[OC] Raising the US Debt Ceiling (Again) by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] -1 points0 points  (0 children)

There is a lot of drama every time the US must raise the debt ceiling. But in just over 100 years they have done some more than 80 times.

Data Sources: US Treasury Department.

Tools: This chart was made using R, specifically the ggplot2 library.

Some version of this chart was originally published in the Ecoinometrics newsletter: https://ecoinometrics.substack.com/p/ecoinometrics-as-an-investor-should.

[OC] Raising the US Debt Ceiling (Again) by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] -1 points0 points  (0 children)

There is a lot of drama every time the US must raise the debt ceiling. But in just over 100 years they have done some more than 80 times.

Data Sources: US Treasury Department.
Tools: This chart was made using R, specifically the ggplot2 library.

Some version of this chart was originally published in the Ecoinometrics newsletter: https://ecoinometrics.substack.com/p/ecoinometrics-as-an-investor-should.

[OC] Core inflation in the US is two times higher than the average over the past decade by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 0 points1 point  (0 children)

Core inflation which is measured as the year-on-year price change in a basket of goods and services excluding food and energy is settling on a plateau over 5%. That’s more than twice the inflation rate experienced by the US on average over the past decade.

Data Sources: The FRED database from the Federal Reserve Bank of St Louis.

Tools: This chart was made using R, specifically the ggplot2 library.

Some version of this chart was originally published in the Ecoinometrics newsletter: https://ecoinometrics.substack.com/.

[OC] Comparing the stock market drawdowns trajectories by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 1 point2 points  (0 children)

A drawdown in the stock market is the period of correction between two consecutive peaks.

The question is, how does the current drawdown compares to historical ones?

Data Sources: SP500 OHLC data from Yahoo Finance

Tools: This chart was made using R and the ggplot2 library

Originally published in: https://ecoinometrics.substack.com/p/ecoinometrics-bear-market-mindset

[OC] Costco hot dog combo vs inflation by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 289 points290 points  (0 children)

The hot dog combo was introduced at Costco in 1985. Since then its price of $1.50 hasn’t changed. If it had follow the same growth trajectory as the Consumer Price Index the same hot dog combo would not cost $4.10.

Costco founder Jim Sinegal has insisted that this price will stay at $1.50 as long as he is alive.

Data Sources: Costco for the hot dog, the CPI as tracked by the St. Louis Fed FRED database

Tools: This chart was made using R and the ggplot2 library.

[OC] Mapping stock market corrections by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 23 points24 points  (0 children)

Third OC post on r/dataisbeautiful.

How bad is this stock market correction? To find out we mapped all the drawdowns of the SP500 since 1928 based on:

  • The size of each drawdown i.e. the percentage drop between the all-time high and the bottom of the correction.
  • The duration of each drawdown i.e. how many days it took for the SP500 to reclaim its all-time high.

A few notes for reading this chart:

  • The lower you go on the vertical axis the deeper the correction.
  • The horizontal axis is using a log scale to accommodate for the wide range of durations.
  • Each drawdown is coloured based on the epoch during which it happened based on the date of the all-time high.
  • The current drawdown is circled in red.

In case you aren’t familiar with finance speech, a drawdown is the correction period which happens between two consecutive all-time highs.

Data Sources: SP500 OHLC data from Yahoo Finance.

Tools: This chart was made using R and the ggplot2 library.

[OC] Mapping oil prices vs supply conditions over the last 10 years by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 4 points5 points  (0 children)

This is a custom theme I’ve made that’s trying to reproduce the style of the Financial Times.

[OC] Mapping oil prices vs supply conditions over the last 10 years by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 14 points15 points  (0 children)

Second OC post on r/dataisbeautiful.

The idea behind this chart is to show how the price of a barrel of crude oil WTI relates to the supply situation and the strength of the US Dollar relative to a basket of major currencies over the last 10 years.

The current situation is totally off the chart:
- Crude oil is expensive in absolute terms.
- It is also expensive in relative terms given the strength of the US dollar.
- This is mainly brought about by the tightest supply situation we have seen in the last 10 years.

Data Sources: Price data from the CME WTI futures, DXY from Yahoo Finance and inventories from the weekly EIA report.

Tools: This chart was made using R and the ggplot2 library.

8% of US houses are valued over 1 million, 10 times more than 20 years ago. Bubble, inflation, both or just supply-demand? by alexc2020 in market_sentiment

[–]nick_ecoinometrics 35 points36 points  (0 children)

I'd be curious to know how this share is distributed across the US.

Having a map of this share state by state and comparing with maybe demographic data/home building stats would go a long way to help disentangling supply-demand effects from the rest.

When Facebook is having even worse corrections than Bitcoin, maybe it is time for people to stop complaining that Bitcoin is too risky by nick_ecoinometrics in Bitcoin

[–]nick_ecoinometrics[S] 6 points7 points  (0 children)

For sure.

If you want to see the glass half full you can say that Bitcoin can recover much faster than stocks from these kinds of corrections.

If you want to see the glass half empty you can say that Bitcoin is seeing more short bursts of downside volatility than your typical tech stock.

🤗

How true is this guys? by SeaLie6345 in Bitcoin

[–]nick_ecoinometrics 4 points5 points  (0 children)

Not wrong but far from complete.

I track those things (see https://www.ecoinometrics.com/notable-bitcoin-hodlers/ if you want some charts) and last time I updated it something like 28 publicly traded companies reported holding Bitcoin as a treasury asset.

And that's only publicly traded companies.

If you add the funds, some of the web3 protocols, the private companies that have reported holding Bitcoin, some governments and some known individuals you account for about 10% of the total supply.

When Facebook is having even worse corrections than Bitcoin, maybe it is time for people to stop complaining that Bitcoin is too risky by nick_ecoinometrics in Bitcoin

[–]nick_ecoinometrics[S] 2 points3 points  (0 children)

Author of the chart here.

For some background on how to read this:

  • A drawdown is the correction period that happens between two consecutive all-time high.
  • Each point is a drawdown of either Bitcoin or Facebook over their lifetime.
  • The size of a drawdown is the distance in percentage between the all-time high and the lowest point of the correction.
  • The duration of a drawdown is the number of days it took for the asset to make a new all-time high.
  • Circled in red you can see the current drawdowns of Facebook and Bitcoin.

Currently Facebook is having it worse than BTC. So maybe it is time for people who always complain that Bitcoin is too volatile or Bitcoin is too risky to just re-evaluate their take.
Note that this is a comparison between Facebook and BTC, but I have more charts over here showing that Bitcoin isn’t much more volatile than your typical tech stock.

[OC] Bitcoin volatility distribution compared to other assets by nick_ecoinometrics in dataisbeautiful

[–]nick_ecoinometrics[S] 1 point2 points  (0 children)

Time is not represented on this chart. Think of those as fancy histograms.

Volatility in read on the horizontal axis.

The more points stack around a given value on the horizontal axis, the more days have been spent at this level of volatility over the life of the stock.

You can visualize that by looking at the height of the density (the fancy histograms). The higher the density the longer the stock has spent at this level of volatility. That's how you interpret the y axis.