Margin Calls – Note Quote.

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Unlike FOREX margin, which is a single yet dynamic figure that constantly fluctuates based on the notional value of the contracts being traded, futures margin is relatively static. Although the exchange and brokerage firms have the right to increase, or decrease, margin requirements at any time, changes are typically infrequent.

The premise of margin is to mitigate risk exposure to the exchange and brokerage firms by ensuring that traders have enough funds on deposit to cover losses that might reasonably be seen within a trading session. Accordingly, futures exchanges set margin rates based on current market volatility and not necessarily the nominal value of the contract, which is the dominant method in FOREX. Nominal value is the total worth of the currency contract when leverage is eliminated. However, as the nominal value increases, the futures exchanges tend to increase margin simply because, at higher prices, currencies tend to see larger price moves and expose traders to additional risk.

When traders refer to their futures margin requirement, they are referring to the initial margin. In other words, “initial margin” and “margin” are often used synonymously. In detail, initial margin is the amount of capital the exchange requires a trader to have on deposit to hold a given currency futures contract beyond the close of trade on the session the order was executed. For example, if the initial margin for a standard-sized Euro futures contract is $5,400, a trader should have at least this much in a trading account to execute a trade that is intended to be held overnight. Day traders are not necessarily subject to the same requirements.

The minimum account balance that must be maintained at the close of trade to avoid a margin call is known as the maintenance margin. Futures exchanges typically set the maintenance margin at about 70% to 80% of the initial margin. Should an account balance dip below the maintenance margin requirement, as measured by the close of trade on any particular day, a margin call is generated and the trader is required to bring the account back above the initial margin. This can be done through position liquidation, adding funds to the trading account, or even mitigating margin using option hedges. Once an official margin call is triggered, it is no longer enough to bring the equity above the maintenance margin level; the account must meet the initial margin. A margin call is triggered only if the account is in violation at the close of a trading session. At any point intraday, it is nearly irrelevant. Therefore, it is quite possible for an account to experience a margin deficit in the middle of the trading day only to be off the hook by the close of trade, and vice versa. This differs from FOREX, where traders are commonly issued intraday margin calls. This is because their margin requirement is being consistently measured as opposed to solely at the end of the trading day, as is the protocol in futures.

Margin calls state account details such as open positions, required initial and maintenance margin, the margin deficiency, and current account value. In addition to a formal notice, brokerage firms display margin call details on the trader’s daily statements, including the number of days the margin call has been active. Futures brokers typically give traders two or three days to eliminate a margin call on their own accord, but each brokerage firm is different. Deep-discount brokers tend to be much less lenient when it comes to margin calls and forced account liquidation.

If a client goes one step beyond a simple margin call and is in danger of losing more than the funds on deposit, it is not uncommon for risk management clerks to force liquidate positions regardless of the brokerage firm and service type, and they have every right to do so.

If traders must have the initial margin on deposit to enter a trade, there are exceptions for those who enter a trade based on the premise of offsetting their risk and obligation by the end of that particular trading session. For those traders engaged in the practice of day trading, brokerage firms, and even individual brokers, will often negotiate a discounted margin rate offering more leverage than is granted to traders who are holding positions overnight. For the purpose of margin, day trading is any activity in which trades are entered and exited within a single trading session. In today’s world, the currency futures markets trade nearly 24 hours per day. Therefore, it is entirely possible for a trade to be entered in the evening, held overnight, and offset before the close of the day session to be treated as a “day trade.” Conversely, although this trade was held “overnight,” under the usual pretense of the phrase, both the entry and the exit occurred within a single trading session and, therefore, falls into the day-trading category in regard to margin.

Depending on a trader’s established relationship with his brokerage firm, or more importantly an individual broker, the margin charged on any intraday positions may be anywhere from 50% to 10% of the exchange’s stipulated overnight rate. Naturally, only those clients believed to be responsible enough to have access to excessively low margin requirements are awarded the privilege; irresponsible traders are viewed as a credit risk to the brokerage and might not be granted the same freedoms. This is similar to the threats posed by those with low credit scores to a credit card company. With that said, as a means of risk management implemented by brokerage firms, some platforms are now capable of automatically liquidating accounts in danger of losing more than what is currently deposited. In the case of auto-liquidation, brokers might extend even more lenient margin policies to day traders simply because the luxury of auto-liquidation mitigates risk to the firm. Similar to the way a trader analyzes the market in terms of risk and reward, brokerage firms assess clients on a risk/reward basis and proceed accordingly. Brokerage revenue is commission based; they want you to trade, but not if it isn’t worth the potential consequences.

Futures brokers who have auto-liquidate capabilities often ask clients to sign a disclosure statement acknowledging they are aware that positions might be offset without prior consent to the client if the account is deemed to be in danger of going negative, although they technically have the right to do so even without the agreement. A common practice among futures brokers is to strategically place a stop order at a price that would prevent the account from losing more than is on deposit. However, as futures traders become more and more self-directed, this courtesy is slowly becoming less popular simply because in some ways it poses additional risk and potential liability to the broker. For example, “unruly” clients can easily cancel a stop order placed on their behalf to prevent a debit balance, and brokers simply don’t have time to babysit accounts to ensure clients don’t do so. In addition, if a stop order is placed for a specific number of contracts and the trader reduces the size of the position without adjusting the stop order, he might attempt to hold the brokerage firm liable for any erroneously resulting trades.

Bullish or Bearish. Note Quote.

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The term spread refers to the difference in premiums between the purchase and sale of options. An option spread is the simultaneous purchase of one or more options contracts and sale of the equivalent number of options contracts, in a different series of the class of options. A spread could involve the same underlying: 

  •  Buying and selling calls, or 
  •  Buying and selling puts.

Combining puts and calls into groups of two or more makes it feasible to design derivatives with interesting payoff profiles. The profit and loss outcomes depend on the options used (puts or calls); positions taken (long or short); whether their strike prices are identical or different; and the similarity or difference of their exercise dates. Among directional positions are bullish vertical call spreads, bullish vertical put spreads, bearish vertical spreads, and bearish vertical put spreads. 

If the long position has a higher premium than the short position, this is known as a debit spread, and the investor will be required to deposit the difference in premiums. If the long position has a lower premium than the short position, this is a credit spread, and the investor will be allowed to withdraw the difference in premiums. The spread will be even if the premiums on each side results are the same. 

A potential loss in an option spread is determined by two factors: 

  • Strike price 
  • Expiration date 

If the strike price of the long call is greater than the strike price of the short call, or if the strike price of the long put is less than the strike price of the short put, a margin is required because adverse market moves can cause the short option to suffer a loss before the long option can show a profit.

A margin is also required if the long option expires before the short option. The reason is that once the long option expires, the trader holds an unhedged short position. A good way of looking at margin requirements is that they foretell potential loss. Here are, in a nutshell, the main option spreadings.

A calendar, horizontal, or time spread is the simultaneous purchase and sale of options of the same class with the same exercise prices but with different expiration dates. A vertical, or price or money, spread is the simultaneous purchase and sale of options of the same class with the same expiration date but with different exercise prices. A bull, or call, spread is a type of vertical spread that involves the purchase of the call option with the lower exercise price while selling the call option with the higher exercise price. The result is a debit transaction because the lower exercise price will have the higher premium.

  • The maximum risk is the net debit: the long option premium minus the short option premium. 
  • The maximum profit potential is the difference in the strike prices minus the net debit. 
  • The breakeven is equal to the lower strike price plus the net debit. 

A trader will typically buy a vertical bull call spread when he is mildly bullish. Essentially, he gives up unlimited profit potential in return for reducing his risk. In a vertical bull call spread, the trader is expecting the spread premium to widen because the lower strike price call comes into the money first. 

Vertical spreads are the more common of the direction strategies, and they may be bullish or bearish to reflect the holder’s view of market’s anticipated direction. Bullish vertical put spreads are a combination of a long put with a low strike, and a short put with a higher strike. Because the short position is struck closer to-the-money, this generates a premium credit. 

Bearish vertical call spreads are the inverse of bullish vertical call spreads. They are created by combining a short call with a low strike and a long call with a higher strike. Bearish vertical put spreads are the inverse of bullish vertical put spreads, generated by combining a short put with a low strike and a long put with a higher strike. This is a bearish position taken when a trader or investor expects the market to fall. 

The bull or sell put spread is a type of vertical spread involving the purchase of a put option with the lower exercise price and sale of a put option with the higher exercise price. Theoretically, this is the same action that a bull call spreader would take. The difference between a call spread and a put spread is that the net result will be a credit transaction because the higher exercise price will have the higher premium. 

  • The maximum risk is the difference in the strike prices minus the net credit. 
  • The maximum profit potential equals the net credit. 
  • The breakeven equals the higher strike price minus the net credit. 

The bear or sell call spread involves selling the call option with the lower exercise price and buying the call option with the higher exercise price. The net result is a credit transaction because the lower exercise price will have the higher premium.

A bear put spread (or buy spread) involves selling some of the put option with the lower exercise price and buying the put option with the higher exercise price. This is the same action that a bear call spreader would take. The difference between a call spread and a put spread, however, is that the net result will be a debit transaction because the higher exercise price will have the higher premium. 

  • The maximum risk is equal to the net debit. 
  • The maximum profit potential is the difference in the strike
    prices minus the net debit. 
  • The breakeven equals the higher strike price minus the net debit.

An investor or trader would buy a vertical bear put spread because he or she is mildly bearish, giving up an unlimited profit potential in return for a reduction in risk. In a vertical bear put spread, the trader is expecting the spread premium to widen because the higher strike price put comes into the money first. 

In conclusion, investors and traders who are bullish on the market will either buy a bull call spread or sell a bull put spread. But those who are bearish on the market will either buy a bear put spread or sell a bear call spread. When the investor pays more for the long option than she receives in premium for the short option, then the spread is a debit transaction. In contrast, when she receives more than she pays, the spread is a credit transaction. Credit spreads typically require a margin deposit. 

Financial Fragility in the Margins. Thought of the Day 114.0

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If micro-economic crisis is caused by the draining of liquidity from an individual company (or household), macro-economic crisis or instability, in the sense of a reduction in the level of activity in the economy as a whole, is usually associated with an involuntary outflow of funds from companies (or households) as a whole. Macro-economic instability is a ‘real’ economic phenomenon, rather than a monetary contrivance, the sense in which it is used, for example, by the International Monetary Fund to mean price inflation in the non-financial economy. Neo-classical economics has a methodological predilection for attributing all changes in economic activity to relative price changes, specifically the price changes that undoubtedly accompany economic fluctuations. But there is sufficient evidence to indicate that falls in economic activity follow outflows of liquidity from the industrial and commercial company sector. Such outflows then lead to the deflation of economic activity that is the signal feature of economic recession and depression.

Let us start with a consideration of how vulnerable financial futures market themselves are to illiquidity, since this would indicate whether the firms operating in the market are ever likely to need to realize claims elsewhere in order to meet their liabilities to the market. Paradoxically, the very high level of intra-broker trading is a safety mechanism for the market, since it raises the velocity of circulation of whatever liquidity there is in the market: traders with liabilities outside the market are much more likely to have claims against other traders to set against those claims. This may be illustrated by considering the most extreme case of a futures market dominated by intra-broker trading, namely a market in which there are only two dealers who buy and sell financial futures contracts only between each other as rentiers, in other words for a profit which may include their premium or commission. On the expiry date of the contracts, conventionally set at three-monthly intervals in actual financial futures markets, some of these contracts will be profitable, some will be loss-making. Margin trading, however, requires all the profitable contracts to be fully paid up in order for their profit to be realized. The trader whose contracts are on balance profitable therefore cannot realize his profits until he has paid up his contracts with the other broker. The other broker will return the money in paying up his contracts, leaving only his losses to be raised by an inflow of money. Thus the only net inflow of money that is required is the amount of profit (or loss) made by the traders. However, an accommodating gross inflow is needed in the first instance in order to make the initial margin payments and settle contracts so that the net profit or loss may be realized.

The existence of more traders, and the system for avoiding counterparty risk commonly found in most futures market, whereby contracts are made with a central clearing house, introduce sequencing complications which may cause problems: having a central clearing house avoids the possibility that one trader’s default will cause other traders to default on their obligations. But it also denies traders the facility of giving each other credit, and thereby reduces the velocity of circulation of whatever liquidity is in the market. Having to pay all obligations in full to the central clearing house increases the money (or gross inflow) that broking firms and investors have to put into the market as margin payments or on settlement days. This increases the risk that a firm with large net liabilities in the financial futures market will be obliged to realize assets in other markets to meet those liabilities. In this way, the integrity of the market is protected by increasing the effective obligations of all traders, at the expense of potentially unsettling claims on other markets.

This risk is enhanced by the trading of rentiers, or banks and entrepreneurs operating as rentiers, hedging their futures contracts in other financial markets. However, while such incidents generate considerable excitement around the markets at the time of their occurrence, there is little evidence that they could cause involuntary outflows from the corporate sector on such a scale as to produce recession in the real economy. This is because financial futures are still used by few industrial and commercial companies, and their demand for financial derivatives instruments is limited by the relative expense of these instruments and their own exposure to changes in financial parameters (which may more easily be accommodated by holding appropriate stocks of liquid assets, i.e., liquidity preference). Therefore, the future of financial futures depends largely on the interest in them of the contemporary rentiers in pension, insurance and various other forms of investment funds. Their interest, in turn, depends on how those funds approach their ‘maturity’.

However, the decline of pension fund surpluses poses important problems for the main securities markets of the world where insurance and pension funds are now the dominant investors, as well as for more peripheral markets like emerging markets, venture capital and financial futures. A contraction in the net cash inflow of investment funds will be reflected in a reduction in the funds that they are investing, and a greater need to realize assets when a change in investment strategy is undertaken. In the main securities markets of the world, a reduction in the ‘new money’ that pension and insurance funds are putting into those securities markets will slow down the rate of growth of the prices in those markets. How such a fall in the institutions’ net cash inflow will affect the more marginal markets, such as emerging markets, venture capital and financial futures, depends on how institutional portfolios are managed in the period of declining net contributions inflows.

In general, investment managers in their own firms, or as employees of merchant or investment banks, compete to manage institutions’ funds. Such competition is likely to increase as investment funds approach ‘maturity’, i.e., as their cash outflows to investors, pensioners or insurance policyholders, rises faster than their cash inflow from contributions and premiums, so that there are less additional funds to be managed. In principle, this should not affect financial futures markets, in the first instance, since, as argued above, the short-term nature of their instruments and the large proportion in their business of intra-market trade makes them much less dependent on institutional cash inflows. However, this does not mean that they would be unaffected by changes in the portfolio preferences of investment funds in response to lower returns from the main securities markets. Such lower returns make financial investments like financial futures, venture capital and emerging markets, which are more marginal because they are so hazardous, more attractive to normally conservative fund managers. Investment funds typically put out sections of portfolios to specialist fund managers who are awarded contracts to manage a section according to the soundness of their reputation and the returns that they have made hitherto in portfolios under their management. A specialist fund manager reporting high, but not abnormal, profits in a fund devoted to financial futures, is likely to attract correspondingly more funds to manage when returns are lower in the main markets’ securities, even if other investors in financial futures experienced large losses. In this way, the maturing of investment funds could cause an increased inflow of rentier funds into financial futures markets.

An inflow of funds into a financial market entails an increase in liabilities to the rentiers outside the market supplying those funds. Even if profits made in the market as a whole also increase, so too will losses. While brokers commonly seek to hedge their positions within the futures market, rentiers have much greater possibilities of hedging their contracts in another market, where they have assets. An inflow into futures markets means that on any settlement day there will therefore be larger net outstanding claims against individual banks or investment funds in respect of their financial derivatives contracts. With margin trading, much larger gross financial inflows into financial futures markets will be required to settle maturing contracts. Some proportion of this will require the sale of securities in other markets. But if liquidity in integrated cash markets for securities is reduced by declining net inflows into pension funds, a failure to meet settlement obligations in futures markets is the alternative to forced liquidation of other assets. In this way futures markets will become more fragile.

Moreover, because of the hazardous nature of financial futures, high returns for an individual firm are difficult to sustain. Disappointment is more likely to be followed by the transfer of funds to management in some other peripheral market that shows a temporary high profit. While this should not affect capacity utilization in the futures market, because of intra-market trade, it is likely to cause much more volatile trading, and an increase in the pace at which new instruments are introduced (to attract investors) and fall into disuse. Pension funds whose returns fall below those required to meet future liabilities because of such instability would normally be required to obtain additional contributions from employers and employees. The resulting drain on the liquidity of the companies affected would cause a reduction in their fixed capital investment. This would be a plausible mechanism for transmitting fragility in the financial system into full-scale decline in the real economy.

The proliferation of financial futures markets has only had been marginally successful in substituting futures contracts for Keynesian liquidity preference as a means of accommodating uncertainty. A closer look at the agents in those markets and their market mechanisms indicates that the price system in them is flawed and trading hazardous risks in them adds to uncertainty rather than reducing it. The hedging of financial futures contracts in other financial markets means that the resulting forced liquidations elsewhere in the financial system are a real source of financial instability that is likely to worsen as slower growth in stock markets makes speculative financial investments appear more attractive. Capital-adequacy regulations are unlikely to reduce such instability, and may even increase it by increasing the capital committed to trading in financial futures. Such regulations can also create an atmosphere of financial security around these markets that may increase unstable speculative flows of liquidity into the markets. For the economy as a whole, the real problems are posed by the involvement of non-financial companies in financial futures markets. With the exception of a few spectacular scandals, non-financial companies have been wary of using financial futures, and it is important that they should continue to limit their interest in financial futures markets. Industrial and commercial companies, which generate their own liquidity through trade and production and hence have more limited financial assets to realize in order to meet financial futures liabilities in times of distress, are more vulnerable to unexpected outflows of liquidity in proportion to their increased exposure to financial markets. The liquidity which they need to set aside to meet such unexpected liabilities inevitably means a reduced commitment to investment in fixed capital and new technology.

Option Spread. Drunken Risibility.

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The term spread refers to the difference in premiums between the purchase and sale of options. An option spread is the simultaneous purchase of one or more options contracts and sale of the equivalent number of options contracts, in a different series of the class of options. A spread could involve the same underlying:

  •  Buying and selling calls, or
  •  Buying and selling puts.

Combining puts and calls into groups of two or more makes it feasible to design derivatives with interesting payoff profiles. The profit and loss outcomes depend on the options used (puts or calls); positions taken (long or short); whether their strike prices are identical or different; and the similarity or difference of their exercise dates. Among directional positions are bullish vertical call spreads, bullish vertical put spreads, bearish vertical spreads, and bearish vertical put spreads.

If the long position has a higher premium than the short position, this is known as a debit spread, and the investor will be required to deposit the difference in premiums. If the long position has a lower premium than the short position, this is a credit spread, and the investor will be allowed to withdraw the difference in premiums. The spread will be even if the premiums on each side results are the same.

A potential loss in an option spread is determined by two factors:

  • Strike price
  • Expiration date

If the strike price of the long call is greater than the strike price of the short call, or if the strike price of the long put is less than the strike price of the short put, a margin is required because adverse market moves can cause the short option to suffer a loss before the long option can show a profit.

A margin is also required if the long option expires before the short option. The reason is that once the long option expires, the trader holds an unhedged short position. A good way of looking at margin requirements is that they foretell potential loss. Here are, in a nutshell, the main option spreadings.

A calendar, horizontal, or time spread is the simultaneous purchase and sale of options of the same class with the same exercise prices but with different expiration dates. A vertical, or price or money, spread is the simultaneous purchase and sale of options of the same class with the same expiration date but with different exercise prices. A bull, or call, spread is a type of vertical spread that involves the purchase of the call option with the lower exercise price while selling the call option with the higher exercise price. The result is a debit transaction because the lower exercise price will have the higher premium.

  • The maximum risk is the net debit: the long option premium minus the short option premium.
  • The maximum profit potential is the difference in the strike prices minus the net debit.
  • The breakeven is equal to the lower strike price plus the net debit.

A trader will typically buy a vertical bull call spread when he is mildly bullish. Essentially, he gives up unlimited profit potential in return for reducing his risk. In a vertical bull call spread, the trader is expecting the spread premium to widen because the lower strike price call comes into the money first.

Vertical spreads are the more common of the direction strategies, and they may be bullish or bearish to reflect the holder’s view of market’s anticipated direction. Bullish vertical put spreads are a combination of a long put with a low strike, and a short put with a higher strike. Because the short position is struck closer to-the-money, this generates a premium credit.

Bearish vertical call spreads are the inverse of bullish vertical call spreads. They are created by combining a short call with a low strike and a long call with a higher strike. Bearish vertical put spreads are the inverse of bullish vertical put spreads, generated by combining a short put with a low strike and a long put with a higher strike. This is a bearish position taken when a trader or investor expects the market to fall.

The bull or sell put spread is a type of vertical spread involving the purchase of a put option with the lower exercise price and sale of a put option with the higher exercise price. Theoretically, this is the same action that a bull call spreader would take. The difference between a call spread and a put spread is that the net result will be a credit transaction because the higher exercise price will have the higher premium.

  • The maximum risk is the difference in the strike prices minus the net credit.
  • The maximum profit potential equals the net credit.
  • The breakeven equals the higher strike price minus the net credit.

The bear or sell call spread involves selling the call option with the lower exercise price and buying the call option with the higher exercise price. The net result is a credit transaction because the lower exercise price will have the higher premium.

A bear put spread (or buy spread) involves selling some of the put option with the lower exercise price and buying the put option with the higher exercise price. This is the same action that a bear call spreader would take. The difference between a call spread and a put spread, however, is that the net result will be a debit transaction because the higher exercise price will have the higher premium.

  • The maximum risk is equal to the net debit.
  • The maximum profit potential is the difference in the strike
    prices minus the net debit.
  • The breakeven equals the higher strike price minus the net debit.

An investor or trader would buy a vertical bear put spread because he or she is mildly bearish, giving up an unlimited profit potential in return for a reduction in risk. In a vertical bear put spread, the trader is expecting the spread premium to widen because the higher strike price put comes into the money first.

So, investors and traders who are bullish on the market will either buy a bull call spread or sell a bull put spread. But those who are bearish on the market will either buy a bear put spread or sell a bear call spread. When the investor pays more for the long option than she receives in premium for the short option, then the spread is a debit transaction. In contrast, when she receives more than she pays, the spread is a credit transaction. Credit spreads typically require a margin deposit.

High Frequency Traders: A Case in Point.

Events on 6th May 2010:

At 2:32 p.m., against [a] backdrop of unusually high volatility and thinning liquidity, a large fundamental trader (a mutual fund complex) initiated a sell program to sell a total of 75,000 E-Mini [S&P 500 futures] contracts (valued at approximately $4.1 billion) as a hedge to an existing equity position. […] This large fundamental trader chose to execute this sell program via an automated execution algorithm (“Sell Algorithm”) that was programmed to feed orders into the June 2010 E-Mini 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. The execution of this sell program resulted in the largest net change in daily position of any trader in the E-Mini since the beginning of the year (from January 1, 2010 through May 6, 2010). [. . . ] This sell pressure was initially absorbed by: high frequency traders (“HFTs”) and other intermediaries in the futures market; fundamental buyers in the futures market; and cross-market arbitrageurs who transferred this sell pressure to the equities markets by opportunistically buying E-Mini contracts and simultaneously selling products like SPY [(S&P 500 exchange-traded fund (“ETF”))], or selling individual equities in the S&P 500 Index. […] Between 2:32 p.m. and 2:45 p.m., as prices of the E-Mini rapidly declined, the Sell Algorithm sold about 35,000 E-Mini contracts (valued at approximately $1.9 billion) of the 75,000 intended. [. . . ] By 2:45:28 there were less than 1,050 contracts of buy-side resting orders in the E-Mini, representing less than 1% of buy-side market depth observed at the beginning of the day. [. . . ] At 2:45:28 p.m., trading on the E-Mini was paused for five seconds when the Chicago Mercantile Exchange (“CME”) Stop Logic Functionality was triggered in order to prevent a cascade of further price declines. […] When trading resumed at 2:45:33 p.m., prices stabilized and shortly thereafter, the E-Mini began to recover, followed by the SPY. [. . . ] Even though after 2:45 p.m. prices in the E-Mini and SPY were recovering from their severe declines, sell orders placed for some individual securities and Exchange Traded Funds (ETFs) (including many retail stop-loss orders, triggered by declines in prices of those securities) found reduced buying interest, which led to further price declines in those securities. […] [B]etween 2:40 p.m. and 3:00 p.m., over 20,000 trades (many based on retail-customer orders) across more than 300 separate securities, including many ETFs, were executed at prices 60% or more away from their 2:40 p.m. prices. [. . . ] By 3:08 p.m., [. . . ] the E-Mini prices [were] back to nearly their pre-drop level [. . . and] most securities had reverted back to trading at prices reflecting true consensus values.

In the ordinary course of business, HFTs use their technological advantage to profit from aggressively removing the last few contracts at the best bid and ask levels and then establishing new best bids and asks at adjacent price levels ahead of an immediacy-demanding customer. As an illustration of this “immediacy absorption” activity, consider the following stylized example, presented in Figure and described below.

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Suppose that we observe the central limit order book for a stock index futures contract. The notional value of one stock index futures contract is $50. The market is very liquid – on average there are hundreds of resting limit orders to buy or sell multiple contracts at either the best bid or the best offer. At some point during the day, due to temporary selling pressure, there is a total of just 100 contracts left at the best bid price of 1000.00. Recognizing that the queue at the best bid is about to be depleted, HFTs submit executable limit orders to aggressively sell a total of 100 contracts, thus completely depleting the queue at the best bid, and very quickly submit sequences of new limit orders to buy a total of 100 contracts at the new best bid price of 999.75, as well as to sell 100 contracts at the new best offer of 1000.00. If the selling pressure continues, then HFTs are able to buy 100 contracts at 999.75 and make a profit of $1,250 dollars among them. If, however, the selling pressure stops and the new best offer price of 1000.00 attracts buyers, then HFTs would very quickly sell 100 contracts (which are at the very front of the new best offer queue), “scratching” the trade at the same price as they bought, and getting rid of the risky inventory in a few milliseconds.

This type of trading activity reduces, albeit for only a few milliseconds, the latency of a price move. Under normal market conditions, this trading activity somewhat accelerates price changes and adds to the trading volume, but does not result in a significant directional price move. In effect, this activity imparts a small “immediacy absorption” cost on all traders, including the market makers, who are not fast enough to cancel the last remaining orders before an imminent price move.

This activity, however, makes it both costlier and riskier for the slower market makers to maintain continuous market presence. In response to the additional cost and risk, market makers lower their acceptable inventory bounds to levels that are too small to offset temporary liquidity imbalances of any significant size. When the diminished liquidity buffer of the market makers is pierced by a sudden order flow imbalance, they begin to demand a progressively greater compensation for maintaining continuous market presence, and prices start to move directionally. Just as the prices are moving directionally and volatility is elevated, immediacy absorption activity of HFTs can exacerbate a directional price move and amplify volatility. Higher volatility further increases the speed at which the best bid and offer queues are being depleted, inducing HFT algorithms to demand immediacy even more, fueling a spike in trading volume, and making it more costly for the market makers to maintain continuous market presence. This forces more risk averse market makers to withdraw from the market, which results in a full-blown market crash.

Empirically, immediacy absorption activity of the HFTs should manifest itself in the data very differently from the liquidity provision activity of the Market Makers. To establish the presence of these differences in the data, we test the following hypotheses:

Hypothesis H1: HFTs are more likely than Market Makers to aggressively execute the last 100 contracts before a price move in the direction of the trade. Market Makers are more likely than HFTs to have the last 100 resting contracts against which aggressive orders are executed.

Hypothesis H2: HFTs trade aggressively in the direction of the price move. Market Makers get run over by a price move.

Hypothesis H3: Both HFTs and Market Makers scratch trades, but HFTs scratch more.

To statistically test our “immediacy absorption” hypotheses against the “liquidity provision” hypotheses, we divide all of the trades during the 405 minute trading day into two subsets: Aggressive Buy trades and Aggressive Sell trades. Within each subset, we further aggregate multiple aggressive buy or sell transactions resulting from the execution of the same order into Aggressive Buy or Aggressive Sell sequences. The intuition is as follows. Often a specific trade is not a stand alone event, but a part of a sequence of transactions associated with the execution of the same order. For example, an order to aggressively sell 10 contracts may result in four Aggressive Sell transactions: for 2 contracts, 1 contract, 4 contracts, and 3 contracts, respectively, due to the specific sequence of resting bids against which this aggressive sell order was be executed. Using the order ID number, we are able to aggregate these four transactions into one Aggressive Sell sequence for 10 contracts.

Testing Hypothesis H1. Aggressive removal of the last 100 contracts by HFTs; passive provision of the last 100 resting contracts by the Market Makers. Using the Aggressive Buy sequences, we label as a “price increase event” all occurrences of trading sequences in which at least 100 contracts consecutively executed at the same price are followed by some number of contracts at a higher price. To examine indications of low latency, we focus on the the last 100 contracts traded before the price increase and the first 100 contracts at the next higher price (or fewer if the price changes again before 100 contracts are executed). Although we do not look directly at the limit order book data, price increase events are defined to capture occasions where traders use executable buy orders to lift the last remaining offers in the limit order book. Using Aggressive sell trades, we define “price decrease events” symmetrically as occurrences of sequences of trades in which 100 contracts executed at the same price are followed by executions at lower prices. These events are intended to capture occasions where traders use executable sell orders to hit the last few best bids in the limit order book. The results are presented in Table below

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For price increase and price decrease events, we calculate each of the six trader categories’ shares of Aggressive and Passive trading volume for the last 100 contracts traded at the “old” price level before the price increase or decrease and the first 100 contracts traded at the “new” price level (or fewer if the number of contracts is less than 100) after the price increase or decrease event.

Table above presents, for the six trader categories, volume shares for the last 100 contracts at the old price and the first 100 contracts at the new price. For comparison, the unconditional shares of aggressive and passive trading volume of each trader category are also reported. Table has four panels covering (A) price increase events on May 3-5, (B) price decrease events on May 3-5, (C) price increase events on May 6, and (D) price decrease events on May 6. In each panel there are six rows of data, one row for each trader category. Relative to panels A and C, the rows for Fundamental Buyers (BUYER) and Fundamental Sellers (SELLER) are reversed in panels B and D to emphasize the symmetry between buying during price increase events and selling during price decrease events. The first two columns report the shares of Aggressive and Passive contract volume for the last 100 contracts before the price change; the next two columns report the shares of Aggressive and Passive volume for up to the next 100 contracts after the price change; and the last two columns report the “unconditional” market shares of Aggressive and Passive sides of all Aggressive buy volume or sell volume. For May 3-5, the data are based on volume pooled across the three days.

Consider panel A, which describes price increase events associated with Aggressive buy trades on May 3-5, 2010. High Frequency Traders participated on the Aggressive side of 34.04% of all aggressive buy volume. Strongly consistent with immediacy absorption hypothesis, the participation rate rises to 57.70% of the Aggressive side of trades on the last 100 contracts of Aggressive buy volume before price increase events and falls to 14.84% of the Aggressive side of trades on the first 100 contracts of Aggressive buy volume after price increase events.

High Frequency Traders participated on the Passive side of 34.33% of all aggressive buy volume. Consistent with hypothesis, the participation rate on the Passive side of Aggressive buy volume falls to 28.72% of the last 100 contracts before a price increase event. It rises to 37.93% of the first 100 contracts after a price increase event.

These results are inconsistent with the idea that high frequency traders behave like textbook market makers, suffering adverse selection losses associated with being picked off by informed traders. Instead, when the price is about to move to a new level, high frequency traders tend to avoid being run over and take the price to the new level with Aggressive trades of their own.

Market Makers follow a noticeably more passive trading strategy than High Frequency Traders. According to panel A, Market Makers are 13.48% of the Passive side of all Aggressive trades, but they are only 7.27% of the Aggressive side of all Aggressive trades. On the last 100 contracts at the old price, Market Makers’ share of volume increases only modestly, from 7.27% to 8.78% of trades. Their share of Passive volume at the old price increases, from 13.48% to 15.80%. These facts are consistent with the interpretation that Market Makers, unlike High Frequency Traders, do engage in a strategy similar to traditional passive market making, buying at the bid price, selling at the offer price, and suffering losses when the price moves against them. These facts are also consistent with the hypothesis that High Frequency Traders have lower latency than Market Makers.

Intuition might suggest that Fundamental Buyers would tend to place the Aggressive trades which move prices up from one tick level to the next. This intuition does not seem to be corroborated by the data. According to panel A, Fundamental Buyers are 21.53% of all Aggressive trades but only 11.61% of the last 100 Aggressive contracts traded at the old price. Instead, Fundamental Buyers increase their share of Aggressive buy volume to 26.17% of the first 100 contracts at the new price.

Taking into account symmetry between buying and selling, panel B shows the results for Aggressive sell trades during May 3-5, 2010, are almost the same as the results for Aggressive buy trades. High Frequency Traders are 34.17% of all Aggressive sell volume, increase their share to 55.20% of the last 100 Aggressive sell contracts at the old price, and decrease their share to 15.04% of the last 100 Aggressive sell contracts at the new price. Market Makers are 7.45% of all Aggressive sell contracts, increase their share to only 8.57% of the last 100 Aggressive sell trades at the old price, and decrease their share to 6.58% of the last 100 Aggressive sell contracts at the new price. Fundamental Sellers’ shares of Aggressive sell trades behave similarly to Fundamental Buyers’ shares of Aggressive Buy trades. Fundamental Sellers are 20.91% of all Aggressive sell contracts, decrease their share to 11.96% of the last 100 Aggressive sell contracts at the old price, and increase their share to 24.87% of the first 100 Aggressive sell contracts at the new price.

Panels C and D report results for Aggressive Buy trades and Aggressive Sell trades for May 6, 2010. Taking into account symmetry between buying and selling, the results for Aggressive buy trades in panel C are very similar to the results for Aggressive sell trades in panel D. For example, Aggressive sell trades by Fundamental Sellers were 17.55% of Aggressive sell volume on May 6, while Aggressive buy trades by Fundamental Buyers were 20.12% of Aggressive buy volume on May 6. In comparison with the share of Fundamental Buyers and in comparison with May 3-5, the Flash Crash of May 6 is associated with a slightly lower – not higher – share of Aggressive sell trades by Fundamental Sellers.

The number of price increase and price decrease events increased dramatically on May 6, consistent with the increased volatility of the market on that day. On May 3-5, there were 4100 price increase events and 4062 price decrease events. On May 6 alone, there were 4101 price increase events and 4377 price decrease events. There were therefore approximately three times as many price increase events per day on May 6 as on the three preceding days.

A comparison of May 6 with May 3-5 reveals significant changes in the trading patterns of High Frequency Traders. Compared with May 3-5 in panels A and B, the share of Aggressive trades by High Frequency Traders drops from 34.04% of Aggressive buys and 34.17% of Aggressive sells on May 3-5 to 26.98% of Aggressive buy trades and 26.29% of Aggressive sell trades on May 6. The share of Aggressive trades for the last 100 contracts at the old price declines by even more. High Frequency Traders’ participation rate on the Aggressive side of Aggressive buy trades drops from 57.70% on May 3-5 to only 38.86% on May 6. Similarly, the participation rate on the Aggressive side of Aggressive sell trades drops from and 55.20% to 38.67%. These declines are largely offset by increases in the participation rate by Opportunistic Traders on the Aggressive side of trades. For example, Opportunistic Traders’ share of the Aggressive side of the last 100 contracts traded at the old price rises from 19.21% to 34.26% for Aggressive buys and from 20.99% to 33.86% for Aggressive sells. These results suggest that some Opportunistic Traders follow trading strategies for which low latency is important, such as index arbitrage, cross-market arbitrage, or opportunistic strategies mimicking market making.

Testing Hypothesis H2. HFTs trade aggressively in the direction of the price move; Market Makers get run over by a price move. To examine this hypothesis, we analyze whether High Frequency Traders use Aggressive trades to trade in the direction of contemporaneous price changes, while Market Makers use Passive trades to trade in the opposite direction from price changes. To this end, we estimate the regression equation

Δyt = α + Φ . Δyt-1 + δ . yt-1 + Σi=120i . Δpt-1 /0.25] + εt

(where yt and Δyt denote inventories and change in inventories of High Frequency Traders for each second of a trading day; t = 0 corresponds to the opening of stock trading on the NYSE at 8:30:00 a.m. CT (9:30:00 ET) and t = 24, 300 denotes the close of Globex at 15:15:00 CT (4:15 p.m. ET); Δpt denotes the price change in index point units between the high-low midpoint of second t-1 and the high-low midpoint of second t. Regressing second-by-second changes in inventory levels of High Frequency Traders on the level of their inventories the previous second, the change in their inventory levels the previous second, the change in prices during the current second, and lagged price changes for each of the previous 20 previous seconds.)

for Passive and Aggressive inventory changes separately.

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Table above presents the regression results of the two components of change in holdings on lagged inventory, lagged change in holdings and lagged price changes over one second intervals. Panel A and Panel B report the results for May 3-5 and May 6, respectively. Each panel has four columns, reporting estimated coefficients where the dependent variables are net Aggressive volume (Aggressive buys minus Aggressive sells) by High Frequency Traders (∆AHFT), net Passive volume by High Frequency Traders (∆PHFT), net Aggressive volume by Market Makers (∆AMM), and net Passive volume by Market Makers (∆PMM).

We observe that for lagged inventories (NPHFTt−1), the estimated coefficients for Aggressive and Passive trades by High Frequency Traders are δAHFT = −0.005 (t = −9.55) and δPHFT = −0.001 (t = −3.13), respectively. These coefficient estimates have the interpretation that High Frequency Traders use Aggressive trades to liquidate inventories more intensively than passive trades. In contrast, the results for Market Makers are very different. For lagged inventories (NPMMt−1), the estimated coefficients for Aggressive and Passive volume by Market Makers are δAMM = −0.002 (t = −6.73) and δPMM = −0.002 (t = −5.26), respectively. The similarity of these coefficients estimates has the interpretation that Market Makers favor neither Aggressive trades nor Passive trades when liquidating inventories.

For contemporaneous price changes (in the current second) (∆Pt−1), the estimated coefficient Aggressive and Passive volume by High Frequency Traders are β0 = 57.78 (t = 31.94) and β0 = −25.69 (t = −28.61), respectively. For Market Makers, the estimated coefficients for Aggressive and Passive trades are β0 = 6.38 (t = 18.51) and β0 = −19.92 (t = −37.68). These estimated coefficients have the interpretation that in seconds in which prices move up one tick, High Frequency traders are net buyers of about 58 contracts with Aggressive trades and net sellers of about 26 contracts with Passive trades in that same second, while Market Makers are net buyers of about 6 contracts with Aggressive trades and net sellers of about 20 contracts with Passive trades. High Frequency Traders and Market Makers are similar in that they both use Aggressive trades to trade in the direction of price changes, and both use Passive trades to trade against the direction of price changes. High Frequency Traders and Market Makers are different in that Aggressive net purchases by High Frequency Traders are greater in magnitude than the Passive net purchases, while the reverse is true for Market Makers.

For lagged price changes, coefficient estimates for Aggressive trades by High Frequency Traders and Market Makers are positive and statistically significant at lags 1-4 and lags 1-10, respectively. These results have the interpretation that both High Frequency Traders’ and Market Makers’ trade on recent price momentum, but the trading is compressed into a shorter time frame for High Frequency Traders than for Market Makers.

For lagged price changes, coefficient estimates for Passive volume by High Frequency Traders and Market Makers are negative and statistically significant at lags 1 and lags 1-3, respectively. Panel B of Table presents results for May 6. Similar to May 3-5, High Frequency Traders tend to use Aggressive trades more intensely than Passive trades to liquidate inventories, while Market Makers do not show this pattern. Also similar to May 3-5, High Frequency Trades and Market makers use Aggressive trades to trade in the contemporaneous direction of price changes and use Passive trades to trade in the direction opposite price changes, with Aggressive trading greater than Passive trading for High Frequency Traders and the reverse for Market Makers. In comparison with May 3-5, the coefficients are smaller in magnitude on May 6, indicating reduced liquidity at each tick. For lagged price changes, the coefficients associated with Aggressive trading by High Frequency Traders change from positive to negative at lags 1-4, and the positive coefficients associated with Aggressive trading by Market Makers change from being positive and statistically significant at lags lags 1-10 to being positive and statistically significant only at lags 1-3. These results illustrate accelerated trading velocity in the volatile market conditions of May 6.

We further examine how high frequency trading activity is related to market prices. Figure below illustrates how prices change after HFT trading activity in a given second. The upper-left panel presents results for buy trades for May 3-5, the upper right panel presents results for buy trades on May 6, and the lower-left and lower-right present corresponding results for sell trades. For an “event” second in which High Frequency Traders are net buyers, net Aggressive Buyers, and net Passive Buyers value-weighted average prices paid by the High Frequency Traders in that second are subtracted from the value-weighted average prices for all trades in the same second and each of the following 20 seconds. The results are averaged across event seconds, weighted by the magnitude of High Frequency Traders’ net position change in the event second. The upper-left panel presents results for May 3-5, the upper-right panel presents results for May 6, and the lower two panels present results for sell trades calculated analogously. Price differences on the vertical axis are scaled so that one unit equals one tick ($12.50 per contract).

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When High Frequency Traders are net buyers on May 3-5, prices rise by 17% of a tick in the next second. When HFTs execute Aggressively or Passively, prices rise by 20% and 2% of a tick in the next second, respectively. In subsequent seconds, prices in all cases trend downward by about 5% of a tick over the subsequent 19 seconds. For May 3-5, the results are almost symmetric for selling.

When High Frequency Traders are buying on May 6, prices increase by 7% of a tick in the next second. When they are aggressive buyers or passive buyers, prices increase by increase 25% of a tick or decrease by 5% of a tick in the next second, respectively. In subsequent seconds, prices generally tend to drift downwards. The downward drift is especially pronounced after Passive buying, consistent with the interpretation that High Frequency Traders were “run over” when their resting limit buy orders were “run over” in the down phase of the Flash Crash. When High Frequency Traders are net sellers, the results after one second are analogous to buying. After aggressive selling, prices continue to drift down for 20 seconds, consistent with the interpretation that High Frequency Traders made profits from Aggressive sales during the down phase of the Flash Crash.

Testing Hypothesis H3. Both HFTs and Market Makers scratch trades; HFTs scratch more. A textbook market maker will try to buy at the bid price, sell at the offer price, and capture the bid-ask spread as a profit. Sometimes, after buying at the bid price, market prices begin to fall before the market maker can make a one tick profit by selling his inventory at the best offer price. To avoid taking losses in this situation, one component of a traditional market making strategy is to “scratch trades in the presence of changing market conditions by quickly liquidating a position at the same price at which it was acquired. These scratched trades represent inventory management trades designed to lower the cost of adverse selection. Since many competing market makers may try to scratch trades at the same time, traders with the lowest latency will tend to be more successful in their attempts to scratch trades and thus more successful in their ability to avoid losses when market conditions change.

To examine whether and to what extent traders engage in trade scratching, we sequence each trader’s trades for the day using audit trail sequence numbers which not only sort trades by second but also sort trades chronologically within each second. We define an “immediately scratched trade” as a trade with the properties that the next trade in the sorted sequence (1) occurred in the same second, (2) was executed at the same price, (3) was in the opposite direction, i.e., buy followed by sell or sell followed by buy. For each of the trading accounts in our sample, we calculate the number of immediately scratched trades, then compare the number of scratched trades across the six trader categories.

The results of this analysis are presented in the table below. Panel A provides results for May 3-5 and panel B for May 6. In each panel, there are five rows of data, one for each trader category. The first three columns report the total number of trades, the total number of immediately scratched trades, and the percentage of trades that are immediately scratched by traders in five categories. For May 3-6, the reported numbers are from the pooled data.

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This table presents statistics for immediate trade scratching which measures how many times a trader changes his/her direction of trading in a second aggregated over a day. We define a trade direction change as a buy trade right after a sell trade or vice versa at the same price level in the same second.

This table shows that High Frequency Traders scratched 2.84 % of trades on May 3-5 and 4.26 % on May 6; Market Makers scratched 2.49 % of trades on May 3-5 and 5.53 % of trades on May 6. While the percentages of immediately scratched trades by Market Makers is slightly higher than that for High Frequency Traders on May 6, the percentages for both groups are very similar. The fourth, fifth, and sixth columns of the Table report the mean, standard deviation, and median of the number of scratched trades for the traders in each category.

Although the percentages of scratched trades are similar, the mean number of immediately scratched trades by High Frequency Traders is much greater than for Market Makers: 540.56 per day on May 3-5 and 1610.75 on May 6 for High Frequency Traders versus 13.35 and 72.92 for Market Makers. The differences between High Frequency Traders and Market Makers reflect differences in volume traded. The Table shows that High Frequency Traders and Market Makers scratch a significantly larger percentage of their trades than other trader categories.