代写data编程、代做Python程序语言

日期：2024-11-21 09:40

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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