theoretically optimal strategy ml4t

The report is to be submitted as. For our discussion, let us assume we are trading a stock in market over a period of time. You should create the following code files for submission. As will be the case throughout the term, the grading team will work as quickly as possible to provide project feedback and grades. For each indicator, you should create a single, compelling chart (with proper title, legend, and axis labels) that illustrates the indicator (you can use sub-plots to showcase different aspects of the indicator). You also need five electives, so consider one of these as an alternative for your first. Please address each of these points/questions in your report. The file will be invoked run: entry point to test your code against the report. For this activity, use $0.00 and 0.0 for commissions and impact, respectively. This is the ID you use to log into Canvas. ML4T Final Practice Questions 5.0 (3 reviews) Term 1 / 171 Why did it become a good investment to bet against mortgage-backed securities. (up to -100 points), If any charts are displayed to a screen/window/terminal in the Gradescope Submission environment. Code implementing a TheoreticallyOptimalStrategy object (details below). . Stockchart.com School (Technical Analysis Introduction), TA Ameritrade Technical Analysis Introduction Lessons, (pick the ones you think are most useful), Investopedias Introduction to Technical Analysis, Technical Analysis of the Financial Markets, A good introduction to technical analysis. (-5 points if not), Is there a chart for the indicator that properly illustrates its operation, including a properly labeled axis and legend? Introduce and describe each indicator you use in sufficient detail that someone else could reproduce it. The following textbooks helped me get an A in this course: Here are the statistics comparing in-sample data: The manual strategy works well for the train period as we were able to tweak the different thresholds like window size, buy and selling threshold for momentum and volatility. We encourage spending time finding and research indicators, including examining how they might later be combined to form trading strategies. Ensure to cite any sources you reference and use quotes and in-line citations to mark any direct quotes. In the case of such an emergency, please contact the, Complete your assignment using the JDF format, then save your submission as a PDF. If simultaneously have a row minimum and a column maximum this is an example of a saddle point solution. This is the ID you use to log into Canvas. (up to -100 points), Course Development Recommendations, Guidelines, and Rules. 1. They should comprise ALL code from you that is necessary to run your evaluations. a)Equal to the autocorrelation of lag, An investor believes that investing in domestic and international stocks will give a difference in the mean rate of return. We do not provide an explicit set timeline for returning grades, except that all assignments and exams will be graded before the institute deadline (end of the term). Once grades are released, any grade-related matters must follow the. technical-analysis-using-indicators-and-building-rule-based-strategy, anmolkapoor.in/2019/05/01/technical-analysis-with-indicators-and-building-rule-based-trading-strategy-part-1/, Technical Analysis with Indicators and building a ML based trading strategy (Part 1 of 2). Note: The Sharpe ratio uses the sample standard deviation. Also note that when we run your submitted code, it should generate the charts and table. The JDF format specifies font sizes and margins, which should not be altered. You should create a directory for your code in ml4t/manual_strategy and make a copy of util.py there. Use only the functions in util.py to read in stock data. You may not use any code you did not write yourself. See the Course Development Recommendations, Guidelines, and Rules for the complete list of requirements applicable to all course assignments. You may not use an indicator in Project 8 unless it is explicitly identified in Project 6. This is a text file that describes each .py file and provides instructions describing how to run your code. Create a set of trades representing the best a strategy could possibly do during the in-sample period using JPM. Please keep in mind that the completion of this project is pivotal to Project 8 completion. section of the code will call the testPolicy function in TheoreticallyOptimalStrategy, as well as your indicators and marketsimcode as needed, to generate the plots and statistics for your report (more details below). This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Some indicators are built using other indicators and/or return multiple results vectors (e.g., MACD uses EMA and returns MACD and Signal vectors). Use only the data provided for this course. When the short period mean falls and crosses the, long period mean, the death cross occurs, travelling in the opposite way as the, A golden cross indicates a future bull market, whilst a death cross indicates, a future down market. Provide one or more charts that convey how each indicator works compellingly. Only code submitted to Gradescope SUBMISSION will be graded. If you submit your code to Gradescope TESTING and have not also submitted your code to Gradescope SUBMISSION, you will receive a zero (0). Floor Coatings. Please submit the following files to Gradescope, Important: You are allowed a MAXIMUM of three (3) code submissions to Gradescope, Once grades are released, any grade-related matters must follow the, Assignment Follow-Up guidelines and process, alone. These should be incorporated into the body of the paper unless specifically required to be included in an appendix. We hope Machine Learning will do better than your intuition, but who knows? You are allowed to use up to two indicators presented and coded in the lectures (SMA, Bollinger Bands, RSI), but the other three will need to come from outside the class material (momentum is allowed to be used). Benchmark: The performance of a portfolio starting with $100,000 cash, investing in 1000 shares of JPM, and holding that position. Please keep in mind that the completion of this project is pivotal to Project 8 completion. For our report, We are are using JPM stock, SMA is a type of moving mean which is created by taking the arithmetic mean, of a collection of data. You may not use an indicator in Project 8 unless it is explicitly identified in Project 6. You will submit the code for the project in Gradescope SUBMISSION. When a short period moving mean goes above a huge long period moving mean, it is known as a golden cross. sshariff01 / ManualStrategy.py Last active 3 years ago Star 0 Fork 0 ML4T - Project 6 Raw indicators.py """ Student Name: Shoabe Shariff GT User ID: sshariff3 GT ID: 903272097 """ import pandas as pd import numpy as np import datetime as dt import os This is the ID you use to log into Canvas. Ml4t Notes - Read online for free. (up to 3 charts per indicator). The Project Technical Requirements are grouped into three sections: Always Allowed, Prohibited with Some Exceptions, and Always Prohibited. Technical indicators are heuristic or mathematical calculations based on the price, volume, or open interest of a security or contract used by traders who follow technical analysis. Make sure to cite any sources you reference and use quotes and in-line citations to mark any direct quotes. The, number of points to average before a specific point is sometimes referred to as, In our case, SMA aids in smoothing out price data over time by generating a, stream of averaged out prices, which aids in suppressing outliers from a dataset, and so lowering their overall influence. (up to -5 points if not). The performance metrics should include cumulative returns, standard deviation of daily returns, and the mean of daily returns for both the benchmark and portfolio. In the case of such an emergency, please contact the Dean of Students. You are encouraged to develop additional tests to ensure that all project requirements are met. import TheoreticallyOptimalStrategy as tos from util import get_data from marketsim.marketsim import compute_portvals from optimize_something.optimization import calculate_stats def author(): return "felixm" def test_optimal_strategy(): symbol = "JPM" start_value = 100000 sd = dt.datetime(2008, 1, 1) ed = dt.datetime(2009, 12, 31) This file should be considered the entry point to the project. , where folder_name is the path/name of a folder or directory. Another example: If you were using price/SMA as an indicator, you would want to create a chart with 3 lines: Price, SMA, Price/SMA. Regrading will only be undertaken in cases where there has been a genuine error or misunderstanding. You should create a directory for your code in ml4t/manual_strategy and make a copy of util.py there. It can be used as a proxy for the stocks, real worth. Once you are satisfied with the results in testing, submit the code to Gradescope SUBMISSION. While Project 6 doesnt need to code the indicators this way, it is required for Project 8, In the Theoretically Optimal Strategy, assume that you can see the future. We will learn about five technical indicators that can. Note: The format of this data frame differs from the one developed in a prior project. Make sure to answer those questions in the report and ensure the code meets the project requirements. Please submit the following files to Gradescope SUBMISSION: Important: You are allowed a MAXIMUM of three (3) code submissions to Gradescope SUBMISSION. You will have access to the ML4T/Data directory data, but you should use ONLY the API functions in util.py to read it. Create a set of trades representing the best a strategy could possibly do during the in-sample period using JPM. Create a set of trades representing the best a strategy could possibly do during the in-sample period using JPM. You signed in with another tab or window. For the Theoretically Optimal Strategy, at a minimum, address each of the following: There is no locally provided grading / pre-validation script for this assignment. Bollinger Bands (developed by John Bollinger) is the plot of two bands two sigma away from the simple moving average. (The indicator can be described as a mathematical equation or as pseudo-code). The following adjustments will be applied to the report: Theoretically optimal (up to 20 points potential deductions): Code deductions will be applied if any of the following occur: There is no auto-grader score associated with this project. We hope Machine Learning will do better than your intuition, but who knows? Ten pages is a maximum, not a target; our recommended per-section lengths intentionally add to less than 10 pages to leave you room to decide where to delve into more detail. This assignment is subject to change up until 3 weeks prior to the due date. Please submit the following file to Canvas in PDF format only: Do not submit any other files. manual_strategy/TheoreticallyOptimalStrategy.py Go to file Cannot retrieve contributors at this time 182 lines (132 sloc) 4.45 KB Raw Blame """ Code implementing a TheoreticallyOptimalStrategy object It should implement testPolicy () which returns a trades data frame We want a written detailed description here, not code. fantasy football calculator week 10; theoretically optimal strategy ml4t. You should submit a single PDF for this assignment. All work you submit should be your own. Some indicators are built using other indicators and/or return multiple results vectors (e.g., MACD uses EMA and returns MACD and Signal vectors). In Project-8, you will need to use the same indicators you will choose in this project. # def get_listview(portvals, normalized): You signed in with another tab or window. You will have access to the data in the ML4T/Data directory but you should use ONLY . Regrading will only be undertaken in cases where there has been a genuine error or misunderstanding. Enter the email address you signed up with and we'll email you a reset link. Once you are satisfied with the results in testing, submit the code to Gradescope SUBMISSION. These should be incorporated into the body of the paper unless specifically required to be included in an appendix. In your report (described below), a description of each indicator should enable someone to reproduce it just by reading the description. If a specific random seed is used, it must only be called once within a test_code() function in the testproject.py file and it must use your GT ID as the numeric value. You are constrained by the portfolio size and order limits as specified above. Thus, the maximum Gradescope TESTING score, while instructional, does not represent the minimum score one can expect when the assignment is graded using the private grading script. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. Provide a compelling description regarding why that indicator might work and how it could be used. The main part of this code should call marketsimcode as necessary to generate the plots used in the report. Ten pages is a maximum, not a target; our recommended per-section lengths intentionally add to less than 10 pages to leave you room to decide where to delve into more detail. No credit will be given for code that does not run in this environment and students are encouraged to leverage Gradescope TESTING prior to submitting an assignment for grading. The Project Technical Requirements are grouped into three sections: Always Allowed, Prohibited with Some Exceptions, and Always Prohibited. In Project-8, you will need to use the same indicators you will choose in this project. This framework assumes you have already set up the. However, it is OK to augment your written description with a, Do NOT copy/paste code parts here as a description, It is usually worthwhile to standardize the resulting values (see. Considering how multiple indicators might work together during Project 6 will help you complete the later project. In this case, MACD would need to be modified for Project 8 to return your own custom results vector that somehow combines the MACD and Signal vectors, or it would need to be modified to return only one of those vectors. Code must not use absolute import statements, such as: from folder_name import TheoreticalOptimalStrategy. No credit will be given for coding assignments that do not pass this pre-validation. file. In the Theoretically Optimal Strategy, assume that you can see the future. While Project 6 doesnt need to code the indicators this way, it is required for Project 8. Provide a chart that illustrates the TOS performance versus the benchmark. View TheoreticallyOptimalStrategy.py from ML 7646 at Georgia Institute Of Technology. import datetime as dt import pandas as pd import numpy as np from util import symbol_to_path,get_data def Describe the strategy in a way that someone else could evaluate and/or implement it. Assignments should be submitted to the corresponding assignment submission page in Canvas. However, sharing with other current or future, students of CS 7646 is prohibited and subject to being investigated as a, -----do not edit anything above this line---, # this is the function the autograder will call to test your code, # NOTE: orders_file may be a string, or it may be a file object. An improved version of your marketsim code accepts a trades DataFrame (instead of a file). 2.The proposed packing strategy suggests a simple R-tree bulk-loading algorithm that relies only on sort-ing. Values of +2000 and -2000 for trades are also legal so long as net holdings are constrained to -1000, 0, and 1000. To review, open the file in an editor that reveals hidden Unicode characters. You are not allowed to import external data. Here are my notes from when I took ML4T in OMSCS during Spring 2020. The library is used extensively in the book Machine Larning for . You may find our lecture on time series processing, the Technical Analysis video, and the vectorize_me PowerPoint to be helpful. We do not anticipate changes; any changes will be logged in this section. Some indicators are built using other indicators and/or return multiple results vectors (e.g., MACD uses EMA and returns MACD and Signal vectors). Code provided by the instructor or is allowed by the instructor to be shared. We encourage spending time finding and researching indicators, including examining how they might later be combined to form trading strategies. An indicator can only be used once with a specific value (e.g., SMA(12)). @param points: should be a numpy array with each row corresponding to a specific query. Course Hero is not sponsored or endorsed by any college or university. You will not be able to switch indicators in Project 8. The technical indicators you develop here will be utilized in your later project to devise an intuition-based trading strategy and a Machine Learning based trading strategy. The indicators should return results that can be interpreted as actionable buy/sell signals. GitHub Instantly share code, notes, and snippets. Scenario TourneSol Canada, Ltd. is a producer of, Problem: For this particular assignment, the data of different types of wine sales in the 20th century is to be analysed. and has a maximum of 10 pages. 0 stars Watchers. diversified portfolio. for the complete list of requirements applicable to all course assignments. 7 forks Releases No releases published. After that, we will develop a theoretically optimal strategy and compare its performance metrics to those of a benchmark. If we plot the Bollinger Bands with the price for a time period: We can find trading opportunity as SELL where price is entering the upper band from outside the upper band, and BUY where price is lower than the lower band and moving towards the SMA from outside. def __init__ ( self, learner=rtl. Please submit the following files to Gradescope SUBMISSION: You are allowed a MAXIMUM of three (3) code submissions to Gradescope SUBMISSION. These should be incorporated into the body of the paper unless specifically required to be included in an appendix. Epoxy Flooring UAE; Floor Coating UAE; Self Leveling Floor Coating; Wood Finishes and Coating; Functional Coatings. Ten pages is a maximum, not a target; our recommended per-section lengths intentionally add to less than 10 pages to leave you room to decide where to delve into more detail. HOLD. Theoretically Optimal Strategy will give a baseline to gauge your later projects performance. In Project-8, you will need to use the same indicators you will choose in this project. These should be incorporated into the body of the paper unless specifically required to be included in an appendix. You are encouraged to submit your files to Gradescope TESTING, where some basic pre-validation tests will be performed against the code. section of the code will call the testPolicy function in TheoreticallyOptimalStrategy, as well as your indicators and marketsimcode as needed, to generate the plots and statistics for your report (more details below). There is no distributed template for this project. Are you sure you want to create this branch? Within each document, the headings correspond to the videos within that lesson. Bonus for exceptionally well-written reports (up to 2 points), Is the required report provided (-100 if not), Are there five different indicators where you may only use two from the set discussed in the lectures (i.e., no more than two from the set [SMA, Bollinger Bands, RSI])? Please keep in mind that the completion of this project is pivotal to Project 8 completion. Close Log In. Develop and describe 5 technical indicators. The directory structure should align with the course environment framework, as discussed on the. Neatness (up to 5 points deduction if not). You should also report, as a table, in your report: Your TOS should implement a function called testPolicy() as follows: Your testproject.py code should call testPolicy() as a function within TheoreticallyOptimalStrategy as follows: The df_trades result can be used with your market simulation code to generate the necessary statistics. This is an individual assignment. Our bets on a large window size was not correct and even though the price went up, the huge lag in reflection on SMA and Momentum, was not able to give correct BUY and SELL opportunity on time. June 10, 2022 Code implementing a TheoreticallyOptimalStrategy (details below). Technical analysis using indicators and building a ML based trading strategy. Any content beyond 10 pages will not be considered for a grade. We have you do this to have an idea of an upper bound on performance, which can be referenced in Project 8. Zipline is a Pythonic event-driven system for backtesting, developed and used as the backtesting and live-trading engine by crowd-sourced investment fund Quantopian. If the required report is not provided (-100 points), Bonus for exceptionally well-written reports (up to +2 points), If there are not five different indicators (where you may only use two from the set discussed in the lectures [SMA, Bollinger Bands, RSI]) (-15 points each), If the submitted code in the indicators.py file does not properly reflect the indicators provided in the report (up to -75 points). Create a set of trades representing the best a strategy could possibly do during the in-sample period using JPM. As will be the case throughout the term, the grading team will work as quickly as possible to provide project feedback and grades. Floor Coatings. df_trades: A single column data frame, indexed by date, whose values represent trades for each trading day (from the start date to the end date of a given period). For each indicator, you should create a single, compelling chart (with proper title, legend, and axis labels) that illustrates the indicator (you can use sub-plots to showcase different aspects of the indicator). Create a Manual Strategy based on indicators. result can be used with your market simulation code to generate the necessary statistics. Framing this problem is a straightforward process: Provide a function for minimize() . The purpose of the present study was to "override" self-paced (SP) performance by instructing athletes to execute a theoretically optimal pacing profile. They can be calculated as: upper_band = sma + standard_deviation * 2, lower_band = sma - standard_deviation * 2. Legal values are +1000.0 indicating a BUY of 1000 shares, -1000.0 indicating a SELL of 1000 shares, and 0.0 indicating NOTHING. Charts should be properly annotated with legible and appropriately named labels, titles, and legends. You can use util.py to read any of the columns in the stock symbol files. We want a written detailed description here, not code. manual_strategy. PowerPoint to be helpful. Considering how multiple indicators might work together during Project 6 will help you complete the later project. Introduce and describe each indicator you use in sufficient detail that someone else could reproduce it. Students are allowed to share charts in the pinned Students Charts thread alone. that returns your Georgia Tech user ID as a string in each .py file. stephanie edwards singer niece. Gradescope TESTING does not grade your assignment. 6 Part 2: Theoretically Optimal Strategy (20 points) 7 Part 3: Manual Rule-Based Trader (50 points) 8 Part 4: Comparative Analysis (10 points) . Please note that there is no starting .zip file associated with this project. While such indicators are okay to use in Project 6, please keep in mind that Project 8 will require that each indicator return one results vector. This is the ID you use to log into Canvas. (-10 points if not), Is the chart correct (dates and equity curve), including properly labeled axis and legend (up to -10 points if not), The historical value of benchmark normalized to 1.0, plotted with a green line (-5 if not), The historical value of portfolio normalized to 1.0, plotted with a red line (-5 if not), Are the reported performance criteria correct? If you use an indicator in Project 6 that returns multiple results vectors, we recommend taking an additional step of determining how you might modify the indicator to return one results vector for use in Project 8. The report will be submitted to Canvas. You should have already successfully coded the Bollinger Band feature: Another good indicator worth considering is momentum. Please note that there is no starting .zip file associated with this project. For example, Bollinger Bands alone does not give an actionable signal to buy/sell easily framed for a learner, but BBP (or %B) does. You will have access to the data in the ML4T/Data directory but you should use ONLY the API . You will not be able to switch indicators in Project 8. Please address each of these points/questions in your report. This assignment is subject to change up until 3 weeks prior to the due date. You should submit a single PDF for this assignment. Note: Theoretically Optimal Strategy does not use the indicators developed in the previous section. If you submit your code to Gradescope TESTING and have not also submitted your code to Gradescope SUBMISSION, you will receive a zero (0). A simple strategy is to sell as much as there is possibility in the portfolio ( SHORT till portfolio reaches -1000) and if price is going up in future buy as much as there is possibility in the portfolio( LONG till portfolio reaches +1000). Now we want you to run some experiments to determine how well the betting strategy works. The directory structure should align with the course environment framework, as discussed on the local environment and ML4T Software pages. Please submit the following file to Canvas in PDF format only: Please submit the following files to Gradescope, We do not provide an explicit set timeline for returning grades, except that everything will be graded before the institute deadline (end of the term). The report is to be submitted as. You are allowed unlimited resubmissions to Gradescope TESTING. About. You may not use any libraries not listed in the allowed section above. Backtest your Trading Strategies. The submitted code is run as a batch job after the project deadline. You will have access to the ML4T/Data directory data, but you should use ONLY the API functions in util.py to read it. However, it is OK to augment your written description with a pseudocode figure. No credit will be given for coding assignments that do not pass this pre-validation. The Gradescope TESTING script is not a complete test suite and does not match the more stringent private grader that is used in Gradescope SUBMISSION. This Golden_Cross indicator would need to be defined in Project 6 to be used in Project 8. Transaction costs for TheoreticallyOptimalStrategy: In the Theoretically Optimal Strategy, assume that you can see the future. You signed in with another tab or window. Assignment 2: Optimize Something: Use optimization to find the allocations for an optimal portfolio Assignment 3: Assess Learners: Implement decision tree learner, random tree learner, and bag. More specifically, the ML4T workflow starts with generating ideas for a well-defined investment universe, collecting relevant data, and extracting informative features. Assignments should be submitted to the corresponding assignment submission page in Canvas. Once grades are released, any grade-related matters must follow the Assignment Follow-Up guidelines and process. This is an individual assignment. For each indicator, you should create a single, compelling chart (with proper title, legend, and axis labels) that illustrates the indicator (you can use sub-plots to showcase different aspects of the indicator). Watermarked charts may be shared in the dedicated discussion forum mega-thread alone. Please submit the following file(s) to Canvas in PDF format only: Do not submit any other files. Second, you will develop a theoretically optimal strategy (TOS), which represents the maximum amount your portfolio can theoretically return. You will not be able to switch indicators in Project 8. . 'Technical Indicator 3: Simple Moving Average (SMA)', 'Technical Indicator 4: Moving Average Convergence Divergence (MACD)', * MACD - https://www.investopedia.com/terms/m/macd.asp, * DataFrame EWM - http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.ewm.html, Copyright 2018, Georgia Institute of Technology (Georgia Tech), Georgia Tech asserts copyright ownership of this template and all derivative, works, including solutions to the projects assigned in this course. The algorithm first executes all possible trades . However, it is OK to augment your written description with a. Not submitting a report will result in a penalty. You should create the following code files for submission. Assignments should be submitted to the corresponding assignment submission page in Canvas. Provide a compelling description regarding why that indicator might work and how it could be used. Use the revised market simulator based on the one you wrote earlier in the course to determine the portfolio valuation. 2/26 Updated Theoretically Optimal Strategy API call example; 3/2 Strikethrough out of sample dates in the Data Details, Dates and Rules section; Overview. It is not your 9 digit student number. To review, open the file in an editor that reveals hidden Unicode characters. . In the Theoretically Optimal Strategy, assume that you can see the future. Develop and describe 5 technical indicators. . The main part of this code should call marketsimcode as necessary to generate the plots used in the report. The, Suppose that the longevity of a light bulb is exponential with a mean lifetime of eight years. By making several approximations to the theoretically-justified procedure, we develop a practical algorithm, called Trust Region Policy Optimization (TRPO).

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