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  • High Frequency Proprietary Trading 0 comments
    May 7, 2013 3:10 PM

    Proprietary Trading occurs when a firm or individual trades securities risking their own capital for profits as opposed to profiting from commission dollars by processing trades on behalf of the clients of the firm (U.S. Securities and Exchange Commission, 2008). Some of the underlying technologies contributing to high frequency trading include user-friendly Application Programming Interfaces (APIs) allowing for trading strategies to be automated based on input data criteria (Kim, 2007, P. 23)

    In order to understand the scope of the activities which can be defined as proprietary trading, we must first identify the structure of the US securities markets and financial services firm. The underlying securities-related organizations which make up the infrastructure of the financial services market are exchanges which contain multiple markets, both primary and secondary in which sellers offer shares or contracts for sales and buyers, commonly referred to as bidders, bid for ownership of the underlying securities (Gehm, 2008). These industries started on the streets of New York & Chicago and have now progressed to digital systems matching bids & offers. Some examples of exchanges are the NASDAQ, NYSE, AMEX, CME and LSE (Gehm, 2008).

    An exchange is an organization, which allows transactions of financial products to occur in an orderly manner and in a centralized location (physical or virtual) (Gutmann, 2008) Stock exchanges are the most widely known example. The New York Stock Exchange (NYSE) and the National Association of Securities Dealer Automated Quotation (NASDAQ) are the two most important stock exchanges in the United States. (Jarrow, 2011)

    For future contract exchanges, The Chicago Mercantile Exchange (CME) is the leading exchange. (Gutmann, 2008) Most proprietary trading firms have access to some or all previously mentioned US exchanges but also access to the London Stock Exchange which is the most important stock exchange in Europe. Other markets include Euronext and the Toronto Stock Exchange.

    A market is the consolidation of exchanges or transactions in a specific financial product. For example the US stock market is the consolidation of all the transactions happening in the stocks exchanges in United States. Other popular markets are the futures market and the options market which together can be called the derivatives market. (Gutmann, 2008)

    Exchanges are generally divided into two divisions: primary and secondary markets. The primary market is for new issues of securities, as distinguished from the secondary market, where previously issued securities are bought and sold. A market is primary if the proceeds of the sales go to the issuer of the securities sold.

    There is no physical or virtual defined location for the primary market. The transactions are rather happening between investment banks and institutional investors. (Benoit, 2012) Once all the transactions for an issue are completed on the primary market, there is what we call an Initial Public Offering (IPO) and the stocks start trading on the secondary market. (Jarrow, 2011)

    The recent public concern over proprietary trading activities mostly revolve around institutional order manipulation using algorithms to make split-second decisions and outpace the opportunities for less sophisticated investors while increasing volatility in the market. Generally, the way this is accomplished is through order-manipulation. (Jarrow, 2011). Weston (2000) contends this idea: "The competitiveness of dealer and auction markets has recently become a contentious debate in both political and academic spheres. Proponents of dealer markets such as the Nasdaq argue that competition for order flow between market makers reduces transaction costs. Moreover, the ease of entry and exit in dealer markets may also contribute to lower trading costs. Conversely, proponents of auction market systems argue that expositing limit orders to the public lowers trading costs by allowing investors to trader with each other directly."

    Participating firms and investors place requests or advertisement with the intention to buy or sell a specific financial product. An order identifies the terms relative to price, quantity and conditions in which it needs to be matched. An order is said to be open or pending until it is matched with an opposite order. An open order can normally be cancelled by the sender. (Gutmann, 2008) For example, if you sent a request to buy 1000 shares of MSFT at 24.50 this is considered to be a buy order on MSFT. A buy order is called a bid and a sell order is called an offer. The best bid and offer on a stock from all participants is called the NBBO (highest bid and lowest offer).

    New York University's leading high-frequency trading expert Uri Aboutboul notes "Contrary to arbitrageurs who make financial markets more efficient by taking advantage of and thereby eliminating mispricings, high frequency traders can create a mispricing that they unknowingly exploit to the disadvantage of ordinary investors. This mispricing is generated by the collective and independent actions of high frequency traders, coordinated via the observation of a common signal."

    There are five considerations investors and/or firms need to think about when sending an order and they are: side (is it a buy or a sell), size (the amount of shares), route (is is a NYSE or NASDAQ stock), ticker (the stock's symbol) and condition (is it a fill or cancel order) . (Gehm, 2008)

    An order becomes a transaction when it matches with another order that can fulfill its conditions (a sell order matching a buy order). In this case we say that the order has been filled or executed. Therefore a transaction, which is also called a trade, always has a buy side and a sell side. From the previous example if somebody else sends an order to sell 1000 MSFT at 24.50 then a transaction is recorded and both orders are filled. If the sell order would only be for 500 shares then the buy order of 1000 shares would be partially filled and 500 shares would still be open (standing as a pending order). (Gehm, 2008)

    By convention we say that a trader is buying when he buys from the offer (also referred as taking the offer); and biding when he place a buy order below the best offer. In the same manner, we say that he is selling if he places a sell order at the bid price (also referred as hitting the bid); and offering if he is offering above the best bid (Gehm, 2008). Algorithmic trading systems such as automated high-frequency trading systems (often referred to as a blackbox in trading jargon) have the ability to view the order flow through their market-making activities and therefore raise the average bid, displacing investors waiting to have orders filled as well as causing the illusion of volume which does not accurately represent the true bid price of the underlying security in question (Narang, 2009). Further identification of the multiple types of orders poses a question, what other type of influence can market-makers have on the price of underlying securities as a result of using multiple order types.

    There are multiple ways A limit order is an order to buy/sell at a specific price or lower/higher. Execution can happen at the price specified or at a better price (rarely). Price improvements happen more on the NYSE at the open or the close because the specialist is going to find a price that can match the most orders Limit orders are standing in the market if they are not executed. They will be only filled if a match with another order can be made. Limit orders are popular among algorithmic trading systems because they limit the risk of errors. (Kim, 2007)

    A market order is an order to buy or sell a security at the best price available. Market buy orders are filled against available limit order in the market. Market orders can be very dangerous for many reasons. One big concern is the trader has no control over what price they get. In some case dishonest Market Makers and dealers could cancel and move their limit orders if they see a big order coming in.

    Also, it is important to note there is a big difference between buying/selling 1000 shares and 10000 shares but sometimes it is easy to mistakenly enter an extra 0. Those are called keystroke errors and they happen all the time in the market.

    If you own stocks, you are said to be long that stock. For example if you send a buy order on 1000 Shares of MSFT and get filled, you are now long 1000 share (assuming you had no previous trades/transaction in MSFT); however, it is also possible when you trade to sell stocks that you don't own. This is often referred to as "shorting". The investor or firm trading the security are borrowing it with the intention to sell it on the market and buy it later at a lower price (obviously if the stock goes up, they will be paying a higher price to buy it back and therefore lose money on the operation). (Gehm, 2008)

    When selling stocks that are not owned by the investor or firm selling them, a negative position in that stock is created and the firms are said to be in a "short" position. For example if you send a short order of 1000 Shares of MSFT and get filled, you are now short 1000 share (assuming you had no previous trades/transaction in MSFT). You now have -1000 shares in your possession.

    Short selling in an important tool for market-makers and proprietary trading firms, because they allow traders to take advantage of a declining stock/future price (sell high, buy low). Since stock prices fluctuate every day, if a trader can only go long, he or she will miss out on at least half of the opportunities to profit on each business day. (Gehm, 2008)

    Despite its popularity amongst proprietary traders, most of the investing public does not know about short selling. This results in a long bias towards investments. Trading firms have more knowledge than the general public in this area. This paper aims to identify the disadvantages high-frequency trading systems (sometimes referred to as ATS or Automated Trading Systems) as used by financial institutions doing business with the organizations selling their stock on an exchange pose to investors and what can be done to remedy this.

    Throughout the day securities inventory/position will constantly change. It varies from a positive amount of shares that the firm owns to a negative amount of shares which they are short of. When there is no inventory or no position the term in the trading jargon is that you are flat. (Gehm, 2008). Therefore, if you had no execution on a stock you are said to be flat. The concept of Long/Short and Flat is fundamental to trading.

    Many questions remain unanswered regarding the use of algorithmic trading systems in financial institutions. Some of the questions this paper aims to answer are: What are the restrictions, liabilities and income sources of proprietary trading firms?; How do Electronic Communications Networks and Dark-pools function?; What are the implications of the proposed legislation regarding high frequency trading on the access to liquid markets by retail investors?

    References

    24, O. (n.d.). SEC Charges Goldman Sachs With Fraud in Structuring and Marketing of CDO Tied to Subprime Mortgages; 2010-59; April 16, 2010. U.S. Securities and Exchange Commission (Home Page). Retrieved February 13, 2012, from sec.gov/news/press/2010/2010-59.htm

    Banks Gear Up for a Battle - WSJ.com. (n.d.). Business News & Financial News - The Wall Street Journal - Wsj.com. Retrieved February 13, 2012, from online.wsj.com/article/SB100014240527487...

    Benoit, D. (n.d.). Volcker on Volcker: The Letter From Paul - Deal Journal - WSJ. WSJ Blogs - WSJ. Retrieved February 13, 2012, from blogs.wsj.com/deals/2012/02/13/volcker-o.../

    Gehm, F. (2010). The lowdown on high frequency trading. Futures Magazine Group, 39(5).

    Guide to Broker-Dealer Registration (April 2008). (n.d.). U.S. Securities and Exchange Commission (Home Page). Retrieved February 13, 2012, from www.sec.gov/divisions/marketreg/bdguide.htm

    Gutmann, M. (2008). Automated high frequency retail trading. Futures Magazine Group, 37(11). Retrieved March, 2012.

    Jarrow, Robert A. and Protter, Philip, A Dysfunctional Role of High Frequency Trading in Electronic Markets (June 29, 2011). Johnson School Research Paper Series No. 08-2011.

    Kim, K. (2007). Electronic and algorithmic trading technology: The complete guide. Amsterdam: Academic Press, an imprint of Elsevier.

    Narang, R. K. (2009). Chapter 1. In Inside the black box: The simple truth about quantitative trading. Hoboken, NJ: Wiley.

    Weston, J. (2000). Competition on the Nasdaq and the Impact of Recent Market Reforms. The Journal of Finance, 55(6).

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