People DM me asking what it takes to be that top 5% successful day trader
I always refer to 5 dimension trading techniques, never published anywhere: Now you have it.
1st Dim: Price action 15M with volume - chart analysis, pattern recognition, trend analysis, major S/R levels
Jim's 2 books on Market profiles - must read for anybody who is serious about day-trading as well as swing trading.
Great tools to spot the large institutional trading fingerprint & intentions, combining with volume profile would pinpoint perfect intraday S/R
It would take about at least 1 year screen time to paper trade profitably before trading the real account.
So, please do not ask me about which tools are better. Actually, I have no idea.
However, I have followed #ticktool for a while, it seemed to be a good starting point
Absolutely not promoting anything, just answer some DM questions
Hint: Liquidity Moves Market
Below is an important old post about what moves the market?
We have talked about the Sentiment extremes moves market, evidenced by the extreme Fear to extreme Greed $VIX Mean Reversion strategy (see pinned posts)
The MMs, large institutions, hedge funds & speculators all trying to make the most liquidity in the market to work in their favor.
Some fading the crowd, liquidity hunting all day, fake break-outs and break-downs etc. dis/acc
https://t.co/LwlRbXzS88
I need to make one thing clear
— Kerberos007 (@kerberos007) April 13, 2019
1 Your bias, market blogs, commentaries, forums, market gurus, tweets, divergences etc CANNOT move price in any direction
2 Liquidity, sentiments & bid/ask volume made by market participants move market
3 $VIX strategy trades sentiment extremes
And what is the easiest way to find the most liquidity in the market?
1 - Major S/R levels - including trend-line, month/week/daily MP and Fib lvls.
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Keep dwelling on this:
Further Examination of the Motif near PRRA Reveals Close Structural Similarity to the SEB Superantigen as well as Sequence Similarities to Neurotoxins and a Viral SAg.
The insertion PRRA together with 7 sequentially preceding residues & succeeding R685 (conserved in β-CoVs) form a motif, Y674QTQTNSPRRAR685, homologous to those of neurotoxins from Ophiophagus (cobra) and Bungarus genera, as well as neurotoxin-like regions from three RABV strains
(20) (Fig. 2D). We further noticed that the same segment bears close similarity to the HIV-1 glycoprotein gp120 SAg motif F164 to V174.
https://t.co/EwwJOSa8RK
In (B), the segment S680PPRAR685 including the PRRA insert and highly conserved cleavage site *R685* is shown in van der Waals representation (black labels) and nearby CDR residues of the TCRVβ domain are labeled in blue/white
https://t.co/BsY8BAIzDa
Sequence Identity %
https://t.co/BsY8BAIzDa
Y674 - QTQTNSPRRA - R685
Similar to neurotoxins from Ophiophagus (cobra) & Bungarus genera & neurotoxin-like regions from three RABV strains
T678 - NSPRRA- R685
Superantigenic core, consistently aligned against bacterial or viral SAgs
Further Examination of the Motif near PRRA Reveals Close Structural Similarity to the SEB Superantigen as well as Sequence Similarities to Neurotoxins and a Viral SAg.
The insertion PRRA together with 7 sequentially preceding residues & succeeding R685 (conserved in β-CoVs) form a motif, Y674QTQTNSPRRAR685, homologous to those of neurotoxins from Ophiophagus (cobra) and Bungarus genera, as well as neurotoxin-like regions from three RABV strains
(20) (Fig. 2D). We further noticed that the same segment bears close similarity to the HIV-1 glycoprotein gp120 SAg motif F164 to V174.
https://t.co/EwwJOSa8RK
In (B), the segment S680PPRAR685 including the PRRA insert and highly conserved cleavage site *R685* is shown in van der Waals representation (black labels) and nearby CDR residues of the TCRVβ domain are labeled in blue/white
https://t.co/BsY8BAIzDa
Sequence Identity %
https://t.co/BsY8BAIzDa
Y674 - QTQTNSPRRA - R685
Similar to neurotoxins from Ophiophagus (cobra) & Bungarus genera & neurotoxin-like regions from three RABV strains
T678 - NSPRRA- R685
Superantigenic core, consistently aligned against bacterial or viral SAgs
1/OK, data mystery time.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
This New York Times feature shows China with a Gini Index of less than 30, which would make it more equal than Canada, France, or the Netherlands. https://t.co/g3Sv6DZTDE
That's weird. Income inequality in China is legendary.
Let's check this number.
2/The New York Times cites the World Bank's recent report, "Fair Progress? Economic Mobility across Generations Around the World".
The report is available here:
3/The World Bank report has a graph in which it appears to show the same value for China's Gini - under 0.3.
The graph cites the World Development Indicators as its source for the income inequality data.
4/The World Development Indicators are available at the World Bank's website.
Here's the Gini index: https://t.co/MvylQzpX6A
It looks as if the latest estimate for China's Gini is 42.2.
That estimate is from 2012.
5/A Gini of 42.2 would put China in the same neighborhood as the U.S., whose Gini was estimated at 41 in 2013.
I can't find the <30 number anywhere. The only other estimate in the tables for China is from 2008, when it was estimated at 42.8.
