Some Simple Rules for Option Buying Setup!

You can change them as per your comfort.

1/
Hello, my name is Gal,
I am an Israeli citizen, and I want to convey this urgent message to the world: Contrary to what you are told, Israel has not "returned to normal" in any way >>

2/ Moreover, despite the desire to create a setting as if there was a full and normal routine here - the Israeli Ministry of Health JUST RECOMMENDED TODAY TO EXTENT THE DECLARATION OF A “STATE OF EMERGENCY” in Israel >>

3/ to which is the foundation for coercion, violation of basic rights, severe discrimination under a "green mark (pass)", prolonged closure (Of about 5 months overall) and a lot of undemocratic and not “routine" restrictions. >

4/ If the situation in Israel had "returned to routine thanks to the astounding success of vaccines" then the "state of emergency" would not have continued.

5/ In fact, since the beginning of the "vaccination project" there has been only more intimidation and in many ways - even though the closure has been lifted, much more coercion.

🧵EMA + VWAP STRATEGY

Every trader has a go-to strategy that works best for them. My trading is all about keeping it simple stupid and revolves around two indicators - Exponential moving averages and vwap.

Here's the strategy that I utilize on nearly 80% of my trades.

👇

What are Exponential Moving Averages?

EMA's are a type of moving average that places a greater weight on more recent data points.

8EMA = Exponential Moving Averages of the last 8 candle closing prices.

EMA's adjust with respect to chart time frame.

What is VWAP?

Volume Weighted Average Price - A key intraday indicator in my trading that offers the true average price based on price & volume.

Calculation: (Price x # of shares traded) / total shares traded

EMA's I use

- 8
- 21
- 50

While I do utilize the 50EMA, the 8 & 21 EMA are most important for this strategy. Some people use the 9 and 20 which are essentially the same thing. REMEMBER: EMA'S adjust with respect to time frames.

A+ Set Up Criteria - (What I look for)

ANTARVEDI LAKSHMI NARASIMHA SWAMY, EAST GODAVARI DIST.(AP)

Located where Vasistha Godavari joins Bay of Bengal.

Present structure was built by Kapanati Krishnamma of Agnikula Kshatriya clan in 1823.

It is one of the oldest among 32 Narasimha Kshetras in AP.
@LostTemple7

Legend says that here Maharishi Vasishta prayed to Narasimha to end the demon Rakta Vilochana.

Narasimha created Maha Maya, also called Ashwaroodambika or Gurralakka to suck his blood as he got a boon from Brahma that blood falling from his body would produce another demon.

After his death, the stream of blood was let out by Maya to form a pond called Rakta Kulya.

Narasimha,then,washed Sudarshan Chakra at a place called Chakra Tirtha.

Brahma is said to have performed Yagna and installed Shiva Linga here. Hence the place was called Antarvedi.

Later Sri Rama prayed here and Arjun also visited here.

Panchamrita Abhishekam is done every day.
One can have Nijarupa Darshanam (main murti without any decorative shield) between 6.00 a.m. and 8.00 a.m.

Anna Prasadam is very famous and distributed daily from 10:30 to 2 pm.

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.