Value Area Forex Strategy: Trading the Value Area - Singapore Forex Trading, Singapore Forex Academy, Singapore Forex Association

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Value Area Forex Strategy: Trading the Value Area

 The Value Area is a range of prices where the majority of trading volume took place on the prior trading day. In specific, this area is the range where 70% of the prior day’s volume happened. The value area is approximately one standard deviation above and below the average highest volume price. With this knowledge, there are specific probabilities of market behavior we can understand to digest the value area. The value area gives us an idea of where the smart money is playing ball and where the institutions are guiding the market.

Like other popularized strategies, I think this is useful to know. However, I wouldn’t hold your breath on returns for this strategy in reality. I’ve done some backtesting and can’t seem to reach the 80% that the authors and evangelists of this strategy claim. 

Being generous, I’m able to get up to 65%+. It is, however, difficult to spot scenarios where the 80% rule really kicks in for filling. I don’t doubt that accurately trading the value area is profitable. It is a challenge to identify when the trade is available and to execute on it appropriately. 

Though I’m new to the idea and perhaps a well-established system or algorithmic method could perform well. If you can do so, I can imagine a world where the strategy could play out in your favor.

80% Rule

If the market opens above the value area and does not return to the value area this is a heavily bullish signal. However, if the market opens above the value area and returns to the value area this is very bearish.
Example Bullish Signal
Similarly, if the market opens below the value area and does not return to the value area this is a bearish signal. If the market opens below the value area but returns to the value area this is a bullish signal.
Example Bearish Signal
This return to the value area from an open above or below the value area is what satisfies the 80% rule.
This rule works because it’s indicative of institutional pressure. When the market opens above or below the value area and stays above or below, this is a signal institutions are buying and it would likely be a fool’s errand to oppose the activity of the smart money.
At their core, the markets are simple. When there are more buyers than sellers, prices go up. When there are more sellers, markets go down. Understanding all of the factors playing into market behavior, however, is mind-numbingly difficult. We can make some interesting observations about the market based on the 80% rule. Simply put, resting inside the value area is indicative of balance in the markets. There is a roughly even amount of buyers and sellers and we’ll see an oscillation between the highs and lows of the value area. Of course, we want to initiate any buying or selling as close to the tops and bottoms of the value area as possible with tight stops in place. If the price falls out of the value area we can quickly stop out and save from further losses. If the price follows the 80% rule we can profit off the filling of the value area.
In this crude graph I show an example of trading the value area. We can see an example where the price shot above the previous day’s average volume and without a return to the value area we are best suited staying out of this trade. The next day we see the stock trade between the value area for the bulk of the day, following the 80% rule. You can see the stock dropped below the value area and then returned to the value area for two 30 minute candles; it performed this action twice. It followed the 80% rule both times.
Charted Using TradingView
Whether you’re trading this algorithmically and have programmed this trade or are trading this manually, you must either program appropriate stops or plan for appropriate manual stops. Stay disciplined and follow your strategy; don’t let emotions guide your trade. It’s interesting to study these various strategies and see how different strategies guide traders’ daily activities. The more strategies we can identify and create algorithmic systems and backtest for the better.

Conclusion