LICENSE

@@ -1,13 +1,3 @@
-Zero-Clause BSD
-=============
+Copyright (c) 2023-2024 Luke Wilson. All rights reserved.
 
-Permission to use, copy, modify, and/or distribute this software for
-any purpose with or without fee is hereby granted.
-
-THE SOFTWARE IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL
-WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES
-OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE
-FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY
-DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN
-AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT
-OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
+This software is not available for use, modification, or reproduction (and this is not a comprehensive list of restrictions). The project is only open source so that it can be made available on my resume.

README.md

@@ -1,21 +1,4 @@
 # autotrader
+Copyright 2023-2024 Luke Wilson. All rights reserved.
 
-> [WARNING]: There are still many bugs to be fixed, this software is not ready to be used for live trading. PRs and bug fixes welcome!
->
-> If you still feel like importing the library into your project, I highly recommend vendoring it (copying it directly to the folder).
-
-Autotrader is a forex quantitative trading engine I developed in two weeks using Go. The unique backtesting simulations runs a user-designed trading algorithm against historical market data. The simulation accounts for brokerage fees, hedging, leverage, market orders, limit orders, stop orders, and more. Once a reliable strategy has been identified, the user can run the trading algorithm they created on their live brokerage account.
-
-Autotrader inserts layers of abstraction all the way down from the implementation of the trading strategy to the orders and positions maintained by the brokers over their JSON REST APIs. All financial algorithms and data structures used in this project were developed from scratch, including a time series table inspired by the NumPy Python data science library.
-
-The following page is a report generated by Autotrader when backtesting a naive SMA crossover strategy using realtime Forex market data:
-
-![Graph of live trades as executed by the strategy.](images/livetrades-example.jpeg)
-
-![Return on investment of the strategy plotted over time.](images/profit-example.jpeg)
-
-![Profitability graph of the strategy.](images/profitability-example.jpeg)
-
-## License
-
-Zero-clause BSD (0BSD)
+The source code is only publicly available to view so that I can present it on my resume.