Educational Piece: Why Are There So Many Small Trades in ASX Stocks?

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“I have a question relating to the 'course of sales' of regular ASX stocks. Why are there so many small trades of shares in the course of sales, a lot of the time for only 1 or 2 shares, especially in the larger companies? Such small numbers aren’t listed in the ‘depth’ columns of buyers or sellers, so what are they?” - Phil

If you look on a brokerage platform at the ‘course of sales’ data, there are often numerous small trades of one or two shares in larger companies (see the image below). 

Course of sales data for Commbank (ASX: CBA). Source: CommSec.

This may seem puzzling, especially since these small numbers don’t seem to match up with the order book (which shows how many buyers and sellers are lining up to order at different prices):

So what’s going on here?

Algorithmic Trading:

Algorithmic trading uses powerful computers to execute trades at high speeds. These algorithms are programmed to buy or sell shares based on predefined conditions.

For example, an algorithm might be programmed to break down a large order into smaller parts to minimise market impact. So a 1,000-share order might be divided into 100 orders of 10 shares each.

Notably, companies such as Commonwealth Bank of Australia (CBA) or BHP Group (BHP) often have lots of these small trades due to the high volume of algo-trading.

Why would an algo want to break up a trade?

Imagine you are a broker and a client comes to you wanting to sell 10,000 units of a low liquidity stock. 

But if the top-most buyer with the best price only wants 5,000 units, you’ll still be left with 5,000 units to liquidate. 

As such, your order will keep dropping down further and further to the ever-lower available prices (this is called ‘slippage’). 

Worse still: you will be signalling to the market what you are doing.

A savvy trader watching this might realise that you are dumping a big position. They could simply wait until the price drops, buy the stock at the depressed price, wait for the rebound as more ‘normal’ supply and demand dynamics return, and then sell for a profit. 

• In a tight market, if you add a lot of supply quickly, prices can only fall. 

• If the supply/demand equation balances quickly, prices will snap back almost as fast.

And of course, it won’t just be humans looking to take advantage of your big order. Buy-side algorithms are designed to specifically identify and capitalise on these opportunities. 

So to avoid this, sell-side algorithms will break up the order into many smaller parts – often as little as a single share – to avoid detection. It will then trade those smaller parcels over the course of the session(s), either when demand is available, at different price points, or in time increments (i.e. maybe every five minutes). 

What we’re basically left with is an algorithmic arms race, with the world’s smartest data scientists and analysts attempting to outwit and outplay each other – with billions on the line.

Why aren’t these small trades listed in the depth columns?

The reason you don't see these small trades in the depth columns is due to the way the ASX provides information. Here’s the lowdown…

Market depth displays the number of buy orders and sell orders at each price point for a given security:

However, the ASX only shows aggregated orders in the depth columns, and the minimum size for aggregation is usually much higher than one or two shares.

So, those small trades are still happening, but they're just not individually displayed in the depth view.

Should You Worry About These Small Trades?

For most retail investors, this algorithmic arms race isn’t something that is likely to affect you, purely because a retail investor’s order size is likely to be small (too small to impact the price when buying or selling).

Of course, there are exceptions to this. If you’re reading on a low-liquidity stock (i.e. something outside the All Ordinaries), there is more potential for retail investor action to impact things. 

But for the most part, it’s simply wise to be aware of the deeper roots behind these single-stock trades…and to remind yourself that for all the hype around AI, robots have already been embedded in the investing world for decades.