Spencer Li

Weekly Market Wrap: Strong NFP Jobs Data Boosts Stock Markets!

Thumbnail banner weekly market wrap x3

Thumbnail banner weekly market wrap x3

For subscribers of our “Daily Trading Signals”, we now also include a “Weekly Market Report”, where we provide a weekly deep-dive on the market, including fundamentals, technicals, economics, and portfolio management:

Click here for last week’s market report (28 August 2023)
Click here to subscribe for the latest market report (04 September 2023)
Click here to see the archives of all our past market reports

Market Recap & Upcoming Week

Last week was filled with pivotal financial events, with key remarks and strategic decisions driving markets across the globe. At the heart of the discussions was the Federal Reserve’s cautious stance on rates. Chair Jerome Powell, during his speech at both Jackson Hole and the Kansas City Fed’s annual symposium, highlighted concerns over persistent inflation, suggesting that high interest rates might continue.

On the jobs front, the US Bureau of Labor Statistics (BLS) announced on Friday that the US Nonfarm Payrolls (NFP) saw an increase of 187,000 in August, surpassing the anticipated market forecast of 170,000.

While the stock markets showed resilience by recording gains in major indices like the S&P 500, Dow Jones, and Nasdaq, the financial community remains divided on the Fed’s future actions. Speculations have pushed short-term Treasury yields slightly higher, and all eyes are set on upcoming inflation and job data.

UBS made headlines with its record $29 billion net profit following the acquisition of Credit Suisse, solidifying its stature in global wealth management. The successful integration and optimistic future projections indicate a prosperous path ahead for UBS.

In international updates, China took decisive steps to boost its capital markets. The government’s announcement of a tax cut on trading was met with positivity, as evidenced by the notable jump in the CSI 300 Index and Hong Kong’s Hang Seng Index. This move comes at a crucial time, given China’s faltering economy and recent challenges in the stock market.

As we approach the upcoming week, investors should keep a vigilant eye on the housing and energy sectors. Do take note that it will be a slightly shorter trading week, as U.S. equity markets remain closed for Labor Day.

PMI surveys from S&P Global and the ISM, coupled with the Fed’s Beige Book and China’s inflation data, will provide crucial insights into global economic health. Furthermore, earnings reports from Gamestop, American Eagle Outfitters, and Kroger are set to roll out, potentially setting the tone for retail sector dynamics in the latter part of the year.

 

 

Daily Trading Signals (Highlights)

We cover 3 main markets with a total of 200+ counters, so we will never run out of trading opportunities:

By covering a broad range of markets, we can focus our attention (and capital) on whichever market currently gives the best returns.

 

trading signals AUDCAD 010923

AUDCAD – Potential shorting opportunity to look out for.

 

trading signals DBC 010923

Commodities ETF (DBC) – After breaking the bearish trendline, prices are now forming a cup and handle accumulation pattern.

 

trading signals US100 010923

NASDAQ 100 (US100) – Following up on this trade entry, it is now in the money, and prices are likely to continue heading up to test the previous high. 💰🔥💪🏻

 

trading signals USDCHF 010923

USDCHF – Keep an eye for a potential bear flag breakdown.

 

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Moving Average Crossover Strategies

Moving averages are often the first technical indicator traders will utilize when they set out to understand trading. However, even highly competent traders who have knowledge of many advanced tools often continue to rely on moving averages, highlighting their significance in technical analysis.

These averages play a critical role across the trading spectrum, providing insights into market trends and potential turning points.

Types of Moving Average Crossovers

Moving averages can be used in various ways, such as providing support and resistance levels, or indicating potential turning points through crossovers. Each trader may have their preferred averages, but it is useful to categorize them into two groups: long-term and short-term.

Long-Term Moving Averages

Long-term moving averages, such as the 50, 100, and 200-day averages, are slower moving and provide less sensitivity to short-term price action.

These averages typically offer fewer signals, but the rarity of these signals can enhance their perceived importance. Due to their slower nature, long-term averages carry the risk of producing lagging signals, meaning they may confirm trends or reversals after they have already begun.

Short-Term Moving Averages

Conversely, short-term moving averages, like the 5, 10, 20, and 50-day averages, offer more reactive indicators, providing traders with timely signals based on recent price action.

These averages generate more frequent signals, which can be beneficial for active trading. However, this increased frequency can also lead to a higher number of false signals, making them more susceptible to market noise.

When employing a moving average crossover strategy, the key is to use the shorter, more reactive average as an indicator of potential market direction.

Crossover strategies are typically more effective in trending markets, where sideways trading tends to produce numerous buy and sell signals without substantial results.

Golden Cross and Death Cross

Long-term moving average crossovers can often be labeled as ‘golden crosses’ or ‘death crosses’ depending on their bullish or bearish implications.

For example, in a 100-day and 200-day simple moving average (SMA) strategy, a ‘golden cross’ occurs when the 100-day SMA crosses above the 200-day SMA, signaling a bullish trend. Conversely, a ‘death cross’ occurs when the 100-day SMA crosses below the 200-day SMA, indicating a bearish trend.

These long-term crossovers can illustrate both the strengths and weaknesses of a longer-term SMA crossover strategy. For instance, on a USD/CNH chart, a death cross might indicate a sell signal when the shorter SMA crosses below the longer SMA, potentially marking the start of a significant downtrend.

However, the lagging nature of these signals means that by the time the crossover occurs, much of the price movement may have already happened, reducing the effectiveness of the signal.

Short-Timeframe Crossover Signals

Shorter-term moving average strategies, such as the 10-day and 20-day SMA crossover, provide a different trading experience. These moving averages track price action more closely, resulting in a higher number of signals.

While this can be advantageous in trending markets, it often leads to a greater number of false signals in sideways markets. The key to success with short-term crossovers lies in distinguishing between trending and consolidating market phases.

By analyzing price action alongside the moving averages, traders can better identify when a trend is truly beginning or ending, thus avoiding false signals.

Alternate Forms of Moving Averages

Not all moving averages are created equal. While the simple moving average (SMA) is commonly used, other types of moving averages, such as the exponential moving average (EMA), offer different insights.

The EMA, for example, gives more weight to recent prices, making it more responsive to current market conditions. This responsiveness can provide more timely signals compared to the SMA, particularly in fast-moving markets.

Three Moving Average Strategy

A strategy that incorporates multiple moving averages can provide a balanced approach by combining short-term and long-term elements.

For example, using a triple EMA strategy, where short, medium, and long-term EMAs are analyzed together, can help traders identify trending markets.

In a strong trend, these EMAs will align in sequence, with the shortest EMA closest to the price and the longest EMA furthest away.

Incorporating price action analysis with this strategy can further enhance its effectiveness by confirming whether the market is trending or consolidating.

Concluding Thoughts

Moving averages, whether simple, weighted, or exponential, remain a cornerstone of technical analysis for traders of all levels.

Their ability to smooth out price data and reveal trends makes them invaluable tools in identifying support and resistance levels, trend direction, and potential reversal points.

By understanding the strengths and weaknesses of different moving averages and their crossover strategies, traders can develop more effective trading strategies, whether they are focusing on short-term or long-term market movements.

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Types of Moving Averages (Simple, Exponential, Weighted)

The Simple Moving Average (SMA) is one of the most basic forms of moving averages.

It calculates the average price of a security over a specified period by summing the prices and then dividing by the number of periods.

For example, to calculate a 10-day SMA, you would add up the closing prices of the last 10 days and divide by 10.

This method gives equal weight to all prices within the period, which means that older prices have the same influence on the average as more recent ones.

Weighted Moving Average (WMA)

The Weighted Moving Average (WMA) differs from the SMA in that it assigns greater weight to more recent data points.

This is done by multiplying each price by a specific weighting factor, which decreases as you move further back in time.

The weighting factors are usually based on the number of periods used.

For instance, in a 5-day WMA, the most recent day’s price might be multiplied by 5, the previous day by 4, and so on, until the first day is multiplied by 1.

The sum of these products is then divided by the sum of the weighting factors to produce the WMA.

This method makes the WMA more sensitive to recent price changes, which can be advantageous for traders who want to capture shifts in market momentum more quickly.

Exponential Moving Average (EMA)

The Exponential Moving Average (EMA) is another form of weighted moving average that assigns more significance to recent prices.

However, unlike the WMA, the EMA applies an exponential multiplier, meaning the rate at which older data decreases is not linear but exponential.

This makes the EMA more responsive to recent price changes while still accounting for older data.

The EMA is calculated in three steps: first, by computing the SMA over a specific period; second, by calculating the multiplier, which is [2/(selected time period + 1)]; and third, by applying this multiplier to the difference between the current price and the previous EMA.

This value is then added to the previous EMA to produce the current EMA.

Differences Between SMAs, WMAs, and EMAs

The primary difference between these types of moving averages lies in how they treat the data points in the calculation:

  • SMA: Treats all data points equally, making it a simple and straightforward indicator. However, it is slower to respond to price changes, particularly when compared to other moving averages.
  • WMA: Assigns more weight to recent data, making it more responsive to changes in price trends than the SMA. The WMA reacts faster to price changes, which can be useful in volatile markets.
  • EMA: Goes a step further by applying an exponential multiplier, giving the most recent prices even more weight. This makes the EMA the most responsive of the three moving averages, often preferred by traders who need to react quickly to changes in market conditions.

Choosing the Right Moving Average

The choice between using an SMA, WMA, or EMA largely depends on your trading strategy and the time frame you are focusing on:

  • SMA: Best for identifying long-term trends and support/resistance levels. It is less prone to whipsaws (false signals) but also less responsive to recent price changes.
  • WMA: Suitable for traders who want a moving average that responds more quickly to price changes without the extreme sensitivity of an EMA.
  • EMA: Ideal for short-term traders and those looking to capture rapid price movements. It reacts quickly to new information, making it useful for detecting early signs of trend reversals.

Limitations of Moving Averages

Despite their usefulness, moving averages have certain limitations:

  • Lagging Indicator: All moving averages are lagging indicators, meaning they are based on past data and may not reflect real-time changes in market conditions. This can result in delayed signals, especially in fast-moving markets.
  • Whipsaws: Shorter-period moving averages, particularly EMAs, can produce false signals or whipsaws, especially in choppy or sideways markets. This can lead to premature entries or exits.
  • No Predictive Power: Moving averages do not predict future prices; they only indicate the direction of the current trend. Traders must use them in conjunction with other indicators and analysis methods.

Practical Applications of Moving Averages

Moving averages are versatile tools used in various ways:

  • Trend Identification: Moving averages help traders determine the overall direction of the market. A rising moving average suggests an uptrend, while a falling one indicates a downtrend.
  • Support and Resistance: MAs can act as dynamic support and resistance levels. For example, in an uptrend, the price may pull back to the moving average before resuming its upward trajectory.
  • Crossovers: Moving average crossovers are popular trading signals. For instance, a bullish crossover occurs when a short-term MA crosses above a long-term MA, signaling a potential upward trend.
  • Filtering Noise: Moving averages smooth out price data, making it easier to spot trends and reduce the impact of short-term fluctuations.

Advanced Moving Averages

Besides the basic SMAs, WMAs, and EMAs, there are other, more advanced moving averages that traders might consider:

  • Triangular Moving Average (TMA): This is a double-smoothed SMA that gives more weight to the middle portion of the data set, providing an even smoother average.
  • Double Exponential Moving Average (DEMA): Designed to reduce the lag of traditional moving averages, DEMA is a combination of a single EMA and a double EMA, offering faster response times.

Concluding Thoughts

Moving averages, including SMAs, WMAs, and EMAs, are essential tools in technical analysis that help traders identify trends and make informed trading decisions.

Each type of moving average has its strengths and weaknesses, with the SMA offering simplicity, the WMA providing a quicker response to recent prices, and the EMA offering the most sensitivity to price changes.

Traders should choose the moving average that best suits their trading style and use it in conjunction with other indicators to confirm signals and reduce the risk of false signals.

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Moving Average Indicator

A moving average (MA) is a widely used stock indicator in technical analysis, designed to smooth out price data by calculating an ongoing average price over a specific period.

This smoothing process helps mitigate the impact of random, short-term fluctuations, providing a clearer view of the stock’s overall price trend.

Understanding a Moving Average (MA)

Moving averages are essential tools for identifying the trend direction of a stock and determining its support and resistance levels.

Since they rely on past prices, moving averages are considered lagging indicators, meaning they reflect trends that have already begun.

The longer the period considered in the moving average, the greater the lag. For example, a 200-day moving average will lag more than a 20-day moving average because it incorporates a broader range of past prices.

Types of Moving Averages

Simple Moving Average (SMA)

A simple moving average (SMA) calculates the arithmetic mean of a set of prices over a specific period.

To compute the SMA, you sum the closing prices over the chosen period and then divide by the number of days in that period.

The SMA is particularly effective in evaluating the strength of a current trend but is less useful in predicting price movements in sideways or range-bound markets.

Exponential Moving Average (EMA)

The exponential moving average (EMA) gives more weight to recent prices, making it more responsive to new information.

This weighting process helps the EMA react quicker to price changes than the SMA, which treats all data points equally.

Due to its sensitivity to recent price action, the EMA is preferred by traders who require quicker signals, although it can generate more false signals.

How Moving Averages Work

Moving averages are commonly used to identify trend direction.

For instance, a rising moving average suggests that the stock is in an uptrend, while a declining moving average indicates a downtrend.

Moreover, moving averages are instrumental in confirming momentum through crossovers.

A bullish crossover occurs when a short-term moving average crosses above a longer-term moving average, indicating upward momentum. Conversely, a bearish crossover happens when a short-term moving average crosses below a longer-term moving average, signaling downward momentum.

Examples of Moving Averages

  • SMA Example: If you have a 10-day SMA, you would calculate the average of the closing prices over the last 10 days. As each new day’s price is added, the oldest day’s price is dropped from the calculation, resulting in a constantly updated average.
  • EMA Example: To calculate a 20-day EMA, you first compute the 20-day SMA, then apply a multiplier (smoothing factor) to weigh recent prices more heavily.

Applications of Moving Averages

  • Bollinger Bands®: A Bollinger Band® is a technical indicator that uses a moving average to define the middle band, with additional bands plotted at a distance of two standard deviations above and below the moving average. This setup helps identify overbought and oversold conditions.
  • Moving Average Convergence Divergence (MACD): The MACD tracks the relationship between two moving averages—usually the 26-day EMA and the 12-day EMA. A nine-day EMA of the MACD (signal line) is then plotted on the same graph, helping traders identify potential buy and sell signals.
  • Golden Cross: A golden cross occurs when a short-term moving average (e.g., 15-day) crosses above a long-term moving average (e.g., 50-day). This pattern is considered a bullish signal, indicating that a strong uptrend may be on the horizon.

Concluding Thoughts

A moving average (MA) is a fundamental tool in technical analysis, offering a clearer perspective on price trends by smoothing out short-term volatility.

While the SMA provides an evenly weighted average, the EMA gives more emphasis to recent data, making it more responsive to new trends.

Both types of moving averages are valuable in identifying trend directions and confirming momentum, especially when used alongside other technical indicators.

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What are Trend Indicators or Trend Following Indicators?

Trend-following indicators are technical tools that measure the direction and strength of trends within a chosen time frame.

Some trend-following indicators are plotted directly on the price panel.

These indicators issue a bearish signal when positioned above the price and a bullish signal when situated below the price.

Others are drawn below the panel, generating upticks and downticks from 0 to 100 or across a central ‘zero’ line.

These indicators create bullish or bearish divergences when their signals oppose the price action.

Characteristics of Trend-Following Indicators

Most trend-following indicators are ‘lagging,’ meaning they generate a buy or sell signal after a trend or reversal is already underway.

The moving average is the most popular lagging trend-following indicator.

These indicators can also be ‘leading,’ predicting price action before it begins by using multiple calculations and comparing momentum across different time frames.

Parabolic Stop and Reverse (Parabolic SAR) is a well-known leading trend-following indicator.

Functions of Trend-Following Indicators

Trend-following indicators serve three primary functions:

  1. Alerting the Technician: They alert the technician to a developing trend or an impending reversal.
  2. Predicting Price Direction: They predict short- and long-term price direction.
  3. Confirming Observations: They confirm observations and signals in the price pattern and other technical indicators.

Signal reliability is dependent on the settings used for drawing the trend-following indicator.

For example, a 50-day moving average and a 200-day moving average generate unique buy and sell signals that may work in one time frame but not in another.

Types of Trend-Following Indicators

Simple Moving Average (SMA)

The Simple Moving Average (SMA) measures the average price across a range of price bars chosen by the technician.

It is a highly effective tool for evaluating the strength of the current trend and determining whether an established trend will continue or reverse.

The SMA is less effective in sideways and range-bound markets.

Interactions between the price and the moving average generate bullish and bearish divergences, which evaluate trend strength and direction.

Exponential Moving Average (EMA)

The Exponential Moving Average (EMA) measures the average price across a range of price bars but places greater weight on more recent data points.

This ‘weighted moving average’ responds more quickly to recent price action than the SMA, theoretically generating earlier buy and sell signals.

However, this weighting also tends to generate more false signals than the SMA.

Average Directional Index (ADX/DMS)

The Average Directional Index (ADX/DMS) measures the strength or weakness of an active trend.

It uses moving averages in several time frames to generate three lines—ADX, +DMI, and -DMI.

These lines cross higher or lower through a panel with values between 0 and 100.

ADX measures the strength of an uptrend when +DMI is above -DMI and the strength of a downtrend when +DMI is below -DMI.

Moving Average Convergence-Divergence (MACD)

Moving Average Convergence-Divergence (MACD) is a widely used technical tool that analyzes the relationship between moving averages set at different intervals.

MACD generates directional lines or a histogram that gauges current momentum and price direction.

It is calculated by subtracting a 26-period EMA from a 12-period EMA, with a 9-period EMA of the MACD, called the ‘signal line,’ added to the plot.

Parabolic Stop and Reverse (Parabolic SAR)

Developed by RSI creator Welles Wilder Jr., the Parabolic Stop and Reverse (Parabolic SAR) is used to confirm trend direction and generate reversal signals.

Indicator data points generate dots above or below the price on the main chart panel.

The calculation applies an ‘invisible’ trailing stop, forcing the indicator to change direction when hit, marking a potential trend reversal.

Additional Trend-Following Indicators

  • Accumulative Swing Index: Evaluates the long-term trend through changes in opening, closing, high, and low prices.
  • Alligator: Uses three Fibonacci-tuned moving averages to identify trends and reversals.
  • Aroon: Evaluates whether a security is trending or range-bound and, if trending, the strength or weakness of the advance or decline.
  • Elder Ray Index: Evaluates buying and selling pressure by separating price action into bull and bear power.
  • ZigZag: Connects plot points on a price chart that reverse whenever the asset reverses by more than a specified percentage.

Concluding Thoughts

Trend-following indicators are essential tools for traders and investors aiming to capitalize on market trends.

While they offer valuable insights into the direction and strength of trends, their effectiveness can vary based on the settings and market conditions.

Using these indicators in conjunction with other technical analysis tools can enhance their reliability and help traders make more informed decisions.

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