Introduction

The mean-variance relationship has long been a focus in finance literature. Traditional financial theories propose a positive mean-variance relationship (Merton, 1973), i.e. bearing high (low) risk should be rewarded by high (low) returns, empiricalstudies document at best inconclusive evidence with three mainstreams due to different economic settings and volatility modelselection. French et a1. (1987), Scruggs (1998), Ghysels et a1. (2005), Lundblad (2007), Pastor et a1. (2008), Brandt and Wang (201o), and Rossi and Timmermann (2o1s), 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 a1. (2011), Fiore and Saha (2o15), and Booth et a1. (2016),among others, document a negative mean- variance relationship. Turner et a1. (1989), Glosten et a1. (1993), Sun et a1. (2017),and Wang et a1. (2017), among others, report both positive and negative relationship between risk and returns.

Behavior financial theories highlight investor sentiment in influencing stock prices, despite the traditional ones positing that stock prices are the discounted future cash flows and arbitrage leaves little space for investor sentiment (Fama, 1965). De Long eta1. (199o) argue that sentiment investors trading together brings systematic risk into stock markets. The risk originated from the stochastic shifts in investor sentiment imposes arbitrage limits on rational investors, impeding them from trading against noiseinvestors. As a result, the mispricing caused by sentiment investors is persistent. Baker and Wurgler (2006) state two routeswhereby investor sentiment can cause persistent impact on stock prices: (i) uninformed demand shocks, and (ii) limits on arbitrage. Uninformed demand shocks naturally persist in that irrational investors misbeliefs could be further strengthened by othersjOlRlRQ on the bandwagon (Brown and Cliff, 2005, p. 407). Limits on arbitrage demotivate arbitrageurs from relieving the impact of investor sentiment since they are commonly subject to relatively restricted

investment horizons and can hardly accurately forecast how the impact will persist. Therefore, one can observe that high levels of optimism (pessimism) would cause high (low) concurrent returns, and given the mean-reversion property, overpricing (underpricing) would be corrected and followed by low (high) subsequent returns.

Combining two streams of literature, Yu and Yuan (2o11), by sampling the US stock market, evidence the risk-return tradeoff amid low-sentiment periods but not over high-sentiment periods.

In line with the above-mentioned points, please prepare a report with a specific emphasis on the following seven requirements:

Required:

3. Critically review related literature, and summarise and evaluate approaches to construct proxies for investorsentiment. [12 marks

While attempting requirements 1 7 you should follow academic writing style format relying on journal artlcles. Failing to do so will lead to a FAIL in this module.

Guideline coverage of issues/answers expectations:

Requirement 3:

1. Specific reasons why proxies are requlred for investor sentiment.
2. Summarise main types proxies for investor sentiment
3. Evaluate merits and drawbacks of each type.