| Author | Source |
|---|---|
| u/Sar7814 |
You know how I know I love GME? I just read this entire paper on dark pools on my muthafuckin birthday bitches. Figured this ape is getting older, need to gain more wrinkles in this ape brain.
Okay THIS paper is on HFTs (High Frequency Trades) and Dark Pools:
High-frequency trading and dark pools: sharks never sleep
Needless to say I was lured by the title. I have posted this as a summary and condensed version of the paper for you apes to hopefully gain some insights from this information that we may be able to use in deepening our understanding of the effects these dark pools are having on GME, and really the market as a whole.
What is High Frequency Trading (HFT)?
HFT employs sophisticated computer programming to execute stock transactions at extremely fast speeds in order to take advantage of small and often momentary changes in stock prices.
With this new-found acceleration, the capacity of exchanges as measured by order messages per day has gone from one million in 1995 to hundreds of millions by 2009, and during the same period throughput as measured by messages per second has gone from 20 to over 100,000.
Okay so how is High Frequency Trading related to dark pools?
High-frequency traders (HFTs) use different trading strategies but there are some common characteristics, including trading on their own account rather than on behalf of clients; utilising high-speed computer programs to generate, route and execute orders rapidly on multiple exchanges; maintaining unhedged positions for small fractions of a second; and submitting high rates of orders that are cancelled before the order is executed
In order for these trading strategies to work high-frequency traders need a speed advantage. To achieve such speeds, these traders pay to “co-locate” or “cross-connect” their trading computers in the buildings of public exchanges or “dark pools” in order to increase the speed with which they receive information, enabling the traders to rapidly place and cancel orders.
“Those speed and technology advantages allow high frequency traders to profile the pending orders on an exchange in order to detect the presence of large pending orders, usually from institutional investors. This ‘information leakage,’ allows high frequency traders to trade ahead of an anticipated stock purchase or otherwise have an impact on price. This strategy is sometimes referred to as ‘latency arbitrage,’ because the trader is seeking to exploit the relative slowness, or ‘latency,’ in the transmission of market data experienced by other participants. Barclays itself commonly labelled these types of high frequency strategies as ‘toxic,’ ‘predatory,’ or ‘aggressive.’
But what…actually…is it..?
In addition to the 11 public stock exchanges in the United States there are dozens of privately owned and operated trading venues, including venues known as ”dark pools”. Public stock exchanges match tens of millions of orders to buyers and sellers each day, and these are generally visible to participants, and executions of orders are posted immediately. Public exchanges immediately display to the market the submission of pending stock orders; dark pools do not.
“Dark pools, defined in contrast to ‘lit’ trading venues where trading intentions and activity are visible, provide access to non-displayed liquidity. A dark pool is an OTC (over-the-counter) venue for reporting purposes, which has the practical value that unmatched trade orders are not displayed on an open order book. The use of dark pools is typically found where disclosure of trading intent might prove injurious to price efficiency. For example, moving a large block of shares onto the market might impact counterparty pricing; feeding the same block through a dark pool (in smaller lots) will conceal the size of the overall trade (annnnd we know this because we be dealing with this erry gaddamn day)
A quote from Thomas Caldwell on dark pools:
“Large institutional investors know that if they start trying to push through a large block of shares at a certain price – even if the block is broken into many small trades on several ATSs and markets – they can trigger a flood of high-frequency orders that immediately move market prices to the institution’s disadvantage. … That’s why institutions have flocked to so-called dark pools operated by ATSs such as Instinet, and individual dealers like Goldman Sachs. The pools allow traders to offer prices without publicly revealing their identities and tipping their hand.”
“Because these large, dark pools are opaque to other investors and to regulators, they inhibit the free trade that depends on open and transparent auction markets to work, but are considered by institutional investors as a safer place to trade than the open market”
Okay so there’s this one specific dark pool started by Barclays:
“In October, 2013, Barclays prepared a trading analysis for a major institutional investor that services millions of individual accounts both inside the United States and abroad (‘Institutional Investor’).
The analysis determined that:
Approximately 88% of this Institutional Investor’s sampled trades in dark venues were executing in Barclays’ dark pool;
Approximately 60% of the trading counterparties for the Institutional Investor’s sampled orders were high frequency trading firms.” In preparation for a meeting with the Institutional Investor to explain these findings, two senior Directors prepared a PowerPoint presentation that included the results of the trading analysis. Two days before the scheduled meeting, one of those Directors was called into a meeting with senior leadership in the Equities Electronic Trading division, who instructed him not to disclose the findings to the client. According to this Director, ‘there was no suggestion at that meeting, or at any other point, that the analysis was wrong,’ merely that it should not be shared with the client because it reflected poorly on Barclays. (god I hate these cunts)
Distinct types of HFT firms include:
independent proprietary firms, which use private funds and specific strategies which remain secretive, and may act as market-makers, generating automatic buy and sell orders continuously throughout the day;
broker-dealer proprietary desks, which are part of traditional broker-dealer firms but are not related to their client business, and are operated by the largest investment banks; and
hedge funds, which focus on complex statistical arbitrage, taking advantage of pricing inefficiencies between asset classes and securities.
Agarwal distinguished high-frequency traders from the rest of the market, which generally employs algorithmic trading: “High frequency traders typically act in a proprietary capacity, making use of a number of strategies and generating a very large number of trades every single day. They leverage technology and algorithms from end-to-end of the investment chain – from market data analysis and the operation of a specific trading strategy to the generation, routing, and execution of orders and trades. What differentiates HFT from algorithmic trading is the high frequency turnover of positions as well as its implicit reliance on ultra-low latency connection and speed of the system.
So what’s even good about dark pools?
“As noted, the defence of HFT is built around the principle that it increases liquidity, narrows spreads and improves market efficiency. The high number of trades made by high frequency traders results in greater liquidity in the market.”
But there are critical differences between high-frequency traders and traditional market makers:
High-frequency traders do not have an affirmative market-making obligation, ie. they are not obliged to provide liquidity by constantly displaying two side quotes, which may translate into a lack of liquidity during volatile conditions
High-frequency traders contribute little market depth due to the marginal size of their quotes, which may result in larger orders having to transact with many small orders, and this may impact on overall transaction costs.
High-frequency trader quotes are barely accessible due to the extremely short duration for which the liquidity is available when orders are cancelled within milliseconds.
HFT Risks
..There are more deliberate aspects of HFT strategies which may present serious problems for market structure and functioning, and where conduct may be illegal, eg. order anticipation seeks to ascertain the existence of large buyers or sellers in the marketplace and then to trade ahead of those buyers and sellers in anticipation that their large orders will move market prices (literally what is happening every gaddamn day)
HFT strategies can resemble traditional forms of market manipulation that violate the Exchange Act according to the SEC:
Spoofing and layering occurs when traders create a false appearance of market activity by entering multiple non bonafide orders on one side of the market at increasing or decreasing prices in order to induce others to buy or sell the stock at a price altered by the bogus orders.
Painting the tape involves placing successive small numbers of buy orders at increasing prices in order to stimulate increased demand.
Quote stuffing and price fade are additional HFT dubious practices: quote stuffing is a practice that floods the market with huge numbers of orders and cancellations in rapid succession which may generate buying or selling interest, or compromise the trading position of other market participants. Order or price fade involves the rapid cancellation of orders in response to other trades.
When HFTs go bad….
“On 6 May 2010 the prices of many US-based equity products experienced an extraordinarily rapid decline and recovery, as major equity indices in the securities and futures markets plunged 6% in minutes, and then quickly rebounded: “The so-called ‘Flash Crash’ sent shockwaves through global equity markets. The Dow Jones experienced its largest ever intraday point fall, losing $1 trillion of market value in the space of half an hour. History is full of such fat-tailed falls in stocks. Was this just another to add to the list, perhaps compressed into a smaller time window? No. This one was different. For a time, equity prices of some of the world’s biggest companies were in free-fall. They appeared to be in a race to zero. Peak to trough, Accenture shares fell by over 99%, from $40 to $0.01. At precisely the same time, shares in Sotheby’s rose three thousand-fold, from $34 to $99,999.99.”
This near disaster resulted when a large fundamental trader, against a backdrop of unusually high volatility and thinning liquidity, initiated a sell programme to sell a total of 75,000 contracts (valued at approximately $4.1 billion) as a hedge to an existing equity position. The trader executed the sell program via an automated execution algorithm (the “Sell Algorithm”) that was programmed to feed orders into the market to target an execution rate set to 9% of the trading volume calculated over the previous minute, but without regard to price or time.
With the Sell Algorithm only targeting trading volume, and neither price nor time, it executed the sell program in just 20 minutes, and chaos ensued. Many of the US market’s 8,000 individual equities and exchange-traded funds suffered price declines of between 5% and 15%, while over 20,000 trades across 300 securities were executed at prices more than 60% away from their values moments before. In the midst of this chaotic algorithmically programmed frantic buying and selling, the high-frequency traders were buyers of the initial batch of orders submitted by the Sell Algorithm; however, as conditions rapidly deteriorated “lacking sufficient demand from fundamental buyers or cross-market arbitrageurs, HFTs began to quickly buy and then resell contracts to each other – generating a ‘hotpotato’ volume effect as the same positions were rapidly passed back and forth. Between 2:45:13 pm and 2:45:27 pm, HFTs traded over 27,000 contracts, which accounted for about 49 per cent of the total trading volume, while buying only about 200 additional contracts net.”
The joint report from the US SEC and the US Commodity Futures Trading Commission (CFTC) concluded one key lesson is that under stressed market conditions, the automated execution of a large sell order can trigger extreme price movements, especially if the automated execution algorithm does not take prices into account.
“The SEC developed a circuit breaker to pause trading across US markets in a security that has experienced a 10% price change in the previous 5 minutes, and on 10 June 2010 approved the application of this circuit breaker to securities included in the S&P 500.29 (ayeee theres our SSR comin in). But guess what, even with SSR, all of these trades are still going through the dark pools…
However, it is clear that neither financial markets nor regulators fully comprehend the potential impact of HFT, or regulate its activity in any meaningful way, powerfully illustrating that we still have got a lot to learn from the recent financial crisis (this paper was published in 2010).”
What does all of this mean? Tbh, it is hard to connect these dots in a precise way to understand exactly what is happening to who and when, but SOMETHING is happening. We are seeing JP Morgan sell 13 BILLION in treasury securities, this means they need to increase their liquidity, and this is also helping MMs like Citadel increase their liquidity as well now that those bonds are out in the market. More bonds= more liquidity. If they need this much liquidity, they must be lacking it elsewhere. I hope that I am wrong, and that we are not witnessing the beginning of a market crash, but there are lots of similarities here with 2008. Everything is built on this house of cards that USED to be the housing market, and now is US securities (particularly 10 year bonds). I’m just a dumb ape, but seems to me everything is going to be royally fucked if the markets main source of liquidity (US Treasury Securities) goes to shit because it has been devalued by the amount they have been oversold. Also hoping some wrinkle brains can read over the dark pool info and gain some insights. Please share if ya do. Thanks apes.