ced5a5f5e9 Market making involves placing a limit order to sell (or offer) above the current market price or a buy limit order (or bid) below the current price on a regular and continuous basis to capture the bid-ask spread. Traders may, for example, find that the price of wheat is lower in agricultural regions than in cities, purchase the good, and transport it to another region to sell at a higher price. Researchers showed high-frequency traders are able to profit by the artificially induced latencies and arbitrage opportunities that result from quote stuffing.[61]. What was needed was a way that marketers (the "sell side") could express algo orders electronically such that buy-side traders could just drop the new order types into their system and be ready to trade them without constant coding custom new order entry screens each time. Suppose a trader desires to sell shares of a company with a current bid of $20 and a current ask of $20.20.
Algorithmic trades require communicating considerably more parameters than traditional market and limit orders. At about the same time portfolio insurance was designed to create a synthetic put option on a stock portfolio by dynamically trading stock index futures according to a computer model based on the BlackScholes option pricing model. In late 2010, The UK Government Office for Science initiated a Foresight project investigating the future of computer trading in the financial markets,[80] led by Dame Clara Furse, ex-CEO of the London Stock Exchange and in September 2011 the project published its initial findings in the form of a three-chapter working paper available in three languages, along with 16 additional papers that provide supporting evidence.[81] All of these findings are authored or co-authored by leading academics and practitioners, and were subjected to anonymous peer-review. This is of great importance to high-frequency traders, because they have to attempt to pinpoint the consistent and probable performance ranges of given financial instruments. A special class of these algorithms attempts to detect algorithmic or iceberg orders on the other side (i.e. It provides multi-threading for work items of the provider process . Example: One of the most popular Arbitrage trading opportunities is played with the S&P futures and the S&P 500 stocks.
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