Stock-index Arbitrage

Stock-index Arbitrage

Another form of program trading is called “stock-index arbitrage.” A position in a portfolio stocks is combined with an index futures contract with the objective of producing a perfectly hedged position and an abnormally large risk-free return. Arbitrage opportunities arise whenever the value of an index future and the value of the underlying security diverge.

The benefits of index arbitrage are twofold. First, by increasing trading in both underlying stocks and derivative products, liquidity in both markets is enhanced. Second, arbitrage trades link markets together and ensure that both the underlying securities and the derivative instruments are appropriately priced.

But have program trading and the use of derivative products increased volatility in the stock market? In part, the apparent increase in volatility is the result of a scale effect. A daily move of 50 points with the Dow Jones average near 2,500 is no greater than a 16-point move during the early 1980s with the Dow at 800. Through the end of the 1980s, all the worst point declines in the Dow Jones Industrial Average occurred during the 1986-89 time period. When the price changes are recast in terms of percentage changes, however, most of the worst days in the market all occurred over fifty years ago.

To be sure, October 19, 1987, holds the record in terms of single-day loss, measured either in points or as a percent. Friday, the 13th, October 1989, was also an unusually volatile day. And stock market volatility during the 1970s and 1980s was higher than during the 1950s and 1960s. But there are, I believe, good economic reasons for this increase in volatility. During the 1950s and 1960s, inflation remained very low and stable. Interest rates and bond prices moved very little. We had fixed and relatively stable exchange rates with our major trading partners. Economic activity was also near full employment.

The basic economic environment became far less stable by the 1970s and 1980s. Inflation accelerated and bond prices became more volatile, especially after the Federal Reserve abandoned its policy of iterest-rate smoothing. Moreover,exchange rates also became highly volatile as world capital markets became closely integrated so that it was possible to move billions of dollars among currencies almost instantaneously. Unemployment rates in the 1980s became more volatile too, reaching levels not experienced since the 1930s. Thus, basic economic uncertainty increased dramatically, affecting all markets. Finally, trading has become far more concentrated – being dominated by large institutional investors.

I am convinced that the general increase in volatility of financial markets compared with the 1950s and 1960s reflects this increase in basic economic uncertainty and the growing institutionalization of our markets. Products such as futures and options arise to cope with this increased uncertainty. They are used by professional investors to shift and control risk and to respond to market movements. This means that the growth of derivative products results from an attempt to cope with increased underlying volatility. Blaming derivative products and related program trading for the volatility in the stock market is as illogical as blaming the thermometer for measuring uncomfortable temperatures. And even if they do make the market more quickly responsive to changes in underlying conditions or the sentiment of large institutions, this is a sign of a well-functioning stock market, not an inefficient one. Eliminating new instruments and trading techniques would make our markets less efficient and risk seeing institutions develop to facilitate such trading abroad.

After the crash of 1929, legislation was introduced to prohibit the use of telephones to transmit margin orders. At the start of the 1990s, program trading was the target. But technology does not move markets, it merely facilitates the flow or orders. Program trading is not the mindless computer-driven technique that keeps the market from reflecting fundamental values. It reflects human decisions about the value of stocks, made easier to execute because of computers. If institutions decide to sell, they will do so whether by computers, telephones, or even hand signals from open window to brokers outside as was the case in earlier times.

A Fox. Photo by Elena

Obviously daily movements in the popular stock market indices that are large enough to catch newspaper headlines are upsetting, especially to the individual investor, who feels at the mercy of the large institutional traders. But should the wise investor then leave the stock market entirely, as some individuals have apparently decided? Absolutely not! To paraphrase a common expression, “if you can keep your head when those around you are losing theirs, you do understand the problem and know the best way to cope with it.” The long-term investor can and should ignore short-term market volatility. The losers from stock market volatility will be the institutions that trade frequently in a futile attempt to time the market, not steady individual investors who buy and hold for the long term.

Concluding Comments

I have emphasized that market valuations rest on both logical and psychological factors. The theory of valuation depends on the projection of a long-term stream of dividends whose growth rate is extraordinary difficult to estimate. Moreover, the appropriate risk premiums for common equities are changeable and far from obvious either to investors or to economists. Thus, there is room for the hopes, fears, and favorite fashions of market participants to play a role in the valuation process. Indeed, I emphasized how history provides extraordinary examples of markets in which psychology seemed to dominate the pricing process, as in the tulip-bulb mania in seventeenth-century Holland and the biotechnology boom in the late 1980s. Thus I harbor some doubts that we should consider that the current array of market prices always represents the best estimates available of appropriate discounted value.

Nevertheless, one has to be impressed with the substantial volume of evidence suggesting that stock prices display a remarkable degree of efficiency. Information contained in past prices or any publicly available fundamental information is rapidly assimilated into market prices. Prices adjust so well to reflect all important information that a randomly selected and passively managed portfolio of stocks performs as well as or better than the portfolios selected by the experts. If some degree of mispricing exists, it does not persist for long. “True value will always out” in the stock market. Moreover, whatever mispricing there is usually is only reconizable after the fact, just as we always know Monday morning the correct play the quarterback should have called.

Pricing irregularities may well exist and even persist for periods of time and markets can be influenced by fads and fashions. Eventually, however, any excesses in market valuations will be corrected. Undoubtedly, with the passage of time and with the increasing sophistication of our data bases and empirical techniques, we will document further departures from efficiency and be able to understand their causes more fully. But I suspect that the end result will not be an abandonment of the belief of many in the profession that the stock market is remarkably efficient in its utilization of information.

Burton G. Malkiel. A Random Walk Down Wall Street, including a life-cycle guide to personal investing. First edition, 1973, by W.W. Norton and company, Inc

Rates of Change

Rates of Change

By S.A. Corey (excerpt)

The footage of the accident plays on a little wall monitor in the medical center. The actual water had been too deep for natural light to find them, so the images have been enhanced, green and aquamarine added, shafts of brightness put in where a human eye – if it hadn‘t been crushed by the pressure – would have seen only darkness. The image capture has been done by a companion submarine to document the months-long trek, and either it was a calm day in the deep water or image processing has steadied it. Diana can imagine herself floating in the endless expanse of an ocean so vast it is like looking up at the stars. Karlo sits beside her, his hands knotted together, his eyes on the screen. The contrast between the squalid, tiny world of the medical center and the vast beauty on the screen disorients her.

The first of them swim into sight. A ray with wide gray wings, sloping through the salt water. With nothing to give a sense of scale, it could be larger than whales or hardly bigger than a human. There is no bump to show where the carapace holding a human brain and spine might have slotted into it. There is no scar to mark an insertion point. Another of the creatures passes by the camera, curving up the deep tides with grace and power. Then another. Then a dozen more. A school of rays. And one of them – she can’t begin to guess which – her son. In some other context, it might have been beautiful.

“It’s all right,” Karlo says, and she doesn’t know what he means by it. That the violence she was about to see had already happened, that she ought not be disturbed by the alien body that Stefan had chosen over his own, that her anger now won’t help. The words could carry anything.

A Gothic City. Photo by Elena

A disturbance strikes the rays, a shock moving through the group. The smooth cohesion breaks, and they whirl, turning one way and then the other. Their distress is unmistakable.

“What happened?” Karlo says. “What that it?”

“Be quiet,” Diana says. She leans forward, filling her view with the small screen like she might be able to dive through it. There in the center of the group, down below the camera, two of the rays swirl around each other, one great body butting into the other. A fight or a dance. She can’t read the intent in the movements. One breaks off, skimming wildly up, speeding through the gloom and the darkness. The other follows, and the floating camera turns to track them. As they chase each other, another shape slides into the frame, also high above. Another group of three alien bodies moving together, unaware of the chase rising up from below. The impact seems comical. The lead ray bumps into the belly of the middle of the three. The little camera loses focus, finds it again. Four rays swimming in a tight circle around one that lists on its side, its wings stilled and drifting.

That is my son, she thinks. That is Stefan. No emotions rise at the idea. It is absurd. Like seeing a rock cracked under a hammer or a car bent by a wreck: the symbol of a tragedy, but not the thing itself. It is some sea animal, something that belongs to the same world as sharks and angler fish. Inhuman. She knows it is her boy floating there, being pulled toward the surface by the emergency services pods, but she cannot make herself feel it.

“They attacked him,” she says, testing the words. Hoping that they will carry the outrage she wants to feel. “They attacked him, and they left him for dead.”

“They were playing and there was an accident,” Karlo says. “They didn’t leave him for dead.”

“They where are they? His friends, it that’s what you call them? I don’t see them here.”

“They can’t breath air,” Karlo says, as if that excuses everything. “They’ll come once the trip is over. Or, when he gets better, he can go back to them.”

Her breath leaves her. She turns to stare at him. His eyes, so unlike the ones she’d known when they had been married, cut to her and away again.

Trapping the Pleistocene

Trapping the Pleistocene

By James Sarafin (excerpt)

He could see the lighted tower, looming ever larger through occasional gaps in the trees, well before he arrived. An example of the newest footprint-reducing architecture, the tower was built like a giant morel: a tall, narrow cap with an irregular, ridged surface overhanging a smaller, round base. No, not a morel; if that tower was a mushroom, it had to be one of the poisonous varieties. From a hub level in the tower cap, the thin lines of skyways spread out in various directions. Like a giant spiderweb.

When he saw the government’s sign at the compound’s surface entrance, his foot went to the brake pedal and his hands twitched, wanting to turn the wheel back toward home. But he followed the entrance ramp into the compound. He drove through parklands where elk and camels grazed, over a creek, and the length of a small lake where swans swam in pairs, to arrive at a small paved area before a tower entrance. It held no other vehicles but looked as good as anyplace to park the truck, so he did. The outside of the tower base presented a rough, ridged surface with no windows or seams. He pulled his wool cap down over his forehead and raised his windows or seams. He pulled his wool cap down over his forehead and raised his hands to push open a door. He stumbled slightly when his hands met no resistance and he felt a puff of air as he passed through the non-existent door into the building. The lobby’s outer wall appeared to be made entirely of one-way glass that allowed a view of the compound outside. Or maybe he was only looking at video screens. It probably made no difference to the tower-dwellers.

The floor was covered with some mutated form of living grass that lay in a short, dense mat like a golf green. He gouged its surface with his boot-toe and watched it begin repairing itself. Imagine that crap growing over your foot, eh, Katie? From a wall of the tower’s core a waterfall trickled down and formed a stream that meandered across the floor to his left. A few of the dark-robed tower-dwellers strolled and loitered, communing with their view of the outdoors. Others scurried in or out of the elevators. They paid him no mind.

Trapping the Pleistocene. Photo by Elena

Jack had walked through the lobby, halfway around the tower’s core, when a voice growled his name from behind him. He turned and saw what looked like a cross between an orangutan and a human woman. She wore no clothing and was covered with straw-blonde hair, long but thin and with no underfur. Her face was bare ahead of her ears and heavily made-up. Her arms hung nearly to her knees and her breasts halfway to her waist; the breasts swung across her torso as she moved.

“Mr. Morgan, the director’s office is this way.” She smiled open-mouthed, displaying ivory canines. She seemed amused by his reaction.

“How do you know who I am?”

“We were expecting you. You’re not connected, so you’re the anomaly here.”

She turned and knuckle-walked to the nearest lift, wiggling her hips as she went. He moved to follow and almost fell on his face as a weight dragged on his right leg, the one with the bad knee. Some kind of cleaner robot had wheeled itself across the floor and was licking the half-dried mud off his boot. He licked to the hub floor, the one with the transit stations, where the skyways spread out like the spokes of a wheel. Caught in the spiderweb.

Machine Learning

Machine Learning

by Nancy Kress (excerpt)

Building 18 was devoted to machine learning. Ethan’s research partner, Jamie Peregoy, stood in their lab, welcoming this afternoon’s test subject, Cassie McAvoy. The little girl came with her mother every Monday, Wednesday, and Friday after school. Ethan took his place at the display console.

That end of the lab was filled with desks, computers, and messy folders of printouts. The other end held child-sized equipment: a musical keyboard, a video-game console, tables and chairs, blocks, and puzzles. The back wall was painted a supposedly cheerful yellow that Ethan fund garish. In the center, like a sentry in no-man’s land, stood a table with coffee and cookies.

“The problem with machine learning isn’t intelligence,” Jamie always said to visitors.” It’s defining intelligence. Is it intelligence to play superb chess, crunch numbers, create algorithms, carry on a conversation indistinguishable from a human gabfest? No. Turing was wrong. True intelligence requires the ability to learn for oneself, tackling new tasks you haven’t done before, and that requires emotion, and we learn best when emotional arousal is high. Can our Mape do that? No, she cannot.”

If visitors tried to inject something here, they were out of luck. Jamie would go into full-lecture mode, discoursing on the role of the hippocampus in memory retention, on how frontal-lobe injuries taught us that too little emotion, no how arousal levels were a better decision making as deeply as too much emotion, on how arousal levels were a better predictor of learning retention than whether the learning was positive or negative. Once Jamie got going, he was as unstoppable as a star running back, which was what he resembled. Young, brilliant, and charismatic, he practically glittered with energy and enthusiasm. Ethan went through periods where he warmed himself as Jamie’ inner fire, and other periods where he avoided Jamie for days at a time.

Machine Learning. Photo by Elena

MAIP, the MultiFuture Research Artificial Intelligence Program based in the company’s private cloud, could not play chess, could not feel emotion, and could only learn within defined parameters. Ethan, whose field was the analysis of how machine learning algorithms performed, believed that true AI was decades off, if ever. Did Jamie believe that? Hard to tell. When he spoke their program’s name, Ethan could hear that to Jamie it was a name, not an acronym. He had given MAIP a female voice. “Someday,” Jamie said, “she’ll smarter than we are.” Ethan had not asked Jamie to define “someday.”

The immediate, more modest goal was for MAIP to learn what others felt, so that MAIP could better assist their learning.

“Hello, Cassie, Mrs. McAvoy,” Jamie said, with one of his blinding smiles. Cassie, a nine-year-old in overalls and a t-shirt printed with kittens, smiled back. She was a prim little girl, eager to please adults. Well-mannered, straight A’s, teacher’s pet. “Never any trouble at home,” her mother had said, with pride. Ethan guessed she was not popular with other kids. But she was a valuable research subject, because MAIP had to learn to distinguish between genuine human emotions and “social pretense” – feeling expressed because convention expected it. When Cassie said, “I like you,” did she mean it?

“Ready for the minuet, Cassie?” Jamie asked.

“Yes.”

“Then let’s get started! Here’s your magic bracelet, princess!” He slipped it onto her thin wrist. Mrs. McAvoy took a chair at the back of the lab. Cassie walked to the keyboard and began to play Bach’s “Minuet in G,” the left-hand part of the arrangement simplified for beginners. Jamie moved behind her, where she could not see him. Ethan studied MAIP’s displays.

Sensors in Cassie’s bracelet measured her physiological responses: heart rate, blood pressure, respiration, skin conductance, and temperature. Tiny cameras captured her facial-muscle movement and eye saccades. They keyboard was wired to register the pressure of her fingers. When she finished the minuet, MAIP said, “That was good! But let’s talk about the way you arch your hands, okay, Cassie?” Voice analyzers measured Cassie’s responses: voice quality, timing, pitch. MAIP used the data to adjust the lesson: slowing down her instruction when Cassie seemed too frustrated, increasing the difficulty of what MAIP asked for when the child showed interest.

They moved on, teacher and pupil, to Bach’s “Polonaise in D.” Cassie didn’t know this piece as well. MAIP was responsive and patient, tailoring her comments to Cassie’s emotional data.

Inhuman Garbage

Inhuman Garbage

By Kristie Kathryn Rusch (excerpt)

Getting the crime scene unit to a warehouse outside of the dome took more work than Ethan Broduer liked to do. Fortunately, he was a deputy coroner, which meant he couldn’t control the crime scene unit. Someone with more seniority had to handle requisitioning the right vehicle from the Police Department yards outside the dome, and making certain the team had the right equipment.

Broduer came to the warehouse via train. The ride was only five minutes long, but it made him nervous.

He was born inside the dome, and he hated leaving it for any reason at all, especially for a reason involving work. So much of his work had to do with temperature and conditions, and if the body had been in an airless environment at all, it had an impact on every aspect of his job.

He war relieved when he arrived at warehouse and learned that the body had never gone outside of an Earth Normal environment. However, he was annoyed to see that he would be working with Noelle DeRicci.

She was notoriously difficult and demanding, and often asked coroners to redo something or double-check their findings. She’d caught him in several mistakes, which he found embarrassing.

Then she had had the gall to tell him that he should probably double-check all of his work, considering its shoddy quality.

Romantic Interlude. Photo by Elena

She stood next to a crate, the only one of thousands that was open. She was rumpled – she was always rumpled – and her curly black hair looked messier than usual.

When she saw him approach, she glared at him.

“Or, lucky me,” she said.

Broduer bit back a response. He’d been recording everything since he got off the train inside the warehouse’s private platform, and he didn’t want to show any animosity toward DeRicci on anything that might go to court.

“Just show me the body and I’ll get to work,” he said.

She raised her eyebrows at the word “work,” and she didn’t have to add anything to convey her meaning. She didn’t think Broduer worked at all.

“My biggest priority at the moment is an identification,” DeRicci said.

And his biggest priority was to do this investigation right. But he didn’t say that. Instead he looked at the dozen of crates spread out before him.

“Which one am I dealing with?” he asked, pleased that he could sound so calm in the face of her rudeness.

She placed a hand on the crate behind her. We was pleased to see that she wore gloves. He had worked with her partner Rayvon Lake before, and Lake had to be reminded to follow any kind of procedure.

But Broduer didn’t see Lake anywhere.

“Have you had cases involving the waste crates before?” DeRicci asked Broduer.

“No,” he said, not adding that he tried to pass anything outside the dome ont anyone else, “but I’ve heard about cases involving them. I guess it’s not that uncommon.”

“Hmm,” she said looking toward a room at the far end of the large warehouse. “And here I thought they were.”

Broduer was going to argue his point when he realized that DeRicci wan’t talking to him now. She was arguing with someone she had already spoken to.

“Can you get me information on that?” DeRicci asked Broduer.

He hated it when detectives wanted him to do their work for them. “It’s in the records.”

DeRicci made a low, growly sound, like he had irritaed her beyond measure.

So he decided to tewak her a bit more. “Just search for warehouses and recycling and crates -”

“I know,” she said. “I was hoping your office already had statistics.”

“I’m sure we do, Detective,” he said, moving past her, “but you want me to figure out what killed this poor creature, right? Not dig into old cases.”

“I think the old cases might be relevant,” she said.

He shrugged. He didn’t care what was or wasn’t relevant to her investigation. His priority was dealing with this body.

“Excuse me,” he said, and slipped on his favorite pair of gloves. Then he raised the lid on the crate