Discuss the theoretical underpinnings in (i) Yu and Yuan (2011) and Wang (2018a), and (ii) Wang (2018b) and Wang and Duxbury (2021)

Individual Assessed Coursework Brief
The work should not exceed 3,500 words. Excessive assignments will be penalised according to section 9.13 of Regulation 9 Regulation Governing Postgraduate Taught Awards: “Assessed work which exceeds a specified maximum permitted length will be subject to a penalty deduction of marks equivalent to the percentage of additional words over the limit. The limit excludes bibliographies, diagrams and tables, footnotes, tables of contents and appendices of data.”

Introduction
The mean-variance relationship has long been a focus in finance literature. Traditional financial theories propose a positive mean-variance relationship, or risk-return tradeoff (Merton, 1973), i.e. bearing high (low) risk should be rewarded by high (low) returns, empirical studies document at best inconclusive evidence with three mainstreams due to different economic settings and volatility model selection. French et al. (1987), Scruggs (1998), Ghysels et al. (2005), Lundblad (2007), Pástor et al. (2008), Brandt and Wang (2010), and Rossi and Timmermann (2015), among others find the risk-return tradeoff despite being less significant in some cases. On the other hand, Nelson (1991), Brandt and Kang (2004), Baker et al. (2011), Fiore and Saha (2015), and Booth et al. (2016), among others, document a negative mean-variance relationship. Turner et al. (1989), Glosten et al. (1993), Sun et al. (2017), and Wang et al. (2017), among others, report both positive and negative relationship between risk and returns.
A wide range of theories are proposed to explain the weak risk-return tradeoff, such as investor sentiment (Yu and Yuan, 2011; Wang, 2018a&b; Wang and Duxbury, 2021) and differences in overnight and intraday returns (Wang, 2021).
In line with the above, answer the following requirements:
Required:
1. Discuss the theoretical underpinnings in (i) Yu and Yuan (2011) and Wang (2018a), and (ii) Wang (2018b) and Wang and Duxbury (2021) [20 marks]
2. Critically review literature, and summarise and evaluate approaches to construct proxies for investor sentiment. [12 marks]
3. Suppose that you decide to extend the US evidence from Wang (2021) to an emerging market. Select the market and justify your selection. [8 marks]
4. For the selected market, present and interpret descriptive statistics of (i) overnight returns, (ii) intraday returns, and (iii) total returns. [15 marks]
5. Select one method to filter conditional volatility. Present and interpret descriptive statistics of conditional volatility of (i) overnight returns, (ii) intraday returns, and (iii) total returns. [20 marks]
6. Examine the mean-variance relation for (i) overnight returns, (ii) intraday returns, and (iii) total returns. Interpret. [25 marks]

While attempting requirements you should follow academic writing style format relying on journal articles. Failing to do so leads to a 30-mark deduction.

Guideline coverage of issues/answers expectations:
Requirement 1:
1. Provide theoretical underpinnings of empirical findings in Yu and Yuan (2011) and Wang (2018b).
2. Provide theoretical underpinnings of empirical findings in Wang (2018b) and Wang and Duxbury (2021).
3. Make comparison between (i) and (ii).

Requirement 2:
1. Provide reasons why proxies are needed for investor sentiment.
2. Summarise main types of proxies for investor sentiment
3. Critically evaluate each type.

Requirement 3:
1. Select an emerging market.
2. Justify your choice from at least two main perspectives: (i) Provide criteria used to label the selected market as an emerging market; (ii) Explain reasons why the research question as in Wang (2021) is of particular interest in your selected market.

Requirement 4:
1. Present descriptive statistics of three returns.
2. Interpret.

Requirement 5:
1. Select the method to filter conditional volatility.
2. Present descriptive statistics of conditional volatility of three returns.
3. Interpret.

Requirement 6:
1. Examine the mean-variance relation for three returns.
2. Interpret.

Relevant References (You may use these references to help to produce your work)
Baker, M., Wurgler, J., 2006. Investor sentiment and the cross-section of stock returns. Journal of Finance 61 (4), 1645−1680.
Baker, M., Wurgler, J., 2007. Investor sentiment in the stock market. Journal of Economic Perspectives 21 (2), 129−151.
Brown, G.W., Cliff, M.T., 2005. Investor sentiment and asset valuation. Journal of Business 78 (2), 405−440.
Daniel, K., Hirshleifer, D., Subrahmanyam, A., 1998. Investor psychology and security market under- and overreactions. Journal of Finance 53 (6), 1839−1886.
French, K.R., Schwert, G.W., Stambaugh, R.F., 1987. Expected stock returns and volatility. Journal of Financial Economics 19 (1), 3−29.
Hendershott, T., Livdan, D., Rösch D., 2020. Asset pricing: A tale of night and day. Journal of Financial Economics 138 (3), 635–662.
Lou, D., Polk, C., Skouras, S., A tug of war: Overnight versus intraday expected returns. Journal of Financial Economics 134 (1), 192–213.
Qiu, L., Welch, I., 2006. Investor sentiment measures. Working paper, National Bureau of Economic Research.
Schmeling, M., 2009. Investor sentiment and stock returns: Some international evidence. Journal of Empirical Finance 16 (3), 394−408.
Tetlock, P.C., 2007. Giving content to investor sentiment: The role of media in the stock market. Journal of Finance 62 (3), 1139−1168.
Wang, W., 2018a. Investor sentiment and the mean-variance relationship: European evidence. Research in International Business and Finance 46, 227–239.
Wang, W., 2018b. The mean–variance relation and the role of institutional investor sentiment. Economics Letters 168, 61–64.
Wang, W., 2020. Institutional investor sentiment, beta, and stock returns. Finance Research Letters 37, 1–7.
Wang, W., 2021. The mean–variance relation: A 24-hour story. Economics Letters 208, 1–3.
Wang, W., Duxbury, D., 2021. Institutional investor sentiment and the mean-variance relationship: Global evidence. Journal of Economic Behavior and Organization 191, 415–441.
Wang, Y.H., Keswani, A., Taylor, S.J., 2006. The relationships between sentiment, returns and volatility. International Journal of Forecasting 22 (1), 109−123.
Yu, J., Yuan, Y., 2011. Investor sentiment and the mean-variance relation. Journal of Financial Economics 100 (2), 367−381.