Stock Market Risk Premium Research Articles

Online Investor Sentiment via Machine Learning

In this paper, we propose utilizing machine learning methods to determine the expected aggregated stock market risk premium based on online investor sentiment and employing the multifold forward-validation method to select the relevant hyperparameters. Our empirical studies provide strong evidence that some machine learning methods, such as extreme gradient boosting or random forest, show significant predictive ability in terms of their out-of-sample performances with high-dimensional investor sentiment proxies. They also outperform the traditional linear models, which shows a possible unobserved nonlinear relationship between online investor sentiment and risk premium. Moreover, this predictability based on online investor sentiment has a better economic value, so it improves portfolio performance for investors who need to decide the optimal asset allocation in terms of the certainty equivalent return gain and the Sharpe ratio.

How is the ECB’s quantitative easing transmitted to the financial markets?

PurposeOver the last few years, the European Central Bank (ECB) has adopted unconventional monetary policies. These measures aim to boost economic growth and increase inflation through the bond market. The purpose of this paper is to study the impact of the ECB’s quantitative easing (QE) on the investor’s behavior in the stock market.Design/methodology/approachFirst, the authors theoretically identify the transmission channels of the QE shocks to the stock market. Then, the authors empirically assess the financial market’s responses to QE shocks in a data-rich environment using a factor augmented VAR (FAVAR).FindingsThe results show that the ECB’s unconventional monetary policy positively affects the stock market. A QE shock leads to an increase in stock prices and a drop in the realized volatility and the implied risk premium. The authors also suggest that the ECB’s QE is transmitted to the stock market through five main channels: the liquidity, the expectation, the portfolio reallocation, the interest rates and the risk premium channels.Practical implicationsThe findings help to better understand the behavior of stock market assets in a data-rich economic context and guide investors and policymakers in the presence of unconventional monetary tools. For instance, decision-makers and investors should consider the short-term effect of the QE interventions and the changing behavior of the financial actors over time. In addition, high stock market returns can increase risk appetite. This can lead investors to underestimate the market risk. Decision-makers and market participants should take into consideration the impact of the large injection of money through the QE, which may raise the risk of a speculative bubble in the financial market.Originality/valueTo the best of the authors’ knowledge, this is the first study that incorporates a theoretical and empirical analysis to explore QE transmission to the stock market in the European context. Unlike previous studies, the authors use the shadow rate proposed by Wu and Xia (2017) to quantify the effect of the ECB’s QE in a data-rich environment. The authors also include two key risk indicators – the stock market risk premium and the realized volatility – to capture investors’ behavior in the stock market following QE shocks.

Dynamic Autoregressive Liquidity (DArLiQ)

We introduce a new class of semiparametric dynamic autoregressive models for the Amihud illiquidity measure, which captures both the long-run trend in the illiquidity series with a nonparametric component and the short-run dynamics with an autoregressive component. We develop a generalized method of moments (GMM) estimator based on conditional moment restrictions and an efficient semiparametric maximum likelihood (ML) estimator based on an iid assumption. We derive large sample properties for our estimators. Finally, we demonstrate the model fitting performance and its empirical relevance on an application. We investigate how the different components of the illiquidity process obtained from our model relate to the stock market risk premium using data on the S&P 500 stock market index.

Empirical Analysis of the Relationship of Stock Market, Exchange Rate, CDS Spreads and VIX Index in Turkey

Küresel entegrasyon süreçlerinin hız kazanmasıyla yaşanan krizlerin yapısındaki ortak noktanın genel olarak ülke risk primindeki artışlar veya büyük açık ekonomilerde ortaya çıkan oynaklıkların olduğu görülmektedir. Bu çalışmanın amacı Türkiye’de borsa endeksi, döviz kuru, risk primi (CDS) ve korku endeksi (VIX) arasındaki ilişkileri incelemektir. Bunun için ARDL sınır testinden yararlanılmıştır. Analiz dönemi olarak hem veri bulunabilirliği açısından hem de Türkiye ekonomisi için yapısal bir dönüm noktası olan Şubat 2001 sonrası dönem kullanılmıştır. Literatürden farklı olarak hem ülke risk primini temsil eden CDS primi, hem de yurtdışı risk alma iştahını ve dolayısıyla yurtdışı konjonktürü yansıtan VIX endeksi aynı modelde kullanılmıştır. Bu şekilde CDS ve VIX göstergelerinin aynı modelde kullanılması sonucunda borsa endeksi üzerindeki etkilerinin aynı düzeyde olup olmadığı sorusuna ışık tutulmaya çalışılmıştır. Elde edilen ampirik bulgulara göre Türkiye’de borsa endeksini döviz kuru, CDS primi ve VIX endeksi etkilemektedir. Küresel piyasalara entegre bir ülke olan Türkiye’de bu sonucun beklentiler dahilinde düşünülmektedir. Yani döviz kuru, ülke risk primi ve yurtdışı risk alma iştahında meydana gelen değişimlerin borsa hareketleri üzerinde etkisi bulunmaktadır. Sonuçlarımız, küresel risk alma iştahını temsilen VIX endeksine kıyasla ülke riskini temsil eden CDS priminin BİST 100 için önemli bir gösterge olduğunu göstermektedir. Bu durumda hisse senedi piyasalarında incelenen değişkenlerin önemini öne çıkarmaktadır.

COVID Asymmetric Impact on the Risk Premium of Developed and Emerging Countries’ Stock Markets

We estimated the stock market risk premium during the COVID-19 pandemic with a GARCH-in-Mean (GARCH-M)(1,1) model. The analysis then explored the presence of regime changes using a two-regime Markov-Switching GARCH (MS GARCH)(1,1) model. The sample we used included the stock market indexes of nine countries from three geographical regions, including: North America (Canada, USA, and Mexico), South America (Brazil and Argentina), and Asia (Japan, South Korea, Hong Kong, and Singapore), over two periods: (a) pre-COVID (from 1 January 2015 to 31 December 2019); and (b) COVID (from 1 January 2020 to 31 December 2021). Our GARCH-M(1,1) estimation results indicate that the more developed countries’ stock markets experienced an important increase in their risk premium during the COVID period, likely explained by the massive government anticyclical policies. By contrast, developing countries’ stock markets, particularly in Latin America, experienced a reduction, and in some cases, even a total loss of the risk premium effect. From the perspective of investors and portfolio risk managers, the identification of high and low volatility periods and their estimated probability of occurrence is useful for the characterization of stress scenarios and the design of emerging strategies. For governments and central bankers, the implementation of different policies should respond to the more likely scenarios but should also be prepared to respond to other less likely scenarios. Institutional preparedness to respond to as many different scenarios as may be identified with the use of MS GARCH models can make their interventions more successful. This work presents an objective example of how the use of MS GARCH models may be of use to practitioners in both the financial industry and government. We confirmed that the results of a two-regime MS GARCH model are superior to those obtained from a single-regime model.

Stock Market and No‐Dividend Stocks

ABSTRACTWe develop a stationary model of the aggregate stock market featuring both dividend‐paying and no‐dividend stocks within a familiar, parsimonious consumption‐based equilibrium framework. We find that such a simple feature leads to profound implications supporting several stock market empirical regularities that leading consumption‐based asset pricing models have difficulty reconciling. Namely, the presence of no‐dividend stocks in the stock market leads to a lower correlation between stock market returns and the aggregate consumption growth rate, a nonmonotonic and even negative relation between the stock market risk premium and its volatility, and a downward‐sloping term structure of equity risk premia.

Investor Attention and Stock Returns

AbstractWe propose an investor attention index based on proxies in the literature and find that it predicts the stock market risk premium significantly, both in sample and out of sample, whereas every proxy individually has little predictive power. The index is extracted using partial least squares, but the results are similar by the scaled principal component analysis. Moreover, the index can deliver sizable economic gains for mean-variance investors in asset allocation. The predictive power of the investor attention index stems primarily from the reversal of temporary price pressure and from the stronger forecasting ability for high-variance stocks.

Monetary Policy and Stock Market Valuation

This paper estimates the effect of monetary policy on the term structure of stock market risk premia. Stock market risk premia are solved using analysts’ dividend forecasts and dividend future prices. Although risk-free rates have decreased after the global financial crisis, the results indicate that the expected long-term average stock market return has remained quite stable at around 9 percent. This implies that the average stock market risk premium has increased since the financial crisis. The prices of dividend futures suggest that the rise is related to changes in the term structure of risk premia. The effect of monetary policy on risk premia is analysed using VAR models and local projection methods. According to the results, monetary policy easing raises the average risk premium. The effect is driven by a rise in long-horizon risk premia.

ESG and the Market Return

We propose an environmental, social, and governance (ESG) index. We find that it has significant power in predicting the stock market risk premium, both in- and out-of-sample, and delivers sizable economic gains for mean-variance investors in asset allocation. Although the index is extracted by using the PLS method, its predictability is robust to using alternative machine learning tools. We find further that the aggregate of environmental variables captures short-term forecasting power, while that of social or governance captures long-term. The predictive power of the ESG index stems from both cash flow and discount rate channels.

Monetary Policy and Stock Market Valuation

This paper estimates the effect of monetary policy on the term structure of stock market risk premia. Stock market risk premia are solved using analysts’ dividend forecasts and dividend future prices. Although risk-free rates have decreased after the global financial crisis, the results indicate that the expected long-term average stock market return has remained quite stable at around 9 percent. This implies that the average stock market risk premium has increased since the financial crisis. The prices of dividend futures suggest that the rise is related to changes in the term structure of risk premia. The effect of monetary policy on risk premia is analysed using VAR models and local projection methods. According to the results, monetary policy easing raises the average risk premium. The effect is driven by a rise in long-horizon risk premia.

Macroeconomic Tail Risks and Asset Prices

AbstractI document that dividend growth and returns on the aggregate U.S. stock market are more correlated with consumption growth in bad economic times. In a consumption-based asset pricing model with a generalized disappointment-averse investor and small, IID consumption shocks, this feature results in a realistic equity premium despite low risk aversion. The model is consistent with the main facts about stock market risk premiums inferred from equity index options, remains tightly parameterized, and allows for analytical solutions for asset prices. An extension with non-IID dynamics accounts for excess volatility and return predictability, while preserving the model’s consistency with option moments.Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Investor Attention and Stock Returns

We find that investor attention proxies proposed in the literature collectively have a common component that has significant power in predicting stock market risk premium, both in-sample and out-of-sample. This common component is well extracted by using partial least squares, scaled principal component analysis, and principal component analysis approaches. Moreover, this component can deliver sizable economic gains for mean-variance investors in asset allocation. The predictive power of investor attention for the aggregate stock market primarily stems from the reversal of temporary price pressure and from the stronger forecasting ability for high-variance stocks.

Asset Prices and No-Dividend Stocks

We develop a stationary model of the aggregate stock market featuring both dividend-paying and no-dividend stocks within a familiar, parsimonious consumption-based equilibrium framework. We find that such a simple feature leads to profound implications supporting several stock market empirical regularities that leading consumption-based asset pricing models have difficulty reconciling. We show that the presence of no-dividend stocks in the stock market leads to a lower correlation between the stock market return and aggregate consumption growth rate, a non-monotonic and even a negative relation between the stock market risk premium and its volatility, and a downward sloping term structure of equity risk premia. When we quantify these effects, we find them to be economically significant. We also find that no-dividend stocks command lower mean returns but have higher return volatilities and higher market betas than comparable dividend-paying stocks, consistently with empirical evidence. We provide straightforward intuition for all these results and the underlying economic mechanisms at play.

Corporate Activities and the Market Risk Premium

While existing asset pricing studies focus on macroeconomic variables to predict stock market risk premium, we find that an aggregate index of corporate activities has substantially greater predictive power both in- and out-of sample, and yields much greater economic gain for a mean-variance investor. The predictive ability of the corporate index stems from its information content about future cash flows and expected corporate investments. Cross-sectionally, the corporate index performs particularly well for stocks with great information asymmetry.

The Share of Systematic Risk in Foreign Exchange and Stock Markets

Is there a common systematic risk between the foreign exchange market and the stock market? To answer this question, a two-country affine model of exchange rates is proposed to obtain a so-called Forex-specific factor. We show that this factor is an important driver of the stock market risk premium. Not only it contributes a sizable portion of exchange rate volatility, but also outperforms the commonly-used financial and macroeconomic variables in terms of predicting stock excess returns. The predictive power is robust with respect to forecasting horizons, and to different industry and characteristic portfolios. In addition, the cross-sectional study shows that the Forex-specific factor has substantial explanatory power for cross-section return differences of industry portfolios, the performance is better than Fama-French three factor model and is comparable with that of the up-to-date five factor model.

Stock market integration and risk premium: Empirical evidence for emerging economies of South Asia

This article investigates the dynamics of regional financial integration and its determinants in an international setting. We test a conditional version of the International Capital Asset Pricing Model (ICAPM) accounting for the deviations from Purchasing Power Parity (PPP) as well as temporal variations in both regional and local sources of risk. Using data from five major South Asian markets (Malaysia, Thailand, Singapore, Indonesia, and Sri Lanka), our results support the validity of an ICAPM and indicate that the risk is regionally priced. Furthermore, we show that changes in the degree of regional stock market integration are explained principally by the U.S. term premium, and the level of market openness, whatever the measure of currency risk. Finally, and as expected, the degree of stock market integration varies considerably over time and from one market to another. As intense market integration induces both benefits and risks, our findings should have significant implications for economic policies and market regulations in emerging, frontier-emerging and transition countries, particularly for countries from the same region.

What Determines REIT Returns in Turkey? An Application of Time-Varying Arbitrage Pricing Model in an Emerging REIT Market

This paper investigates the macroeconomic sources of time-varying risk premia in Turkish REIT industry within the arbitrage pricing theory framework. Turkish REIT industry differs substantially from the global REIT market as Turkish REITs do not have to pay out dividends, yet enjoy the exemption from paying corporate taxes, and have highly concentrated ownership structure. These fundamental differences have significant impacts on the performance of REITs compared to other stocks listed on Borsa Istanbul (BIST), especially in terms of the inflationhedging characteristics and time-varying systematic risk behaviour. This article evaluates the Turkish REIT industry by using a time-varying multifactor model, which compares the REIT industry excess returns with various macroeconomic factors, including GDP growth, industrial production growth, inflation risk premium, and stock market risk premium. Our results provide the evidence of time-varying linkages among macroeconomic risks and the conditional first and second moments of excess returns on REITs. We find that among the macroeconomic factors, inflation risk appears to be the major concern in REIT investment. Additionally, Turkish REITs behave more like stocks than real estate. The documented perverse inflation hedges of REITs, the positive correlation between REIT returns and volatility of real economic activity, and the significant influence of ISE equity risk premium on REIT returns can be quoted as the indications of deviation of REITs’ performance from real estate performance. If REITs behave more like stocks than real estate, the diversification benefits of having REITs in a multi-asset portfolio is seriously reduced.

Impulse Response Functions and Causality Test of Financial Stress and Stock Market Risk Premiums

Using the vector autoregressive (VAR) framework, this study empirically documents the impulse response functions of financial stress and market risk premiums and performs a causality test of these two variables. The analysis of the monthly changes of the Federal Reserve Bank of St. Louis Financial Stress Index and excess returns on the CRSP value-weighted index from 1994:2 to 2012:5 shows that market risk premiums become negative in the first, second and third, fourth and twelfth months following the financial stress shock. The degree of financial stress drops in the first, second, fourth, fifth, seventh, tenth months following risk premium shock. There is no observed feedback response from financial stress to market risk premium shock. The Granger causality test results show that financial stress Granger-causes market risk premiums to drop significantly, and there is no reverse causation recorded in this case. In addition, the time-series OLS regression analysis shows a statistically significant negative coefficient (b = -8.50; t = -9.20) when explanatory variable is the monthly changes in financial stress.

Commercial Paper Rates and Stock Market Excess Returns

This study investigates how commercial paper rates respond to the innovations in stock market risk premiums. The unrestricted vector autoregression (VAR) analysis of monthly data from 1997:1 to 2012:M6 shows that the changes in the one-, two-, and three-month non-financial and financial commercial paper rates positively respond to the innovations in the excess returns on the CRSP value weighted index. The response is especially strong during the first few months following shocks to stock market risk premiums. The Granger-causality test results show the changes in commercial paper rates can be predicted by the excess returns on the CRSP value weighted index. The findings from this study provide evidence that there is a link between equity market and commercial paper market.

A Joint Analysis of the Effect of Business and Consumer Confidence on Stock Market Risk Premiums

This study is to assess the dynamics effects of business confidence and consumer confidence on stock market risk premiums and to determine the relative importance of business confidence and consumer confidence in forecasting the variability of stock market risk premiums though a variance decomposition. The results show that the response of stock market risk premiums becomes positive immediately following the shocks to business confidence and consumer confidence. Based on the variance decomposition analysis, the variability of stock market risk premiums is 95% due to its own shock and the rest is due to the shocks to business confidence (1%) and consumer confidence (4%) for the 3-month horizon. For the 6-month horizon, the variability of stock market risk premiums is 93% due to its own shock, 2% due to business confidence shock and 5% due to consumer confidence shock. The forecast error of stock market risk premiums is 90% due to its own shock and the rest is due to the shocks to business confidence (4%) and consumer confidence (6%) for the 12-month horizon. The results from the OLS time-series regression show that business confidence and consumer confidence jointly explain around 7.42% of the variation of stock market risk premiums.