With my friend mathematician we are starting new group of algo traders and we are going to write some articles in this field. We wrote first article here, hope you will finde it helpfull, we will dive deeper in next articles of course: Algorithmic Trading: What it is and what strategies this modern form of trading hides Trading on the stock exchange — for many, a synonym for speed, risk and big wins or losses. But while some still imagine stockbrokers with a phone to their ear and a sweaty forehead, the world of finance has changed dramatically in recent years. Algorithmic trading came on the scene, which we could loosely translate as algorithmic trading. The term encompasses much more than just machines that buy and sell stocks. Let’s take a closer look and understand what strategies and approaches apply in this environment. What is algorithmic trading? Basically, it is the use of computer programs that carry out financial transactions based on predetermined rules. It sounds simple, but the reality is more complicated. Algorithms can be designed to analyze hundreds and thousands of data points in fractions of a second — something the human brain simply cannot do. Think of it as a trading bot that scans the market, identifies opportunities and makes decisions before you can even blink. But why did such a form of trading arise in the first place? The answer, of course, is efficiency. Algorithmic trading eliminates emotion from the equation and can trade with an accuracy that humans cannot achieve. High-Frequency Trading: The King of Algorithmic Strategies One of the most famous and at the same time the most controversial strategies in algorithmic trading is the so-called high-frequency trading (HFT). These algorithms operate at the millisecond level, buying and selling thousands of positions per day. Many critics argue that HFT can destabilize markets, as a large number of trades in such a short period of time can cause sudden price swings. HFT strategies are dominated by the use of fast connections and computer programs that react to minute changes in the market — for example, fluctuations in share prices, arbitrage between different exchanges or analysis of orders and their patterns. However, this strategy is accessible only to big players with a huge technological background. Trend Following: On the waves of the markets On the other side of the spectrum, we have trend following strategies, which, as the name suggests, are focused on tracking and following trends. These algorithms analyze historical data and try to predict whether a certain market movement will continue. If the algorithm identifies an uptrend, it can start buying; if the trend breaks and starts to decline, the algorithm sells. Trend following has its roots in classic trading and human strategies, but algorithms can elevate this tactic to a completely different level. Their advantage lies in the speed of reaction — by the time a person registers a change in trend, the algorithm can already be several steps ahead. Mean Reversion: Return to the mean One of the other strategies that is popular in algorithmic trading is the so-called mean reversion. This strategy assumes that the price of an asset that deviates from its average value over a period of time will sooner or later return to that average. Algorithms track market anomalies where the price deviates and initiate trades to profit from this deviation. This strategy can be surprisingly effective, especially in less volatile markets where deviations are more pronounced and less frequent. we will write next articles soon, more deeper about quantitative / algorithmic trading and investing problematics, if you want to join us (if you are mathematician, coder, scientist) feel free to write me comment we are coding our own strategies/systems as part time/hobby
yes but a.) it is not type of game where you have only 2-3 winners and all other are loosers (of course zero sum game but companies print new stocks/shares, new money are printed by banks etc) b.) big players have problems with liquidity for trading c.) i know people who started just 13 years ago and have much better results than quant traders who are 30 years in the game d.) for example look at Alex Gerko from XTX he is just 43 years old, some algo funds as you said are 40 years operating even before he was born. Now he is leader of algo trading and have better resutls than biggest companies, started from he bottom " garage" and was biggest tax payer in UK.
It is 2 or 3 winners. The rest are absorbed or leave. Xtx was not started from a garage but from a PhD from Deutsche bank.. big players provide the liquidity. It's mainly market making and relative value
I know at least 40 sucesfull algo trading / quant funds and at least 100 hedge funds that are making hundreds of millions every year. Then why you trade / invest?
Are you referring to trading or investing. Funds or hft shops. Yes, there are many funds investing other people's money, taking a cut, and delivering sub par returns. As for trading firms, they consolidate and there are a few good ones left
both, also investing funds use very often quantitative approach, btw investing vs trading difference is just timeframe - how long you hold trades Some funds hold for seconds, some for days, some for weeks, some for months and some for many years and yes regarding alex and deutche bank, it wasnt that they gave him information, strategy, knowledge etc. do you know the story behind? he gave them strategy in relatively short time