Markets

Two Charts That Show How Trading Dynamics Change Over Time

Two Charts That Show How Trading Dynamics Change Over Time

Risk is an interesting concept.

It is mathematically calculated as the standard deviation of daily returns, which are then annualized to “volatility,” expressed as a percentage, which makes them comparable to “per-annum” returns on a portfolio.

However, most investors probably think of “risk” as the probability of a loss, not the amount a stock price bounces around.

Interestingly, that’s closer to how options traders think of risk, too. The Black Scholes option pricing model that was developed in the 1960s even found a way to convert that same daily “volatility” to a probability-weighted expected loss. That in options becomes the “premium” required to purchase an option.

But what does portfolio and options math have to do with trading?

Volatility affects trading spreads, volume and dark trading, too

The concept of risk, measured as volatility, applies to trading too. As we show below, it helps explain why spreads and liquidity change as markets change.

If we look over a recent 12-month window, we see periods of calm (low volatility and stable prices) and panic (high volatility and price falls). This allows us to highlight the interrelationships that drive markets and in turn affect trading (Chart 1a and 1b).

In short, when risk increases, the probability of loss also increases, known as “adverse selection”.  Traders rationally widen spreads so the balance between spread capture and adverse selection remains.

However the data also show that once markets return to equilibrium, spreads also return to more “normal” levels.

Chart 1a and 1b: Spreads increase during periods of volatility, which typically occurs when markets selloff. That also usually triggers higher volumes and a flight to lit-exchange quotes.

Spreads

Source: Nasdaq Economic Research, SIP, FactSet

Specifically these charts show:

  • When the market sells off (grey line in Chart 1a falls) the volatility, shown as the VIX index, spikes almost instantly (green line turns to red)
  • When the VIX spikes, spreads also widen (the level of the green-red line rises, with the y-axis showing the average large cap spread)
  • Previously, we’ve seen that when spreads are artificially wider, we see more dark trading (see Three Charts that Show How Smart Traders Compress Wide Spreads)
  • However, if spreads widen because of a volatility spike (thickness of the line in chart 1b, or the height of the line in chart 1a) the reverse happens and we instead see an increase in lit trading (yellow color in Chart 1b)
  • On days when market fear (VIX) rises or the market sells off, we see very high volume days (the height of the black-yellow line vs y-axis in chart 1b)
  • Very high volume days are driven by two things:
    1. Index rebalance and derivatives expiry days, including the Russell and S&P reconstitutions, or
    2. New and important news: the trade & tariff war, earnings disappointments and rate hikes in 2018 all contributed to periods of elevated volatility and volumes.( In fact after running at about 6.3billion shares traded per day in Q3, volume increased 34% to 8.5 billion in the remaining three months of 2018, reaching a high of 9.2 billion shares in December, typically a quiet month)

Is the VIX equal to Volatility?

The media often calls the VIX the “fear index.” That’s because it essentially measures the market’s expectations of future volatility.  It is technically a forward-looking measure extracted from option prices with expiries on average one-month away. It is computed using the “implied volatility” from a series of S&P 500 options, which is actually reverse engineered (using the Black Scholes formula) from the prices being paid for options in the market, along with interest rates and the other inputs into the model.

We should highlight that that’s different from what we talked about initially. When volatility is calculated from historical daily returns, it is called “realized volatility.”

Typically the two are related. But because realized volatility is using historical data, it takes longer for new return information to incrementally affect the volatility calculation. In contrast, implied volatility is computed from the price of options being traded now, so it adjusts instantly to price-in new information about macro and market risks.

That’s visible when you consider the charts above. The VIX (which we show as red color in chart 1a) increases almost instantly as the market (shown as the grey line in chart 1a) falls to account for new news.

Spreads widening when volatility spikes makes economic sense

A resting order is economically the same as a short "option" as you are trying to earn the spread (premium), but if you get filled and you're wrong, your downside is unlimited.

So given spread = premium, and option premium goes up as volatility goes up, so should spreads widen on stocks when volatility increases.

So what does this all mean for investors?

Investors and the media often fear markets that are moving dramatically. However, what this shows is that dramatic market moves are “normal,” and they are accompanied by more (not less) liquidity, as additional investors join in the market to discover the new equilibrium price.

We also find that markets react quickly, and rationally, to breaking news. Spreads widen, prices adjust, volumes spike. Although this looks unstable, it is actually price discovery in action.

When the market is “moving fast” to absorb news, the benefits of completing a trade increases. In other words, the opportunity cost of waiting increases. Consequently, in these market periods, traders prefer to trade instantly on exchanges rather than wait for fills in the dark.

However, in volatile markets prices are also more likely to move as well. And it is at these times that it makes even more sense to put limits on your orders.

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Phil Mackintosh

Nasdaq

Phil Mackintosh, Nasdaq Chief Economist, has 28 years of experience in the Finance industry, including roles on the sell-side, buy-side and at accounting firms, which included managing trading, research and risk teams. He is an expert in index construction and ETF trading and has published extensive research on trading, ETFs and market structure.

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