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On September 15th, data from the National Bureau of Statistics showed that in August, the year-on-year decline in new residential property prices in first-tier cities was 0.9%, a decrease of 0.2 percentage points compared to the previous month. Specifically, prices in Beijing, Guangzhou, and Shenzhen fell by 2.3%, 1.9%, and 2.3% respectively, while Shanghai saw an increase of 3.0%. In second- and third-tier cities, the year-on-year declines in new residential property prices were 2.7% and 4.1% respectively, both narrowing by 0.1 percentage points. In August, the year-on-year decline in existing residential property prices in first-tier cities was 2.7%, a decrease of 1.0 percentage point compared to the previous month. Specifically, prices in Beijing, Shanghai, Guangzhou, and Shenzhen fell by 3.5%, 0.8%, 3.8%, and 2.7% respectively. In second- and third-tier cities, the year-on-year declines in existing residential property prices were 4.9% and 5.6% respectively, both narrowing by 0.2 percentage points.New Residential Housing Prices: 1. Beijing: August new residential housing prices -0.2% month-on-month (previous value -0.3%), -2.3% year-on-year (previous value -2.3%). 2. Shanghai: August new residential housing prices +0.4% month-on-month (previous value +0.2%), +3.0% year-on-year (previous value +3.0%). 3. Guangzhou: August new residential housing prices +0.1% month-on-month (previous value +0.1%), -1.9% year-on-year (previous value -2.2%). 4. Shenzhen: August new residential housing prices +0.2% month-on-month (previous value +0.2%), -2.3% year-on-year (previous value -2.9%). Second-hand Residential Housing Prices: 1. Beijing: August second-hand residential housing prices -0.1% month-on-month (previous value 0.0%), -3.5% year-on-year (previous value -4.5%). 2. Shanghais existing home prices in August increased by 0.3% month-on-month (previous value +0.3%) and decreased by 0.8% year-on-year (previous value -2.0%). 3. Guangzhous existing home prices in August remained unchanged month-on-month (previous value +0.4%) and decreased by 3.8% year-on-year (previous value -4.7%). 4. Shenzhens existing home prices in August increased by 0.1% month-on-month (previous value +0.2%) and decreased by 2.7% year-on-year (previous value -3.6%).National Bureau of Statistics: Beijings second-hand housing prices in August decreased by 0.1% month-on-month (previous value +0%) and decreased by 3.5% year-on-year (previous value -4.5%).According to the National Bureau of Statistics, the price of second-hand residential properties in Shenzhen rose 0.1% month-on-month in August (up 0.2% in the previous month) and fell 2.7% year-on-year (down 3.6% in the previous month).September 15th - The 2026 China Carbon Market Conference was held in Wuhan, Hubei Province this morning, and the "National Carbon Market Development Report (2026)" was released at the conference. Reporters learned that as of the end of August, the national carbon emission trading market had accumulated transactions exceeding 900 million tons, with a transaction value exceeding 60 billion yuan. The national carbon market has grown from nothing to a significant stage, playing a crucial role in promoting the achievement of carbon peaking and carbon neutrality goals.

How to Enhance Your Moving Average Crossover Strategy

Aria Thomas

Mar 25, 2022 09:33

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Moving Average Crossover

The moving average crossover strategy is designed to locate the middle of a trend. A trend is defined as price movement in which prices move in a certain direction over time. In general, trends are either upward or downward, while sideways movements are considered consolidation rather than trends. Capital markets trade in tight consolidative patterns around 70% of the time and trend just 30% of the time. With this in mind, it is critical to be able to recognize a trend and capitalize on it as soon as it becomes apparent.

What Is the Best Way to Capture a Trend?

Short-term moving averages may capture short-term patterns. A moving average is the average of a specified time, and when a new data point is added, the first period of the average is discarded. A moving average crossover strategy looks for instances when a short term moving average crosses above or below a longer term moving average to create a short term trend.


For example, if the 5-day moving average of USD/JPY prices crosses above the 20-day moving average of USD/JPY prices, a short term trend may be in place. One trading strategy may be to buy USD/JPY prices when the moving averages cross over, hoping to ride an upswing in the currency pair. An investor may try to capture up, down, and sideways movement by combining a short, medium, and long term moving average.


Longer moving averages are used to capture longer-term patterns in a financial market. When the 20-day moving average of gold prices crosses below the 50-day moving average, as seen in the gold chart, a medium term trend is deemed to be in place.

Problems with a Standard Moving Average Crossover

The notion of a moving average crossover is appealing, but a basic issue is that while the market is consolidating, a moving average crossover will provide a lot of false signals. Between April 2014 and April 2015, the 5 / 20 moving average crossover provided 5-signals that did not forecast a trend. This does not imply you would not have earned money trading this strategy, but you would not have seen a big upward (or negative) bias in the currency pair.


One method to improve a moving average crossover strategy is to include extra research that will sift out some of the misleading signals. For example, by adding a Bollinger band (developed by John Bollinger - this research helps form a histogram of prices above and below a mean level) to the 5 /20 crossover strategy, you can also assist in defining a range.


In the instance of the USD/JPY, you could only buy the currency pair when the 5-day moving average crossed the 20-day moving average and the exchange rate crossed above the Bollinger band high (2 standard deviations above the 20-day moving average) during an x-day period. The number of days (x) is subjective, although a duration of fewer than three days is desirable. By adding another layer, the strategy becomes more resilient, but also less common.