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2. 14 Day Trading Strategies for Beginners - AOL

   www.aol.com/10-best-day-trading-strategies...

   This helps automate some of the trading strategy, as well as protect traders from losing money on a trade if prices swing too quickly to manually trade. 3. Pullback Trading Strategy.

3. Day trading - Wikipedia

   en.wikipedia.org/wiki/Day_trading

   Chart of the NASDAQ-100 between 1994 and 2004, including the dot-com bubble. Day trading is a form of speculation in securities in which a trader buys and sells a financial instrument within the same trading day, so that all positions are closed before the market closes for the trading day to avoid unmanageable risks and negative price gaps between one day's close and the next day's price at ...

4. Trading strategy - Wikipedia

   en.wikipedia.org/wiki/Trading_strategy

   The trading strategy is developed by the following methods: Automated trading; by programming or by visual development. Trading Plan Creation; by creating a detailed and defined set of rules that guide the trader into and through the trading process with entry and exit techniques clearly outlined and risk, reward parameters established from the outset.

5. Short-term trading - Wikipedia

   en.wikipedia.org/wiki/Short-term_trading

   There are two main schools of thought: swing trading and trend following. Day trading is an extremely short-term style of trading in which all positions entered during a trading day are exited the same day. Short term trading can be risky and unpredictable due to the volatile nature of the stock market at times. Within the time frame of a day ...

6. 5 options trading strategies for beginners - AOL

   www.aol.com/finance/5-options-trading-strategies...

   This options trading strategy is the flipside of the long put, but here the trader sells a put — referred to as “going short” a put — and expects the stock price to be above the strike ...

7. Algorithmic trading - Wikipedia

   en.wikipedia.org/wiki/Algorithmic_trading

   These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software. [5] [6] Examples of strategies used in algorithmic trading include systematic trading, market making, inter-market spreading, arbitrage, or pure speculation, such as trend following.