Introduction
Tell me if this sounds familiar. You encounter what appears to be a perfect trade set up on the charts. Your entry is clean, your stop loss is clearing the structure it needs to and your target is realistic. What could possibly go wrong? Your entry gets hit so now all you need to do is ride the wave to profit. That is until, to your horror, price clips your stop loss taking you out of the trade at a loss, only to turn around and go in the direction you thought it would. For me personally, this was easily the most frustrating thing to see. I’d done everything right and yet somehow, I was still losing.
Early on in my trading journey, I was under the impression that market movements were simply the aggregate sum of supply and demand from participants. As I progressed, especially since I started learning concepts taught by Michael Huddlestone, it became clear that retail traders such as myself were simply cogs in a much larger machine controlled and manipulated by Smart Money Entities.
The term ‘Smart Money’ simply refers to entities typically characterised as having extremely large volumes of money, are well informed in the markets and have proven experience and success. Think hedge funds, market makers and institutional investors. Not just whales. Moby-Goddamn-Dick Whales.
There are many ways in which Smart Money will look to extract profits from financial markets, and arguably the most important centres around liquidity.
What is Liquidity?
Put simply, liquidity refers to the efficiency and ease with which an item or asset can be converted to cash without affecting it’s market price.
Highly liquid assets are transacted frequently and with ease. They typically have more stable price action as it requires more volume to cause a change in price. Cash is the most liquid asset as everyone is ready to transact with it.
Low liquidity assets are typically harder to buy and sell. This may be due to:
- Cost as a barrier to entry
- Ease of access to transactions (i.e. is there an easy way to find other buyers and sellers)
- A lack of participants in transacting that asset
- Or a combination of them all.
Fine art is an example of a relatively illiquid asset. There’s only a finite number of people in the world who will buy or sell art and the expense of the asset will price most people out of a purchase.
Hypothetical Scenario
So let’s play out a scenario to demonstrate how liquidity can affect price. Say for example a new token is released that I really want to buy called $LWY and I have $5000 ready to go. I go to a marketplace and the order book looks like this.
If I were to go straight to a market order with $5000, it will use the entirety of my money to buy as much $LWY as possible. The cheapest listing price is $500 per token BUT there isn’t $5000 worth of $LWY for sale at that price. What will happen is I will be forced to buy up the order book in order to fill my order. By the time I’m done, I will have bought:
- 2 $LWY @ $500 = $1000
- 4 $LWY @ 600 = $2400
- 1 $LWY @ $700 = $700
- 1.125 $LWY @ $800 = $900
Giving me a total of 8.125 $LWY for the $5000 I started with.
There are two consequences here:
- I have driven up the cheapest price of the token to $800
- I am 1.875 $LWY worse off than if I had been able to spend all my $5000 at $500 a token.
This is the dilemma that Smart Money faces. Because they transact with enormous sums of money, it is difficult for them to carry out the volume that they require without driving up the price and in the process, worsening the deal along the way.
As such, they must seek zones where there are a large volume of opposing orders they can use to fill their own.
If they are looking to buy, they need to find a zone with a large volume of sell orders to fill their books.
If they are looking to sell, they need to find a zone with a large volume of buy orders to fill their books.
So how do they do it?
Let’s See It In Action
Let’s dive into this chart here. We’ve seen relatively equal highs put in which retail traders will get taught to identify as a level of resistance. We also have a level of support which has been marked and it appears as though price is starting to approach this level.
Retail traders get taught to long from a level of support. It’s a level where price has held previously and should therefore have a higher probability of bouncing from. As all good traders are taught, we manage our risk with stop losses that clear previous wicks low which has been marked with the blue ray. Your stop loss will usually be in the form of a sell-stop (i.e. when price hits this level, a market order is triggered to sell your position). Pretty stock standard trade set-up.
Alternatively you may be a breakout trader, have a bearish bias and are looking to short a break of support. You might set your short order as a sell-stop to trigger a short once price clears the previous structure to short down.
This combination of sell-stop orders from people’s stop-losses for longs and triggers for shorts creates a zone or pool of sell orders. A Smart Money entity will identify this as an excellent spot to fill all their buy orders because after all, every buyer needs a seller.
Lo and behold, price has been pushed down into this zone by Smart Money to fill their buy orders and immediately bounced back up. Now, Smart Money’s dilemma is they’ve just bought a ton of Bitcoin at this price level and need to find somewhere to sell their holdings. What they need, are buyers.
As we previously noted, the top of the range is characterised by relative equal highs. As a retail trader, you might see the opportunity to:
- Short from resistance. This may be from either the top of the highest candle open (first setup) or from the top of the candle that started the range (second setup). Either way, retail traders are taught to have their stop losses clearing structure which in the case of a short, exists as a buy-stop order.
- Or they might have a bullish bias and wish to trade a breakout of the range long. This may be in the form of a buy-stop order once the previous wick-high is cleared.
We now have a zone with a large volume of buy-stop orders. The perfect spot for Smart Money to offload their holdings for profit.
Like clockwork.
Conclusion
There are many strategies that Smart Money entities will use to maximise their profit, but the fundamental issue they face is liquidity and it’s what makes liquidity the biggest driver of market moves. You’ll see these kinds of movements playout on both high and low time frames and even within each other. Truth be told, the example above also contains smaller movements that follow the same principle.
Can you see them now? Unlike traditional Technical Analysis, we’re not looking for magical arbitrary trend lines or pattern formations to guide our decision making. We’re instead driven by an understanding of the underlying mechanics of the financial market.
Does it always play out this cleanly? Absolutely not! This is an example of Smart Money seeking liquidity in a consolidation phase in the market. What about uptrends or downtrends? What about if we break out of consolidation? Perhaps that’s something for another time.
The ultimate question is where is the liquidity for Smart Money to do what they want to do? Tools such as Hyblock can be used to identify such levels. Fortunately, my fellow Kreator Garth has you covered with his Weekly Analysis of Bitcoin’s Hyblock Chart.