A trader always trades keeping a certain framework, idea or process in mind which he follows to achieve benefits out of his trades by either maximising the profits or minimizing the losses or both! A good strategy in place increases the chances of acquiring the targeted benefits and maximising the returns. Certain parameters help in gauging the efficiency of the trading strategy.
Selecting a trading strategy or devising one on your own requires you to know the working of these strategies and how they help in trading. We have listed down some of the best blogs of QuantInsti on trading strategies for beginners as well as advanced learners that you definitely need to check to grow and enhance your knowledge of trading strategies.
Here are some of our top blogs on trading strategies:
This is the go-to blog if you want to learn all about Algorithmic Trading strategies. A comprehensive description of algorithmic trading strategies like Momentum-based Strategies, Arbitrage, Statistical Arbitrage, Market Making and Machine Learning In Trading., it also discusses the working, types and modelling ideas for them. The blog further continues to give you a step-by-step method for building an algorithmic trading strategy.
Fibonacci ratios are used for time-series analysis to find support level. This blog explains what these ratios are and how they can be used to retrace the prices of stock. It begins by defining what a Fibonacci sequence is and states some interesting facts about it. The blog explains the Fibonacci Retracement Strategy and demonstrates a Python code to implement the same. It includes concepts like Fibonacci ratios and Fibonacci Retracement levels.
Iron Condor trading strategy, which is a combination of bull put spread and bear call spread options trading strategies, can be used by traders even with a small account. The blog starts by explaining the strategy and its working with simple examples and then moves ahead to demonstrate how to implement this strategy using Python. It uses Options data of Yes Bank Limited to execute this strategy. Along with the Python code, one can also learn how to calculate maximum profit and maximum loss which can help us determine how the strategy will work.
A trader holds a position in both Call and Put Options with the same Strike Price, the same expiry date and with the same asset to execute the Straddle Options trading strategy. How to practice this strategy, what are its types and how can you profit from this strategy is all explained in this blog. Implementation of this strategy is demonstrated using a Python code, along with the calculation of the call and put payoffs.
A candlestick depicts the OHLC prices of a specific time period for a security. Candlestick charts are widely used to denote the prices and for technical analysis. The blog explains how to plot the chart using Python. It also takes us through a candlestick trading strategy known as ‘Three Daily Candles’ and gives the Python code to implement this strategy.
What are diagonal spreads and how can they be used to devise a trading strategy? This blog answers this question and compares the different types of spreads like Vertical Spreads, Horizontal Spreads, Calendar Spreads, and Diagonal Spreads. It also shows us how to calculate the maximum profit and loss using the diagonal spread trading strategy. Implementation of this strategy in Python and demonstration of its payoff chart is also covered in this blog.
The blog starts off by discussing in brief about the Butterfly Spread Options Trading strategy, which a combination of Bull Spread and Bear Spread, then moves on to listing the components of a Butterfly strategy. Further, we understand the calculation of parameters of the Butterfly Spread strategy like maximum profit and loss, limited profit and loss, and break-even points. Finally, the blog provides us with the implementation of this strategy in Python and calculation of payoffs like the call payoff, long call payoff, higher strike long call payoff, short call payoff and butterfly spread payoff.
This blog talks about how Stereoscopic Portfolio framework can be used to improve a quantitative trading strategy. The blog contains detailed mathematical descriptions of concepts like Gaussian Mixture Models, K-Means Clustering, and Random Forests. It contains the Python code for Portfolio construction in a step-by-step manner.
The Iron Butterfly Options Trading strategy runs on similar lines as the Butterfly Spread Options Trading strategy and is a combination of bull spread and bear spread strategies. The blog demonstrates the construction of the payoff chart of this strategy and calculations of parameters like maximum profit and loss, and break-even points. We learn the implementation of this strategy from the given Python code which uses the HDFC options data.
The direction, momentum and support-resistance levels for the time series data can be determined using the Ichimoku cloud indicator. Along with explaining the Ichimoku cloud indicator and its calculations, the blog also provides us with the Python code to implement this trading strategy for cryptocurrencies using the OHLC data.
Collars are a type of protective options trading strategy which protect against huge losses but also limit enormous gains. The blog discusses the components, working and implementation of the Collar Options trading strategy. It also lists the various scenarios in which this strategy can be applied. An example of this strategy and its payoff charts is demonstrated in Python using the data from IDBI Bank Ltd.
These were some of the blogs which familiarize you with the different strategies used for trading effectively. In case you wish to acquire more practical knowledge and want to learn more about various trading strategies and their implementations, you can check out the below course which covers 19+ trading strategies and their executions in Python.
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