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518 points bwfan123 | 2 comments | | HN request time: 0s | source
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cs702 ◴[] No.44483909[source]
According to Indian regulators, every trading day Jane Street would:

1) buy large volumes of stocks and/or stock futures that are part of an index tracking India’s banking sector, early in the day,

2) subsequently place large options trades, betting that the index would decline or volatility would spike later in the day, and

3) later in the day, cash out of the large long positions, dragging the index lower, making far more money on the options trades than on the long positions.

Jane Street can and likely will claim the firm was only arbitraging away pricing inefficiencies, nothing more, nothing less. It was just business as usual, etc., etc.

However, given the scale of the operation, Jane Street's actions sure look like textbook market manipulation. Calling it like I see it.

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naveen99 ◴[] No.44484082[source]
Ok, but what moron was selling them the puts , and not seeing the pattern after a couple of days of this ? Sebi logic seems questionable.
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lopatin ◴[] No.44484167[source]
Presumably retail options traders and less sophisticated firms
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naveen99 ◴[] No.44484312{3}[source]
Yeah, I think volatility in the indian market was way too low, and Jane street just juiced it. normally that would be a losing proposition, but too many existing players were short volatility habitually… answer is not to kick Jane street out, but to enjoy the taxes Jane street pays on the gains…
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lumost ◴[] No.44484426{4}[source]
Low volatility is good for everyone engaged in long term asset management. Jane Street just found a way to make everyone else less money while making a small amount for themselves.
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1. MichaelZuo ◴[] No.44484554{5}[source]
> Low volatility is good for everyone engaged in long term asset management.

According to who?

There are plenty of pension funds nowdays that have people specialized in picking up mid sized companies after big drops.

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2. mrcode007 ◴[] No.44484765[source]
it’s a known effect. Without going into details here, you can calculate first crossing time of a barrier in a stochastic process and observe that often the first crossing time decreases as the volatility increases. From there you can set one barrier at 0 (default) and draw your own conclusion.