Luckshury Profile picture
Aug 7, 2023 11 tweets 3 min read Read on X
Forming a Daily Bias

a thread 🧵 Image
In this thread, I will cover the following:

- 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) Image
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 Image
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. Image
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. Image
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. Image
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. Image
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
hope you found this valuable, likes and retweets are appreciated

Let me know below what thread you would like to see next 👇

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More from @Luckshuryy

May 16
footprint charts (a complete guide)

a thread 🧵 Image
footprint vs regular charts:

footprint charts are a cleaner visual of the time & sales data.

it places buy/sell info on a per cluster basis, inside the candle.

doing this allows for easier identification of high volume/delta zones, absorption & trapped traders. Image
tick sizes:

inside the footprint, the cluster is divided into price blocks. Changing the tick size changes the granularity of these price blocks within each cluster.

larger tick size for increased volatility, lower the tick size when less volatile. Image
Read 7 tweets
May 1
market sessions: a complete guide

a thread 🧵 Image
Asia (00-06)

I tend to treat it as a mini "monday range" but for intra-day purposes.

It's initial break of range can be a good indication as for the rest of days direction, similar to monday range.

Break one side of the range and it protects the other side of it.

example ↓ Image
London (06-12)

my favourite session to gain a bias off.

1 - london puts in the daily high/low
2 - price moves against it (running stops)
3 - buy where people exit the market
4 - target london pivot being taken out

example ↓ Image
Read 7 tweets
Apr 23
naked point of control (nPOC)

a thread 🧵 Image
what are npocs:

point of control - where the most volume has occurred within a given volume profile.

naked poc - means it is yet to be revisited and left untapped.

npocs are most commonly "left untapped" due to trending moves pushing away from an area of value. Image
time-based npocs:

npocs are most commonly used across daily, weekly, and monthly timeframes, mostly used for medium/high timeframe reactions.

I recommend for lower time frames marking 15m/30m npocs, when used in confluence, can act as good intra-day levels for mean reversion setups.

example ↓Image
Read 6 tweets
Apr 11
monday range: a complete guide

a thread 🧵 Image
what is monday range?

using the high/low of monday as a anchor to form a bias for the remainder of the week.

marking this out from tuesday morning is the most common practice and what I would recommend.

- sweeps
- clean breaks

both used to form bias from tuesday onwards. Image
sweeps:

sweeps above/below monday range can be an early sign of mean reversion to the opposite side of monday range.

identifying new longs being caught offside above/below can be an early indication of this.

check:

- open interest (increasing)
- delta increasing (if above)
- delta decreasing (if below)

if price sees acceptance back into monday range, traders are offside and push price back to the opposite side of mondays range.

example ↓Image
Read 6 tweets
Mar 24
vwap: a complete guide

a thread 🧵 Image
what is vwap:

(volume weighted average price)

most commonly calculated through averaging the high, low & close.

helps determine who is in control, buyers or sellers.

price above vwap = buyers in control
price below vwap = sellers in control

vwap = fair value

example ↓ Image
time-based vwap:

the most common vwap is time-based resetting at the daily open of each day.

I find time-based vwaps to be most useful after some time has been spent away from the vwap before reverting back towards it for a reaction.

note - weekly/monthly vwaps can also be used in the exact same manner just through higher timeframes.

example ↓Image
Read 8 tweets
Mar 9
open interest (simplified):

a thread 🧵 Image
open interest vs price:

price ↑ with positive OI: New longs pushing price up
price ↑ with negative OI: Shorts getting squeezed

price ↓ with positive OI: New shorts pushing price up
price ↓ with negative OI: Longs getting squeezed

when new positions, whether long or short, drive price, they add the dynamic that if pushed offside, price can squeeze in the opposite direction.

example - new shorts pushing price ↓Image
early positions:

positions opening too early, can be a good reason for trend continuation, hence I will not fade a move prematurely if oi rises too quickly.

when new positions open too eagerly it creates new stops either above or below the continuation pivot.

example ↓ Image
Read 7 tweets

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