We need to understand misinformation & disinformation as systems, not just individual actions. An economy of false information.
[this thread continues from what I posted last night, about some of the most prominent South African misinfo posters]
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I can't tell if I'm agreeing or disagreeing with @jc_econ.
There is no relationship b/w deficits & interest rates in the US & many other advanced economies. Centuries of dynamic institution building underpin our reserve currency status that allows rates to be a function of economic fundamentals, flows & policy not credit risk 1/3
— Dr. Julia Coronado (@jc_econ) January 26, 2021
Increasing government spending or reducing taxes increases demand (or reduces saving). This raises the price of loanable funds or the interest rate.
In a dynamic context, more demand means a stronger economy, the central bank raises interest rates sooner, and long rates rise.
(As an aside, we are not close to the United States needing to worry about credit risk and the risks are more overstated than understated in most other advanced economies too. But credit risk is not always & everywhere irrelevant, just look at the UK in 1976 or Canada in 1994.)
Interest rates have fallen over the last 20 yrs while debt has risen. This does not necessarily mean that debt rising causes interest rates to fall. It could also mean that other things have happened at he same time that pushed down interest rates more than debt pushed them up.
The suspects for these "other things" include slower productivity growth, slower popln growth, higher inequality, less investment, etc. All of which either increase the supply of saving or reduce the demand for investment, reducing the equilibrium interest rate.
"A trend factor using multiple time lengths outperforms ST reversal, momentum, and LT reversal, which are based on the three price trends separately."
https://t.co/udkvsdw2Lz
2/ This resembles combining multiple measures of ST reversal, momentum, and LT reversal (forecasts determined by walking forward rather than using signs from the full sample).
Unlike normal moving average signals, these are *cross-sectional.* More below:
https://t.co/wkIFLg9jtK
1/ Cross-Sectional and Time-Series Tests of Return Predictability: What Is the Difference? (Goyal, Jegadeesh)
— Darren \U0001f95a (@ReformedTrader) June 18, 2019
"The difference between the performances of TS and CS strategies is largely due to a time-varying net-long investment in risky assets."https://t.co/CSIn3ujN2R pic.twitter.com/XHnVmIart4
3/ Unsurprisingly, the Trend factor formed by this approach outperforms benchmarks in terms of both Sharpe ratio and tail metrics. It's combining momentum with two factors that are negatively correlated to it AND using multiple specifications.
More here:
https://t.co/x8Tloz3iyL
1/ An Executive Summary (in Tweet form) of our new paper
— Adam Butler (@GestaltU) March 27, 2019
Dual Momentum \u2013 A Craftsman\u2019s Perspective
Download here: https://t.co/Y9GlGNohBg
Everything that follows in this thread is based on HYPOTHETICAL AND SIMULATED RESULTS. pic.twitter.com/9m5YJnTdtq
4/ "Average return and volatility of the trend factor are both higher in recession periods. However, the Sharpe ratio is virtually the same.
"Interestingly, all of the factors still have positive average returns.
"Momentum experiences the greatest increase in volatility."
5/ "In terms of maximum drawdown and the Calmar ratio, the trend factor performs the best.
"The trend factor is correlated with the short-term reversal factor (35%), long-term reversal factor (14%), and the market (20%) but is virtually uncorrelated with the momentum factor."
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It's all in French, but if you're up for it you can read:
• Their blog post (lacks the most interesting details): https://t.co/PHkDcOT1hy
• Their high-level legal decision: https://t.co/hwpiEvjodt
• The full notification: https://t.co/QQB7rfynha
I've read it so you needn't!
Vectaury was collecting geolocation data in order to create profiles (eg. people who often go to this or that type of shop) so as to power ad targeting. They operate through embedded SDKs and ad bidding, making them invisible to users.
The @CNIL notes that profiling based off of geolocation presents particular risks since it reveals people's movements and habits. As risky, the processing requires consent — this will be the heart of their assessment.
Interesting point: they justify the decision in part because of how many people COULD be targeted in this way (rather than how many have — though they note that too). Because it's on a phone, and many have phones, it is considered large-scale processing no matter what.