Using chart.Posn()

One of the most enlightening things about a trading system is exploring what positions it took over the course of the trading simulation, as well as when it had its profits and drawdowns. Looking at a picture of the performance can deliver a great deal of insight in terms of refining similar trading systems in the future.

In this exercise, you will use the chart.Posn() function. This generates a crisp and informative visualization of the performance of your trading system over the course of the simulation.

Your portfolio strategy (portfolio.st) is preloaded into your environment.

This exercise is part of the course

Financial Trading in R

Exercise instructions

Use chart.Posn() to view your trading system's performance over the course of the simulation for SPY.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Use chart.Posn to view your system's performance on SPY
chart.Posn(Portfolio = ___, Symbol = "___")

Edit and Run Code

This exercise is part of the course

Financial Trading in R

IntermediateSkill Level

4.8+

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Exercise 1: Why do people trade?Exercise 2: Identifying types of trading philosophies - I Exercise 3: Identifying types of trading philosophies - II Exercise 4: Identifying types of trading philosophies - III Exercise 5: Pitfalls of various trading systems Exercise 6: How to prevent overfitting Exercise 7: Getting financial data Exercise 8: Plotting financial data Exercise 9: Adding indicators to financial data Exercise 10: Adding a moving average to financial data

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Exercise 1: Setting up a strategy I Exercise 2: Understanding initialization settings - I Exercise 3: Understanding initialization settings - II Exercise 4: Setting up a strategy II Exercise 5: Understanding initialization settings - III Exercise 6: Understanding initialization settings - IV

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Exercise 1: Introduction to indicators Exercise 2: The SMA and RSI functions Exercise 3: Visualize an indicator and guess its purpose - I Exercise 4: Visualize an indicator and guess its purpose - II Exercise 5: Indicator mechanics Exercise 6: Implementing an indicator - I Exercise 7: Implementing an indicator - II Exercise 8: Implementing an indicator - III Exercise 9: Indicator structure review Exercise 10: Code your own indicator - I Exercise 11: Code your own indicator - II Exercise 12: Apply your own indicator

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Exercise 1: Introduction to signals Exercise 2: Signal or not? - I Exercise 3: Signal or not? - II Exercise 4: sigComparison and sigCrossover Exercise 5: Using sigComparison Exercise 6: Using sigCrossover Exercise 7: sigThreshold Exercise 8: Using sigThreshold - I Exercise 9: Using sigThreshold() - II Exercise 10: sigFormula Exercise 11: Using sigFormula()Exercise 12: Combining signals - I Exercise 13: Combining signals - II

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Exercise 1: Introduction to rules Exercise 2: Using add.rule() to implement an exit rule Exercise 3: Specifying sigcol in add.rule()Exercise 4: Specifying sigval in add.rule()Exercise 5: More rule mechanics Exercise 6: Specifying orderqty in add.rule()Exercise 7: Specifying ordertype in add.rule()Exercise 8: Specifying orderside in add.rule()Exercise 9: More rule mechanics II Exercise 10: Specifying replace in add.rule()Exercise 11: Specifying prefer in add.rule()Exercise 12: Using add.rule() to implement an entry rule Exercise 13: Order sizing functions Exercise 14: Implementing a rule with an order sizing function

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Exercise 1: Analyzing your strategy Exercise 2: Running your strategy Exercise 3: Profit factor Exercise 4: Percent positive Exercise 5: Visualizing your strategy Exercise 6: Using chart.Posn()

Current Exercise

Exercise 7: Adding an indicator to a chart.Posn() chart Exercise 8: Additional analytics Exercise 9: Cash Sharpe ratio Exercise 10: Returns Sharpe ratio in quantstrat