Avoiding Beartraps using SMA within TradingView (TV)
ที่อัปเดต:
Beartraps are sudden upward movements in stock price which follow a longer downward movement. These traps can catch the best traders causing you to buy into a stock during a momentary upward trend. By using SMA (simple moving average) I believe that you can examine the historical performance of a stock and avoid being trapped.
I’ve recently been caught in the massive landslide in stock values and have been trying to rationalize holding-firm vs taking a loss before the loss becomes excessive. In a subsequent post I will dive into the mathematics of why taking losses is better than holding onto a losing stock which may not rebound for years. Following the dot-com bubble in 2000, some stocks took 8 to 12 years to recover. If you had held firm, and if the company didn’t go bankrupt, you had a huge interval to break-even on the cost of your investment. But the true cost was much higher because of the normal exponential compounding on profitable investments. With this in mind, it may be smarter to cut losses than to ride-out the loss.
I believe the current situation may be a historical move in stock prices caused by a rapid rise in interest rates. This may be one of those events that has a longer recovery time horizon than a normal drop in price.
I am new to trading (but a seasoned business owner) and I recently made a hard decision to jettison all of my ARK stocks, taking a substantial loss. If I had really considered this method (described below), and used it to trigger my exit from the ARK’s, I would have had substantially lower losses.
One of the most basic indicators we can apply to a chart is the SMA, or Simple Moving Average. When applied to a stock, this is essentially an averaging window, which slides in time. As stock price increases, the price is added to the series and the SMA increases. Similarly as the stock goes down the SMA decreases. This isn’t rocket science.
Discussing the non-obvious - implications of SMA and data frequency:
The SMA is an averaging interval, so depending on the display resolution selected in TV the interval can be for a fraction of a minute, to days. The relationship here is a bit difficult to understand so I will give you some examples.
If the data interval in TV is set to 1-min, and you use an SMA-50, you are averaging (smoothing) 50 data samples (50-minutes) into each plotted SMA point.
If the data interval in TV is set to 1-hour, and you use an SMA-50, you are averaging (smoothing) 50 data samples (50-hours) into each plotted SMA point. Big difference!
Since there are 390 minutes in the trading day, we can build a table showing the number of trading days that correlate to a given SMA using a given data-frequency within TV.
I can’t post my data table here but I will try to post a link to a spreadsheet below.
Here are some values that I’ve found to be useful:
TradingView data frequency SMA I’ve found useful
4-hr SMA-50
2-hr SMA-100
1-hr SMA-200
30-min SMA-400
To try this within Tradingview:
Open your favorite stock
Set the Tradingview data frequency by clicking the box just to the right of the stock symbol in the top-left corner of your Tradingview chart.
Apply the color-alternating 50-SMA:
Add Fx
Search for: Simple Moving Averages by stocksinboxx
Add this to your chart
select properties for this function.
under Style tab at top, disable (un-check) all SMA #'s except for SMA #5
under Inputs tab, scroll down to line that reads: SMA #5, and set whatever interval you like, I have been using 50
click ok
Zoom out to view whatever interval is interesting, try 3-months or 12-months.
You can now go back into the SMA and adjust the interval. As you select a larger number, you will notice fewer color transitions in the SMA trend.
I’ve recently been caught in the massive landslide in stock values and have been trying to rationalize holding-firm vs taking a loss before the loss becomes excessive. In a subsequent post I will dive into the mathematics of why taking losses is better than holding onto a losing stock which may not rebound for years. Following the dot-com bubble in 2000, some stocks took 8 to 12 years to recover. If you had held firm, and if the company didn’t go bankrupt, you had a huge interval to break-even on the cost of your investment. But the true cost was much higher because of the normal exponential compounding on profitable investments. With this in mind, it may be smarter to cut losses than to ride-out the loss.
I believe the current situation may be a historical move in stock prices caused by a rapid rise in interest rates. This may be one of those events that has a longer recovery time horizon than a normal drop in price.
I am new to trading (but a seasoned business owner) and I recently made a hard decision to jettison all of my ARK stocks, taking a substantial loss. If I had really considered this method (described below), and used it to trigger my exit from the ARK’s, I would have had substantially lower losses.
One of the most basic indicators we can apply to a chart is the SMA, or Simple Moving Average. When applied to a stock, this is essentially an averaging window, which slides in time. As stock price increases, the price is added to the series and the SMA increases. Similarly as the stock goes down the SMA decreases. This isn’t rocket science.
Discussing the non-obvious - implications of SMA and data frequency:
The SMA is an averaging interval, so depending on the display resolution selected in TV the interval can be for a fraction of a minute, to days. The relationship here is a bit difficult to understand so I will give you some examples.
If the data interval in TV is set to 1-min, and you use an SMA-50, you are averaging (smoothing) 50 data samples (50-minutes) into each plotted SMA point.
If the data interval in TV is set to 1-hour, and you use an SMA-50, you are averaging (smoothing) 50 data samples (50-hours) into each plotted SMA point. Big difference!
Since there are 390 minutes in the trading day, we can build a table showing the number of trading days that correlate to a given SMA using a given data-frequency within TV.
I can’t post my data table here but I will try to post a link to a spreadsheet below.
Here are some values that I’ve found to be useful:
TradingView data frequency SMA I’ve found useful
4-hr SMA-50
2-hr SMA-100
1-hr SMA-200
30-min SMA-400
To try this within Tradingview:
Open your favorite stock
Set the Tradingview data frequency by clicking the box just to the right of the stock symbol in the top-left corner of your Tradingview chart.
Apply the color-alternating 50-SMA:
Add Fx
Search for: Simple Moving Averages by stocksinboxx
Add this to your chart
select properties for this function.
under Style tab at top, disable (un-check) all SMA #'s except for SMA #5
under Inputs tab, scroll down to line that reads: SMA #5, and set whatever interval you like, I have been using 50
click ok
Zoom out to view whatever interval is interesting, try 3-months or 12-months.
You can now go back into the SMA and adjust the interval. As you select a larger number, you will notice fewer color transitions in the SMA trend.
บันทึกช่วยจำ
Try opening SQ with an 1-hr resolution and an SMA-50.Then try SQ with a 5-min resolution and an SMA-600
Then try SQ with a 1-min resolution and an SMA-3000
Those three things are equivalent. The right numbers will vary with the stock as some are much more turbulent than others. I think the interesting thing is that this may be another tool in the toolbox to help understand what you're seeing in TV.
-d
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