A simple Trading system with 2 #movingaverages 13 & 21Sma
What signal it gave today ?
"Sell triggered @ 17365 When 1st 15 min. candle
closed below 13 & 21Sma"
And, then #Nifty fell to 17267, almost 💯points
"Part Book"

More from Van Ilango (JustNifty)
Remembered it & made entry @ open for the "High rewarding 3rd wave"
Much appreciation🙏 to @ap_pune for his regular sharing of vital info. & wisdom from years of experience.
#auropharma "Hour t/f" for "Traders"
— Van Ilango (JustNifty) (@JustNifty) March 21, 2022
In search of the highly rewarding 2nd wave entry.
Today's & tomorrow's #priceaction would have more clarity for entry either @ 615-620 or above 655 https://t.co/20S0Lvc7ej pic.twitter.com/OFlf9MLkqz
His simple mechanical system of MACD multi t/f with 4 Hour setting seems to remove whipsaws & is producing amazing result with #Nifty
Experience speaks - you listen and adopt
Develop patience to wait for such good set up. Now trail your SL once price has gains https://t.co/jC8tcrZ0Cv

Book mark this and revisit every day or every week till you get it right as a trader. Coming from an experienced trader like @MaverickAmit01 , it's priceless.
— Van Ilango (JustNifty) (@JustNifty) July 31, 2021
Wish we had it when we started out.\U0001f64f https://t.co/0NYKqedy9w
#Elliottwave puts #PriceAction in it's context
— Van Ilango (JustNifty) (@JustNifty) December 2, 2021
You're 1 undisputed expert on prime source of everything, #PriceAction
Let beginner start with #PriceAction & then step up to 12345 & ABC
Baby steps alone will take to maturity
Read this book months ago - "Rich Experience shared"\U0001f64f https://t.co/VUbG6F5Ems pic.twitter.com/PProaFsMsV
More from Screeners
BTW Nifty Metal has inverse correlation with USDINR. https://t.co/X6cqVcYF3V

We know how our stock market has weathered the FII selling.
— Sandeep Kulkarni (@moneyworks4u_fa) June 10, 2022
But the equally big story is how Rupee has weathered $50bn+ outflows since Oct 2021. Hats off to RBI Governor Das & his team for having the vision of building huge reserves in his tenure. pic.twitter.com/CVuF9dM361
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Imagine for a moment the most obscurantist, jargon-filled, po-mo article the politically correct academy might produce. Pure SJW nonsense. Got it? Chances are you're imagining something like the infamous "Feminist Glaciology" article from a few years back.https://t.co/NRaWNREBvR pic.twitter.com/qtSFBYY80S
— Jeffrey Sachs (@JeffreyASachs) October 13, 2018
The article is, at heart, deeply weird, even essentialist. Here, for example, is the claim that proposing climate engineering is a "man" thing. Also a "man" thing: attempting to get distance from a topic, approaching it in a disinterested fashion.

Also a "man" thing—physical courage. (I guess, not quite: physical courage "co-constitutes" masculinist glaciology along with nationalism and colonialism.)

There's criticism of a New York Times article that talks about glaciology adventures, which makes a similar point.

At the heart of this chunk is the claim that glaciology excludes women because of a narrative of scientific objectivity and physical adventure. This is a strong claim! It's not enough to say, hey, sure, sounds good. Is it true?
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.