- Published on
CME Group Futures Spec Visualized
- Authors
- Name
- Teddy Xinyuan Chen
I trade the 3 major indexes, and I need to choose the proper instrument when opportunities present themselves.
Futures are great if you're confident in your trade - if you think it's high probability, by no means, choose them. They provide extreme leverage, one /ES contract let you swing 300k capital with just 16k margin. 1% move in the index translates to 3k profit or loss. Such large contract calls for more stringent risk management (or make sure you have enough capital to weather the storm and for the S&P to recover).
If not using futures, other options include the index ETFs and the leveraged versions of them (SPXL/UPRO, TQQQ, TNA, for intraday trades), and straight options on them.
If using leveraged ETFs (shares or options), slippage and spread are also a concern. Besides that, commissions and fees on futures and options also need to be considered.
In my private note I've calculated the required capital for the same exposure for each index - contact me if you're interested.
This page shows how some of the popular contracts compare to each other in terms of notional value, capital efficiency and more. It helps me understand how large the contracts are, how large is 1 tick relative to the notional value, and the volatility and risks associated with them.
Go to this Datasette instance to see the full data or run more analysis.
Table of Contents
Links
- Datasette (play with and download data here): https://tastytrade-futures-spec.teddysc.me/tastytrade-futures-spec/futures
- Update to date CME product specs: https://www.cmegroup.com/markets/products.html (it's a handful)
- Source code (Jupyter notebook and Plotly HTMLs): https://gist.github.com/tddschn/eb93439f3e50674b2cfdf5f094f3ec28
Visualizations
Color coded by the category of the contract. Hover over the bars to see more details.
If the iframe doesn't load correctly, click on "Full Screen" - that usually works.
For calculating notional value, the close price used are from 2024-11-01 (SPX dipped to near SMA 50 on this day - we're in earnings season and the week before election results come out) from Yahoo Finance.
Contract Notional Values
Before plotting this I thought /BTC was the largest contract (it has enormous tick value and margin requirement), but it's slightly smaller than /NQ as of 11/1/2024 - BTC's pull back was much deeper than the equity market.
It's amazing how small the agricultural contracts (on the right) are compared to index futures. Forex and energy too. /GC is pretty large, but other metals are much smaller.
The Micro Ether (/MET) is so so small - I wonder who that's for.
Overnight Margins
Y is on log scale. Micros are usually 1/10 of the regular contract (10 /VXM = 1 /VX).
Margin to Notional Ratio (Capital Efficiency)
The "most liquid" 3 month SOFR futures (/SR3) has a ridiculous low margin to notional ratio of ~1/1000 (you controlls 1 million with 1 thousand dollars).
/RTY can be very volatile sometimes, rallying pre-market only to drop like a stone at the open. The higher margin to notional ratio is justtified IMO.
/RTY sell off on 2024-10-21 at market open, while the S and Q were having an extremely good morning until 10:20 - they continued pre-market rally like VWAP wasn't there. /RTY dropped 42.5 points in 2 hours, if you were long and did nothing, you'd be down $2,125 per contract. :)
Notional ATR14
14 day Average True Range (ATR) is a measure of volatility. It's the "average" of the daily ranges over the last 14 days.
Notional ATR14 = ATR14 * Full Point Multiplier
Y is on log scale.
Although /BTC is roughly as same size (notional value) as /NQ, it moves twice as much. 1 contract of /BTC gives you exposure to 5 bitcoins, and an average daily change in notional value of 12.7K.
Some futures traders dislike /ES for how slow it moves, but it still moves decently large (3k a day). Plus it has less wicking than /NQ.
atr14 = talib.ATR(data["High"], data["Low"], data["Close"], timeperiod=14).iloc[
-1
]
# https://ta-lib.org/functions/
ATR14 %
ATR14 / Close price as percentages.
Energy (natrual gas and crude oil) moves relatively more compared to BTC. Metals are more tamed.
Surprisingly, the least diversified price-weighted Dow futures /YM is the most tamed of the indexes - this is also reflected below in the Margin Requirement to Notional Value comparison below.
Margin to Notional ATR14 Ratio (True Capital Efficiency)
Notional ATR14 = ATR14 * Full Point Multiplier
df["margin-atr14-ratio"] = df["Overnight Requirement"] / df["notional-atr14"]
At a glance, /NQ and /RTY are more capital efficient than /ES, but they are more volatile and harder to trade.
Margin/Notional to ATR14-%
df["margin/notional to atr14-%"] = df[f"margin/notional-{date_today_yyyy_mm_dd}"] / df["atr14-%"]
I'm not sure how to interpret this complex ratio.
Tick Value to Notional Ratio
/ZB and /UB are fun.
Exchange Fee to Notional Ratio
Pretty useless ratio, just to see if there's a pattern.