The Research HUB: Intraday Trading Primer
How To Run Intraday Trades and Build Intraday Models
Hey everyone,
This article is going to be an educational primer on intraday trading. You will notice that I have written primers on the S&P500 (link), bonds (link), and FX (link), BEFORE this one. This is intentional because understanding the big picture is a prerequisite.
Intraday trading is the most difficult timeframe to operate on unless you have a very very clear advantage. The problem is that intraday trading is marketed to the retail community as THE way to make money. On top of this, intraday trading is almost always framed incorrectly because people typically focus on some type of rule or setup instead of understanding HOW liquidity provision works on an intraday timeframe.
What do I mean by this? Well think about it like this, I might have some type of rule that is great at executing trades and extracting returns. However, if I only know that rule and not HOW the system works or WHY that rule works, then eventually I will lose my edge. The market doesn’t operate according to the rules you might employ for execution and trading. Those rules are the process by which you maneuver the uncertainty of markets, NOT how they operate.
For example, you might have a moving average crossover or a specific % pullback that you use as a signal for taking action. While this might work in a backtest and maybe even on a forward-looking basis, the rule doesn’t dictate what the market is supposed to do.
This is where Soros basically got his fame. His whole idea was not finding rules to make money but identifying when the rules changed.
Let me share a tangible example of an intraday edge that eventually faded. Earlier this year, we saw 0dte option flow have a significant impact on intraday price action, especially if we had a large deviation before lunchtime that went to an open interest level. Basically, if there was a large deviation on the upside or downside to a large open interest level where a lot of 0dte volume was taking place, I would basically fade the move. Eventually, this type of characteristic disappeared and the strategy began to lose money.
If your ability is connected to a single scenario or rule, it will eventually fade. This is why you need to have a correct understanding of the liquidity provision mechanics in the market so that you can adapt to the market correctly.
In the first article, I explained this process (link):
Also, refer to the article on risk on risk off regimes for further elaboration on this:
In this article, we are going to break down the following:
Intraday Liquidity Provision Theory
Players and Timeframes
Pure Price Actions and Information Tension
Building Blocks For Quantifying Intraday Price Action
Options Flow
Intro:
Instead of starting with, “Look for x type of pattern to get long or short,” we want to start by examining the underlying mechanics of the market and its microstructure that both cause patterns and change them.
Knowing the WHY behind specific price action characteristics, allows you to build views/strategies that have durability. Blindly following “statistical facts” is a sure way to get into trouble when the rules of the game change. It goes back to that famous poker quote:
Look Around the Poker Table; If You Can’t See the Sucker, You’re It
Intraday Liquidity Provision Theory:
We are going to start partially on a theoretical note and go over some principles of liquidity:
Why does the price even move?
Fundamentally, the price of any asset moves because there ISN’T liquidity for the bid or the ask. For example, if the S&P500 is moving up, it is because there are more buyers than sellers. However, it is that the buyers need to move the price higher in order to get filled by more sellers.
When I think about price, it moves because there isn’t enough liquidity to satisfy the buyers or sellers. Theoretically, market participants don’t need to move the price to get their orders filled IF a player on the opposite side comes in with a comparable-sized order.
You might have seen this before in markets where the price is pinned at a specific level and a large number of transactions get run through as volume spikes. Basically, two or more players find an agreed-upon price and enough size to transact against so that the price doesn’t need to move dramatically (obviously this doesn’t last for long).
This type of dynamic is the opposite of a situation where a player must move the price to obtain liquidity (from this book):
Big picture, when I think about buyers and sellers, both need to either transact against the opposite in comparable size OR move the price until they get their fill. A lot of the intraday moves we see function as the liquidity provision mechanism for this.
Liquidity and Time:
The limitation of this theory is that execution and liquidity in the market don’t function in a linear and smooth fashion. This is part of the reason noise exists in markets. Liquidity is never evenly distributed through time.
This makes intuitive sense. Sometimes you might see a very smooth intraday trend in the price of an asset only to be slammed down by a huge sell order.
Understanding these ideas of price, volume, liquidity and time will be key when we begin to quantify the periods of time for optimal execution during the day.
Shadow On The Wall:
The final part of theory I want to touch on is that the price action and volume we see are only a reflection of the true underlying supply and demand components. While all of our P&L is ultimately denominated in the price, there is a lot more going on under the surface that is unseen.
More Resources:
If you want to spend more time understanding the microstructure and mechanics of the market in this shorter-term timeframe, check out the following resources:
Trades, Quotes and Prices Book. Amazing book!
The following papers:
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2668277
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=488422
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1712822
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2549739
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2878945
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=569982
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1913982
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4259584
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3900141
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2852760
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3305277
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3687746
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1127744
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3551166
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=675665
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=741365
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3479741
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=965674
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3497001
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=241728
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=988886
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1342228
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1787625
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1373762
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3714230
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=229959
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2996221
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4320775
https://www.smallake.kr/wp-content/uploads/2015/11/SSRN-id2668277.pdf
https://ericbudish.org/wp-content/uploads/2022/06/Flow-Trading-June-23-2022.pdf
https://www.researchgate.net/publication/314510860_Effects_of_the_Limit_Order_Book_on_Price_Dynamics
https://www.readcube.com/articles/10.2139%2Fssrn.1914293
https://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=3209&context=open_access_dissertations
https://hal.science/hal-00397652v3/document
https://epubs.siam.org/doi/10.1137/130911196
https://hughchristensen.com/papers/academic_papers/SSRN-id1499209.pdf
https://www.hindawi.com/journals/sp/2021/9949565/
https://www.nber.org/system/files/working_papers/w25855/w25855.pdf
https://mpra.ub.uni-muenchen.de/101684/2/MPRA_paper_101684.pdf
http://tesi.luiss.it/27169/1/701851_PECCHIARI_MATTEO.pdf
https://edoc.hu-berlin.de/bitstream/handle/18452/4997/57.pdf?sequence=1
https://hughchristensen.com/papers/academic_papers/SSRN-id1433488.pdf
https://www.sciencegate.app/document/10.2139/ssrn.2022650
https://www.tse-fr.eu/sites/default/files/medias/doc/wp/fit/10-147.pdf
https://www.unibocconi.eu/wps/wcm/connect/aff80f23-9082-4c33-8bba-5399f2c01efb/rindi.pdf?MOD=AJPERES
https://sciendo.com/article/10.2478/fiqf-2020-0004?tab=references
https://arxiv.org/pdf/1312.3349.pdf
https://davidpublisher.com/Public/uploads/Contribute/5b1a2dbbe1a79.pdf
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1108485
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1108485
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=459000
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2238087
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=956476
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1997092
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=676564
https://onlinelibrary.wiley.com/doi/10.1111/agec.12642
https://www.researchgate.net/publication/228469567_Optimal_display_of_iceberg_orders
https://link.springer.com/article/10.1007/s10436-017-0304-1
https://www.researchgate.net/publication/228261446_Optimal_Dipslay_of_Iceberg_Orders
https://openaccess.city.ac.uk/id/eprint/17333/14/10.1007%252Fs10436-017-0304-1.pdf
https://www.readcube.com/articles/10.2139%2Fssrn.3074049
http://fmwww.bc.edu/repec/esLATM04/up.23536.1081939804.pdf
https://www.econstor.eu/bitstream/10419/266836/1/1100.pdf
If you want to look into the specific types of limit order book dynamics that the resources above reference, look into Trading Technologies . They have some great resources on their website.
Players and Timeframes:
Being aware of the players and their respective timeframes is one of the most crucial evaluations you can perform when identifying if you even have an advantage intraday.
While there isn’t always a clear distinction between players, generally speaking, you have the HFT players, Stat Arb players, market makers, and then institutional players seeking liquidity for longer-term views/constraints.
If you have no clear informational edge, then you’re basically set up to lose if you compete against the HFT or Stat Arb guys. What does this mean practically? If you are trading on a 5-minute time horizon, it is HIGHLY unlikely you will consistently make money.
Let me provide an example. This is from Machine Learning for Asset Managers (Elements in Quantitative Finance)
Think about the types of models and strategies a firm is running in order to accomplish this type of trade. It is WAY MORE complex than using some moving averages and technical levels.
What Is The Implication?
The main idea here is that if you are trading on an intraday timeframe where you are trying to take advantage of moves on a 5-minute-15-minute chart, you’re against people who have a significant informational advantage and speed advantage against you.
It is not about “working harder” here. Unless you have access to the same degree of tools and speed, it will ultimately be like a kindergartener playing 1-on-1 against Shaquille O'Neal.
Now this is the question we finally come to. If you don’t have an advantage against these players, how in the world can you make money on a shorter timeframe? This is what the rest of the article lays out.
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