Last week Goldman Sachs hosted an investor call with a focus on the US Economic Outlook including opinions on inflation, Bitcoin, and gold. According to Goldman, Bitcoin is not scarce (Bitcoin Cash and Bitcoin SV), used in money laundering (1MDB scandal?), and doesn’t consider Bitcoin as an asset class (tell that to the CFTC). On the other hand they did point out how Bitcoin’s volatility could present an opportunity to certain traders. Bottom line being, Goldman does not advise their clients to buy either gold or Bitcoin.
While Goldman’s clients may not being buying Bitcoin, companies like Grayscale and Square purchased the equivalent of 50% of newly mined Bitcoin in Q1 2020. This purchase amount only accounts for new supply added to the market before Bitcoin’s latest halving. As more companies create avenues for customers and clients to purchase Bitcoin or receive Bitcoin through rewards (Lolli), the demand will heat up while new supply is now only half of what it has been for the past 4 years.
Market Update - 5/30/20
Bitcoin- $9,650
Ether- $242
Gold- $1,729
DJI- 25,383.11
NASDAQ- 9,489.87
S&P 500- 3,044.31
NYSE- 11,802.94
New Developments
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zk-STARKS to solve Ethereum’s scalability & privacy dilemma
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Zcash upcoming Heartwood upgrade will activate on mainnet at block 903,000
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350% increase in Ethereum addresses holding Ether since January of 2018
glassnode @glassnode
There are now 40 million #Ethereum addresses holding #ETH. That's an increase of more than 350% since $ETH saw its ATH price in early 2018. 
May 24th 2020
108 Retweets361 Likes
Industry Insight’s
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John Wolpert, Baseline Protocol for Enterprises
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Flipside Crypto, Stablecoin Use Cases
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Ether as Digital Gold, Messari
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Ryan Watkins, Crypto Research at Messari
Ryan Watkins @RyanWatkins_
ETH is increasingly close to being flipped on its own blockchain. Whether or not it does will likely depend on the growth of stablecoins vs growth in the value of ETH. 
May 28th 2020
18 Likes
Python Activity
Sentiment Analysis on Recent Ethereum Articles using newsapi.org:
# Import libraries
import os
import pandas as pd
from newsapi import NewsApiClient
from nltk.sentiment.vader import SentimentIntensityAnalyzer
analyzer = SentimentIntensityAnalyzer()
# Read your api key environment variable
api_key = os.getenv("NEWSAPI_KEY")
# Create a newsapi client
newsapi = NewsApiClient(api_key=api_key)
# Fetch the Ethereum news articles
ethereum_articles = newsapi.get_everything(q="ethereum", language="en")
# Create the ethereum sentiment scores DataFrame
ethereum_sentiments = []
for article in ethereum_articles["articles"]:
try:
text = article["content"]
date = article["publishedAt"][:10]
sentiment = analyzer.polarity_scores(text)
compound = sentiment["compound"]
pos = sentiment["pos"]
neu = sentiment["neu"]
neg = sentiment["neg"]
ethereum_sentiments.append({
"text": text,
"date": date,
"compound": compound,
"positive": pos,
"negative": neg,
"neutral": neu
})
except AttributeError:
pass
# Create DataFrame
ethereum_df = pd.DataFrame(ethereum_sentiments)
# Reorder DataFrame columns
cols = ["date", "text", "compound", "positive", "negative", "neutral"]
ethereum_df = ethereum_df[cols]
# Describe the Ethereum Sentiment
ethereum_df.describe()
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The picture above generated a sentiment analysis using SentimentIntensityAnalyzer from nltk.sentiment.vader on 17 different articles written about Ethereum sorted by most recent publish date. The analysis determines whether the authors of the articles were overall positive, negative, or neutral in regard to what they wrote about the subject matter. The Compound Mean is what I would first look at to get an initial description on the dataset. A quick side note important to remember, this code can be copy and pasted for anyone to use but the user will have to generate their own API Key through NewsAPI.
