A Story of Liquidity, Volatility, and Returns

Most of us implicitly know what liquidity is, or at least we pretend to mostly to sound smart during Thanksgiving when we hide our lifetime profit-and-loss from family members who look up to us as the ‘investor’ (“she knows stocks”).

Liquidity, for a more bookish definition, is the ability to sell or buy some asset (in the future the only asset will be bitcoin, for instance) without changing the market price much. This is intuitive when you think about it — when you sell that one AAPL stock you bought at $135 when AAPL later hit $105, you didn’t actually change the market price much, if at all. On the other extreme, in a neighborhood where 3 houses are for sale (including yours, after losing all your money on Robinhood), once you finally close the sale (to appease your bankruptcy-restructured creditors) the other two houses might change in price quite a lot (since there’s less supply).

For Mr. Retail, in most circumstances market liquidity isn’t something you actually think about, because you’re buying 1 contract or maybe 10, and there’s a guy at Virtu more than happy to sell you that shitty OTM call (free money?). However, for large players, and in the context of the market at large, liquidity isn’t just a side note — it’s perhaps the most important feature of the market itself.

Liquidity and the Order Book

For massive players in the market (institutions, Masa Son on Ambien, etc.), liquidity dominates how one enters and exits, rather than using crayons or more advanced crayons (like NOPE). In general, institutions don’t DCA in or wait for the next shooting star Batman doji to confirm a signal to buy one share and post about it on Twitter — they arrange sales of millions of shares at once, which tends to have a large impact on the available market price (the spot).

Moreover, most securities don’t have enough orders on the book to fill millions of shares at once, so our unfortunate institution is at the mercy of filling the order piecemeal, while other investors gouge them mercilessly (if you know someone needs 2 million shares filled, why wouldn’t you charge them as much as possible?).

How do they get around that? Lots of very smart people make liquidity their full time job (nerds), and there’s multiple known (and probably many unknown) ways that institutions move money around:

  1. Block trades — Block trades are large blocks of an asset which are negotiated directly between one party and another party. Most block trades occur between institutions (hedge funds, banks, etc.) and are over-the-counter so you never actually see them. In a block trade, the two parties arrange privately a price to sell/buy which is usually at a discount to the market price. This allows the order to stay private, which otherwise might severely impact market price. These are not reported by default to the tape (Consolidated Tape System).
  2. Dark pool — Dark pools aren’t a sinister word. They’re effectively closed off markets (kind of like a VPN) that are managed privately that don’t give info for participants about the market depth, so HFT algos and the like can’t prey on customers. They can also be completely intra-company and are often used by market makers at big institutions to fill orders. The orders unlike block trades do end up on the tape, but usually not immediately. DIX is a famous indicator that looks at buying/selling pressure in dark pools.

Icebergs — Icebergs are a way for large participants to obfuscate their orders by breaking into chunks, where a market maker will repeatedly broadcast a limit order at a certain price (or price range) with a quantity. This usually implies breaking one order (the iceberg) into smaller, tractable chunks to avoid influencing market price too much. These do appear on the tape as well.

Liquidity and Volatility

So you might be asking — why do I care about this? First off, you’re the one reading a trading blog post, not me. Nerd. Secondly, liquidity is important for even retail to understand for two reasons — volatility (how much the price of the asset moves) and returns (how much money you will make/lose).

A good example of liquidity and my personal favorite is SPY, the largest ETF that tracks the S&P 500 Index in the world, and at least currently the most liquid ticker on the planet. Want to buy 1,000,000 shares of SPY? On a good day, that might just be a blip on the float, and you might not change the price much or at all. On a day like today (where about 25.5 million shares, as of this time have changed hands), you might move it quite a large amount.

What’s interesting though, is the relationship between liquidity and volatility — in general, when markets are more liquid, there’s less volatility*, and when they’re less liquid there is more volatility.

Let’s look at why this is the case intuitively. Suppose I have a market with exactly 5 items (Funko pops, let’s say). I’m a buyer, and I really really want one of those 5 Funko pops — like really badly. Since there are only 5 in all of existence, I need to be prepared to pay likely more than the Funko is actually fairly worth to get one of them, because the seller knows how few of them exist and will look to make as much money as possible from me.

Let’s flip the script now, and pretend we’re selling one of the 5 pops. Let’s say it turns out the other 4 were owned by Jeffrey Epstein, and now the pop itself is synonymous with toxicity. From $500/pop, now suddenly no one wants to buy it. What do you do? You sell it for anything you can, whether it’s $5 or $50.

Conversely, in a high liquidity market, the opposite effect occurs. If there’s a lot of liquidity, I can easily liquidate my Funko pop for the fair market value, because there will be an eager buyer to pick it up. However, I can’t easily sell it for more than the fair market value either, because there’s a just-as-eager seller available to undercut my prices and make the transaction.

This effect is asset-independent for the most part — the relationship between liquidity and volatility isn’t unique to the stock market, but occurs in Forex, Bitcoin, real estate, and just about any marketplace you can think of.

However, the important thing to understand is that this applies to average liquidity — and we’ll look at why next.

Liquidity and Returns

An especially adept reader will point out to me on twitter the following graph, or some variation thereof:

The graph roughly plots daily share trading volume (a proxy of SPY liquidity) compared to the daily range (which ostensibly here means high-low spread in daily prices. We can observe a quite clear correlation — on days with higher volume, the spread between the SPY daily high and low gets wider; on days with low volume, the spread gets smaller. The general consensus is thus:

  • In times of low trading volume, fortune (and statistics) favor bullish movements
  • In times of high trading volume, best run for cover (selloffs)

At this point you should say “But didn’t you just tell me the opposite is supposed to happen?”

And that’s correct; intuitively, the opposite should happen (we should expect the graph to be inverted, basically).

However, the key word here is daily volume — instantaneous daily volume isn’t a precise measure of underlying liquidity (it is a proxy in most cases), and the highest range movements/highest volume days are usually catalyzed (e.g. market selloffs tend to occur on high volume, since everyone is panicking).

Over long timescales, a different picture emerges:

Increased liquidity over time (in this case on E-Mini Futures) correlates strongly negatively to volatility, especially forward looking. This fits with our intuitive understanding.

But — volatility is a good thing. This might be a shocker for those dented by the March 2020 crash, but in general volatility is one of the major factors driving investor returns — a.k.a. the whole reason we’re in the market to begin with (to make/lose money).

Let’s think about why.

In a perfectly liquid market in the absence of news or fundamental changes, there’s no real reason why the price of an asset should change much. If there’s an infinite amount of buyers and sellers, I should be able to buy and sell an asset at roughly the same price repeatedly without moving it up or down, because in each transaction the following holds:

  • If I try to sell the asset for more — another seller could come in and undercut me, selling it at the prevailing market price.
  • If I try to buy the asset for more — I will be allowed to (sure, it’s free money for the seller), but if I then try to sell it again, the first point applies.

However, in periods of illiquidity, I can move the spot — if I’m the only seller or buyer in town, I effectively get to set the price. This is why the following graph occurs:

We can see (although the graph is quite old) a positive correlation between volatility and returns on an asset (in this case, global indices). While volatility is also positively correlated with negative short-term returns (since duh, crashes) over the long term it is a necessary ingredient to generating high returns as well (since duh, Tesla).

This in fact is a restatement of one of the major tradeoffs of diversification — with diversification of your portfolio, you will reduce your risk, but also (almost always) reduce your total return. This is why for instance, the S&P returns on average roughly 10% (from 1926 to 2018, for example), but sometimes its constituents move a lot more (example: since 2015 $MSFT has returned approximately 300%).

Conclusions

In summary, there’s a time-tested relationship between volatility, liquidity, and stock returns. It’s important as a trader to be mindful of the relationship, and understand it no matter what system you use (crayons, order flow, or indicator nonsense). In my next post I’ll go into capitalizing on it with various strategies (dispersion, selling premium and the VRP, and structural illiquidity and delta hedging). Cheers.