In finance, a trading strategy is a fixed plan that is designed to achieve a profitable return by going long or short in markets. The main reasons that a properly researched trading strategy helps are its verifiability, quantifiability, consistency, and objectivity.
For every trading strategy one needs to define assets to trade, entry/exit points and money management rules. Bad money management can make a potentially profitable strategy unprofitable.
Trading strategies are based on fundamental or technical analysis, or both. They are usually verified by backtesting, where the process should follow the scientific method, and by forward testing (a.k.a. 'paper trading') where they are tested in a simulated trading environment.
The term trading strategy can in brief be used by any fixed plan of trading a financial instrument, but the general use of the term is within computer assisted trading, where a trading strategy is implemented as computer program for automated trading.
Technical strategies can be broadly divided into the mean-reversion and momentum groups.
Long/short equity. A long short strategy consists of selecting a universe of equities and ranking them according to a combined alpha factor. Given the rankings we long the top percentile and short the bottom percentile of securities once every rebalancing period.
Pairs trade. A pairs trading strategy consists of identifying similar pairs of stocks and taking a linear combination of their price so that the result is a stationary time-series. We can then compute z-scores for the stationary signal and trade on the spread assuming mean reversion: short the top asset and long the bottom asset.
Swing trading strategy; Swing traders buy or sell as that price volatility sets in and trades are usually held for more than a day.
Scalping (trading); Scalping is a method to making dozens or hundreds of trades per day, to get a small profit from each trade by exploiting the bid/ask spread.
Day Trading; The Day trading is done by professional traders; the day trading is the method of buying or selling within the same day.
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Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.
Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. Those working in the field are quantitative analysts (quants). Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, investment management and other related finance occupations. The occupation is similar to those in industrial mathematics in other industries.
Trend following or trend trading is a trading strategy according to which one should buy an asset when its price trend goes up, and sell when its trend goes down, expecting price movements to continue. There are a number of different techniques, calculations and time-frames that may be used to determine the general direction of the market to generate a trade signal, including the current market price calculation, moving averages and channel breakouts.
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