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This paper investigates the generalized Fisher hypothesis for nine equity markets in the Asian countries. It states that the real rates of return on common stocks and the expected inflation rate are independent and that nominal stock returns vary in a one‐to‐one correspondence with the expected inflation rate. The regression results indicate that stock returns in general are negatively correlated to both expected and unexpected inflation, and that common stocks provide a poor hedge against inflation. However, the results of the VAR model indicate the lack of a unidirectional causality between stock returns and inflation. It also fails to find a consistent negative response neither of inflation to shocks in stock returns nor of stock returns to shocks in inflation in all countries. It appears that the generalized Fisher hypothesis in the Asian markets is as puzzling as in the developed markets.

The impact of accounting earnings based compensation contracts an effort allocation is analyzed using an agency‐theoretic model. In this model, the CEO of a publicly traded firm expends effort on operational short‐run activities and strategic long‐run activities. The shareholders desire the CEO to expend more effort in the strategic long‐run activities because the return to shareholders depends more on long‐run than short‐run activities. More specifically, they desire the effort to be allocated between these two activities on the proportion of the sensitivity of stock returns to these two activities. Compensating the CEO based on the stock returns performance measure is shown to induce the CEO to exert the desired proportion of effort in the long‐run activities. Unlike stock returns, accounting earnings are believed to focus more on the short‐run performance of the firm and not reflect the full impact of a CEO's long‐run effort. Compensating the CEO based on accounting earnings, in addition to stock returns, is shown to induce the CEO to expend less than the desired proportion of effort in long‐run activities. As the emphasis placed on accounting earnings relative to stock returns increases, the CEO decreases the proportion of effort expended in long‐run activities. On the positive side, including accounting earnings in the contract increases the total effort that the CEO exerts in short‐run and long‐run activities. The benefit accruing from the increase in total effort more than offsets the dysfunctionality caused by the short‐run focus. More specifically, adding accounting earnings to the incentive contract is shown to increase the expected return to the shareholders. In summary, while accounting earnings cause the CEO to be short‐run focused, their use in the incentive contract improves the firm's performance by motivating the CEO to work harder overall.

Understanding correlations between stock and direct real estate returns, which is the key factor that determines diversification benefits in a portfolio, helps formulate and implement better investors' asset allocation and risk management strategies. The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. The purpose of this study is to test the time‐varying correlations of returns between general stocks and direct real estate.

This study uses the dynamic conditional correlation (DCC) model, which is a simplified version of the multivariate generalised autoregressive conditional heteroskedasticity (GARCH) model, proposed by Engle to test the time‐varying correlations between stock and direct real estate returns in six markets, which include the USA, the UK, Ireland, Australia, Hong Kong and Singapore.

The empirical results show significant time‐varying effects in the conditional covariance between stock returns and direct real estate returns. The results vary across different real estate sub‐sectors, and across different countries. It is observed that the conditional covariance increases in the boom markets, but becomes weaker in the post‐crisis periods. The authors observed significant jumps in the conditional covariance between the two asset markets in Singapore and Hong Kong in the post‐1977 Asian Financial crisis periods and in the post‐2007 US Sub‐prime crisis periods.

The past studies find that direct real estate returns have a low unconditionally (long‐run) correlation with the returns of equities. However, assuming that such correlation is constant throughout all periods is implausible. This study fills in the gap by using the dynamic conditional correlation models to allow for time‐varying effects in the correlations between stock and real estate returns.

The aim of this paper is to examine the relationship between weather (temperature) and stock market returns using daily data from Portugal; also, to examine whether the temperature is driven by calendar‐related anomalies such as the January and trading month effects.

Daily financial and weather data from Lisbon Stock Exchange (PSI 20 index) and Lisbon capital for the period 1995‐2007 are considered. The paper employs an AR(1)‐TGARCH(1,1) model under several distributional assumptions (Normal, Student's‐t and GED) for the errors.

Empirical results show that temperature affects negatively the PSI20 stock returns in Portugal. Moreover, temperature is dependent of both January and trading month effects. Stock returns were found to be positive in January and higher over the first fortnight of the month. Lower temperature in January leads to higher stock returns due to investors' aggressive risk taking.

Further research should investigate the impact of other meteorological variables (humidity, amount of sunshine) and other calendar anomalies on the course and behaviour of major international stock indices using data before and after the recent crisis.

The findings are helpful to financial managers, investors and traders dealing with the Portuguese stock market.

The contribution of this paper is to provide evidence on the empirical linkages between temperature and stock market returns using GARCH models. To better understand the relationship between the temperature and stock market returns, the paper also examines whether the returns are higher in winter (January effect) and during the first or second fortnight of the month (trading month effect). To the best of the author's knowledge, this is the first empirical investigation on weather and stock market returns relationship for Portugal.

In the increasingly globalized economy, foreign exchange fluctuations have multiple, conflicting effects on domestic stock prices. The purpose of this paper is to examine return data to determine the relation between the dollar’s value and stock prices as it relates to monetary policy.

The authors examine US stock returns over a 40-year period, which is classified according to monetary policy and dollar trend. To better understand the impact of foreign exchange fluctuations, the authors estimate a model of stock returns using the three Fama-French factors and a momentum factor. Then the authors explore the underlying economic fundamentals that drive the sharp difference in annual returns between periods when the dollar is in an uptrend trend with loose monetary policy and periods when the dollar is in a downtrend with tight monetary policy.

Over the last 40 years, US stock returns were 2.5 times higher when the dollar was trending up vs down. The factor model of returns shows that equity returns are positively associated with periods when the dollar appreciated. Returns were particularly high when the dollar was in an uptrend during accommodative monetary policy. During these periods, stocks in the consumer goods and services industries provided relatively high returns. This occurred with strong economic growth due to consumer spending. Stocks exhibited the lowest returns when the dollar was depreciating and the Federal Reserve was tightening.

The key contribution of the research is that currency trends should be analyzed in the light of monetary policy. During periods of accommodative monetary policy and dollar appreciation, the US stock market provided average returns of 18.7 percent compared to −3.29 percent during a period of restrictive monetary policy and dollar depreciation. This result is driven by stronger economic growth, which is composed of consumer spending that more than offsets the dollar’s impact on net exports.

The purpose of this paper is to investigate the profitability of momentum investment strategy and the predictive power of trading volume for equities listed in the Australian Stock Exchange.

Following the Lee and Swaminathan's approach, portfolios on past returns and past trading volume is constructed. In this approach, all stocks are ranked independently on the basis of past returns and past trading volume. The stocks are then assigned to one of five portfolios based on past returns and one of three portfolios based on trading volume over the same period.

A strong momentum effect for the Australian market during the period 1988 through 2002 is observed. Further, momentum plays an important role in providing information about stocks. Past trading volume appears to predict both the magnitude and persistence of price momentum.

Substantial momentum observed in monthly stock returns has investment implications. Abnormal returns vary from 0.3 to 7 per cent per month in the intermediate horizon.

This study provides an out of sample evidence by examining the relationship between “trading volume” (measured by the turnover ratio) and “momentum” strategies in an Australian setting.

Historical stock prices have long been used to evaluate a stock’s future returns as well as the risks associated with those returns. Similarly, historical dividends have been used to evaluate the intrinsic value of a stock using, among other methods, a dividend discount model. In this chapter, we propose an alternate use of the dividend discount model to enable an investor to assess the risks associated with a particular stock based on its dividend history. In traditional applications of the dividend discount model for stock valuation, the value of a stock is the net present value of its future cash dividends. We propose an alternative approach in which we calculate the internal rate of return for a stream of future cash dividends assuming the current stock price. We use a bootstrapping approach to generate a stream of future cash dividends, and use a Monte Carlo simulation approach to run multiple trials of the model. The probability distribution of the internal rates of return obtained from the simulation model provides an investor with an expected percentage return and the standard deviation of the return for the stock. This allows an investor to not only compare the expected internal rates of return for a group of stocks but to also evaluate the associated risks. We illustrate this internal rate of return approach using stocks that make up the Dow Jones Industrial Average.

Negative relationship between the return of a stock and its liquidity suggests that the illiquid stocks are riskier than liquid stocks. Thus, researchers tend to include the stock liquidity as a variable in asset pricing models, where the stock and market liquidities are usually considered as independent. The purpose of this paper is to reexamine the relationship between the return of a stock and its liquidity by using a relative measure that links the individual stock liquidity with market‐wide liquidity.

Multivariate regressions are employed to examine the effect of relative market liquidity on the stock return while controlling the effects of other factors.

Negative relationship between the stock return and liquidity is confirmed, but the relationship is not linear. It is found that the relative measure of liquidity is not a substitute, but complement to other liquidity measures used in prior studies. It is also found that fluctuation in relative stock liquidity does not positively affect the return.

The study is conducted on New York Stock Exchange and American Stock Exchange exchanges using monthly data. The robustness tests using the daily or weekly data are not conducted.

Findings may suggest that investors do not seriously concern about the fluctuations of individual stock liquidity, provided that the stock liquidity is higher than the average market liquidity.

For the first time, the liquidity risk is tested using a relative measure instead of an absolute measure. Since fluctuation in stock liquidity does not positively affect the return, a new question arises whether the variability in liquidity can reflect the liquidity risk.

The purpose of this paper is to examine the relation between gold return and stock market return and whether its relation changes in times of consecutive negative market returns for an emerging market, Malaysia.

The paper applies the autoregressive distributed model to link gold returns to stock returns with TGARCH/EGARCH error specification using daily data from August 1, 2001 to March 31, 2010, a total of 2,261 observations.

A significant positive but low correlation is found between gold and once‐lagged stock returns. Moreover, consecutive negative market returns do not seem to intensify the co‐movement between the gold and stock markets as normally documented among national stock markets in times of financial turbulences. Indeed, there is some evidence that the gold market surges when faced with consecutive market declines.

Based on these results, there are potential benefits of gold investment during periods of stock market slumps. The findings should prove useful for designing financial investment portfolios.

The paper evaluates the role of gold from a domestic perspective, which should be more relevant to domestic investors in guarding against recurring heightened stock market risk.

Existing empirical studies that document momentum trading strategies do not provide any insight on how investors choose the time horizon that is used to compute the past stock returns. Indeed, since past returns over overlapping time periods are positively correlated, it is hard to identify the exact historical time period on which investors base their trading strategies and to investigate whether such a period is unique. The purpose of this paper is to investigate this and reach some conclusions.

In this paper the author uses experimental setting to analyze how investors choose which of the past returns to use as a basis for their trading strategies and whether this choice depends on their investment horizon. The advantage of this experimental setting over the existing empirical research is the ability to control for the investment horizon of the subjects and the ability to provide the subjects with a hand‐picked set of stocks with uncorrelated past returns over overlapping time periods. In the study subjects were asked to make short‐term investment decisions based on historical short‐term realized returns over two time intervals of different lengths. In each treatment the subjects were divided into two groups based on the lengths of their investment horizons, which were set to match the lengths of time intervals used to compute the historical returns.

It was found that subjects followed momentum trading strategies based on both historical returns provided to them and paid more attention to the historical returns over the shorter time period. In addition, some evidence was found that subjects with longer investment horizons rely less on momentum strategies.

A wide sample was used to create an original set of observations and conclusions.