Stock Risk Premium Research Articles

Impact of tax changes on the risk premium of the WIG index

The presented article provides an empirical analysis of changes in the risk premium of stocks on the Warsaw Stock Exchange in response to changes in tax rates. The analysis uses a structural VAR model, identified with sign restrictions. This method turns out simple to use and proves to be effective in overcoming the problem of predictability of fiscal policy, which is especially important in studies using variables from financial markets. The results show an increase in the risk premium following a sudden tax hike, accompanied only by a temporary reduction in GDP growth. Meanwhile, an anticipated tax hike seems to lower risk premia while being more harmful to GDP dynamics.

How Global Macroeconomic Uncertainty Affects the Equity Risk Premium

This paper introduces a new measure for global macroeconomic uncertainty that captures both upside and downside risks using a no-arbitrage asset pricing framework. The study uses a dynamic panel threshold model to analyze quarterly data from 20 countries between 1996 and 2020, incorporating macroeconomic and financial market variables, as well as risk aversion factors. The findings reveal a significant nonlinear effect of global uncertainty on stock risk premiums. High global uncertainty increases the premium investors require for global market risks but decreases it for local market risks. The study also indicates that during uncertain times, investors display risk-averse and liquidity-seeking behavior, opting for safer and more liquid assets. The impact of global macroeconomic uncertainty on stock risk premiums is found to be long-lasting.

Forecasting the stock risk premium: A new statistical constraint

AbstractWe develop a new statistical constraint to improve the stock return forecasting performance of predictive models. This constraint uses a new objective function that combines the Huber loss function with the Ridge penalty. Out‐of‐sample results indicate that our constraint improves the predictive ability of the univariate models. The constrained univariate models significantly outperform the historical average benchmark model assuming no predictability. The forecast improvement based on the new constraint is also evident for multivariate information methods including forecast combination and diffusion index. The model is capable of capturing time‐varying risk which serves as the potential economic explanation of the improved return predictability. Our results are robust to different evaluation subsamples, validation sample lengths, and different risk aversion coefficients.

Persistence of jump-induced tail risk and limits to arbitrage

We present a novel methodology to calculate the jump-induced tail risk premium for individual stocks and examine its effect on the following-month’s returns. The existence of a premium for bearing negative jump-induced tail risk is significantly associated with negative one-month future returns. In contrast, the existence of a positive premium for bearing jump-induced tail risk has no such significant predictive power. Further, we find that the larger is the magnitude of the premium for negative jump-induced tail risk, the greater and longer-lasting is its impact on expected returns. Lastly, the observed ten-day lag taken to fully incorporate negative jump tail information into price is consistent with limits to arbitrage in the underlying stocks.

Research on the Investment Strategy Based on Option Volatility Smiles

Under the Black-Scholes efficient market assumptions, the implied volatility of options should be constant when the option value state and the remaining maturity period change. However, in the real world, the implied volatility of options in different value states will show smile pattern with given remaining maturity period. Numerous empirical studies have found that implied volatility smile slopes have significant predictive function for stock market returns. Based on this, this paper selects the historical trading data of SSE 50 ETF options to verify the existence of option volatility smile in Chinese capital market. And uses the tilt degree of implied volatility as a stock risk premium factor to select stocks, as to obtain a portfolio with excess returns. This paper portrays the morphological characteristics of option implied volatility, as well as confirms the existence of option volatility smile in Chinese capital market. In addition, this paper demonstrates that the tilt of the smile has significant predictive function for the underlying market trend. Finally, this paper constructs an investment strategy using the tilt degree of the implied volatility smile as an indicator. The findings of this study will help investors to select stocks and construct portfolios based on implied volatility in order to obtain higher returns.

Dynamic portfolio decisions with climate risk and model uncertainty

ABSTRACT We study the effect of investment horizon on the optimal stock–bond–cash portfolio in a dynamic model with uncertainty about climate change. The stock risk premium is assumed to be an affine function of the average global temperature and an unobserved factor which is estimated via Bayesian learning. We assume that the probability distribution of future temperature is uncertain. The optimal investment strategy, robust to the uncertainty about climate change, is derived in closed form and analyzed for returns on the S&P500 index and the S&P500 ESG index. We find that stock market investment is quite sensitive to climate uncertainty with allocation to the S&P500 index being the most sensitive. We also show that, even for relatively short time horizons, welfare losses from climate uncertainty could be large for investments in either the S&P500 index or the S&P500 ESG index.

The Real Response to Uncertainty Shocks: The Risk Premium Channel

Uncertainty shocks are also risk premium shocks. With countercyclical risk aversion (RA), a positive shock to uncertainty increases risk and elevates RA as consumption growth falls. The combination of high RA and high uncertainty produces significant equity risk premia in bad times, which in turn, exacerbate the decline of macroeconomic aggregates and equity prices. Moreover, in the cross-section of equity returns, investors demand a risk premium for stocks that perform poorly in times of high uncertainty and elevated risk aversion. In a model with endogenously time-varying RA, uncertainty shocks lead to large falls in investment and equity prices that closely match state-dependent data responses. This paper was accepted by Tomasz Piskorski, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4335 .

Currency risk exposure and the presidential effect in stock returns

Abstract We explore how the US presidential effect in stock returns is connected to the US presidential effect in foreign exchange returns to the US dollar. Our results for the 1973–2016 period show that the existence of a presidential effect in stock returns depends on how a firm’s stock returns are associated with changes in the value of the US dollar. We document that a complex association exists between presidential effects in stock returns, stock risk premiums, macro-economic variables, and the foreign exchange market. Overall, the presidential effect in stock returns is driven by exporters through their exposure to the presidential effect in returns to the US dollar.

Currency risk exposure and the presidential effect in stock returns

We explore how the US presidential effect in stock prices is connected to the US presidential effect in foreign exchange returns to the US dollar. Our results show that the existence of a presidential effect in stock returns depends on how a firm’s stock returns are associated with changes in the value of the US dollar. We document that a complex association exists between presidential effects in stock returns, stock risk premiums, macro-economic variables, and the foreign exchange market.

Forecasting commodity futures returns with stepwise regressions: Do commodity-specific factors help?

The aim of this paper is to assess whether three well-known commodity-specific variables (basis, hedging pressure, and momentum) may improve the predictive power for commodity futures returns of models otherwise based on macroeconomic factors. We compute recursive, out-of-sample forecasts for the monthly returns of fifteen commodity futures, when estimation is based on a stepwise model selection approach under a probability-weighted regime-switching regression that identifies different volatility regimes. We systematically compare these forecasts with those produced by a simple AR(1) model that we use as a benchmark and we find that the inclusion of commodity-specific factors does not improve the forecasting power. We perform a back-testing exercise of a mean–variance investment strategy that exploits any predictability of the conditional risk premium of commodities, stocks, and bond returns, also consider transaction costs caused by portfolio rebalancing. The risk-adjusted performance of this strategy does not allow us to conclude that any forecasting approach outperforms the others. However, there is evidence that investment strategies based on commodity-specific predictors outperform the remaining strategies in the high-volatility state.

Estimation of Value-at-Risk Adjusted under the Capital Asset Pricing Model Based on ARMAX-GARCH Approach

Investors having an understanding of investment statistics are important. Especially quantitative tools related to investment risk measurement. Value-at-Risk Adjusted is one of the investment risk measurement tools, which assumes that returns are not normally distributed.This paper intends to measure investment risk based onValue-at-Risk Adjustedor called Modified Value-at-Risk under the Capital Asset Pricing Model. It is assumed that the return of the market index has a non-constant average and there is a long memory effect. The average of the return of the market index is estimated using ARFIMA models.It is also assumed that the stock risk premium correlates with market risk premiums, and stock risk premiums some time before. The correlation will be analyzed using the ARMAX-GARCH model approach. The Modified Value-at-Risk was then formulated based on the Capital asset Pricing Model with the ARMAX-GARCH model approach.To measure the performance of Modified Value-at-Risk that has been formulated is done with back testing. Back testing is carried out based on the Lopez II method. As a case study, analyzed some data on 10 stocks traded on the capital market in Indonesia.The results of the analysis show that the market index return risk premium significantly follows the ARFIMA model, and the 10 share risk premium significantly follows the ARMAX-GARCH model. Based on the results of back testing calculations indicate that the Value-at-Risk Adjustedor Modified Value-at-Risk is very suitable to be used to measure investment risk in the 10 stocks analyzed.

Estimation of Value-at-Risk Adjusted under the Capital Asset Pricing Model Based on ARMAX-GARCH Approach

Investors having an understanding of investment statistics are important. Especially quantitative tools related to investment risk measurement. Value-at-Risk Adjusted is one of the investment risk measurement tools, which assumes that returns are not normally distributed.This paper intends to measure investment risk based onValue-at-Risk Adjustedor called Modified Value-at-Risk under the Capital Asset Pricing Model. It is assumed that the return of the market index has a non-constant average and there is a long memory effect. The average of the return of the market index is estimated using ARFIMA models.It is also assumed that the stock risk premium correlates with market risk premiums, and stock risk premiums some time before. The correlation will be analyzed using the ARMAX-GARCH model approach. The Modified Value-at-Risk was then formulated based on the Capital asset Pricing Model with the ARMAX-GARCH model approach.To measure the performance of Modified Value-at-Risk that has been formulated is done with back testing. Back testing is carried out based on the Lopez II method. As a case study, analyzed some data on 10 stocks traded on the capital market in Indonesia.The results of the analysis show that the market index return risk premium significantly follows the ARFIMA model, and the 10 share risk premium significantly follows the ARMAX-GARCH model. Based on the results of back testing calculations indicate that the Value-at-Risk Adjustedor Modified Value-at-Risk is very suitable to be used to measure investment risk in the 10 stocks analyzed.

The Fundamental Equity Premium and Ambiguity Aversion in an International Context

Stocks are riskier than bonds. This causes a risk premium for stocks. That the size of this premium, however, seems to be larger than risk aversion alone can explain the so-called “equity premium puzzle”. One possible explanation is the inclusion of a degree of ambiguity in stock returns to account for an additional ambiguity premium, whose size depends on the degree of ambiguity aversion among investors. It is, however, difficult to test this empirically. In this paper, we compute the first firm-level estimation of equity premium based on the internal rate of return (IRR) approach for a total of N = 28,256 companies in 54 countries worldwide. Using a survey of international data on ambiguity aversion, we find a strong and robust relation between equity premia and ambiguity aversion.

A new risk factor based on equity duration

We introduce a new risk factor linking a firms equity duration to investment opportunity risk. Low-duration firms generate short-run cash flows and face strong reinvestment risk. High-duration firms have long-run cash flows and their present value increases when discount rates decrease as a result of a deteriorating investment environment. Our empirical analysis reveals a significant return premium of low-duration stocks, confirming that investors charge a risk premium for stocks with returns that are positively related to the investment environment. Our newly introduced risk factor carries significant risk premiums in cross-sectional asset pricing tests. These premiums are robust to including further risk factors and a variety of different test specifications. Notably, our duration risk factor retains high explanatory power on the cross-section of stock returns in a model including direct measurement of the investment environment via state variable innovations.

Forecasting Commodity Futures Returns: An Economic Value Analysis of Macroeconomic vs. Specific Factors

We test whether three well-known commodity-specific variables (basis, hedging pressure, and momentum) may improve the predictive power for commodity futures returns of models otherwise based on macroeconomic factors. We compute recursive, out-of-sample forecasts for fifteen monthly commodity futures return series, when estimation is based on a stepwise model selection approach under a probability-weighted regime-switching regression that identifies different volatility regimes. Comparisons with an AR(1) benchmark show that the inclusion of commodity-specific factors does not improve the forecasting power. We perform a back-testing exercise of a mean-variance investment strategy that exploits any predictability of the conditional risk premium of commodities, stocks, and bond returns, also taking into account transaction costs caused by portfolio rebalancing. The risk-adjusted performance of this strategy does not allow us to conclude that any forecasting approach outperforms the others. However, there is evidence that investment strategies based on commodity-specific predictors outperform the remaining strategies in the high-volatility state.

Unrealistic Optimism and Asymmetry in the Pricing of Equity Tail Risk

Unrealistic Optimism is the phenomenon whereby human beings are unreasonably optimistic about the likelihood and impact of tail events, and they incorporate information selectively to reinforce that optimistic bias. Specifically, they update their priors more frequently when presented with information that supports the optimistic bias than they do with information that contradicts it. Consequently, new information about extreme positive events is processed quickly and efficiently, but new information about extreme negative events is processed with a lag, and when it is finally processed, it is processed with an optimistic bias which prolongs the amount of time that it takes for the negative information to be fully and correctly incorporated. To test these predictions, this paper introduces a novel methodology to directly calculate the tail risk premium for individual stocks, and then uses this measure to examine the characteristics of this premium in the cross section of stock returns. Information about positive tail events seems to be quickly and relatively efficiently priced, i.e., the existence of a premium for bearing positive tail risk today has no predictive power on future returns. However, same cannot be said of the pricing of extreme negative tail events. The existence of a premium for bearing negative tail risk today is significantly associated lower returns in the future. Moreover, the greater the premium for bearing negative tail risk today, the more negative and more persistent are the future returns.

An Improved Method for Valuing Mature Companies and Estimating Terminal Value

The theory underlying Discounted cash flow (DCF) models is uncontroversial in academia, the economic intuition behind them is straightforward, and the mathematics reassuringly simple. Nevertheless, in practice, they are applied inconsistently with very different valuation results. Because of the assumed infinite life (“going concern”) of a business enterprise, DCF models implicitly assume the ability to forecast future cash flows forever. This forces analysts to make assumptions about the terminal period using simplistic metrics such as P/E or EV/EBITDA to estimate terminal values or to embed a perpetual stream of excess profitability and value creation in the terminal period.The author offers an uncomplicated alternative to these unrealistic assumptions. The first step is to introduce an adjustable fade rate called f. A fade rate of 100% brings about immediate convergence, and a fade rate of 0% specifies no fade and perpetual excess profitability. The notion that excess profits get competed away over time can be modeled by assuming that the spread of (ROIC ‐ r) fades to zero and that economic profit dissipates.Intrinsic value is very sensitive to the fade rate assumption and this helps explain the risk premium for quality stocks. The risk of owning quality stocks is that they lose their economic moat and competitive advantage. An adjustable fade rate provides an excellent means to value the effect of profitability attenuation in a DCF model.

How money illusions and heterogeneous beliefs affect asset prices

We develop a dynamic asset pricing model with two investors with money illusions and heterogeneous beliefs about some aspects of the economy. The model is tractable and delivers closed forms for all equilibrium quantities. The study shows that money illusion leads the nominal shock risk to generate spillover effects on the real side of the economy and affects all equilibrium quantities, even without inflation disagreement. We find that bond yields increase, but the stock price decreases, as money illusion increases. Bond yield and stock price volatilities increase with fundamental disagreement, while the latter decreases with inflation disagreement. We also discover that the stock risk premium is inverse-U shaped as inflation disagreement increases. Moreover, we find that the optimistic investor holds positions in real bonds and stocks, and shorts the nominal bond to hedge against the risk of market changes, which is in line with the pessimistic investor’s beliefs.

Capturing the value premium – global evidence from a fair value-based investment strategy

This paper examines the risk premium of value stocks within a global investment strategy framework. We test whether absolute or relative mispricing is better suited to capturing the global value premium by using fair value-based net asset values (NAVs) as our proxies for fundamental value. We find that investing in the most underpriced stocks relative to the average ratio of price to fundamental value in a country is the key to achieving superior risk-adjusted returns. The annualized excess return of the global value portfolio sorted according to relative mispricing is 10.0%, and remains significant after controlling for common risk factors.

Studying the Impact of Accruals Quality and Market Risk Premium on Stock return Excess Using Fama-French Three Factor Model

Determining effective agents in stock return excess behavior (stock risk premium) is one of the key points in investors decision that its benefit and quality of its elements (like accruals) are the impressive factors on stock return excess (stock risk premium) which influence users decision making. Accruals are temporary adjustments that postpone fulfilled cash flows recognition and estimate error degree. Criteria estimating to study these items quality seem necessary because of affecting over future cash flows. Therefore the current study aims to investigate the effect of accruals quality and market risk premium on stock return excess. In order to examine probe hypothesis, we used Fama-French three-factor model that accruals were added to it. For this aim a sample that includes 88 of accepted companies in Tehran stock exchange between 2005 until 2013 was studied. In order to calculate accruals, we used Dechow et al model (1995) utilizing sectional data and to estimate we used Fama-French model (1993) by multivariable regression method and time series data. This study in nature is collateral and in goal is fundamental-experimental. The conclusions show that between accruals quality factors and stock risk premium there is a negative significant relation and between market and stock risk premium there is a positive significant relation. Moreover, the results indicate that among size agent and stock risk premium also between book value to market value ratio factors and stock risk premium there is a negative significant link.