𝗪𝗵𝘆 𝘆𝗼𝘂𝗿 𝘀𝘁𝗼𝗽 𝗹𝗼𝘀𝘀 𝗮𝗹𝘄𝗮𝘆𝘀 𝗴𝗲𝘁𝘀 𝗵𝘂𝗻𝘁𝗲𝗱 𝗮𝗻𝗱 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗰𝗮𝗻 𝗮𝘃𝗼𝗶𝗱 𝗶𝘁
Imagine…
You manage a hedge fund and want to buy 1 million shares of ABC stock. You know support is at $100 and ABC is currently trading at $110.
Now if you were to buy ABC stock right now, you’ll likely push the price higher and get filled at an average price of $115 — that’s $5 higher than the current price.
So what do you do?
Since you know $100 is an area of support, chances are, there will be a cluster of stop loss underneath it (from traders who are long ABC stock).
So, if you could push the price lower to trigger these stops, there would be a flood of sell orders hitting the market (as buyers will exit their losing positions).
With the amount of selling pressure coming in, you could buy your 1 million shares of ABC stock from these traders which gives you a better average price.
In other words, if an institution wants to long the markets with minimal slippage, they tend to place a sell order to trigger nearby stop losses. This allows them to buy from traders cutting their losses, which offers them a more favourable entry price.
Go look at your charts and you’ll often see the market taking out the lows of support, only to trade higher subsequently.
Now you’re probably wondering:
“So how do I avoid it?”
Simple.
Set your stop loss a distance away from support to give it some buffer so your stop loss doesn’t get eaten too easily.
Here’s how…
- Identify the lows of support
- Find the current Average True Range (ATR) value and subtract 1 ATR from the lows of support
The idea is to define the current market’s volatility and then subtract it from the lows of support.
This way, you are giving your stop loss a buffer that’s based on the volatility of the markets (and not just some random number).
Pro Tip:
If you want a tighter stop loss, you can reduce your ATR multiple, like having 0.5 ATR instead of 1.
price volatility 在 Volatility Definition: Calculation & Market Examples 的相關結果
Volatility represents how large an asset's prices swing around the mean price—it is a statistical measure of its dispersion of returns. · There are several ways ... ... <看更多>