
Staff Report on Algorithmic Trading in U.S. Capital Markets [pdf] - ra7
https://www.sec.gov/files/Algo_Trading_Report_2020.pdf
======
dcolkitt
> They find that when the relative tick size, i.e. the minimum tick size
> increment divided by the stock price, is larger, HFTs compete more intensely
> to be the first one to the front of the limit order book queue in order to
> supply liquidity.

Although I think the SEC has generally done a good job in terms of market
microstructure (especially in terms of resisting ill-informed populist
rhetoric), I really wish they'd start exploring sub-penny tick sizes, at the
very least on the most liquid low-priced stocks.

Since decimalization, it's been two decades since we've had a tick size
reduction in US equities. When certain stocks sit at a one penny bid-ask
spread all day, that's a sign that penny ticks are too economically wide. It's
consumers and ordinary investors that pay the cost in terms of higher spreads.

You can think of the bid-ask spread as the cost of liquidity. It's how much
more you pay for immediate execution. The tick size therefore acts like a
price floor on the cost of liquidity. Why are we imposing a price floor, one
that's much higher than the free market price, on end-consumers? If we reduced
tick sizes from $0.01 to $0.001, the cost of trading for most retail investors
on most stocks would fall by 50% or more.

It blunts the price discovery process. It incentives HFTs to compete in an
arms race of speed to capture queue position, rather than provide better
prices. The only group it really benefits are the incumbent exchanges (who can
avoid competing with new entrants offering better pricing), and large, active
portfolios, like hedge funds, that incur high market impact costs.

~~~
jedberg
I agree with you, but there is an interesting though experiment. What if we
made tick sizes $.000000000000001?

At what point do we get a diminishing return? At what point is it so small
that it blows up the algorithms?

~~~
vii
Well it might blow up some software not expecting these tiny tick sizes but
there is an economic motive for larger tick sizes.

Traders can compete on

\- price

\- queue position

Small ticks mean they compete on price and big ticks mean they compete on
queue position - to trade they need to have an order on the book, offering to
trade at the current tick, that is ahead of other orders.

It's easy to see how the market benefits if people compete on price. However,
it also benefits if people show how much they are willing to buy and sell. No
sophisticated trader wants to reveal that as they will be taken advantage of
when they are wrong. By having bigger tick sizes you incentivise people to try
to get into the queue at these artificially better prices - it pulls liquidity
into the open.

The tick size pilot that concluded in 2019 shows how this balance isn't easy
to strike [https://www.finra.org/rules-guidance/key-topics/tick-size-
pi...](https://www.finra.org/rules-guidance/key-topics/tick-size-pilot-
program)

~~~
rytill
Thank you for this simple explanation.

Lowering tick size helps price discovery, but hurts open liquidity.

Is there some ideal constant average number of ticks between the bid and ask
which optimizes this tradeoff given a desired state of liquidity and price
discovery?

------
nateh90
> Today’s equity market structure is highly fragmented, consisting of fifteen
> national securities exchanges, over thirty alternative trading systems,
> multiple single-dealer platforms within broker-dealers, and other forms of
> order matching

While the fragmentation of trading venues has led to competition on fees, in
my experience it has actually widened the effective spread (spread + fees) and
created a more difficult environment for customers.

Let's say a market-maker would like to trade 100 contracts. Any less than that
is great, and any more than that is bad, as the counter-party is likely well
informed about their trade. With one exchange, the market-maker can post their
100 contracts on that exchange, and be confident that the most risk they will
take on is 100 contracts.

With multiple exchanges, the market-maker now needs to spread their exposure
across exchanges (say, 10 contracts each on 15 exchanges), which can leave
them (A) overexposed across exchanges, and (B) underexposed on any given
exchange.

(A) causes a problem because the market-makers compensate for this risk by
widening spreads. If the most sophisticated counterparties in the market can
access liquidity across exchanges, the market-maker needs to at least
statistically account for that possibility.

(B) causes a problem for customers with less sophisticated market access. In
the example above, a customer with access to 1 of 15 exchanges only has the
ability to trade 10 contracts, when they could trade 150 contracts with
connectivity to all 15 exchanges.

For a real life example of where single listing works, you can currently trade
over 20m of notional value with a spread of about .01 basis points in the ES
future listed on the CME.

Source: HFT trader

~~~
kasey_junk
The CME’s monopoly definitely causes problems though. For instance it’s much
more expensive in fees to trade there and your recourse when you observe
shenanigans is less.

Source: Used to be an HFT.

------
mukundmohan
The money quotes:

Broadly speaking, and as more fully discussed below, algorithmic trading in
the equities and to a lesser extent—in the debt market, has improved many
measures of market quality and liquidity provision during normal market
conditions, though studies have also shown that some types of algorithmic
trading may exacerbate periods of unusual market stress or volatility.
Advances in technology and communications have enabled many market
participants to more efficiently provide liquidity, more efficiently access
market liquidity, implement new trading services, and more effectively manage
risk across a range of markets.

Today, algorithms address many of the problems and decisions that have long
been central to the business of trading. What instrument(s) should be invested
in or traded? What price should be bid or offered? What order size is optimal?
What should be the response to a request for a quotation? What risk will be
taken on by facilitating a trade? How does that risk change with the size of
the trade? Is the risk of a trade appropriate to a firm’s available capital?
What is the relationship between the price of different but related securities
or financial products? To what market should an order be sent? Is it more
effective to provide liquidity or demand liquidity? Should an order be
displayed or non-displayed? To which broker should an order be sent? When
should an order be submitted to a trading center?

------
greatwave1
"Although some studies argue otherwise, a number of academic papers study the
effects of algorithmic trading and high-frequency trading on volatility in
equity markets and find evidence that, under normal market conditions, they
reduce short term volatility."

That's interesting, and goes against the conventional wisdom that markets
driven by automated, high-frequency trading will be much more volatile. I
wonder if HFTs made major changes to avoid another Flash Crash.

~~~
pydry
>That's interesting, and goes against the conventional wisdom that markets
driven by automated, high-frequency trading will be much more volatile.

Only if you ignore the word "normal". Otherwise it's what people have been
saying for years - HFT reduces volatility when the seas are calm and amplifies
it when they're choppy.

------
anthony_r
Never forget that ETFs are only really possible due to HFT. Most ETF users do
not even realise this, unless they ask themselves "how do ETFs actually work",
and they start reading about Authorized Participants.

~~~
ric2b
Can you expand on this? From my understanding ETF's re-balance quite slowly,
once every few months, how does HFT even help, much less make ETF's possible?

~~~
smabie
ETF shares are created and destroyed all the, bringing their value inline with
the underlying. So for a S&P 500 ETF, HFT firms are creating shares when the
price of the ETF is too low and destroying them when they are too high.

It doesn't have to do with how ETFs rebalance, rather how shares are created
and destroyed.

------
supernova87a
While I read the report, here is a question I would love to know more about:

Many of these quant/algorithmic trading firms are exploiting market
inefficiencies at the millisecond (microsecond??) level. To the point that no
human person is participating on the same timescale, yet every "real person's"
trade gets just a little bit shaved off by some algorithm able to take
advantage of it.

What would be so bad about putting in human-sized time intervals as the
minimum trading frequency? Like, buyers and sellers can only be cleared on a
1.0 second frequency, or even 0.1 second frequency. So that the millions of
times-per-second arms race is nullified.

Are these algorithmic trades serving some public good? Why not have the SEC /
exchanges put in this delay for everyone's benefit, and not have these firms
make $ off everyone?

Or is that not actually the main market inefficiency happening / being
questioned here, and the bigger loss is bulk movements driven by algorithms
over hours/days, not milliseconds?

~~~
rmah
If a market did as you suggested, then there would simply be no orders for
0.99999 seconds and then a huge flood of orders at 0.000001 seconds before
execution happens.

~~~
sroussey
Not if they couldn’t be processed in that time.

It is an interesting thought experiment though.. quantize time as well as
price. You could exaggerate to one trade per day for the thought experiment.
Now this would be on human scale so there is a lot of information that would
build up (same when markets are closed). Between that and no time quantization
like now, there are probably a few different positions (like electron
orbitals) where positives and negatives vary quite a bit. Maybe one of them is
better than the current system. Maybe not.

~~~
growse
But.... Why?

What problem is this solving?

Seems like a lot of faff to get people worse prices.

------
bonestamp2
Side question, can anybody recommend a good brokerage for running my own
trading algorithm? I'm getting tired of inputting very similar trades every
day and being limited by the types of limit orders they allow in after hours
trading. So far it looks like the winner might be Interactive Brokers or maybe
Centerpoint (if I meet their guidelines).

~~~
kp98
interactive brokers is really the best you're going to get. Its a low level
API which is generally good. Terrible documentation, in fact the worst
documentation I've ever seen on such a large project, but once you figure it
out it'll give you all the functionality needed.

------
encyclopedia
Related to a new kind of algorithm being used in the market 'Dexamethasone
Announcement Could Have Made Hedge Funds A Fortune — Alpha Week'
[https://www.alpha-week.com/dexamethasone-announcement-
could-...](https://www.alpha-week.com/dexamethasone-announcement-could-have-
made-hedge-funds-fortune)

------
artemonster
While we’re on this topic, can some expert ELI5 how or/why HFT is good for
markets/economy?

~~~
ldoughty
HFT is specifically a tool that benefits the haves (HFT) over the have nots.

It can benefit stock prices for companies too, since it can cause the market
to move more in their direction if machines think they should buy based on
whatever they're programmed to look at.

I looked into this for a while, but I simply felt it was immoral and dropped
the project.

~~~
tuyguntn
> It can benefit stock prices for companies too, since it can cause the market
> to move more in their direction

which can also harm companies if algorithms decide to sell, which might
trigger sell chain for everyone

------
kevinwang
Any highlights or summarizations?

~~~
faitswulff
Haven't read it, but there's a summary section in the attached PDF on page 69.

------
bitxbit
The algos being talked about here do not add true liquidity. The fact that
over 2/3 of investable wealth is parked in passive funds would suggest there’s
not a lot of trading being done (2020 craze excepted). Therefore, what’s
happened in the past decade is artificial liquidity with very sharp unexpected
moves. Some of the biggest algos I’ve seen proliferate and capture exactly
this phenomenon. Started in 2015 with year ends being targeted (see 2018, 2019
and 2020). Of course, the pandemic unleashed a different beast altogether.

~~~
gpderetta
those passive funds still need to continuously rebalance their holdings.

