In this project, we will implement the breakout strategy. We'll find and remove any outliers. We'll test to see if it has the potential to be profitable using a Histogram and P-Value. For the dataset, we'll be using the end of day from Quotemedia.
A breakout trader is a type of trader that uses a breakout strategy. This strategy looks for levels or areas that a security has been unable to move beyond, and waits for it to move beyond those levels (as it could keep moving in that direction). When a price moves beyond one of these levels, it is called a breakout.
Many breakout traders use technical analysis to identify these areas, often using trendlines or price patterns. A breakout trader looks for patterns, for example, instances where the price of a security has been resistant to moving above or below a specific price level or price area. Then, the trader attempts to profit by entering a trade in the breakout direction, assuming that the price will continue to move in that direction.
I am having troubles and conflicts when installing the required libraries declared in requirements.txt. The codes runs successful on Udacity's workspace. However, some codes are failed locally such as function calculate_kstest, which returns different ks_statics and p_values with the grader. I think the version of kstest package I am using locally is different with the one used in Udacity.
├── Compute the highs and lows in a window
├── Compute long and short signals, `short if close < threshold else long`
├── Filter repeated signals within a window
├── Compute lookhead price returns
├── Compute signal returns
├── Filter outliers using Kolmogorov-Smirnov Test
└── Compare significance of signal return to normal distribution
Jinjin Liang authored the main functions in project_2.ipynb, and this README. All other project files were created by Udacity.