MOLDTKPAC

Double Top Buy & T20 Pattern - Bullish triggered above 542.41 daily close on 3% Box Size chart.

1. There are more people added on the list of arrests and executions of famous people but no further intel is available at this time.

ARRESTS and EXECUTIONS OF FAMOUS PEOPLE 2020 UPDATED
Explanation of the latest military tribunal arrests and executions of famous people in 2020.

2. The tribunals are arresting these people in plain clothes. We saw the Obama’s arrest, although we didn’t know it was an arrest at the time. The arrest was done nonchalantly so as to not get noticed by the public.
All arrests of these famous people were done this way.

3. If the person is convicted of child sex trafficking, crimes against humanity or treason, they will be executed.
If the person arrested has evidence on someone else to help their prosecution, or is willing to help Trump, & they want to cooperate, they may be allowed to do so.

4. A sentence of execution down to life in prison may be accepted if their evidence is worth anything.
When a plea deal is done, the defendant must present evidence they have to make their sentence lighter. This information is given to the prosecution, defense, and to the judge.

5. If evidence is accepted, they are presented the plea deal. They will have to make a guilty plea to the crime with a video confession & written statement. That is how all plea deals work.

All famous people arrested were either treasonous or involved in satanic worship rituals.

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.

Low-risk, High-return stocks are what we look for relentlessly

But many of them we know but ignore
some of them don't grab financial headlines

Here are 10 low-risk, high return stocks (that we ignore):

What I mean by “high-return”?

These stocks have OUTPERFORMED the market:

💹Chart with upwards trend Since IPO
💹Chart with upwards trend Over the last 5 Years or since IPO

These are all long-term winners that will keep on winning

What do We Mean by “low-risk”?

A combination of:

❣️Great management
❣️Broad moat
❣️Financially strong
❣️High ROCE
❣️Low Disruption/Dilution/Volatility
❣️Consistent Organic Growth
❣️Assorted Customers/Suppliers
❣️Low debt

1-#CDSL

A depository is a big business and will grow continuously, Its a sustainable business
cause "Market hai toh CDSL bhi hai or rahega"

2- #Dixon

High Management Efficiency with a high ROE of 19.30%
Healthy long-term growth as Net Sales has grown by an annual rate of more than 30%
High Institutional Holdings