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Research Outline
L1094 Applied Finance Project
University of Sussex Business School, Spring Term 2024/2025

Please complete the research outline form and submit it on the Assignment on Canvas by 12pm on Thursday 13 February. Your research outline will be shared with your supervisor for discussion. It is fine even if you are not able to fill in all sections at the first attempt. You can update your research outline as you develop your plans.

Your name: Kaihang Mo
Degree course: Are Chinese Stock Markets Efficient
1.Working Title: It may be different from the assigned topic title.

2.Your motivation: Sketch out what you find interesting about the topic and what you hope to learn about the topic in 100-250 words.
The question of whether Chinese stock markets are efficient is fascinating because it challenges traditional financial theories in a unique context. China’s markets are shaped by state intervention, a high proportion of retail investors, and rapid regulatory changes, all of which may disrupt price efficiency. I’m particularly interested in how government policies, such as support for state-owned enterprises, influence market behavior, and whether the dominance of retail investors leads to herd behavior and inefficiencies. Additionally, the role of technology, like algorithmic trading and big data, in shaping market dynamics is worth exploring. I hope to learn how these factors impact market efficiency over time and how China’s integration into global indices affects its alignment with global standards. This topic offers insights into the intersection of policy, technology, and investor behavior in an evolving financial system.

3.Data: Describe the data you plan to use: For example, describe your key variables (i.e., dependent and explanatory variables) as well as data sources (e.g., URL of locations). Note down the following characteristics of your data:
-the data structure (i.e., cross-section, time series or panel)
-units of the key variables (e.g., currencies, % or indices)
-sample sizes (e.g., the time period, the number of countries, firms or individuals)
1. Dependent Variable: Stock returns of major Chinese indices (e.g., Shanghai Composite Index, Shenzhen Component Index). These will be measured in percentage changes over time.
2. Explanatory Variables:
A.Macroeconomic indicators (e.g., GDP growth, inflation rates, interest rates) to assess their impact on market efficiency.
B.Trading volume and volatility indices to capture market activity and investor behavior.
C.Policy-related variables, such as changes in regulatory frameworks or government interventions in the market.
D.Global market indices (e.g., S&P 500, MSCI World Index) to examine spillover effects and integration.

Data Sources:
Chinese stock market data: Bloomberg or Yahoo Finance.

Data Structure:
A.Time-series data for individual indices (daily frequency).
B.Panel data for cross-listed firms or sector-specific analysis.

Units:
A.Stock returns and macroeconomic indicators in percentages.
B.Trading volume in monetary terms (e.g., CNY).
C.Policy variables as binary indicators or categorical measures.

A.Time period: 2018-2021, to grasp the trends before and after the COVID-19 outbreak in China.
B.Coverage: Major Chinese indices, sector-specific data, and global market comparisons.
4.Key references: Identify up to five key readings that you think will be useful. You may use the references in the project topic list on Canvas (see Units view).

Method: If you can, sketch out some details of how you plan to do your regression analysis. For example, are there conventions in the literature about how they are measured or used in analysis Are you able to say which econometric method you will use for your analysis What problems might you be anticipating