has anyone covering the Wall Street GME reaping and sowing gone into the fact that a lot of the GameStop and directly associated trades have been largely amplified by social listening powered mega firms doing machine learning automated trades because the “idea” of GME is popular?

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This is a really tough problem to resolve, especially if the massive increase in inflows from the trade and financial accounts are sustained, as I expect they will be well into 2021.

Clearly the PBoC would like to see the RMB gradually...

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strengthen. This would keep financial markets stable and promote rebalancing, but the RMB has already strengthened a lot, and this puts unwanted pressure on exporters and “international circulation”.

Although PBoC reserves have been flat, other state-controlled Chinese...

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banks have bought large amounts of dollars, but this is expensive. If these banks have half a trillion dollars of exposure, for example, they are losing at least $15-17 billion annually on negative carry, plus another $20-30 billion just this year from the rise of the RMB.

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Beijing seems also to be trying other measures to slow the rise. The regulators are relaxing capital controls on outflows. In mid October the PBoC cut to zero the reserve requirement ratio for banks doing FX forward trading. This requirement was created in 2018 to reduce...

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downward pressure on the RMB. In late October it suspended the counter-cyclical factor in RMB fixing, which was introduced in 2017 also to reduce downward currency pressure. But in both cases while the RMB dropped a few pips on the news, it quickly resumed its upward climb.

I have read through the grooming report from the Home Office.

Here, in this thread, I will take you through the mathematical hoops they have jumped through in this deeply flawed analysis.

Thread 👇

It is, quite literally, a whitewash. It uses all the standard statistical tricks to avoid concluding a stark and glaring conclusion, which is otherwise plain to see. That there was a sustained, targeted and focussed attack by Pakistani men on white working class and Sikh girls.

**Choose limited data points**

One way to force a conclusion is to only range over a small and carefully chosen set of data points. In this case, the report used a limited number of use cases which largely ignored the high profile grooming gangs of Pakistani origin.

Only Rotherham was considered in earnest, as it could hardly be ignored as the start of it all.

A typical data trick is to only use one troublesome dataset - generally the most high profile one. This gives plausible denial on accusations of manipulation of source data.

_This is what we call “the domain trick”_