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Regardless of how an order gets generated or delivered, it passes through a risk management matrix This matrix is a series of risk management checks that an order undergoes before it is forwarded to the exchange We discussed earlier that the onus of getting the trades settled resides with the broker Any client default will have to be made good to the clearing corporation by the broker Credit defaults are thus undesirable from the point of view of the broker who puts money and credibility on the line on behalf of the customer Hence, these credit and risk management checks are deemed necessary Institutions are normally considered less risky than retail customers That is because they have a large balance sheet compared to the size of orders they want to place They also maintain a lot of collateral with the members they push their trades through.

The problem is that the select approach may be traditional and well understood, but it often.

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Their trades are hence subjected to fewer risk management checks than retail clients The mechanisms followed when orders are accepted and sent to exchanges for matching are the same for both institutions and retail clients However, for retail customers the orders are subjected to tighter risk management checks and scrutiny The underlying assumption in all such risk management checks is that retail clients are less credit worthy and hence more susceptible to defaulting than institutions A recent extension of retail trading has been trading through the Internet This exposes brokers to even more risk because the clients become faceless In the good old days of call and trade (receiving orders by phone), most brokers executed transactions of clients they knew With the advancement in trading channels, the process of account opening became more institutionalized, and the numbers came at the expense of client scrutiny.

Regardless of the particular server you plan to use, Seam requires a Java 5.0 runtime, at a minimum. You can t use any of the annotations provided by JBoss Seam, or by EJB 3.0, in a Java 1.4 environment. If your application server does not operate in a Java 5.0 environment or isn t certified in that environment, you might want to reconsider using Seam, or switch to a different application server to run your Seam applications.

Most brokers who operate on behalf of retail clients these days operate on the full-covered concept This means that while accepting orders from retail clients, they cover their risks as much as possible by demanding an equal value of cash or near cash securities We ll briefly cover how a retail transaction is conducted so you can understand the benefit provided by risk management The method utilized is more or less the same in call and trade as in Internet trading The order delivery mechanism changes, but the basic risk management principle implemented remains the same Here are the steps: 1 The client calls the broker to give the orders for a transaction (in Internet trading the client logs on to the Internet trading site, provides credentials, and enters orders) 2 The broker validates that the order is coming from a correct and reliable source..

requires the construction of state machines so appalling in their complexity that attempts to maintain such code can render one a gibbering wreck. Threaded servers allow for the more natural convention of state being tracked by the position in the code rather than a big data structure. Ruby provides us with a portable threading implementation (itself select based), so let s try that instead with Listing 8-16. Listing 8-16. A Simple Arithmetic Server (Thread Based) require "socket" server = TCPServer.new(34891) while (session = server.accept) Thread.new(session) do |s| command = s.readline.chomp if command =~ /^([\d\.]+) ([\+-\/\*]) ([\d\.]+)$/ x, y = $1.to_f, $3.to_f result = case $2 when "+" then x + y when "-" then x - y when "*" then x * y when "/" then y == 0 "inf" : x / y end s.puts "= #{result}" end s.close end end Hopefully you will notice that this is almost exactly the code from Listing 8-14 except that everything inside the accept has been wrapped in a spawned thread. This idea of wrapping repetitious parallel tasks in threads is applied quite commonly, particularly for network-bound operations. We might easily conceive of an operation that is very low bandwidth but takes a comparatively long time to complete, such as a five-packet ping of a host. Now imagine needing to get the ping status of each host in a list of 1,000. That operation will go much faster if we do 30 40 in parallel at any one time.

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