Market Equity Premium Research Articles

Risk Premium and Volatility Analysis on Indonesia Stock Exchange

Market risk premium and market volatility are important in investment decisions. Volatility is an important variable in derivative securities which is a measure of changes in stock returns. The research focuses on stock return volatility, research that points to a risk premium in emerging markets. The purpose of this study is to explain the relationship between market equity premium and volatility using GARCH (1.1) on the Indonesia Stock Exchange. This research uses daily closing price data of the Indonesia Stock Exchange Composite Index (JCI). The result of this study, that there is a relationship between risk premium and volatility in the Indonesian stock market. The conclusion of this study is to try to test whether there is a relationship from the volatility of return to risk premium in the Indonesian stock market. Using the daily trend of the Indonesian stock market (IDX) from January 2010 to September 2023.

Risk, ambiguity, and equity premium: International evidence

We empirically examine the relation between risk, ambiguity, and market equity premium in 21 international stock markets. After estimating each country's degree of ambiguity from intraday data of iShares country ETFs (exchange-traded funds), we find a positive risk-return tradeoff. Investors' attitudes toward ambiguity is conditional on their expectations of probability of gains, but its relationship is nonlinear. This nonlinearity in ambiguity premium is more prominent in emerging markets. Additionally, we conduct a cross-country analysis, which shows that cross-country variations in cultural and institutional factors affect investors' behavior. Our international evidence supports that ambiguity alongside risk are the key determinants of investors' decision-making.

Does the kitchen‐sink model work forecasting the equity premium?

AbstractWe propose applying partial least squares (PLS) to estimating the previously considered ineffective multivariate regression model when forecasting the market equity premium out‐of‐sample. First, PLS is a dimension reduction method that effectively addresses the issue of multicollinearity prevalent among financial variables. Second, PLS constructs factors with the supervision of past equity premiums, resulting in an explicit linkage between the forecasting target and PLS components. Our empirical results show that the PLS‐estimated kitchen‐sink model consistently and robustly outperforms many competing alternatives, such as shrinkage estimators and forecast combinations, by a statistically and economically significant margin. Our analysis differs from Kelly and Pruitt (2013) in factors such as data source, model estimation and specification, and economic rationale.

Equity premium prediction: keep it sophisticatedly simple

Following the keep-it-sophisticatedly-simple principle, KISS, we propose using the averaging window approach to forecast the market equity premium in unstable environments. First, the estimation methodology of averaging window is a theoretically justified method robust to uncertainties on structural breaks and estimation window sizes. Second, the averaging window method has the obvious advantages of being understandable to forecast users and simple to implement, thus encouraging engagement and criticism. Our empirical results demonstrate the superior performance of the averaging window when forecasting the U.S. market equity premium, exceeding a wide range of methods which have been shown effective, such as shrinkage estimators and technical indicators.

Time-frequency Forecast of the Equity Premium

Any time series can be decomposed into cyclical components fluctuating at different frequencies. Accordingly, in this paper we propose a method to forecast the stock market's equity premium which exploits the frequency relationship between the equity premium and several predictor variables. We evaluate a large set of models and find that, by selecting the relevant frequencies for equity premium forecasting, this method significantly improves in both statistical and economic sense upon standard time series forecasting methods. This improvement is robust regardless of the predictor used, the out-of-sample period considered, and the frequency of the data used.

Cross-Sectional PEG Ratios, Market Equity Premium, and Macroeconomic Activity

This article explores the information content of PEG ratios (price/earnings to growth ratios) for future aggregate returns and economic fundamentals. We first establish an analytic link between PEG ratios and time-varying expected returns of stocks. We then combine the link with empirical asset pricing models to extract market-wide information from cross-sectional PEG ratios. The resultant cross-section estimates of the risk premiums on stock betas serve as proxies for market-wide information. The proxies contain salient information about future market equity premiums and macroeconomic activity both in-sample and out-of-sample. Moreover, the proxies outperform aggregate PEG ratios and the cross-section beta-premium estimate based on conventional valuation ratios and retain incremental power in forecasting future market equity premiums. The results are robust to using various econometric methods for standard error adjustments.

Risk Preferences and the Macroeconomic Announcement Premium

This paper develops a revealed preference theory for the equity premium around macroeconomic announcements. Stock returns realized around pre‐scheduled macroeconomic announcements, such as the employment report and the FOMC statements, account for 55% of the market equity premium. We provide a characterization theorem for the set of intertemporal preferences that generates a nonnegative announcement premium. Our theory establishes that the announcement premium identifies a significant deviation from time‐separable expected utility and provides asset‐market‐based evidence for a large class of non‐expected utility models. We also provide conditions under which asset prices may rise prior to some macroeconomic announcements and exhibit a pre‐announcement drift.

Anchoring-Adjusted Capital Asset Pricing Model

ABSTRACTWhat happens when the capital asset pricing model is adjusted for the anchoring and adjustment heuristic of Tversky and Kahneman [1974]? The surprising finding is that adjusting the capital asset pricing model for anchoring provides a plausible unified framework for understanding almost all of the key asset pricing anomalies. The anomalies captured in the theoretical framework include the well-known size and value effects, high alpha of low beta stocks, accruals, low volatility anomaly, momentum effect, stock splits, and reverse stock splits. The market equity premium is also larger with anchoring. This suggests that the anchoring-adjusted capital asset pricing model may provide the needed unifying structure to behavioral finance.

Risk Preferences and the Macro Announcement Premium

The paper develops a theory for equity premium around macroeconomic announcements. Stock returns realized around pre-scheduled macroeconomic announcements, such as the employment report and the FOMC statements, account for 55% of the market equity premium during the 1961-2014 period, and virtually 100% of it during the later period of 1997-2014, where more announcement data are available. We provide a characterization theorem for the set of intertemporal preferences that generate a positive announcement premium. Our theory establishes that the announcement premium identifies a significant deviation from expected utility and constitutes an asset market based evidence for a large class of non-expected models that features aversion to ”Knightian uncertainty”, for example, Gilboa and Schmeidler [30]. We also present a dynamic model to account for the evolution of equity premium around macroeconomic announcements.

Anchoring Adjusted Capital Asset Pricing Model

Empirical evidence on the behavioral of professional stock analysts suggest that they form qualitatively correct judgments within the same sector, and that they spend most of their research time on sector leaders. This suggest a role for the anchoring and adjustment of Tversky and Kahneman (1974). The surprising finding is that adjusting CAPM for anchoring-influenced judgments provides a plausible unified framework for understanding almost all of the key cross-sectional anomalies facing CAPM. The market equity premium is also larger with anchoring.

Resurrecting the Capital Asset Pricing Model

The capital asset pricing model is generally considered incapable of explaining the stock market behavior. I show that this conclusion is premature, and incorporating a pragmatic approach to approximating optimal Bayesian inference in the model resurrects CAPM. The adjusted CAPM internalizes the well-known size, value, and momentum effects, high-alpha-of-low-beta-stocks, accruals, low volatility anomaly, stock-split anomaly, and reverse stock-split anomaly. The market equity premium is also larger with anchoring. Immediate applications of the adjusted CAPM include improved cost of equity calculation, and improved evaluation of managed portfolio performance.

Equity premia and state-dependent risks

This paper evaluates the empirical relations between equity premia and state-dependent consumption and market risks. These relations are derived by combining the baseline CCAPM with a flexible mixture distribution that admits two regimes. We find that the response of the market equity premium to each risk is significant and state dependent. We also show, from various portfolio returns, that the responses to downside consumption risks are the most frequently significant ones, are often statistically larger than the responses to upside consumption risks, and tend to be larger for firms having smaller sizes and facing more financial distresses.

Do jumps contribute to the dynamics of the equity premium?

This paper investigates whether risks associated with time-varying arrival of jumps and their effect on the dynamics of higher moments of returns are priced in the conditional mean of daily market excess returns. We find that jumps and jump dynamics are significantly related to the market equity premium. The results from our time-series approach reinforce the importance of the skewness premium found in cross-sectional studies using lower-frequency data; and offer a potential resolution to sometimes conflicting results on the intertemporal risk-return relationship. We use a general utility specification, consistent with our pricing kernel, to evaluate the relative value of alternative risk premium models in an out-of-sample portfolio performance application.

Cross-Sectional PEG Ratios, Market Equity Premium, and Macroeconomic Activity

This paper exploits information contained in cross-sectional PEG ratios to extract estimates of the market's expectations for aggregate returns and economic fundamentals. By combining the loglinear present-valuation model and the Capital Asset Pricing Model (CAPM) logic, we establish a theoretic link between PEG ratios and expected returns of stocks. Using this theoretic link, we construct one proxy for aggregate market equity premium and one proxy for macroeconomic fundamentals. The equity premium proxy outperforms alternative predictors and has considerable power in forecasting future market returns over the period of May 1983 to December 2009. The equity premium proxy is also able to forecast future macroeconomic activity such as nonfarm payroll growth, personal consumption expenditure growth, nondurable consumption growth, inflation, and unemployment rate. The fundamentals proxy is highly correlated with unemployment rates both concurrently and intertemporally. The results are generally robust across subsample and to various econometric methods for standard-error adjustments. Our study suggests that the choice of cross-section data is critical to information extraction and that the CAPM remains a vital theoretic tool to guide empirical work.

Cross-Sectional Peg Ratios, Market Equity Premium, and Macroeconomic Activity

Cross-Sectional Peg Ratios, Market Equity Premium, and Macroeconomic Activity

Components of Market Risk and Return

This article proposes a flexible but parsimonious specification of the joint dynamics of market risk and return to produce forecasts of a time-varying market equity premium. Our parsimonious volatility model allows components to decay at different rates, generates mean-reverting forecasts, and allows variance targeting. These features contribute to realistic equity premium forecasts for the U.S. market over the 1840–2006 period. For example, the premium forecast was low in the mid-1990s but has recently increased. Although the market’s total conditional variance has a positive effect on returns, the smooth long-run component of volatility is more important for capturing the dynamics of the premium. This result is robust to univariate specifications that condition on either levels or logs of past realized volatility (RV), as well as to a new bivariate model of returns and RV.