- some MS points
- using stats to help my bias
- directional bias through liquidity
market structure
2 timeframes
- 1h
- 15m
(depending on the type of trader you are)
uptrending
downtrending
rangebound
identifying swing points can be done either using manual lookback or via williams fractal indicator (set to 2 on either side of the swing high)
market structure (2)
notes -
majority of the time price will be within the "rangebound" category.
breaking that "rangebound" environment then deciphers the trending move you are given
high hit rate levels
- level(s) that reset after a certain period (generally daily) which gives me some form of directional bias whether they are below or above price when printed.
high hit rate levels (2)
confluence
the most powerful thing is to use this with is Market structure, below is an exact example of how I would do so.
on a day as such my directional bias would be to look for longs.
liquidity
resting liquidity is important
if I see there is more resting liquidity on one end of a range over another I would favour that direction for my bias.
poor highs/lows
routine check - simply I check my 50tick BTC/USD TPO chart
if there are more than 2 or more blocks at either a high/low then i classify that as a poor H/L
This is typically part of my liquidity routine and these levels have a higher likelihood of being tested.
combination
resting liquidity - below price
high hit rate level - below price
poor highs/lows - below price
I would be favoring shorts that day
and visa versa
finding high hit rate levels
in the future, I will share some of mine, currently they do give me too much of an edge to release
what I suggest is to think about levels you generally feel would be revisited then put the work in and get direct figures on a trial-and-error basis
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total number of outstanding derivative contracts not yet settled.
for every buy there is a sell, but not every buy is a new long and not every sell is a new short.
short close = buy
long close = sell
open interest increases when both sides are opening.
open interest indicator:
when plotted as an indicator below price its particularly helpful for spotting:
> new traders becoming offside
> traders opening positions early
> positional squeezes
more importantly, when watching key areas, watching how open interest reacts as you probe certain levels, such as range highs/lows.
one of my favourites is watching new positions rapidly join in minor bounces as price is in free fall, you see them instantly regret this as momentum continues against them and are forced to close.
stop orders/triggers ā triggered at market and most of the time forced with someone being forced out the market (stopped out).
note - pattern/breakout traders in general can also use trigger orders to buy/sell the breakout.
footprint charts:
displays ONLY market orders.
most common setups is to see market sells on the left with market buys on the right ā bid-ask profile
I find footprints the best for spotting absorption or exhaustion in the markets as they display already transacted data.
i.e when you see lots of sell orders at the same price level without price able to budge it is sufficient evidence to say limits are holding up price.
footprints do not have to be shown on time based charts only either, they are extremely useful when monitoring volume charts, delta charts or range bars, in particular on lower time frame equivalents.
tldr: footprints show a record of already transacted orders, unlike heatmaps displaying resting orders, which have the ability to be pulled/added to.
the naming is meaningless, the core fundamental behind it is that there is a piece of price which price moved quickly through (one candle), relative to the time frame you look at.
first touches:
when price initially revisits this void it can act as a level where:
1. stops are triggered 2. traders attempt to trader for the fill (anticipate a move)
the edge then comes from being able to spot these traders at this initial touch and fade them.