Macro Variables And The Components Of Stock Returns

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Macro Variables And The Components Of Stock Returns

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Author : Paulo F. Maio
language : en
Publisher:
Release Date : 2015

Macro Variables And The Components Of Stock Returns written by Paulo F. Maio and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

We conduct a decomposition for the stock market return by incorporating the information from 124 macro variables. Using factor analysis, we estimate six common factors and run a VAR containing these factors and financial variables such as the market dividend yield and the T-bill rate. Including the macro factors does not have a significant impact in the estimation of the components of aggregate (excess) stock returns -- cash-flow, discount-rate, and interest-rate news. Using the macro factors in the computation of cash-flow and discount-rate news does not significantly improve the fit of a two-factor ICAPM for the cross-section of stock returns.

Revisiting Macroeconomic Factors And Share Returns

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Author : Patrick B. Baghdasarian
language : en
Publisher:
Release Date : 2012

Revisiting Macroeconomic Factors And Share Returns written by Patrick B. Baghdasarian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

This paper examines the effects of macroeconomic variables on the returns of a broad cross-section of emerging stock markets (ESMs) for a relatively recent time period. Specifically, the paper examines the quarterly data of select local and global macroeconomic variables for 9 ESMs over the period 2002-09 using the same methodology that was applied in Fifield et al. (2002) on similar sets of data. Applying the methodology used in Fifield et al. (2002) we find that the local economic variables included in the study can be summarized by net exports, interest rates, and currency, while global variables can be summarized by world-market returns and US interest rates. The paper uses principal component analyses (PCA) to reduce the number of the variables. The principal components (PCs) are then selected by way of ad hoc rules-of-thumbs. A scree test is then applied in conjunction with an analysis of the acceleration factors of each scree plot to provide robustness. Essentially, a minimum of 0.5173 to a maximum of 0.7775 of the variation can be explained by the first PC, while approximately 0.76 to 0.95 of the cumulative variance can be explained by both the first and second PC. We retain the first and second PCs; thus, we can reduce the dimensionality of the variables from six to two variables. The retained PCs are used as inputs into two regression analyses in order to explain the variation of index returns within each of the 9 ESMs over the period 2002-09. The first regression analysis only includes PCs retained that contain global macroeconomic variables, while the second includes both the PCs that contain global macroeconomic variables as well as PCs that contain information at the local level or local macroeconomic information. The R2 and adj. R2 of each regression analysis was compared for robustness. The regression analysis indicates that while global factors are consistently significant with a high degree across the cross-section of ESMs when both the first and second recession analysis is investigated, local factors, do not show consistent significance across the cross-section of ESMs when the second regression analysis is investigated. Additionally, we use the retained global and local PCs as inputs for a third regression analysis in which the residuals of the first model are used as an input for the dependent variable in order to make sure the improvement in the R2 and adj. R2 between the first and second regression analysis are attributed to a robustness versus general improvements of R2 and adj. R2 due to adding additional variables. After examining the R2 and adj. R2 we find that although the first regression analysis has a relatively higher R2 and adj. R2 compared to the second linear mode the first linear model does not provide a high enough R2 or adj. R2. Essentially, both linear models lack predictive prowess because Additionally, the second linear model does not show much improvement to the first when we add additional explanatory variables. This was validated when we examined the R2 and adj. R2 of the third linear model as both variables were significantly lower than the R2 and adj. R2 of the first model. Furthermore, for certain ESM the variance among local variable show a degree of significance, but they do not show the same high degree of significance as compared to the level of significance indicated by the global macroeconomic variables. Finally, cross-validation (CV) was applied to both models. We find that for the ESM that had significant local variables for some & alpha; the second model had a lower mean squared error (MSE) compared to the MSE of the first model.

Stock Return Predictability Macro Economic Regressed Sum Of The Parts Method

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Author : Prince Ratchatasumrit
language : en
Publisher:
Release Date : 2017

Stock Return Predictability Macro Economic Regressed Sum Of The Parts Method written by Prince Ratchatasumrit and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

This research compares and improves stock market return forecasting via the Sum-of-theParts (SOP) method introduced by Ferreira and Santa-Clara (2011) to 3 representative countries from developed, emerging, and frontier market. Our process includes forecasting separately two main decomposed components of the SOP method with macro-economic variables. The two components from SOP method being regressed are growth in price-to-earnings and growth in earnings, while macro-economic variables being used are growth in foreign portfolio investment, log growth in consumer price index, and log growth in industrial production index. The forecasted components are then being sum with dividend-price ratio to forecast one step ahead stock market return. The findings show that macro-economic regressed variables outperform both the historical sample mean approach and original SOP method, with results from out-of-sample R-squared of 7.29% for USA and 5.96% for Vietnam. The results of SOP method, without macro-economic regressed components, do not consistently carry itself up to 2017 data due to correlation issues of forecasted components. The forecasted growth in price-to-earnings multiple in relation to foreign portfolio investment suggested to us that investors in neither of the representative countries suspect foreign investment holdings to have any impact on growth in price-to-earnings multiples. While, investors in United States, unlike Thailand and Vietnam, may have optimistic expectation that growth in inflation, proxied by CPI, indicates growth in price variable in price-to-earnings multiples, encouraging them to purchase equities to prevent loss from devaluation. The forecasted growth in earnings in relation to GDP, proxied by IPI, on the other hand, suggest among investors from United States to bring about the growth in earnings of corporate entities, unlike those from Thailand and Vietnam.

Macrofactors And Stock Returns

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Author : Phillip Rochon Mack
language : en
Publisher:
Release Date : 1987

Macrofactors And Stock Returns written by Phillip Rochon Mack and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with categories.

Selecting Macroeconomic Variables As Explanatory Factors Of Emerging Stock Market Returns

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Author : Chris Bilson
language : en
Publisher:
Release Date : 2008

Selecting Macroeconomic Variables As Explanatory Factors Of Emerging Stock Market Returns written by Chris Bilson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

Emerging stock markets have been identified as being at least partially segmented from global capital markets. As a consequence, it has been argued that local risk factors rather than world risk factors are the primary source of equity return variation in these markets. This paper seeks to address the question of whether macroeconomic variables may proxy for local risk sources. We find moderate evidence to support this hypothesis. Further, we investigate the degree of commonality in exposures across emerging stock market returns using a principal components approach. We find little evidence of commonality when emerging markets are considered collectively, however at the regional level considerable commonality is found to exist.

Can Common Components Eliminate Momentum Returns

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Author : Sirajum Munira
language : en
Publisher:
Release Date : 2008

Can Common Components Eliminate Momentum Returns written by Sirajum Munira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.

This paper investigates the presence of momentum return when priced for common components. Using a sample period from 1926 through 2005 for all stocks listed in the NYSE, AMEX and NASDAQ we show significant momentum return remains both at the portfolio level and at the individual stock level. We report positive and significant alpha of 0.009 when Fama-French three factors and macroeconomic factors are used as common components at the portfolio level. At the individual stock level, though Fama-French factors cannot eliminate momentum return, the premium diminishes when macroeconomic variables are employed. The result is more pronounced when lagged variables are in play and during market upturn. Our results are robust in different sub-periods and when contemporaneous and lagged variables are used. We conclude that common components cannot eliminate momentum return; the explanatory power of macroeconomic variable is conditioned on assumptions like predictor variable and market condition.

The Effects Of Macroeconomic Variables On Stock Prices Conventional Versus News Models

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Author : John Vaz
language : en
Publisher:
Release Date : 2011

The Effects Of Macroeconomic Variables On Stock Prices Conventional Versus News Models written by John Vaz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.

Stock prices are usually analysed and explained in terms of underlying financial indicators, such as earnings per share or dividend payout ratios. Nevertheless, fluctuations in the conditions of the economy can result in changes in demand, which can impact on profits and dividends. Since macroeconomic variables affect financial indicators it follows that macroeconomic variables affect stock prices. If markets are rational and efficient, then stock prices will reflect all known information regarding macroeconomic factors that are perceived to affect stock prices. It follows that stock prices should not change significantly unless there is a surprise or news about the state of the economy (as reflected in unexpected changes in macroeconomic variables). Intuitively, this implies that models of stock price determination based on news ought to be superior to conventional models that use the levels or changes in variables. The utilisation of news in research on stock prices is very limited. Two approaches have been traditionally used to represent the news in the absence of surveys of expectations: either by assuming announcements are news such as those in event studies or by using an econometric time series approach to extract the news components from total changes in the variables, as is the case with the news model. The majority of studies involving news models have been in the foreign exchange market using news estimated econometrically-very little has been done in estimating and testing a macro news model of stock prices and certainly nothing has been done on stock prices in developed economies such as Australia. Thus this research is motivated by the significant gaps in the literature with respect to the development, estimation and testing of a news model of stock prices. Most of the studies that investigate the relations between macro variables and stock prices have been carried out using conventional approaches by estimating models that use the variables in their levels. Some of the multivariable models of stock prices arise as a result of anomalies found in implementing the capital asset pricing model. Other multivariable approaches such as the arbitrage pricing theory (APT), due to Ross (1976), suggest that macro variables are useful, but APT is silent on the appropriate macroeconomic explanatory variables. Furthermore, there have been limited attempts to examine macroeconomic variables collectively, but not with the aim of developing a macro model of stock prices. This thesis presents the results of research that uses comprehensive econometric procedures to investigate which macroeconomic variables have significant effects on Australian stock prices and whether news about such variables can enhance the performance of conventional stock price determination models. Seven macroeconomic variables are examined: interest rates, inflation, the money supply, economic activity, commodity prices, exchange rates and a foreign stock market index to account for spill-over effects. This provides a valuable contribution to the understanding of the individual effects of macroeconomic variables on stock prices and adds to the limited literature regarding the usefulness of news in models of stock price determination. The results from this research demonstrate that although news is a theoretically sound and intuitively plausible basis for improving macro models of stock prices, in practice there is no ex-ante exploitation possible by estimating news utilising econometric methods. Simply put, news cannot be predicted-this is established by using three comprehensive methods of estimating news, which is the residual of a model fitted to the time series data of a particular variable.

Do Macroeconomic Variables Have An Effect On The Us Stock Market

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Author : Dennis Sauert
language : en
Publisher: GRIN Verlag
Release Date : 2010-10

Do Macroeconomic Variables Have An Effect On The Us Stock Market written by Dennis Sauert and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10 with Business & Economics categories.

Seminar paper from the year 2010 in the subject Economics - Case Scenarios, grade: 1.0, Berlin School of Economics, language: English, abstract: The objective of this paper is to examine whether the unanticipated change of specific macroeconomic variables influences the US stock market represented by the S&P 500 using monthly data from 1986 to 2007. Thereby, the performance of the arbitrage pricing theory of Ross (cp. Ross, S., 1976) shall be studied. To explain the behavior of the US stock market return the paper contains the five predefined variables consumer price index (CPI), industrial production index (IPT), money stock M1 (M1), total consumer credit outstanding (TCC) and the term structure of interest rates (Term) which are approximately similar to those variables used by Ross (cp. Chen N. F. et al., 1986, pp. 383-403). Applying the OLS method, it was found that CPI, IPT and Term are negatively related to the US stock return. It was also detected that M1 affects the stock market lagging 8 months and 12 months. However, the test statistics showed that TCC has rather no impact on the US stock market return. To ensure that the ultimate results are not spurious, care will be taken in regards to autocorrelation, multicollinearity, serial correlation as well as heteroskedasticity.

Do Macroeconomic Variables Affect Stock Returns In Brics Markets An Ardl Approach

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Author : Vanita Tripathi
language : en
Publisher:
Release Date : 2015

Do Macroeconomic Variables Affect Stock Returns In Brics Markets An Ardl Approach written by Vanita Tripathi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

The Arbitrage Pricing Theory (APT) propounded by Ross in 1976 argued for a variety of macro economic variables (sources of systematic risk) in explaining stock returns. In the same vein, this paper examines the relationship between macroeconomic variables (GDP, inflation, interest rate, exchange rate, money supply, and oil prices) and aggregate stock returns in BRICS markets over the period 1995-2014 using quarterly data. We have applied Auto Regressive Distributed Lag (ARDL) model to document such a relationship for individual countries as well as for panel data.Contrary to general belief, we find that GDP and inflation are not found to be significantly affecting stock returns in most of BRICS markets mainly because Stock returns generally tend to lead rather than follow GDP and inflation. In line with the theory and literature, we find significant negative impact of interest rate, exchange rate and oil prices on stock returns and a positive impact of money supply.This study would be a valuable addition to the growing body of empirical literature on the subject besides being useful to policy makers, regulators and investment community. Policy makers and regulator should watch out for impact of fluctuations in exchange rate, interest rate, money supply, and oil prices on volatility in their stock markets. Investor can search for arbitrage opportunities in BRICS markets on the basis of these variables but not the basis of GDP or inflation.

Macroeconomic Variables And Common Stock Returns

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Author : Eben Otuteye
language : en
Publisher:
Release Date : 1989

Macroeconomic Variables And Common Stock Returns written by Eben Otuteye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with categories.