CSCI 5832 -- Financial Data Mining (Graduate)

CINF 5832 -- Financial Data Mining (Graduate)
Updated  November 28, 2023

Office and Addresses

Delta 171 Phone 281.283.3805
email: boetticher@uhcl.edu
Secretary: Ms. Caroline Johnson Delta 161 281.283.3860

Face-to-Face Class Hours

Wednesday 7:00 - 9:50, Room: Delta 241, or via Zoom (If necessary)
Zoom information may be found in the Google folder for this course.

Office Hours

Wed 12 - 4 PM, Thurs 9 - 10 AM, or by appointment. Students with appointments have priority. If the suite door is locked, then call my extension (last 4 digits) using the phone in the hallway. Students who have an appointment will have priority over those students who don't. A Zoom session is also possible.

Teaching Assistants

Mr. Angelo Gomez
Email: GomezA0108@UHCL.edu

TA Hours: Monday 10-12, 5-8, Tuesday 1-5, 7-10, Wednesday 1 - 3

Why take this course?

• More than 98 percent or all college courses teach you how to earn money. This course teaches you how to get your money to work for you. This is your chance to work smarter, not harder.

• Your company, your stockbroker may mean well, but nobody will care about your financial health more than you.

Course Description

Mathematically sophisticated financial models are becoming more prevalent in the financial domain. It is possible to manually construct and test various hypotheses; however the process is extremely slow. A preferred approach is to data mine financial instruments in order to identify potentially successful approaches. This course will examine different sources of data and how to apply machine learners in order to construct profitable models. The culminates in the development of an Trading Bot.

The traditional graduate student load is 3 courses. Be prepared to commit 15 to 20 hours per week to this course!

Course Goals

By the end of the course, you will:

• Understand the financial data mining process;

• Understand various technical indicators;

• Have an understanding of various Machine Learners (ML) and how to apply these tools in a financial context;

• Understand what is a backtest;

Course Deliverables

By the end of the course, you will created the following deliverables in Python:

• A tool for reading historic financial data, or live financial data

• Create a set of technical indicators and chart patterns

• Use a set of technical indicators and chart patterns to make effective buy/sell decisions

• Construct a Backtester to assess various financial models;

• Optimize a trading model.

• Apply one or more Machine Learners (ML) to make buy/sell decisions

• Construct a Trading Bot capable using live streaming data

Prerequisites

The prerequisites for this course are at least one programming course or experience in Python. A class in Data Structures (CSCI3333) is recommended. A class in artificial intelligence, machine learning, pattern recognition, algorithms, or statistics would be helpful, but is not required.

I also encourage students who have a business/finance background. Please talk to me about your particular situation.

This course assumes no previous knowledge of finance.

Methodology

Face-to-face lecture and interactive problem solving.

Appraisal:

Grades will be based solely on criteria listed above. No other factors will be considered.

Grading Scale:

    93+ = A; 90 = A-; 87+ = B+; 83+ = B; 80+ = B-;

      77+ = C+; 73+ = C; 70 = C-; 67+ = D+; 63+ = D; 60+ = D-; 0+= F

My motto:

Show disciplined, altruistic, passion.

Required Textbook  

There is no required textbook for this course. Readings will be from various papers and/or tutorials.

Schedule (Tentative)

************************************************************************

Aug 23 - Overview Financial Data Mining Terminology and Concepts

Assignment 01: Read and Display Financial Data

Due date:  Wednesday, September 6^th at 7 PM.

Terms for this week: Financial Data Mining, Temporal data, Time-series data, symbol, bid price, bid size, ask price, ask size, change, trade, Depth Of Market Execution (DOME), tick data, Open, High, Low, Close, Volume, bar graph, candlestick graph, long trade, short trade, what to buy, when to buy,  Market order, limit order, drawdown, stop, day order, bracket trade, types of markets (bull, bear, sideways), stock, index, shares, contracts, leverage, eMinis, expiration date, technical analysis, technical indicators, Simple Moving Average, trading style, position trading, swing trading, day trading, scalp trading, discretionary, system trading, semi-automated trading, automated trading,

Readings for this week

·  Read: WK01 Notes - Introduction

·   Read: WK01A Paper - Man saw futures back in tiny town

·   Read: WK01B Paper - Day Trading Salary

·   Read: WK01C Paper - Algorithmic Trading Review

Aug 30 - Overview Financial Data Mining Terminology and Concepts - Part 2, Code examples, GDB Cup

Quiz 1 Due at noon via email.  See week 1 notes page 4.

Readings and concepts for next week

·  Read:  Week 03 Notes: Unit 2 - Timing the Market: Technical Indicators

·  Read:  WK03 PapersA - Introduction to Technical Analysis

·  Read:  WK03 PapersB - Technical Indicators

·  Read:  WK03 PapersC - Technical indicators - The tools of the trade

·  Read:  WK03 PapersD - 12 Types of Technical Indicators Used by Stock Traders

·  Read:  WK03 PapersE - Best 25 Technical Indicators Every Trader Should Know

·  Read:  WK03 PapersF - Python Backtrader_ A Comprehensive Guide to Algorithmic Trading and Backtesting

·   Reference:  WK03 Reference01 - Glossary of Technical Indicators

·   Reference:  WK03 Reference02 - TA Books bibliography

·   Reference:  WK03 Reference03 - List of Technical Indicators

·   Reference:  WK03 Reference04 - What Is TA-LIB

Terms for next week: Fundamental Analysis, Technical Analysis, Technical Indicator, Formula-based indicators, Function-based indicators, Formation-based indicators, overlay indicators, separate indicators, indicator - desired features (robust, reliable, early entry), market indicators, individual indicators, technical analysis, triggers, crossover of 2 or more indicators, crossing a threshold, positive (or negative) divergence, financial model

Web Pages for Charting

A)   http://stockcharts.com/h-sc/ui?s=IBM

B)   http://www.stockta.com/

Sep 06 - Timing the Market with Technical Indicators, Triggers

Quiz 2 Due by Noon

GDB Cup: Team Identification Form needed by the end of the break

Assignment 1 Due

Assignment 2: Assignment 02 - Create a Set of Technical Indicators

Due date:  Wednesday, September 20^th at 7 PM.

Sep 13 - Technical Indicators in greater details

Readings for next week

·   Read:  Week 05 PapersA PNF_Tutorial

·   Read:  Week 05 PapersB CorePointAndFigureChartPatterns

·   Read:  Week 05 PapersC - Charting Patterns on Price History

      Saswat Anand, Wei-Ngan Chin, Siau-Cheng Khoo, “Charting patterns on price history,”   Proceedings of the sixth ACM SIGPLAN international conference on Functional programming, October, 2001.

Terms for next week: Double Top, Triple Top, Double Bottom, Triple Bottom, Triangles, Wedges, Flags, Pennant, Head and Shoulders

Sep 20 - Charting, Chart Patterns and PNF

Assignment 2A Due

Assignment 2B: Assignment 03 - Triggers

Due date:  Wednesday, October 4^th at 7 PM.

Readings for next week

·   Read:  TBD

Sep 27 - Introduction to Backtesting - Part 1

Assignment 2B Due

Assign Assignment 4 -  Backtesting

Point value: 100 points

Due date:  Wednesday, October 11^th at 7 PM.

Readings for next week

·   Read:  Week 09 Notes - Genetic Algorithms

·   Read:  Week 09 PapersA Genetic-Based Trading Rules - A New Tool to Beat the Market With?

·   Read:  Week 09 PapersB A real-time adaptive trading system using genetic programming

·   Read:  Week 09 PapersC Empirical Study of GP Generated Rules

·   Read:  Week 09 PapersD Technical Market Indicators Optimization using Evolutionary Algorithms   

·   Read:  Week 09 PapersE GENETIC ALGORITHMS FOR ROBUST OPTIMIZATION IN FINANCIAL APPLICATIONS

·   Read:  Week 09 PapersF Comparison of Trade Decision Strategies in an Equity Market GA Trader

Oct 04 - Introduction to Backtesting - Part 2

Assignment 3 Due

Assign Assignment 4 -  Backtesting

Point value: 100 points

Due date:  Wednesday, October 11^th at 7 PM.

Readings for next week

·   Read:  TBD

Oct 11 - How to assess a financial model?

Readings for next week

Oct 18 - Model Optimization and Walk Forward Testing

Assignment 4 Due

Readings for next week

Oct 25 - Machine Learning – Part 1

Readings for next week

Nov 01 - Machine Learning – Part 2

GDB Cup - Practice Round - Due Thursday, November 2^nd, 8 AM (Mail to Boetticher@uhcl.edu)

Readings for next week

·   Read:  Course materials on the Google drive

Terms for next week: Maximum Drawdown (MDD), Sharpe Ratio, Sortino Ratio, Sterling Ratio,

******** November 6 – Last day to withdraw ********

Nov 08 - Automated Trading: Building a Trading Bot

GDB Cup - Round 1 - Due Thursday, November 9^th, 8 AM (Mail to Boetticher@uhcl.edu)

Readings for next week

51 Reasons Why Most Traders Lose Money

What type of trader are you?

Principles of Successful Trading

Lakhani, J., Discipline, Mental Skills and the Psychology of Trading

LO, Andrew W., Dmitry V. REPIN, and Brett N. STEENBARGER, 2005. Fear and Greed in Financial Markets: A Clinical Study of Day-Traders. American Economic Review, 95(2), 352–359.

Brett N. Steenbarger, Behavioral Patterns That Sabotage Traders

Stewart Mayhew, “Problems in financial engineering: security price dynamics and simulation in financial engineering,” Proceedings of the 34th conference on Winter simulation: exploring new frontiers, December 2002

Nov 15 -  Money Management, Risk Mitigation

GDB Cup - Round 2 - Due Thursday, November 16^th, 8 AM (Mail to Boetticher@uhcl.edu)

Nov 22 - Thanksgiving - No Class

GDB Cup - Round 2 - Due Thursday, November 23^rd, 8 AM (Mail to Boetticher@uhcl.edu)

Nov 29 - Market Scanners

GDB Cup - Round 4 - Due Thursday, November 30^th, 8 AM (Mail to Boetticher@uhcl.edu)

FOR NEXT WEEK (IF NOT SOONER)

Dec 06 - GDB Cup Final Results

Peer Review form due at 7 PM via email.

GDB Cup Final results

GDB Cup Results - Fall, 2023

Each week resets to 100K

Money Management Constraints Imposed (IB)

        Blue background = Incurred a penalty for that week.

GDB Cup Results - Fall, 2023

Each week resets to 250K

Unrestricted (Infinity Futures)

        Blue background = Incurred a penalty for that week.

Other Policies

This class has 6 simple rules:

1) Be respectful of others.

2) Be very passionate about your learning and do your best.

3) Be fearless - ask lots of questions in class.

4) Don't be late on anything.

5) Don't ever cheat.

6) Have fun!

Miscellaneous

• Any person with a disability who requires a special accommodation should inform me and contact the Disability services office or call 281 283 2627 as soon as possible.

• You are expected to come fully prepared to every class!

• If there is any religious observance that may interfere with any scheduled exam, homework due date, or attending class, please notify me of the situation during the first 2 weeks of class so that adjustments can be made at that time.

• Please turn off all cell phones, and pagers prior to the start of class.

• I am willing to provide letters of recommendation/references only if you have attained an 'A' in one of my classes, or two 'A-' in two of my classes.

• I highly recommend that you seek out your advisor and complete your Candidate Plan of Study (CPS) as soon as possible. I am normally not available for advising during the summer months.

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