Active Vs. Passive Fund Management

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FINS 2624 ASSIGNMENT 2

EXECUTIVE SUMMARY

To sum up, based on the discussion above, it seems that for the US market, it appeared to

be working under a weak-form of inefficient market considering market anomalies of

momentum effects and pricing-earning ratio and intrinsic measure anomalies. However,

for Australia market, due to the characteristics difference of Australia market, the portfolio

of Australian shares are consistent with the weak-form of market efficiency, however, it

does not apply to the individual stocks. Besides, no intrinsic measure anomalies were

found for the long horizon. Overall, Australia market is more efficiency compared to US

market in terms of weak-from of market efficiency.

In addition, after examining the small firm in January effect anomaly, book to market ratio

anomaly and post earnings announcement price drift anomaly, we could see that Australian

market especially for small firms was influenced by January effect, book to market ratio

and post earnings announcement anomaly, which indicate market inefficiency of Australia

market. On the other hand, for the US market, the last three anomalies all applied to US

market also, and it seems that US market is also not market efficiency.

PART 1

An efficient market exists when the stock price fully reflects all the information available .

There are several ways to test whether the market is efficient. The main tests include event

study, the patterns in stock return, predictors of broad market return, test of anomalies and

the inside information . These tests are conducted by using risk models to calculate the

excess return of the market , the market is said to be efficient if there is no excess return to

be found .

Event study exams the influence on stock price by a specific event and a single-index

model is used :

rt = a + brmt + et => et = rt *ƒ²*ƒ”€š( a + brmt )

rt : stock return during the period t

a : average rate of return during period t with no market return

brmt : sensitivity to market return

et : part of stock return due to firm-specific event

And we call et abnormal return.

There are also other tests, such as patterns in stock return and predictors of broad market

return which are early tests for the market efficiency and are included in the weak form

tests .

The first test is conducted by exam the past stock prices to find the trend . It will need to

calculate the serial correlation of stock market return . If it is positive serial correlation,

then it means what followed by the positive returns is a positive return, otherwise, it is a

negative return . There are problems associated with this test. For the short horizons, a

research conducted by Conrad and Kaul and Lo and Mackinlay found that the correlation

coefficient is quite small for the weekly return which suggested that there is no strong

evidence of the existence of patterns in stock returns over short horizons . However, for the

long run, researchers do find that it tends to have a negative correlation coefficient .

The second test is based on the variables such as dividend/price ratio, earnings yield, and

spread between yields on corporate bonds, and using these variables to predict market

returns . If we can say that market returns are predicted by predicting risk- adjusted

abnormal returns then probably the market is inefficient . However, the difficulty here is

uncertainty about whether the return we get is result from the predictability by using the

indicator in risk premium or risk- adjusted abnormal returns .

Test of anomalies are included in semi strong tests . These tests are normally conducted by

applying the CAPM model that is used to adjust the risk . That is, the risk adjusted returns

are gained by testing both risk adjustment and market efficiency hypothesis .

There are several examples of anomalies. The small firm in January Effect is about the

effect of size . It found that smallest sized firms tend to have a higher return despite the

risk are already been adjusted by using CAPM, and it most occurred in January .

The neglected firm Effect is actually another way to explain the above example of

anomalies, as established by Arbel and Strebel that due to less information available

related to small firms so it makes small firms more risky . Besides the liquidity effects is

another reason to explain the abnormal return of the small firms . When the stocks are ness

liquid it may incur a high cost for transactions, and for small firms it is likely that their

stocks will not be as liquid as big firms .

The other examples include Book to Market Ratio. Researches by Fama and French and

Reinganum found that there is a relationship between book to market ratio and returns so it

is possible for investors to look at the book to market ratio to predict the return and own

abnormal return . The finding makes a big doubt as to the market efficiency .

The last one is Post Earnings Announcement Price Drift. For an efficiency market the price

of stock should reflect the information immediately after the release, however, what in

reality is that price continued to rise or fall through a period after the announcement date

and so was the abnormal returns . It is called Post Earning Announcement Drift.

The last test is inside information. In a case that insiders make big return because of

knowing the inside information, the market is said to be inefficient . As the price of stock

is not fully reflect all the available information.

Besides, for all the tests above, there is one common problem related to the tests. That is,

as the test conducted by using risk models, it may then need to take into account of the

efficiency of the models used .

PART 2

A market anomaly exists where findings cannot be reconciled with the efficient market

hypothesis or when returns when risk adjusted are still abnormal. Prior to examining the

anomalies in the US and Australian markets, it is necessary to examine the different forms

of market efficiency, rendering the violation of specific anomalies to the level of market

efficiency. The weak form of market efficiency maintains that all current prices reflect all

past information, including information derived from technical analysis, history of prices,

trading volumes or short term interest rates. The semi-strong form hypothesis maintains

that all publicly available information should already be impounded into the stock price;

this would obviously include everything that is known about the firm, eg, product line, and

earning forecasts made should reflect in current prices. Strong form efficient hypothesis

asserts that all information, including insider information should be impounded into stock

prices. Thus if markets are efficient, then only new information should affect the future

movement of prices, and since new information is unpredictable , prices should follow a

random walk – that is, they are equally likely to move up or down.

There are five prominent market anomalies highlighted in past research for US markets.

1. Momentum and reversal Effects anomaly also known as the winner-loser anomaly

Momentum effects are observed, where in the short horizon of typically less than three

months, stock that perform well continue to perform well, while stocks performing poorly

continuing to perform poorly. Thus in the short horizon, stock prices exhibit a positive

serial correlation. Serial correlation refers to a tendency for future performance to be

related to the past. Here the price of stock can be (weakly) predicted based on the last

twelve months of past performance. Conrad and Kaul (1988) and Lo and MacKinlay

(1988) observed positive serial correlations for the short horizon. They observed weekly

stock returns on the NYSE , and found the correlations for small stock to be medium,

while correlation for large stocks were small. Overall, while a correlation exists, the

authors found no definite presence of trading opportunity as the correlation was relatively

small. On the other hand, Jegadeesh and Titman (1993) found that instead of looking at

individual stocks, portfolios of the best performing stocks tend to reliably outperform other

stocks on an intermediate horizon of three to twelve months. Many studies have

investigated how individual prices are slow to reaction, possibly explain the weak

correlation for individual stocks, however aggregate information have a quick, and often

overreaction on stock prices, explaining why the momentum effect would be stronger for

portfolios of stocks rather than individual stocks. The positive momentum for these

portfolios was significant so much so that they offered a tangible opportunity for profit

using this strategy. Jagedeesh and Titman (2001) substantiated their early finding in 1993

of the momentum effect providing a favourable investment strategy. Jegadeesh et al.

(2004) observe that analyst often inherently favour high momentum stocks and make

recommendations on that basis. In fact, Burch and Swaminathan (2001) point out a high

proportion of up to 50% of actively managed funds utilize momentum investing. Bird et al.

(2005) point out that investors make no reference to valuation for their decision in the

above regards, that is that investors are irrational, and hence play no importance to correct