代写data编程、代做Python程序语言

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Big Data in Finance – Assignment 1
Algorithmic Trading Assignment
Objective:
Develop and perform algorithmic trades and their strategies using big data in finance.
Requirements:
You are required to do the data analysis in Python. The purpose of this document set is to
perform Big Data Science and artificial intelligence in financial data mining and find out
the similarity and differences between your findings and the results of other researchers
in journal papers.
Introduction:
Algorithmic trading has become an increasingly important tool in the financial markets,
allowing traders to leverage advanced data analysis and decision-making capabilities to
generate profits. In this assignment, you will be tasked with developing and evaluating
several algorithmic trading strategies for the Chinese or Hong Kong stock market, or the
currency exchange market or commodity products in different commodity exchanges in
the world.
Procedures:
1. Selection of Investment Portfolio for initial capital $1,000,000:
1.1 Select one business sector in accordance with Global Industry Classification
Standard in Appendix 1. Each student selects his/her own business sector and no
business sector should be repeated. Design with explanation at least 3 combinations
of investment portfolio in the selected business sector including at least
1. 10 relevant industrial stocks in China (ie. Shanghai, Shenzhen or Hong
Kong Stock Markets), for example,
45101010 Internet Software & Services (8-digit number only)
i. 9988.HK - Alibaba Group Holding Ltd.
ii. 0700.HK - Tencent Holdings Ltd.
iii. BIDU - Baidu, Inc.
iv. 9618.HK - JD.com, Inc.
v. PDD - PDD Holdings Inc 拼多多
vi. 600941.SS - China Moible Ltd 中國移動
vii. …
2. 10 country or crypto currencies for investment portfolio,
i. USD/CNY
ii. EUR/CNY
iii. JPY/CNY
iv. GBP/CNY
v. AUD/CNY
vi. USD/BTC (Bitcoin)
3. 10 commodity products in different commodity exchanges in the world,
i. Gold (XAUUSD)
ii. Silver (XAGUSD)
iii. Crude Oil (USOIL)
iv. Copper (XCUUSD)
v. Wheat (WHEATUSD)
4. or their options, futures and derivatives
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1.2 Benchmark the Investment Portfolios to relevant indices, for examples
Stock Indices in China
• Hang Seng Index
• Shanghai Composite Index
• SZSE Component Index
• CSI 300 Index
• SSE 50 Index
• SSE 180 Index
• SZSE 100 Index
• SZSE 200 Index
1.3 More than 3 investment portfolios would be counted in the bonus marks.
2. Trading Strategies
a. Design with explanation the trading strategies as follows:
1. Single Indicator-Based Strategy
Develop a trading strategy that relies on a single technical indicator, such as the
Shanghai Composite Index's 50-day moving average, the Hang Seng Index's
Relative Strength Index (RSI), or the USD/CNY exchange rate's Stochastic
Oscillator. Explain the rationale behind your chosen indicator and how it can be
used to generate buy and sell signals.
2. Multiple Indicator-Based Strategy
Create a trading strategy that combines multiple technical indicators to make
trading decisions. For example, you could use the 20-day and 50-day moving
averages of the Shenzhen Component Index, along with the MACD indicator, to
generate trading signals. Discuss how you selected the indicators and how you
integrated them into a cohesive decision-making framework.
3. Simple Neural Network AI Strategy
Implement a simple neural network-based trading strategy using stock data from
the Shanghai Stock Exchange or the Hong Kong Stock Exchange, or currency
exchange rates. Describe the architecture of your neural network, the input features
used (e.g., price, volume, technical indicators), and the training process. Explain
how the neural network generates trading signals.
4. Hybrid Indicator-Based and Neural Network AI Strategy
Develop a hybrid trading strategy that combines traditional technical indicators
(such as the 200-day moving average of the CSI 300 Index) with a neural network based model. Discuss the rationale for this approach and how the two components
are integrated to make trading decisions.
5. Simple Deep Learning AI Strategy
Design a deep learning-based trading strategy, such as using a recurrent neural
network (RNN) or a convolutional neural network (CNN) to analyze the historical
price and volume data of Chinese or Hong Kong stocks, or currency exchange rates.
Describe the model architecture, the input data, and the training process. Explain
how the deep learning model is used to generate trading signals.
6. Hybrid Indicator-Based and Deep Learning AI Strategy
Implement a hybrid trading strategy that integrates traditional technical indicators
(e.g., the Bollinger Bands of the Hang Seng Index) with a deep learning-based
model. Explain the benefits of this approach and how the two components work
together to make trading decisions.
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7. Customized Strategies
Customize at least one trading strategy to find out the optimal trading strategy in
your investment combinations. More than one trading strategy would be
counted in the bonus marks.
3. Backtesting
For each of the trading strategies developed, perform a comprehensive backtesting
process using at least two-years historical data from the Chinese or Hong Kong
stock market, the currency exchange market or different commodity exchanges.
This should include:
1. Data Preparation: Obtain and preprocess the necessary historical market
data for your trading strategies.
2. Backtesting Methodology: Describe the backtesting methodology you will
use, including the time period, the evaluation metrics (e.g., returns,
drawdown, Sharpe ratio), and any assumptions or constraints.
3. Backtesting Analytical Results: Present the backtesting results for each
trading strategy, including performance metrics, visualizations (e.g., equity
curves), and a comparative analysis of the strategies. For example,
1. Total return
2. Sharpe ratio
3. Drawdown
4. Win/loss ratio
4. Optimization and Sensitivity Analysis (Optional): Discuss any
optimization techniques you used to improve the performance of your
trading strategies, and conduct a sensitivity analysis to understand the
impact of key parameters on the strategy's performance.
4. Real-Time Live Simulation
To further evaluate the effectiveness of your trading strategies, implement a real time live simulation using current market data from the Chinese or Hong Kong
stock market, or the currency exchange market. This should involve:
1. Data Feeds (Yahoo Finance): Integrate real-time market data feeds into
your trading system.
2. Order Execution: Develop a mechanism to execute trades based on the
signals generated by your trading strategies.
3. Performance Monitoring and its Analysis: Continuously monitor the
performance of your trading strategies in the live market, tracking key
metrics and risk-adjusted performance. For example,
1. Total return
2. Sharpe ratio
3. Drawdown
4. Win/loss ratio
4. Adaptation and Refinement: Discuss how you would adapt and refine
your trading strategies based on the insights gained from the real-time live
simulation.
* Students need to suggest their own business sector. No business sector should be
repeated.
Suggested Sections in the Report:
1. Abstract
2. Introduction and Background
3. Objectives
4. Literature Review (Optional)
5. Investment Portfolio
6. Trading Strategies ***
7. Backtesting and its analysis ***
8. Real-Time Live Simulation and its analysis ***
9. Comparison between Backtesting and the results of Real-Time Live Simulation
10. Discussion (Applications and Implications of Relationship found)
11. Limitations (Any issue related to the Big Data Science / Artificial Intelligence in this
study)
12. Conclusions
13. Recommendations
14. References (the supporting journal and /or conference papers for your findings with
references (pdf files))
15. Appendices ****
*** This section “Research Design and Methodology” should include the Big Data Science
/ Technical Analysis / Artificial Intelligence methods and Python should be used for
programming.
**** Python code should be attached in the appendices.
Bonus:
Bonus marks can be obtained as follows:
1. Except the requirements in Selection of Investment Portfolio in p.1, one
additional Investment Portfolio used. (5 marks each max 5 marks)
2. Except the requirements in trading strategy, one additional Artificial Intelligence,
Technical Analysis (TA), Econometrics, Portfolio Analysis, Risk Analysis or
another quantitative analysis method used not mentioned in this subject with
submission of python code, data and analysis results. However, the bonus
method cannot be the same as in other assignments of Big Data in Finance. (5
marks each)
All bonus marks are justified in acceptance of above offers in accordance with the quality
of references and data. Maximum bonus marks = 20.
Requirements:
Students are required to present their topic (at least 10 mins per student) and to write an
article in English for English classes / Chinese for Chinese classes.
Submission:
Submit all files online with the following: (I:\Terence\ Big Data in Finance\...):
1. An article (at least 10 pages per 1 student, font 12, single line spacing – count text,
figures, tables only) – English for English classes or English in both
a. Word and
b. md (Obsidian) formats (using Word to md)
i. https://www.wordize.com/word-to-markdown/ or
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ii. https://www.zamzar.com/convert/doc-to-md/ (Max 1 MB) or
iii. https://word2md.com/, copy the output to notepad and save as md
2. A presentation file with speaking note and audio (please add the notes below the
powerpoint slides) (at least 5 mins per student) – English powerpoint 2019 or later
(https://support.microsoft.com/en-us/office/record-a-slide-show-with-narration and-slide-timings-0b9502c6-5f6c-40ae-b1e7-e47d8741161c)
3. Python code in Python Format (py files) – 1 master py file with all trading strategies,
3 py for 3 investment portfolios
4. Data Files in Excel / CSV Format (xlsx/CSV) with web address of data source
5. AI prompt for Python code generation (txt file)
6. Analysis Result Files in Excel Format (xlsx)
7. All References (full text journal paper in pdf files)
References:
1. https://www.youtube.com/watch?v=MikiBcP5uQQ&t=3s
2. Web of Science https://www.webofscience.com/wos/woscc/basic-search
3. Scopus https://www.scopus.com/
4. VOSviwer and Scopus https://www.youtube.com/watch?v=QcB9GTHEieY
5. VOSviewer https://www.vosviewer.com/
6. Maxqda https://www.maxqda.com/
7. http://scholar.google.com/
8. http://ec.europa.eu/information_society/activities/egovernment_research/focus/ind
ex_en.htm (eGovernment R&D focus)
9. http://library.ipm.edu.mo/Webpac/eresourcestore.asp?id=100 (ScienceDirect)
10. Other Journals and websites
Date of Submission:
Final Submission: 7 November for Thursday Class & 8 November for Friday
Presentation started at the end of this subject (if necessary)
Group:
1 student in 1 group
Page 6
Appendix 1: Global Industry Classification Standard
10 Energy
1010 Energy
101010 Energy Equipment & Services
• 10101010 Oil & Gas Drilling
• 10101020 Oil & Gas Equipment & Services
101020 Oil, Gas & Consumable Fuels
• 10102010 Integrated Oil & Gas
• 10102020 Oil & Gas Exploration & Production
• 10102030 Oil & Gas Refining & Marketing
• 10102040 Oil & Gas Storage & Transportation
• 10102050 Coal & Consumable Fuel
15 Materials
1510 Materials
151010 Chemicals
• 15101010 Commodity Chemicals
• 15101020 Diversified Chemicals
• 15101030 Fertilizers & Agricultural Chemicals
• 15101040 Industrial Gases
• 15101050 Specialty Chemicals
151020 Construction Materials
• 15102010 Construction Materials
151030 Containers & Packaging
• 15103010 Metal & Glass Containers
• 15103020 Paper Packaging
151040 Metals & Mining
• 15104010 Aluminum
• 15104020 Diversified Metals & Mining
• 15104025 Copper
• 15104030 Gold
• 15104040 Precious Metals & Minerals
• 15104045 Silver
• 15104050 Steel
151050 Paper & Forest Products
• 15105010 Forest Products
• 15105020 Paper Products
20 Industrials
2010 Capital Goods
201010 Aerospace & Defense
• 20101010 Aerospace & Defense
201020 Building Products
• 20102010 Building Products
201030 Construction & Engineering
• 20103010 Construction & Engineering
201040 Electrical Equipment
• 20104010 Electrical Components & Equipment
• 20104020 Heavy Electrical Equipment
201050 Industrial Conglomerates
• 20105010 Industrial Conglomerates
201060 Machinery
• 20106010 Construction Machinery & Heavy Trucks
• 20106015 Agricultural & Farm Machinery
• 20106020 Industrial Machinery
201070 Trading Companies & Distributors
• 20107010 Trading Companies & Distributors
2020 Commercial & Professional Services
202010 Commercial Services & Supplies
• 20201010 Commercial Printing
• 20201050 Environmental & Facilities Services
• 20201060 Office Services & Supplies
• 20201070 Diversified Support Services
• 20201080 Security & Alarm Services
202020 Professional Services
• 20202010 Human Resource & Employment Services
• 20202020 Research & Consulting Services
2030 Transportation
203010 Air Freight & Logistics
• 20301010 Air Freight & Logistics
203020 Airlines
• 20302010 Airlines
203030 Marine
• 20303010 Marine
203040 Road & Rail
• 20304010 Railroads
• 20304020 Trucking
203050 Transportation Infrastructure
• 20305010 Airport Services
• 20305020 Highways & Railtracks
• 20305030 Marine Ports & Services
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25 Consumer Discretionary
2510 Automobiles & Components
251010 Auto Components
• 25101010 Auto Parts & Equipment
• 25101020 Tires & Rubber
251020 Automobiles
• 25102010 Automobile Manufacturers
• 25102020 Motorcycle Manufacturers
2520 Consumer Durables & Apparel
252010 Household Durables
• 25201010 Consumer Electronics
• 25201020 Home Furnishings
• 25201030 Homebuilding
• 25201040 Household Appliances
• 25201050 Housewares & Specialties
252020 Leisure Products
• 25202010 Leisure Products
252030 Textiles, Apparel & Luxury Goods
• 25203010 Apparel, Accessories & Luxury Goods
• 25203020 Footwear
• 25203030 Textiles
2530 Consumer Services
253010 Hotels, Restaurants & Leisure
• 25301010 Casinos & Gaming
• 25301020 Hotels, Resorts & Cruise Lines
• 25301030 Leisure Facilities
• 25301040 Restaurants
253020 Diversified Consumer Services
• 25302010 Education Services
• 25302020 Specialized Consumer Services
2540 Media
254010 Media
• 25401010 Advertising
• 25401020 Broadcasting
• 25401025 Cable & Satellite
• 25401030 Movies & Entertainment
• 25401040 Publishing
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25 Consumer Discretionary (continued)
2550 Retailing
255010 Distributors
• 25501010 Distributors
255020 Internet & Direct Marketing Retail
• 25502020 Internet & Direct Marketing Retail
255030 Multiline Retail
• 25503010 Department Stores
• 25503020 General Merchandise Stores
255040 Specialty Retail
• 25504010 Apparel Retail
• 25504020 Computer & Electronics Retail
• 25504030 Home Improvement Retail
• 25504040 Specialty Stores
• 25504050 Automotive Retail
• 25504060 Home furnishing Retail
30 Consumer Staples
3010 Food & Staples Retailing
301010 Food & Staples Retailing
• 30101010 Drug Retail
• 30101020 Food Distributors
• 30101030 Food Retail
• 30101040 Hypermarkets & Super Centers
3020 Food, Beverage & Tobacco
302010 Beverages
• 30201010 Brewers
• 30201020 Distillers & Vintners
• 30201030 Soft Drinks
302020 Food Products
• 30202010 Agricultural Products
• 30202030 Packaged Foods & Meats
302030 Tobacco
• 30203010 Tobacco
3030 Household & Personal Products
303010 Household Products
• 30301010 Household Products
303020 Personal Products
• 30302010 Personal Products
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35 Health Care
3510 Health Care Equipment & Services
351010 Health Care Equipment & Supplies
• 35101010 Health Care Equipment
• 35101020 Health Care Supplies
351020 Health Care Providers & Services
• 35102010 Health Care Distributors
• 35102015 Health Care Services
• 35102020 Health Care Facilities
• 35102030 Managed Health Care
351030 Health Care Technology
• 35103010 Health Care Technology
3520 Pharmaceuticals, Biotechnology & Life Sciences
352010 Biotechnology
• 35201010 Biotechnology
352020 Pharmaceuticals
• 35202010 Pharmaceuticals
352030 Life Sciences Tools & Services
• 35203010 Life Sciences Tools & Services
40 Financials
4010 Banks
401010 Banks
• 40101010 Diversified Banks
• 40101015 Regional Banks
401020 Thrifts & Mortgage Finance
• 40102010 Thrift & Mortgage Finance
4020 Diversified Financials
402010 Diversified Financial Services
• 40201020 Other Diversified Financial Services
• 40201030 Multi-Sector Holdings
• 40201040 Specialized Finance
402020 Consumer Finance
• 40202010 Consumer Finance
402030 Capital Markets
• 40203010 Asset Management & Custody Banks
• 40203020 Investment Banking & Brokerage
• 40203030 Diversified Capital Markets
• 40203040 Financial Exchanges & Data
402040 Mortgage Real Estate Investment Trusts (REITs)
• 40204010 Mortgage REITs
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4030 Insurance
403010 Insurance
• 40301010 Insurance Brokers
• 40301020 Life & Health Insurance
• 40301030 Multi-line Insurance
• 40301040 Property & Casualty Insurance
• 40301050 Reinsurance
45 Information Technology
4510 Software & Services
451010 Internet Software & Services
• 45101010 Internet Software & Services
451020 IT Services
• 45102010 IT Consulting & Other Services
• 45102020 Data Processing & Outsourced Services
451030 Software
• 45103010 Application Software
• 45103020 Systems Software
• 45103030 Home Entertainment Software
4520 Technology Hardware & Equipment
452010 Communications Equipment
• 45201020 Communications Equipment
452020 Technology Hardware, Storage & Peripherals
• 45202030 Technology Hardware, Storage & Peripherals
452030 Electronic Equipment, Instruments & Components
• 45203010 Electronic Equipment & Instruments
• 45203015 Electronic Components
• 45203020 Electronic Manufacturing Services
• 45203030 Technology Distributors
4530 Semiconductors & Semiconductor Equipment
453010 Semiconductors & Semiconductor Equipment
• 45301010 Semiconductor Equipment
• 45301020 Semiconductors
50 Telecommunication Services
5010 Telecommunication Services
501010 Diversified Telecommunication Services
• 50101010 Alternative Carriers
• 50101020 Integrated Telecommunication Services
501020 Wireless Telecommunication Services
• 50102010 Wireless Telecommunication Services
5 Utilities
5510 Utilities
551010 Electric Utilities
• 55101010 Electric Utilities
551020 Gas Utilities
• 55102010 Gas Utilities
551030 Multi-Utilities
• 55103010 Multi-Utilities
551040 Water Utilities
• 55104010 Water Utilities
551050 Independent Power and Renewable Electricity Producers
• 55105010 Independent Power Producers & Energy Traders
• 55105020 Renewable Electricity
60 Real Estate
6010 Real Estate
601010 Equity Real Estate Investment Trusts (REITs)
• 60101010 Diversified REITs
• 60101020 Industrial REITs
• 60101030 Hotel & Resort REITs
• 60101040 Office REITs
• 60101050 Health Care REITs
• 60101060 Residential REITs
• 60101070 Retail REITs
• 60101080 Specialized REITs
601020 Real Estate Management & Development
• 60102010 Diversified Real Estate Activities
• 60102020 Real Estate Operating Companies
• 60102030 Real Estate Development
• 60102040 Real Estate Services
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