Computing in Stock Market

Technology are applied everywhere in today's stock market including transactions, analysis, information, etc. The information about the stock market flows much faster than ever. Benefit from the technology improvement, the shortening of the period between a trade being initiated and complete, or the reduction of latency as it is known, is the ultimate aim of any stock exchange worth its salt.

• Equity: Equity in stock market represents the remaining interest in assets of a company, spread among individual shareholders of common or preferred stock
• Share: In financial markets, a share is a unit of account for various financial instruments including stocks (ordinary or preferential), and investments in limited partnerships
• Shares outstanding: Shares outstanding that have been authorized, issued, and purchased by investors and are held by them. They have voting rights and represent ownership in the corporation by the person that holds the shares.
• Float: float is what is actually has been sold to the public
• Market Capitalization: The market capitalization is the share price times the number of shares outstanding
  • Example: Apple has a market capitalization of roughly $600 billion based on almost 1 billion shares outstanding and a share price of $600
• Stock Exchange: Provide a secondary market where stockbrokers can buy and sell shares of companies listed on the exchange
  • Stockbrokers pay to be members
  • Companies pay to be listed
  • Example: NYSE, NASDAQ, Amsterdam, London, Paris, Singapore, Shanghai, Bombay, Tokyo, etc…
• Open Outcry: Traders call out and use hand signals on the “floor” of the exchange to indicate buy and sell requests
  • Still used in some commodity exchanges
  • Mostly replaced by electronic trading
• Day Trading: Buying and selling stocks – typically closing out positions on same day
  • Trading on speculation rather than company fundamentals
  • Example: Stock priced at $2 (last trade). Day trader bids $2.001 (at front of list of bids). Waits until others ask $2.01. Day trader asks $2.009 (at front of list of asks). Sells. Makes $0.008 profit - $80 (less commissions) on 10,000 shares. Can do this many times in a day.
  • Works if stock is not too actively traded or too price-volatile
  • Partially responsible for stock bubble in late 90s (dot-com boom)

Basically two ways:

1. Dividends: Company takes operating profit and pays part back to shareholders
2. Increase in share price(Can’t realize profit until shares are sold)

• Company can stop paying dividends or lower dividend amount (note that many companies don’t pay dividends)
• Share price can decrease
• Company can go bankrupt (shares become worthless)

• Helps economy
  • Companies can grow faster than otherwise possible
  • New companies can bring new products to market
  • Companies hire more people with investment
• In general, returns in stock market outperform other investments

Simple economics (supply and demand)

• If there are more buyers than sellers, price that buyers are willing to pay increases until sellers are willing to sell (buyers compete for limited supply)
• If there are more sellers than buyers, price that sellers are willing to take decreases until buyers are willing to buy (sellers compete for limited demand)

• Company earnings: Revenue, profit, change from one quarter to next
• Company events: Layoffs, store closings, scandals, executive firings, purchases of other companies, product announcements, drug approvals/denials, etc.
• Analyst recommendations (pro or con)
  • Example: Analyst says Apple will be at $1000/share within year; stock went from $500/share to $600/share within days
• Outside events
  • September 11 – Markets dropped significantly after reopening
  • European crisis with Greece

• Primary market
  • Companies sell stock initially to fund investment
  • IPO or secondary public offering
• Secondary market
  • Buying and selling of shares owned by public

• Open an account with a stockbroker
  • Full-service brokers
  • Discount brokers
• You place orders to buy/sell with your broker
• Broker executes trades at the exchange on your behalf

• Order to buy consists of number of shares and price bid
  • Price bid can be actual price (limit) or market (current price asked)
  • May bid for partial filling of order or “all-or-nothing” (only buy if I can get all the shares I want at the price I bid)
• Buying on margin uses current holdings as collateral for a loan to buy other stock (more risky)

• Order to sell consists of number of shares and price asked
  • Price asked can be actual price (limit) or market (current price bid)
  • May ask for partial filling of order or “all-or-nothing” (only sell if I can sell all the shares I have at the price I ask)
• Selling short is selling shares I don’t (yet) have with the intention of buying those shares when the price drops
  • If the price goes up instead of down… oops!

• The stock market matches buyers and sellers electronically
  • Transactions only happen when a buyer’s bid and a seller’s ask price are the same
• Brokers make money by charging a commission on each trade (typically both buyers and sellers pay)
• Brokers can also make money by aggregating trades
  • Seller has large “all-or-nothing” ask and broker has buyers for smaller lot sizes at market

• Immediate financial settlement
  • Before electronic trading, took 5-10 days when buying a stock before you could resell
  • Physical stock certificates were often sent to buyers
• Result was less trading volume, more holding stock for longterm investment, and less volatility

Yes.

• Programs make choices to buy and sell stocks for traders Can make decisions to trade and place orders almost instantaneously
• Can cause problems if algorithm bad (1987 stock market crash)
• Benefits large traders, often at expense of small traders

In automated trading milliseconds make a difference.

With algorithms trading, latency in getting price information is a big deal since price changes from time to time in milliseconds.

IPO - ¥610,000/share ($5041/share) of J-COM Trader wanted to sell 1 share at ¥610,000 Instead placed order to sell 610,000 shares at ¥1 each Loss to bank was 3 months profits J-COM ended up being 1/3 owned by Merrill Lynch Tokyo stock exchange lost 1.72%

Trader placed order typing ‘b’ instead of ‘m’ (billion vs. million) for number of shares Share price dropped $61.56 → $39.37 in 20 minutes NYSE dropped 600 points in 20 minutes (and recovered though still off almost 400 points for the day)

http://www.huffingtonpost.com/2012/04/18/mark-gorton-high-frequency-trading_n_1429935.html

The question at the heart of the current debate about high-frequency trading is whether the automation of trading – and in Tower's case, the ability to maximize profits by executing trades faster than anyone else – really does make the world better.

http://www.huffingtonpost.com/robert-auerbach/has-computer-trading-made_b_819664.html

Retail investors should also consider Jim McTague's advice about short-term stock trading: “It has become a shark tank and we are the anchovies.”

http://arstechnica.com/tech-policy/news/2009/08/nyse-builds-computer-trading-mothership-worries-abound.ars

For every technique or technology that comes under the heading of HFT, you can dig up an example of how people did this same thing on a much smaller scale without computers. Therefore, the argument goes, the relatively recent (see below) use of computers to do two orders of magnitude more of these activities in a given timeslice is “nothing new,” despite the fact that the computers are now doing this among themselves without human intervention.

http://prairieecothrifter.com/2011/08/major-problem-modern-day-stock-market.html

Investors should have learned this from the stock market crash in 2008, that there is a major flow in the modern stock markets. That flaw lies in computer algorithms and trading.

1. Is more technology good in this realm? What are the effects?
2. Does the potential for manipulation cause problems? If so, how can we fix so manipulation doesn’t occur?