After a lot of procrastination and preparation, I finally dug out my old trading-theory notes and trading-algo drafts and wrote Part 2 of my series on futures trading methodology…
In Part 1, I laid out the mathematical structure of
$ES,
$NQ and
$VIX futures and how they work.
The new post, part 2 goes from reading a volume profile all the way to a working order:
- What volume and TPO profiles actually measure, and what they don't: traded volume is not order-book liquidity
- How to read the open and the developing auction: prior value, the first 15 minutes, the opening price as the intraday pivot, and the 4 classic opening sequences
- How to scale entries, stops and targets to the day's realized volatility instead of fixed point distances
- 3 precisely defined entry models: a failed excursion back into value, continuation away from value (including going with an opening drive), and expansion from an intraday balance
- A real September 23 ES short, step by step: confirmation, entry, position sizing from the worst permitted fill, execution in IBKR, and 2 different exit policies from the same entry, showing why the exit matters as much as the entry
- And the part most people skip: how little a single winning trade proves, how many trades a track record really needs, and how execution costs quietly eat a "good" reward-to-risk ratio
Along the way I walk through the implementation of my 2 TradingView indicators, HTF Lvls (completed-period POC, value area and VWAP levels) and RV (intraday realized volatility and its rank), including the math behind them and their blind spots.
The rules are a frame, not a machine. They are precise enough to test and log, but meant to discipline judgment, not to replace it.
In the next part, I'll move from the profile to the swing, talking about the 3/10 oscillator, first crosses and divergences across time frames, the rhythm of buy, sell and sell-short days, classic setups (Holy Grail, three-bar triangle, pinball, failure tests), extended runs, market internals (TICK, breadth, volume), and trade management: initial stops, scaling out, runners and re-entry.
And I'll finish it with the practical implementation of the implied probability distribution that I discovered how one can distract from market and positioning datas as the only forward-looking model based on factual datas.
All of it the way I once learned it from my mentors, one of whom appears in the Market Wizards series.
Enjoy the read, and happy learning!
Warmly,
~A❤️