TradingKey - Recently, the Trump administration’s adjustment of tariff policies has caused turbulence in the commodity market. After Trump announced plans to impose tariffs on industrial metals such as steel and aluminum, panic quickly spread to the copper futures market. On February 10th(local time), copper futures on the New York Mercantile Exchange (NYMEX) surged by 2.6%, with the premium of NYMEX copper futures over LME copper futures reaching a record $920 per ton. Since Trump took office, investors have been continuously assessing the potential impact of tariff policies. Copper futures prices on NYMEX have soared, rising more than 10% this month, with the premium over LME copper futures prices also steadily increasing.

In the fast-paced and ever-evolving commodity market, how can investors identify opportunities and mitigate risks? Technical analysis, a key analytical tool, plays a crucial role in commodity trading. Examining historical price movements, trading volumes, and other chart data helps forecast future price trends. This enables investors to recognize critical market shifts within a complex landscape and make well-informed investment decisions.

Chart patterns intuitively reflect the battle between bullish and bearish forces in the market. By observing and analyzing price trend charts, investors can identify recurring patterns that often signal potential changes in price trends. Common chart patterns include double tops, double bottoms, head and shoulders tops, and head and shoulders bottoms.

Double Top Pattern

The Double Top Pattern typically appears at the top of an uptrend. It consists of two peaks of similar height, with a relatively low trough in between. A neckline is formed by connecting the trough between the two peaks. When the price breaks below the neckline, the double top pattern is confirmed. This is often a strong reversal signal, indicating that the uptrend is ending and a downtrend may begin.

(Source: Wikipedia)

Double Bottom Pattern

The Double Bottom Pattern, in contrast, appears at the bottom of a downtrend. It consists of two similar troughs and also features a neckline as a confirmation signal. When the price breaks above the neckline, it indicates that the downtrend may be ending, and an upward trend is likely to unfold.

(Source: Wikipedia)

Head-and-Shoulders Pattern (Top)

The Head-and-Shoulders Pattern (Top) is a relatively reliable reversal pattern that typically forms gradually during an uptrend. It has three peaks: left shoulder, head, and right shoulder. The head is higher than both shoulders, and the neckline is a straight line connecting the low points of the pullbacks from the left and right shoulders. When the price breaks below the neckline, the pattern is confirmed, signaling the reversal of the uptrend.

(Source: Wikipedia)

Head-and-Shoulders Pattern (Bottom)

The Head-and-Shoulders Pattern (Bottom) is the inverse of the Head-and-Shoulders Pattern (Top). It appears at the end of a downtrend, indicating that the market has bottomed out and is preparing for a reversal. When the price breaks above the neckline, investors may consider entering the market with long positions.

(Source: Wikipedia)

Fibonacci Retracement (FR)

Fibonacci Retracement (FR) is a widely used technical analysis tool that helps identify potential support and resistance levels during price corrections within an ongoing trend. Common Fibonacci retracement levels include 23.6%, 38.2%, 50%, 61.8%, and 78.6%. These ratios represent key points where the price is likely to retrace or rebound within its trend.

To apply Fibonacci retracement, traders must select two extreme points on the price chart, typically the high and low points of a significant price movement. Horizontal lines are then drawn at different Fibonacci levels between these points. These levels can serve as potential support in an uptrend or resistance in a downtrend, providing insights into where the price may reverse or continue its trend.

For example, in an uptrend of crude oil prices, if Fibonacci retracement lines are drawn from a specific low point to a high point, the price may find support near the 38.2% or 61.8% retracement levels during a correction before resuming its upward movement.

Bollinger Bands

Bollinger Bands comprise three lines: upper, middle, and lower bands. The middle band is typically a moving average of the price, with a 20-day moving average is commonly used. However, based on different analysis periods and specific requirements. The upper and lower bands are calculated based on the middle band, using a certain multiple of the standard deviation to reflect price volatility

When the price of a commodity moves near the upper band and all three bands (upper, middle, and lower)

 are all rising, it indicates that the market is in a strong uptrend.

Conversely, if the price moves near the lower band and all three bands are sloping downward, it signals a downtrend, with bearish forces being relatively strong.

When the price fluctuates within a narrow range between the upper and lower bands of the Bollinger Bands, and all three bands begin to flatten, it indicates that the market is in a consolidation phase. During this stage, bullish and bearish forces are relatively balanced, and no clear trend direction is present.

Upper picture: red is the upper rail, blue is the middle rail, and green is the lower rail; middle picture: %b value (relative position of closing price); lower picture: bandwidth indicator (width between upper and lower rails)

(Source: Wikipedia)

Moving Average (MA)

A Moving Average (MA) is a curve formed by averaging the closing prices over a specific period and connecting these averages at different times. Common moving averages include: short-term moving averages (e.g., 10-day moving average), medium-term moving averages (e.g., 50-day moving average), and long-term moving averages (e.g., 200-day moving average).

Relative Strength Index (RSI)

The RSI indicator measures the strength of buying and selling pressure in the market by comparing price increases and decreases over a set period. Its ranges from 0 to 100, with 70 and 30 typically serving as the overbought and oversold thresholds.

Moving Average Convergence Divergence (MACD)

Moving Average Convergence Divergence (MACD) consists of three components: fast line (DIF), the slow line (DEA), and the histogram. A buying signal occurs when DIF crosses above DEA, and the histogram shifts from green to red. Conversely, a selling signal appears when DIF crosses below DEA. For example, in the silver market, if silver prices keep hitting new highs while the MACD does not, it often indicates an impending decline. On the other hand, a bullish divergence occurs when the price keeps making new lows while the MACD indicator does not. This signals that selling pressure may be weakening, suggesting a potential price.

(Source: Wikipedia)

Advantages

Reflecting Market Sentiment: Market sentiment plays a crucial role in commodity price fluctuations. helps capture market sentiment by analyzing data such as price trends and trading volumes. When prices rise alongside increasing trading volume, it indicates strong bullish sentiment. Conversely, when the price decline while trading volume decreases, it often signals prevailing bearish sentiment.

Capturing Short-term Fluctuations: For investors seeking short-term trading opportunities, technical analysis helps capture short-term price fluctuations by utilizing technical indicators and chart patterns, providing clear buy and sell signals. For example, in the gold market, investors can take advantage of the crossovers of moving averages, overbought and oversold signals from the Relative Strength Index (RSI), and other indicators to identify price movements and generate profits. When the RSI shows an overbought condition, it suggests that the price may be due for a correction, prompting investors to reduce their positions or sell to lock in gains.

Formulating Trading Strategies: Technical analysis provides a foundation for investors to develop effective trading strategies. By analyzing historical data and chart patterns, investors can identify market trends and recurring patterns. In a volatile market, traders can buy low and sell high by leveraging support and resistance levels. In a trending market, they can capitalize on momentum by following the trend. Additionally, technical analysis helps investors establish stop-loss and take-profit levels,  enabling them to manage risks effectively and improve their trading success rate.

Intuitive and Easy to Understand: The charts and indicators used in technical analysis are more intuitive than those of fundamental analysis. Even investors without extensive financial knowledge can grasp them through study and practice. Novice investors can gain insights into market conditions and trends by observing price charts and indicator curves, allowing them to make informed investment decisions. Technical analysis serves as an excellent introductory tool, helping beginners adapt to the market and accumulate trading experience over time.

Limitations

Insufficiency in Predicting Long-Term Trends: While technical analysis excels in short-term price prediction, it is less effective in forecasting the long-term trends of commodities. Long-term price movements are influenced by complex factors such as the macroeconomy, fundamental supply and demand, and geopolitics. These variables cannot be accurately predicted solely through historical price data and technical indicators, making long-term forecasting a significant challenge for technical analysis.

Lagging Nature: When market trends shift, technical indicators often fail to reflect these changes promptly, causing investors to miss optimal buying and selling opportunities. In a rapidly fluctuating market, by the time the indicators generate signals, prices may have already moved significantly, leading to high entry costs or reduced profit margins. For example, during the early stages of a sharp rise in commodity prices, the moving average may lag behind the price movement. As a result, they may miss the best buying opportunity.

Market Manipulation and Noise Interference: The commodity market is susceptible to artificial manipulation. Large investors or institutions can influence price trends by executing high-volume buy and sell transactions, distorting the signals generated by technical analysis. Additionally, market noise, such as capital flows and rumors, can cause abnormal price fluctuations, reducing the accuracy of technical indicators.. In small commodity markets, individual large investors may leverage their capital advantages to conduct high-frequency transactions within a short period, creating false price trends. This can mislead investors, rendering the signals from technical analysis unreliable and diminishing their reference value.