Metodologia de tranzacționare de înaltă frecvență

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Early developments[ edit ] Computerization of the order flow in financial markets began in the early s, when the New York Stock Exchange introduced the "designated order turnaround" system DOT.

Both systems allowed for the routing of orders electronically to the proper trading post. In practice, program trades were pre-programmed to automatically enter or metodologia de tranzacționare de înaltă frecvență trades based on various factors.

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 Black—Scholes option pricing model. Both strategies, often simply lumped together as "program trading", were blamed by many people for example by the Brady report for exacerbating or even starting the stock market crash.

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Yet the impact of computer driven trading on stock market crashes is unclear and widely discussed in the academic community. These average price benchmarks are measured and calculated by computers by applying the time-weighted average price or more usually by the volume-weighted average price.

It is over. The trading that existed down the centuries has died. We have an electronic market today.

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It is the present. It is the future. These strategies are more easily implemented by computers, because machines can react more rapidly to temporary mispricing and examine prices from several markets simultaneously.

Chameleon developed by BNP ParibasStealth [19] developed by the Deutsche BankSniper and Guerilla developed by Credit Suisse [20]arbitragestatistical arbitragetrend followingand mean reversion are examples of algorithmic trading strategies.

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In MarchVirtu Financiala high-frequency trading firm, reported that during five years the firm as a whole was profitable on 1, out of 1, trading days, [23] losing money just one day, demonstrating the possible benefit of trading thousands to millions of trades every trading day. Percentage of market volume.

Securities and Exchange Commission and the Commodity Futures Trading Commission said in reports that an algorithmic trade entered by metodologia de tranzacționare de înaltă frecvență mutual fund company triggered a wave of selling that led to the Flash Crash.

As a result of these events, the Dow Jones Industrial Average suffered its second largest intraday point swing ever to that date, though prices quickly recovered. A July report by the International Organization of Securities Commissions IOSCOan international body of securities regulators, concluded that while "algorithms and HFT technology have been used by market participants to manage their trading and risk, their usage was also clearly a contributing factor in the flash crash event of May 6, Unlike in the case of classic arbitrage, in case of pairs trading, the law of one price cannot guarantee convergence of prices.

This is especially true when the strategy is applied to individual stocks — these imperfect substitutes can in fact diverge indefinitely.

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In theory the long-short nature of the strategy should make it work regardless of the stock market direction. In practice, execution risk, persistent and large divergences, as well as a decline in volatility can make this strategy unprofitable for long periods of time e. It belongs to wider categories of statistical arbitrageconvergence tradingand relative value strategies.

Such a portfolio typically contains options and their corresponding underlying securities such that positive and negative delta components offset, resulting in the portfolio's value being relatively insensitive to changes in the value of the underlying security. When used by academics, an arbitrage is a transaction that involves no negative cash flow at any probabilistic or temporal state and a positive cash flow in at least one state; in simple terms, it is the possibility of a risk-free profit at zero cost.

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During most trading days these two will develop disparity in the pricing between the two of them. Conditions for arbitrage[ edit ] Further information: Rational pricing § Arbitrage mechanics Arbitrage is possible when one of three conditions is met: The same asset does not trade at the same price on all markets the " law of one price " is temporarily violated. Two assets with identical cash flows do not trade at the same price. An asset with a known price in the future does not today trade at its future price discounted at the risk-free interest rate or, the asset does not have negligible costs of storage; as such, for example, this condition holds for grain but not for securities.

Arbitrage is not simply the act of buying a product in one market and selling it in another for a higher price at some later time. The long and short transactions should ideally occur simultaneously to minimize the exposure to market risk, or the risk that prices may change on one market before both transactions are complete.

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In practical terms, this is generally only possible with securities and financial products which can be traded electronically, and even then, when first leg s of the trade is executed, the prices in the other legs may have worsened, locking in a guaranteed loss.

Missing one of the legs of the trade and subsequently having to open it at a worse price is called 'execution risk' or more specifically 'leg-in and leg-out risk'. 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.

This type of price arbitrage is the most common, but this simple example ignores the cost of transport, storage, risk, and other factors.

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Where securities are traded on more than one exchange, arbitrage occurs by simultaneously buying in one and selling on the other. Such simultaneous execution, if perfect substitutes are involved, minimizes capital requirements, but in practice never creates a "self-financing" free position, as many sources incorrectly assume following the theory. As long as there is some difference in the market value and riskiness of the two legs, capital would have to be put up in order to carry the long-short arbitrage position.

Mean reversion[ edit ] Mean reversion is a mathematical methodology sometimes used for stock investing, but it can metodologia de tranzacționare de înaltă frecvență applied to other processes. In general terms the idea is that both a stock's high and low prices are temporary, and that a stock's price tends to have an average price over time.

An example of a mean-reverting process is the Ornstein-Uhlenbeck stochastic equation.

Algorithmic trading

Mean reversion involves first identifying the trading range for a stock, and then computing the average price using analytical techniques as it relates to assets, earnings, etc. When the current market price is less than the average price, the stock is considered attractive for purchase, with the expectation that the price will rise.

When the current market price is above the average price, the market price is expected to fall. In other words, face bani online câștiga bani fără probleme from the average price are expected to revert to the average.

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The standard deviation of the most recent prices e. Stock reporting services such as Yahoo! Finance, MS Investor, Morningstar, etc.

While reporting services provide the averages, identifying the high and low prices for the study period is still necessary.

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