#UNITEDSPIRITS May outperform big time against #CNXFMCG (FMCG index) https://t.co/6xGk0dg5M8

5 star RSI Strategy by @VishalMalkan

Unconventional approach of 60-40 RSI and range shift concept.

According to him,
whenever the market is bearish,
it won’t be able to cross 60,
and whenever in a bullish trend,
it won’t be able to cross 40.

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So, instead of the 70-30 Relative Strength Index,
we will use the 60-40 range for the RSI indicator for this strategy.

When the
Monthly and Weekly RSI>60,
& when the RSI takes support at 40 in the daily chart,
it may bounce back and most probably it will not go below 40.

If a bullish candle is formed at the 40 RSI level,
the prices may bounce back, and one can enter the stock.

The stoploss can be placed at the low of that bullish candlestick,
and the target can be the 60 RSI level.

When the
Monthly and Weekly RSI<40,
& when the RSI takes resistance at 60 in the daily chart,
it may bounce back and most probably it will not go above 60

If a bearish candle is formed at the 60 RSI level,
the prices may bounce back from there, & 1 can enter the stock 4 shorting

The stoploss can be placed at the high of that bearish candlestick, and the target can be the 40 RSI levels.

#banknifty

This range shift concept can be applied in any timeframe,
whether intraday, daily,weekly, etc.

The chorus of this song uses the shlokas taken from Sundarkand of Ramayana.

It is a series of Sanskrit shlokas recited by Jambavant to Hanuman to remind Him of his true potential.

1. धीवर प्रसार शौर्य भरा: The brave persevering one, your bravery is taking you forward.

2. उतसारा स्थिरा घम्भीरा: The one who is leaping higher and higher, who is firm and stable and seriously determined.

3. ुग्रामा असामा शौर्या भावा: He is strong, and without an equal in the ability/mentality to fight

4. रौद्रमा नवा भीतिर्मा: His anger will cause new fears in his foes.

5.विजिटरीपुरु धीरधारा, कलोथरा शिखरा कठोरा: This is a complex expression seen only in Indic language poetry. The poet is stating that Shivudu is experiencing the intensity of climbing a tough peak, and likening

it to the feeling in a hard battle, when you see your enemy defeated, and blood flowing like a rivulet. This is classical Veera rasa.

6.कुलकु थारथिलीथा गम्भीरा, जाया विराट वीरा: His rough body itself is like a sharp weapon (because he is determined to win). Hail this complete

hero of the world.

7.विलयगागनथाला भिकारा, गरज्जद्धरा गारा: The hero is destructive in the air/sky as well (because he can leap at an enemy from a great height). He can defeat the enemy (simply) with his fearsome roar of war.

What Happened To Bhakt Prahlad after Hiranyakashipu Vadh
#Thread
Prahlada became the mighty king of the Asuras after Shri Narsimha killed Hiranyakashipu. Prahlada was even more powerful than his father, Hiranyakashipu ever was. He enjoyed the love and respect of his subjects.

By virtue of his good behaviour, Prahlada conquered the three worlds easily and Indra ran away from the Heavens. Indra then deceived Prahlada into giving him the power of his behaviour and Prahlada lost control of the three worlds.

Asuras grew angry at the Devas for taking advantage of their King's virtuous behaviour and invaded the heavens. The Devas, afraid of the Asuras, enlisted the help of human Kings such as Yayati, Raji and Kakutstha and defeated them.

Prahlada attacked the gods and defeated Indra in battle, forcing the King of the Gods to run for his life. Indra sought help of Lord Vishnu. Infused with his power, Indra defeated Prahlada. The latter understood that Vishnu was helping Indra in battle and he withdrew his forces.

Prahlada first gave his kingdom to Andhaka, but the latter was defeated by Shiva. So Prahlada gave it to his son Virochana and undertook a Tirtha Yatra.

Shocking fact: Millennial men are less likely to work than any other age and gender demographic in America.

Today, there are 500,000 young men missing from the U.S. workforce.

Research suggests video games & improved leisure tech plays a role in the problem. 👇 Thread:

Following the 2007 to 2009 recession, 25 to 34 year old men exited high school with fewer middle-skill job opportunities than years prior.

During this time, we saw an increased number of men living with parents & choosing unemployment over lower paying jobs.

It's estimated that 24M millennials live w/ their parents.

1 in 4 living in their parents’ home neither go to school nor work.

What's more surprising? 9 in 10 who lived with their parents a year ago are still living there w/ no plans to leave.

Economists are calling millennial men a lost generation.

According to economist David Dorn:

“If you get to the point where you’re turning 30, you’ve never held a real job and you don’t have a college education, then it is very hard to recover at that point.”

Economists suggest this choosiness is a generational trait.

Forbes interview w/ a high school educated man:

"I’m very quick to get frustrated when people refuse to pay me what I’m worth."
“People feel that they have choice nowadays, and they

Important paper from Google on large batch optimization. They do impressively careful experiments measuring # iterations needed to achieve target validation error at various batch sizes. The main "surprise" is the lack of surprises. [thread]

https://t.co/7QIx5CFdfJ

The paper is a good example of lots of elements of good experimental design. They validate their metric by showing lots of variants give consistent results. They tune hyperparamters separately for each condition, check that optimum isn't at the endpoints, and measure sensitivity.

They have separate experiments where the hold fixed # iterations and # epochs, which (as they explain) measure very different things. They avoid confounds, such as batch norm's artificial dependence between batch size and regularization strength.

When the experiments are done carefully enough, the results are remarkably consistent between different datasets and architectures. Qualitatively, MNIST behaves just like ImageNet.

Importantly, they don't find any evidence for a "sharp/flat optima" effect whereby better optimization leads to worse final results. They have a good discussion of experimental artifacts/confounds in past papers where such effects were reported.