1/ If, after reading https://t.co/IzzATArtZl you are still confused how Alpha Homora and IronBank were hacked, here's how the hack was conceived

!!Decode/Thread (12/31/20)

Well this could be the LAST Decode/Thread of the Year ...

... Have a Happy and Safe New Years Eve ...

...

The Great Reset is a massively funded, desperately ambitious, internationally coordinated project led by some of the biggest multinational corporations and financial institutions on the planet.

Devised and put in motion by 0.0001% of people, who honestly believe this world and society need somekind of reset. You might also be wondering what are we resetting from/to as this new firmware is desperately trying to upload itself by another tsunami of mainstreamed propaganda.

One of the most obvious reasons for pushed reset is the infinite expansion economic model reaching its limits and going bust, a fact admitted even by themselves.

However, the super wealthy apparently want to continue staying super wealthy and have no intention of abandoning their position at the top of the world.

Nature’s resources found on Earth are definitely limited in their absolute quantity thus excluding an idea of infinite extraction and wealth accumulation. But this is not their understanding of limited resources, you see.

The most memorable interview I did this year was w/ Stanley Druckenmiller, who famously made $1B shorting the British Pound.

The trading legend's track record includes a 30-year stretch returning 30%+ a year (without a single down year).

Here are 8 investing lessons🧵

1/ Make concentrated bets in high conviction plays

2/ Concentrated bets can sometimes *reduce* risk

3/ Use a multi-disciplinary approach to investing

4/ Know when to sell (he never uses a stop loss)

A potential problem is looming, and the media are pursuing a new story that builds on the following chain of reasoning: 1) higher inflation is coming;2) if CBs increase interest rates debts will explode and recession may ensue; 3) CBs are caught in an impossible dilemma 1/12

It´s perhaps too complex for some tweets, but.. Registered inflation this year is bound to be higher than present forecasts, resulting from one-off price spikes and base effects That will not start a sustained high inflation process, but temporary higher inflation is possible 2/

For example, Euro Area inflation increased suddenly from several months at -0.3% to +0.9% in Jan. This jump resulted mostly from several base effects, especially the change to German VAT. Inflation expectations increasing but higher in the US than in the EA 3/

The major one-off base effect will come from oil prices that decreased abysmally in March 2020 and have recovered. Some estimates put US inflation in April reaching 4%! After vaccinations, later in the year, pent-up consumer demand will also increase prices.4/

Despite the increased spending of accumulated savings, the savings rate will remain higher than before Covid for precautionary reasons (Fig 1). No permanent spending spree will materialise. Wages will remain subdued for a while (Fig2). Higher but not high inflation is coming.5/

Nano Course On Python For Trading
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Module 3

In this post, I will attempt to teach you how to write an algorithm in python to automatically find support and resistance. We shall use the data we downloaded in module 2.

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To visualize price action, I have used the daily candlestick chart. To quantify the meaning of support and resistance, I have taken below definitions:
In a series of 5 continuous candles, if the first three candles make increasing high and then 2 decreasing highs, then the

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high of the third candle is considered resistance. Similarly, if the first 3 candles make lower lows and the next 2 make high lows then the low of the third candle is support.

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The above explanation is for the sake of quantifying support and resistance at a very basic level. These are called fractals. Now let's get started with the code.

mpl_finance is the new module here. We will use its candlestick_ohlc function.

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Now, if you remember, you downloaded data for nifty 50 stocks in module 2. We shall use that data. Let's work on ITC data this time.
We will use data from 1 Jan 2021 to 30 June 2021.

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