bollinger Bands, ADX/DMI, and RSI as core momentum tools, representing trend direction, volatility structure, trend strength, and market sentiment respectively, forming a complementary analysis system.
• Backtesting results show that momentum strategies are highly dependent on market structure: in sideways and weak markets, MACD and RSI are prone to false signals; ADX/DMI risks are relatively controllable but returns are limited; Bollinger Band breakouts perform best during volatility expansion phases, indicating “volatility-based momentum” has advantages in BTC markets.
• To enhance the robustness of momentum strategies in BTC markets, multi-indicator combinations can reduce the risk of single indicator failure.

Introduction

Momentum investing is a class of quantitative strategies based on the continuation of price trends, gaining wide attention in both traditional financial markets and crypto asset markets. This study aims to systematically explore the effectiveness of momentum strategies in the BTC market, analyze their theoretical basis, market behavioral logic, and potential risks, and lay a theoretical foundation for subsequent empirical research.

Concept and Measurement of Momentum

2.1 Definition of Momentum

In financial markets, “momentum” refers to the tendency of an asset’s price to continue moving in the same direction (up or down) over a certain period. This concept is analogous to Newton’s laws of motion: objects tend to maintain their velocity and direction unless acted upon by external forces. Similarly, in financial markets, price movements tend to persist due to inertia, forming sustained upward or downward trends.

2.2 Quantitative Formula for Momentum

To quantify the persistence of price trends, investors often use a simple yet effective momentum calculation formula:

Momentum = Latest asset price – Price at a historical reference point

The difference indicates the momentum during that phase. A positive value (Positive Momentum) signifies an upward trend; a negative value indicates a downward trend. For example, if a stock was priced at $100 one month ago and now is $120, the momentum is: 120 – 100 = 20. This suggests a sustained positive trend over the past month, indicating potential continuation. Investors typically interpret this as a short-term bullish signal but should also consider external factors like market sentiment and macroeconomic conditions.

2.3 Momentum Indicators Based on BTC

In crypto research, BTC is commonly used as a typical example for momentum analysis. Similar to traditional stocks or indices, BTC’s momentum can be measured through price differences over various periods, with short cycles (such as 10-day momentum) being the most common.

The 10-day momentum is calculated as:

BTC 10-day Momentum = Today’s closing price – Closing price 10 days ago

This indicator intuitively shows BTC’s price change over the past 10 days. For example, on November 24, BTC’s price was $87,288, and 10 days earlier it was $94,584, so the 10-day momentum is: 87,288 – 94,584 = -7,296. A negative momentum indicates a downward trend over the past 10 days, with selling pressure dominating. Conversely, a positive value indicates an uptrend with strong buying interest.

2.4 Market Explanation and Dynamic Influencing Factors

Momentum indicators not only reveal the continuation of price trends but can also be combined with historical events, economic cycles, and other factors to better interpret the underlying market drivers. For example:

• Accumulation of positive momentum often occurs during periods of optimistic investor sentiment, improving economic outlooks, or corporate earnings growth.
• Persistent negative momentum is usually associated with rising risk aversion, macroeconomic pressures, or systemic risks.

However, momentum is not an infallible indicator. External shocks like economic crises, policy changes, or sector-specific shocks can rapidly reverse price trends and invalidate momentum signals. Therefore, in practical investment decisions, momentum indicators should be used in conjunction with other technical or fundamental analyses to improve accuracy and stability.

Overview of Momentum Investing

The core idea of momentum strategies is that assets exhibiting clear upward or downward trends tend to continue in the same direction in the short to medium term. Investors identify trend signals, analyze price momentum, and execute buy or sell operations based on the trend direction to seek excess returns. Unlike value investing, which emphasizes fundamental undervaluation, or growth investing, which focuses on future potential, momentum strategies regard price behavior itself as the primary information source.

In traditional equity markets, momentum strategies typically rely on past performance to determine future positioning; in crypto markets, given high volatility and rapid sentiment shifts, momentum features are more prominent, making it a particularly interesting research area.

The theoretical foundation of momentum investing derives from behavioral finance. Due to market participants’ irrational behaviors—such as herd mentality, conformity, overreaction, or underreaction—asset prices can persist in a given direction for some time. Once a trend is established, investor follow-on behavior can further reinforce it, producing a momentum effect.

However, momentum strategies also carry significant risks. Trends may reverse swiftly due to changes in market conditions, sentiment shifts, or unexpected events, leading to high volatility and potential drawdowns. Moreover, the strategy relies on timely recognition and adjustment of positions, requiring continuous market monitoring.

Overall, momentum strategies differ from value investing, which aims to find undervalued assets, or growth investing, which emphasizes future growth potential. Instead, they emphasize the persistence of price trends and the behavioral mechanisms behind them. In the highly volatile BTC market, the existence and stability of momentum effects merit further exploration. This report will analyze the performance and feasibility of momentum strategies in BTC through theoretical review and empirical testing.

Common Momentum Indicators

This chapter systematically introduces the most representative technical indicators used in momentum research, including Moving Average Convergence Divergence (MACD), Bollinger Bands, Average Directional Index/Directional Movement Index (ADX/DMI), and Relative Strength Index (RSI). These indicators characterize market trend direction, volatility structure, momentum strength, and potential reversals from different perspectives, forming a foundational basis for quantitative momentum strategies.

4.1 MACD (Moving Average Convergence Divergence)

4.1.1 Theoretical Basis

MACD, proposed by Gerald Appel in 1979, measures trend development speed and direction by calculating the difference between exponential moving averages (EMA) of different periods. Short-period EMAs are more sensitive to recent information and quickly reflect changes in market momentum; long-period EMAs provide the overall trend direction. MACD essentially captures the second-order momentum (the rate of change of trend) through the difference of moving averages.

Its advantages include:

• Simultaneously capturing trend direction (DIF) and trend strength (histogram)
• Lower sensitivity to noise, suitable for medium-term trend judgment

4.1.2 Indicator Interpretation

Using default parameters (e.g., 12, 26 periods for EMAs), MACD consists of three key components: the MACD line (difference between 12-day and 26-day EMA), the signal line (9-day EMA of MACD), and the histogram (difference between MACD and signal line). The histogram illustrates trend acceleration or deceleration.

For example, during mid-October, prices rose to about $126,193, then quickly declined; MACD lines crossed downward, and the histogram shifted from positive to negative, indicating fading upward momentum. As the overall market weakened, MACD remained below zero, dominated by a bearish trend.

When prices rebounded near $80,646 in late November, the negative momentum started to diminish, hinting at weakening bearishness. However, MACD still remained below zero, suggesting the trend had not fully reversed. These structures remind traders that trend reversals require confirmation, and short-term convergence alone is insufficient as an independent signal.

The zero line of MACD is crucial for trend judgment. When MACD is above zero, short-term EMA exceeds long-term EMA, favoring a bullish market; below zero suggests a bearish environment. Since November, MACD has mainly stayed below zero, correlating with a persistent downtrend.

4.1.3 Usage Tips

The zero line is vital for trend judgment. When MACD is above zero, it indicates bullish momentum; below zero, bearish. Since November, MACD has been below zero, reflecting ongoing decline and typical bear market signals.

Investors often combine MACD with other indicators to enhance signal reliability, such as:

• RSI to confirm overbought/oversold conditions
• Volume to verify the strength of crossovers
• Moving averages to filter out short-term noise

Divergence analysis is also critical: if prices make new lows but MACD fails to do so, it signals weakening downward momentum (bullish divergence). Conversely, if prices make new highs but MACD peaks decline, it indicates weakening upward strength (bearish divergence).

4.2 Bollinger Bands

4.2.1 Theoretical Basis

Bollinger Bands, developed by John Bollinger in the 1980s, measure market volatility using standard deviations of prices and construct dynamic channels. Unlike fixed-width channels, Bollinger Bands expand and contract with volatility, providing a real-time reflection of market environment.

Typically composed of three lines:

• Middle band (MID): 20-day simple moving average (SMA)
• Upper band (UP): MID + 2 × standard deviation
• Lower band (DN): MID – 2 × standard deviation

Based on the statistical property that, under normal distribution, about 95% of prices lie within two standard deviations, Bollinger Bands offer trend direction (via MID) and volatility strength (via band width).

Advantages include capturing both trend and volatility changes: widening bands indicate increased volatility and potential trend acceleration; narrowing bands suggest reduced volatility and possible trend consolidation. The middle band can also serve as a trend reference, making Bollinger Bands useful in both trending and ranging markets.

4.2.2 Indicator Interpretation

Using default settings (20, 2), analysis of daily data shows that during early October, prices surged to around $126,193, with upper band expanding and bands widening, indicating a strong upward trend with increased volatility. Price repeatedly ran along the upper band, typical of trend advancement.

As prices declined from highs, bands contracted, reflecting decreased volatility and a sideways or consolidating phase. During the subsequent downtrend, bands tilted downward, and prices traced along the lower band, confirming a bearish trend. When prices rebounded near $80,646 in mid-November, bands began to narrow, indicating reduced downward momentum, but prices remained below the middle band, so the downward trend was still intact.

Overall, Bollinger Bands clearly depict the trend dynamics: from expansion during strong trending phases, through contraction during consolidation, to potential reversal signals. Their structure provides insights into trend strength and potential turning points.

(# 4.2.3 Usage Tips

Bollinger Bands are used not only for trend detection but also for volatility analysis and price position judgment. Running above the middle band indicates relative strength; breaking below suggests weakening momentum. Since mid-October, prices failed to re-cross the middle band, signaling the establishment of a downtrend.

Band width changes capture volatility cycles: expansion signals trend acceleration; contraction indicates consolidation or potential reversal. For instance, band narrowing from September to early October preceded a breakout.

The upper and lower bands act as dynamic support and resistance levels. Prices near the upper band in a strong trend do not necessarily imply overbought; similarly, near the lower band does not necessarily mean oversold. During the downtrend, multiple touches to the lower band exemplify strong bearish momentum.

Combining Bollinger Bands with other indicators improves reliability. For example, MACD confirmation of trend direction, RSI overbought/oversold signals, or moving averages can enhance decision-making. Multi-indicator validation reduces false signals.

) 4.3 ADX/DMI (Average Directional Index / Directional Movement Index)

4.3.1 Theoretical Basis

ADX and DMI, introduced by J. Welles Wilder Jr., are trend-following indicators that measure trend strength rather than direction. DMI consists of +DI (DMI+) and –DI (DMI–), assessing upward and downward forces respectively; ADX quantifies the overall trend strength based on DMI values.

The core idea is: DMI+ reflects the magnitude of recent upward price movements, DMI– reflects downward movements. When DMI+ exceeds DMI–, the market is in an upward phase; when DMI– exceeds DMI+, the downward phase. ADX, derived from DMI, indicates the strength of the current trend regardless of direction—high ADX suggests a strong trend, low ADX indicates a weak or sideways market.

This dual system provides both trend direction (via DMI) and intensity (via ADX), offering comprehensive trend analysis.

4.3.2 Indicator Interpretation

Default parameters (14 periods) are commonly used. During mid-October, as prices neared $126,193, DMI+ rose sharply above DMI–, indicating increasing bullish momentum; ADX was rising but not yet at high levels, suggesting trend strength was building. As prices declined thereafter, DMI– overtook DMI+, reflecting bearish momentum; ADX began to rise, confirming trend strength.

From late October onward, ADX gradually increased, surpassing 25, indicating a strengthening downtrend. DMI– remained above DMI+, consistent with bearish conditions. As prices approached $80,646 in mid-November and rebounded, DMI– started to decline while DMI+ slightly recovered, signaling weakening downward force. ADX plateaued or declined, implying trend weakening.

Overall, the ADX/DMI system effectively maps the trend’s development from formation to weakening, capturing trend strength changes and directional shifts.

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(# 4.3.3 Usage Tips

The main value of ADX/DMI lies in providing both trend strength and direction. ADX values above 25 generally suggest a trending market; below 20 indicates consolidation or sideways movement. During late October to November, rising ADX alongside falling prices confirmed a strong downtrend.

Crossovers between DMI+ and DMI– signal potential trend shifts: DMI+ crossing above DMI– suggests a bullish reversal; DMI– crossing above DMI+ indicates bearishness. In choppy markets, these signals can be false; thus, ADX’s confirmation is essential.

Combining ADX/DMI with other indicators (e.g., RSI, MACD) enhances reliability. For example, a DMI– crossover with high ADX confirms a strong downtrend; a declining ADX during a crossover warns of potential false signals. In the chart, consistent DMI– dominance and rising ADX during October confirms a robust bearish phase.

Overall, ADX/DMI is best used to confirm trend strength and avoid false signals in ranging markets.

) 4.4 RSI (Relative Strength Index)

4.4.1 Theoretical Basis

RSI, developed by J. Welles Wilder in 1978, measures the velocity and magnitude of price movements by comparing upward and downward price changes over a specified period, usually 14 days. It standardizes momentum on a scale of 0 to 100, facilitating identification of overbought and oversold conditions.

A high RSI (>70) suggests overbought conditions, potentially signaling an upcoming correction; a low RSI (<30) indicates oversold conditions, possibly foreshadowing a rebound. RSI’s oscillatory nature makes it effective in ranging markets but less reliable in strong trending markets without additional context.

4.4.2 Indicator Interpretation

Using default settings, three RSI periods (RSI1, RSI2, RSI3) are examined to analyze market structure:

Before the mid-October peak at $126,193, short-term RSI (RSI1) showed early signs of weakening, indicating a short-term momentum slowdown, while longer-term RSIs (RSI2, RSI3) responded later. Divergence among these periods often signals an approaching trend reversal. Subsequently, prices declined sharply; RSI1 dropped below 30, entering oversold territory, while RSI2 and RSI3 also moved lower, confirming a broad bearish momentum.

During the downtrend, multiple RSIs remained in the 20–30 range, indicating persistent bearish momentum rather than a brief oversold bounce. By mid-November, when prices rebounded near $80,646, all RSIs stabilized and moved out of oversold zones, signaling a potential trend stabilization but not a strong reversal yet. RSIs remained relatively low, reflecting weakened but still cautious bearish sentiment.

The multi-period RSI analysis effectively captures the transition from divergence and trend weakening to oversold conditions and subsequent stabilization, providing insight into momentum shifts across different timescales.

4.4.3 Usage Tips

RSI is mainly used to assess market strength and extreme sentiment conditions. Overbought (>70) and oversold (<30) signals are common triggers for potential reversals. However, in strong trending markets, RSI can remain in extreme zones for extended periods without reversal, so signals must be confirmed with other indicators.

Multi-period RSI combinations improve the accuracy of momentum assessment. Short-term RSIs respond quickly to recent changes, while longer-term RSIs confirm trend stability. When short-term RSI shows divergence while longer-term RSIs do not, reversals are less certain. Conversely, alignment across multiple periods enhances confidence in signals.

RSI is often combined with trend indicators like MACD or ADX/DMI to filter false signals. For example, an RSI oversold signal combined with a weakening trend or divergence from MACD can suggest a higher probability of reversal.

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References

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• Coursera, [https://www.coursera.org/learn/introduction-to-momentum-investing]###https://www.coursera.org/learn/introduction-to-momentum-investing###
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