Market Update
The Bitcoin Halving is about a week away, set for May 12, 2020 at block height 630,000. This will cut the mining reward for solving the next block in half, paid in Bitcoin every ~10 minutes, from 12.5 to 6.25 Bitcoin. Gold recently made the news because lately it has needed to be flown into New York to handle the recent surge of investor demand. In regards to the Stock Market, the recent low in March coincided with news of so-called “QE Infinity”. Given the current situation, The Fed is willing to to do whatever it takes that is within its power to keep the economy flush with cash and companies from going under.
Prices (Monday 5/4/20 Opening)
Bitcoin- $8,825
Ether- $205
Gold- $1,700
S&P 500- 2,815.01
DJI Average- 23,581.55
NASDAQ Composite- 8,555.32
NYSE Composite- 10,965.77
New Developments
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Tokenized Whiskey by Waves Financial
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a16z raises $515 million for its second crypto fund
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Tether (USDT) has a market cap over $7.8 billion across several blockchains and sidechains (Omni, Ethereum, EOS, Liquid, Tron, Algorand)
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Metal launches MetalX, a US and EU exchange offering a variety of trading pairs including their new token Proton.
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“Never bet against America”, Warren Buffet 2020 Berkshire Hathaway Meeting
Industry Opinion’s
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The Fed, Journey through COVID-19 by Qiao Wang
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Bullish on ETH, by Adam Cochran
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S2FX Model by Plan B
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Tether's First Mover Advantage, Ryan Selkis interviews Paolo Ardoino
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Baseline on Ethereum, Paul Brody (EY), Joseph Lubin, John Wolpert (ConsenSys)
Python/FinTech Activity
Python Libraries:
Within programming languages like Python there are built in libraries which help a developer use short cuts to create a solution in code. One such library is pathlib and another is pandas. These two libraries work in tandem with one another. The pathlib library allows a developer to read in a .csv file with data while pandas enables financial analysis tools.
How a starter file may look to import libraries, read in a .csv, concat two datasets in a dataframe:
import pathlib as Path
import pandas as pd
gbtc_data = Path("../Resources/GBTC.csv")
ethe_data = Path("../Resources/ETHE.csv")
gbtc = pd.read_csv(gbtc_data, index_col="date")
ethe = pd.read_csv(ethe_data, index_col="date")
combined_df = pd.concat([gbtc, ethe], axis="columns", join="inner")
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The variable combined_df will represent a dataframe of both GBTC and ETHE information (whatever was provided in the .csv) typically closing price information for every trading day. Couple other things are at work here, index_col=”date” makes the date column of the dataframe the index. Other things in the combined_df like axis="columns", join="inner" combine the datframes on columns rather than rows and joins these columns in an inner manner instead of outer.
Quick Earn Opportunity
This week’s Earn Opportunity is simple. Set up a Coinbase account. Coinbase is more than a cryptocurrency exchange, it is a digital bank trusted by more than 13 million users worldwide. They offer numerous products such as Coinbase App, Coinbase Pro (trading), Coinbase Earn (Learn & Earn), and Coinbase Wallet (DeFi).
