From trading to technical trading, algorithmic trading and HFT trading

Let us go back a little bit and try to look at this phenomenon in the context of the current situation. Financial markets, particularly stock markets, stimulate buying and selling of financial instruments - contracts that give a right for a gradual withdrawal of funds. Different players can be involved in these markets at different times. On the one hand, there are large investment institutions such as pension funds. From time to time they enter the market and make large investments, buying up large numbers of shares, often to hold them for several years. On the other hand, there are fast, less permanent players - we call them traders - who make their money by getting in and out of the market quickly, like nimble sharks swimming between packs of large whales. However, there are several types of trading. If you want to imagine how high-frequency trading came about: To begin with, understand the basic idea behind trading: Financial traders engage in buying and selling financial instruments, such as shares of certain companies. They hope to buy them at a better price so that they can sell them at a higher price, thus making a profit on the transaction.To do this, they use trading robots, reviews of which can be found at https://scammerwatch.com/. Now try to understand technical trading: Traders use a variety of speculation techniques. For example, they may spend hours studying the archives of a certain company. This method is called fundamental trading. They can also analyze the activity of other players in the market and make a decision accordingly. This "technical analysis" of data about prices, orders and volumes of trades made by other traders is the basis of technical trading. Then imagine how this process can be automated: The process of technical trading can be automated, for example, by developing an algorithm that analyses the incoming stream of price, order and trade volume data and, under certain conditions, executes trades. We call this process algorithmic trading. (Note: you can find a difference between algorithmic and automated trading, but for convenience, we will assume that it is the same). Now imagine how this process is accelerated: If you "accelerate" the process of automated/algorithmic trading to high speeds, you get high-frequency trading. Thus, it is easiest to think of HFT trading as very fast algorithmic trading, which is automated technical trading, which in turn is a kind of trading in general. It can be compared, for example, to the slower fundamental trading practised by specialists like George Soros (he and his analysts monitor everything that happens in the world from his office, and then make predictions on certain events). In the end, do not forget that the whole world of trading can be compared to the world of long-term investing, which is exactly what large pension funds do. To return to the sea-animal analogy, HFT companies are piranhas swimming alongside sharks and whales. Pumping up your algorithm Each firm has its own strategy. Some use statistical analysis and various arbitrage techniques, while others use their knowledge of "market microstructure", which supposedly consists of understanding the technical aspects of exchange systems and exploiting them for profit. Some people in turn engage in flash trading, which is said to be a legitimate game of front-running. You might also be flooding the market with order stuffing (a tactic that Dave Lauer, an HFT whistle-blower, calls a financial DDoS attack). You might use layering, perhaps to induce "momentum ignition," which is considered a type of easy market manipulation. Some use aggressive trading strategies designed to cautiously follow trends and exploit opportunities while others are more passive, such as electronic Aikido bots that use minimal energy. If you are interested in some of the strategies, I recommend reading this article by Irene Aldridge. This material may also prove useful. By the way, if you want to understand the nature and essence of this phenomenon, it is always useful to read discussions on technical forums for professional financial experts like Wilmott forums. These experts keep up with the latest news from the world of finance and tend to know the field down to the last detail. How does it all work? High-frequency trading is for the most part just an accelerated version of arbitrage, which is either in the futures market or in stocks traded on the over-the-counter market and sold/re-acquired. In this case, all or most of the income is generated by bonuses earned on share prices. Some firms perform momentum trading at a few milliseconds: when these firms know someone is about to place their orders, they place them first (since they have a speed advantage), move the market up one cent and then make a sell transaction with the original buyer... In addition, they can use flash orders to jump over larger bids. Some go into more accounting detail to make more profitable trades. There are several other strategies used when dealing in securities: some companies study options markets and arbitrage using delta hedgers... Most strategies have more to do with the microstructure of the markets than with mathematics... HFT organisations operate at ultra-high speeds: they can place several million orders a day, depending on the number of markets and trading activity. These companies require very good C++ programming skills, knowledge of API development, minimal knowledge of computer architecture, e.g. how to bypass stack protection and apply the so-called kernel trick. They also need LAN/WAN specialists who can help transfer data to the network a few microseconds faster. Such companies use expensive specialised equipment. A typical switch with a decent speed will cost 50 thousand dollars. The information held by HFT organizations is available to all traders. The only difference is that these organizations have time to use that information in a trade before it is on your computer; the only difference is how fast they receive it and act on it. The latency of their networks and computers is not even milliseconds, but microseconds.