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Inflation risk and stock returns: Evidence from US aggregate and sectoral markets
... There is a large body of literature that focuses on the relationship between inflation and stock market verifying either "Fama hypothesis" or "Fisher hypothesis" (Apergis and Eleftheriou, 2002;Bouri et al., 2023;Cheema et al., 2022;Časta, 2023;Chiang, 2023;Chiang and Chen, 2023). According to Fama hypothesis, inflation has a negative relationship with stock returns. ...
... According to Fama hypothesis, inflation has a negative relationship with stock returns. Similarly, Chiang and Chen (2023) examine the relationship between US inflation and ten sectorial stock indices (financials, health cares, industrials, real estates, consumption goods, retails, basic materials, energy, investment services and technology) and conclude that inflation is negatively correlated with stock returns, except for energy sector, which shows a positive interaction with inflation. Supporting Fama's hypothesis, Raghutla et al. (2020) provide evidence that there is a positive relationship between stock returns and output and a negative one between inflation and output. ...
... Specifically, a 1% increase in CPI, will decrease stock returns by 6.12%. Our results are in line with other researchers ( Chiang and Chen, 2023;Raghutla et al., 2020) verifying the Fama's hypothesis and the negative relationship between stock market and inflation. The validity of the VECM model is verified by the coefficients of the Error Correction Term shown in Table 6. ...
This study explores the interactions between inflation and stock market. We carried out a bibliometric analysis with R package to highlight the worldwide research trends in the field, covering the period of three crises (financial, health crisis and war of Ukraine). Next, using monthly data for the period from 1 March 2020 to 31 August 2023 and based on a vector autoregressive model, impulse response and variance decomposition are performed to explore the dynamic relationships between inflation and Greek stock market. The results reveal the existence of high volatility in Athens' stock market during COVID-19 pandemic, owning to a shock of the inflation. Regarding the period of Ukrainian war, the study verified the Fama's hypothesis that there is a negative relationship between inflation and stock returns. The findings have significant implications for investors and policy makers.
... There is a large body of literature that focuses on the relationship between inflation and stock market verifying either "Fama hypothesis" or "Fisher hypothesis" (Apergis and Eleftheriou, 2002;Bouri et al., 2023;Cheema et al., 2022;Časta, 2023;Chiang, 2023;Chiang and Chen, 2023). According to Fama hypothesis, inflation has a negative relationship with stock returns. ...
... According to Fama hypothesis, inflation has a negative relationship with stock returns. Similarly, Chiang and Chen (2023) examine the relationship between US inflation and ten sectorial stock indices (financials, health cares, industrials, real estates, consumption goods, retails, basic materials, energy, investment services and technology) and conclude that inflation is negatively correlated with stock returns, except for energy sector, which shows a positive interaction with inflation. Supporting Fama's hypothesis, Raghutla et al. (2020) provide evidence that there is a positive relationship between stock returns and output and a negative one between inflation and output. ...
... Specifically, a 1% increase in CPI, will decrease stock returns by 6.12%. Our results are in line with other researchers ( Chiang and Chen, 2023;Raghutla et al., 2020) verifying the Fama's hypothesis and the negative relationship between stock market and inflation. The validity of the VECM model is verified by the coefficients of the Error Correction Term shown in Table 6. ...
... This cutback in spending combined with rising costs of production and uncertain revenue growth can drive an economy into recession and lead to a decline in stock prices. The finding of a negative relationship between real stock returns and expected inflation is consistent with the evidence provided by Fama (1981) , Schwert, (1981), Gallagher and Taylor (2002) and Chiang and Chen (2023) but is inconsistent with reports by Boudoukh and Richardson (1983) and Crowder and Hoffman (1996). ...
... The exceptions occur in India where the coefficients are positive for real stock returns and in some cases in Japan where low real stock returns or spurious correlation are present. The negative relationship between real stock returns and inflation expectation is consistent with the findings documented by Fama (1981), McCarthy et al. (1990) and Chiang and Chen (2023). Evidence indicates that the negative impact on real stock returns even ripples through the channel of US equity 32 market volatility that produces a spillover effect to global markets. ...
This study examines the response of real stock returns to expected inflation and uncertainty as measured by state variable correlated with equity market volatility (EMV). Evidence reveals a significantly negative relationship between real stock returns and expected inflation for each country except some cases in India and Japan. Evidence indicates a negative relationship between real stock returns and uncertainty, which is measured not only by the impact of the Fed’s monetary policy uncertainty but also from various state variables that covary with EMV. These elements have not been explicitly incorporated into test equations in previous studies of the inflation-stock return relationship. The model is robust in its ability to test data for both advanced and emerging markets, level or the first difference of explanatory variables, and various categorical EMVs. Evidence shows that the Fed’s rate hikes respond to the inflation data, displaying a nonlinear impact on real stock returns.
... Kaul (1987) attributed the negative relationship between stock returns and inflation to money demand and countercyclical money supply effects. Many other empirical studies have also supported Fama's hypothesis that common stocks are not a good hedge against inflation and that inflation may be a proxy for a set of real variables (Cohn and Lessard, 1981;Solnik, 1983;Davis and Kutan, 2003;Eldomiaty et al., 2019 &Chiang andChen, 2023). Madadpour and Asgari (2019) argued that most studies that proved the negative relation between stock returns and inflation had primarily focused on developed and low-inflation economies. ...
... Kaul (1987) attributed the negative relationship between stock returns and inflation to money demand and countercyclical money supply effects. Many other empirical studies have also supported Fama's hypothesis that common stocks are not a good hedge against inflation and that inflation may be a proxy for a set of real variables (Cohn and Lessard, 1981;Solnik, 1983;Davis and Kutan, 2003;Eldomiaty et al., 2019 &Chiang andChen, 2023). Madadpour and Asgari (2019) argued that most studies that proved the negative relation between stock returns and inflation had primarily focused on developed and low-inflation economies. ...
... Unfortunately, the empirical literature on the stock return and inflation relationship has been inconclusive. Furthermore, a major shortcoming of the above studies is there is a large body of literature on developed and emerging market economies relative to developing economies (Al-Khazali, 2003;Chiang & Chen, 2023;Lee, 2010;Li, Narayan, & Zheng, 2010;Zhang, 2021). Subsequently, the inflation-stock return is less well understood in the context of small developing economies. ...
... Studies focusing on the effects of inflation on sectoral stock returns have also found inconclusive results Ayinuola (2023) find that inflation negatively and significantly affects aggregate and sectoral stock return in the short run as well as the long run in Nigeria. Chiang and Chen (2023) assess the relationship between stock return and inflation in the US market and find that sectoral stock returns (except the energy sector) are negatively correlated with inflation. However, Osmani, Cheshomi, Salehnia, and Ahmadi Shadmehri (2023) find that inflation positively affects the nominal returns of stocks of different industries in the short term and the long term in Iran. ...
The relationship between stock returns and inflation has important implications for monetary policy and stock market investment and has attracted growing attention from scholars over recent years. Despite this, the empirical evidence so far has been inconclusive. The main objective of this paper is to investigate the impact of inflation on stock returns in the developing stock market of Fiji. We examine the impact of inflation on stock market returns within the GARCH and EGARCH modelling framework using monthly data from 2000:02 to 2018:06 and find that inflation negatively affects stock market returns. Our results indicate the importance of ensuring price stability and suggest that stock market investment will not help hedge against inflation in Fiji. The results suggest that Fiji’s stock market is likely to react more negatively to inflation in response to countercyclical monetary policy and emphasize the significance of portfolio diversification.
... Thirdly, stock price crash risk is also affected by macro factors, including inflation, interest rate, and GDP growth rate. To be precise, stock price crash risk is negatively affected by inflation, which is consistent with findings of Chiang and Chen (2023). Obviously, when inflation increases, the value of real estate assets of companies also increase, but along with that comes an increase in the prices of different types of costs, which can stabilize stock prices. ...
This paper aims to investigate the impact of investor attention on stock price crash risk for 80 listed real estate stocks over the period from 2014 to 2023. Instead of focusing on investor attention for the whole real estate industry, this paper measures investor attention at firm level by using Google Search Volume Index. Moreover, the multiple multivariate regression method is used to analyze 435 observations measured from audited financial statements, daily transaction data, and macro data in the FiinPro Platform. As a result, there is no impact of investor attention on stock price crash risk among real estate stocks examined, while macroeconomic conditions such as inflation, interest rate and GDP growth rate and liquidity are the major factors that influence the price crash risk of real estate stocks in Vietnam.
... According to authors, adopting a green monetary strategy has the potential to help the CBRT achieve its goal of price stability. The short-term relationship between stock returns and inflation in the United States market is examined by Chiang and Chen (2023). Results suggest that the aggregate market data suggest that stock returns are inversely connected to inflation. ...
In literature, studies address the relationship between financial and energy markets. In this context, there are a lot of works which examine the impact of financial markets on energy markets. However, there are not any research undertaken to explore the effect of financial stress index (FSI) on energy-related uncertainty index (EUI). Therefore, this work assesses this relation in the case of US with time-varying parameter vector autoregression (TVP-VAR) model, using monthly data from Quarter 1 1996 to Quarter 3 2022 in the United States (US). The findings reveal that time-varying impacts of FSI on EUI is positive and significant, validating theoretical linkage.
... Inflation is a condition characterized by a continuous increase in general prices, or a situation where the value of money decreases due to an increase in the money supply not being balanced by an increase in the supply of goods (Setyaningrum & Muljono, 2016). The issue of inflation and its impact on economic activity and stock markets has again attracted the attention of households, investors and policy makers after four decades of relatively stable inflation variations (Chiang & Chen, 2023). ...
This research examines the influence of coal prices and inflation on mining sector stock returns in the short and long-term using monthly data from the period January 2009 – December 2020. Data analysis in this study used the Autoregressive Distributed-Lag (ARDL). Based on the results, it can be concluded that in the short term, inflation exerts a negative and significant impact on stock returns in the mining sector. Conversely, coal prices do not influence stock returns in this sector. The long-term findings mirror this pattern, demonstrating that inflation continues to have a negative and significant effect on mining sector stock returns, while coal prices remain uninfluential. Policymakers, investors, and financial actors are advised to consider energy related objectives and developments, particularly in the coal sector, as critical indicators for financial decision-making. It is also important to consider that the timeframe chosen for decision making will significantly impact investment performance, as any variation in time can greatly influence the results. It acknowledges that other factors, such as the Rupiah exchange rate, interest rates, and additional variables, also potentially affect these returns. It is recommended that future studies expand the scope of investigation to include these additional factors to attain a more thorough understanding of the determinants of stock returns in the mining sector.
... In developed markets, studies have highlighted the interplay of monetary policy, inflation, and fiscal stimulus in shaping equity market responses. For instance, Beirne et al. (2020) observed that fiscal and monetary interventions helped stabilize financial conditions, particularly in Asian and European emerging economies, while Chiang and Chen (2023) found a negative relationship between inflation and aggregate stock returns in the US, except for the energy sector. Schrank (2024) notes that monetary policy changes during the crisis had pronounced effects on financial markets in Thailand, with gold providing limited safe-haven functionality compared to its historical performance. ...
This study addresses the confusion between Ordinary Least Squares (OLS) regression and Quantile Regression (QR) in analyzing the impact of macroeconomic variables on financial markets, specifically exchange rates, NSE Nifty returns, and gold prices. It also seeks to identify the key economic factors that influence these financial indicators, as the relationship between economic variables and market performance remains complex and multifaceted. To tackle these challenges, the study compares the effectiveness of both OLS and QR in capturing the impact of macroeconomic variables like inflation, interest rates, and foreign reserves on financial markets. The analysis proceeds by utilizing data from January 2019 to December 2023, sourced from the Reserve Bank of India (RBI), to assess monthly returns (MOM) of the selected financial indicators. A combination of descriptive statistics, Pearson correlation, and regression models is employed to explore the relationships between the variables. The study reveals that QR provides more nuanced insights, outperforming OLS by capturing the heterogeneity of effects across different market conditions, while OLS offers a more generalized view. Overall, the findings underscore the advantages of using Quantile Regression to better understand the conditional relationships between macroeconomic variables and financial market outcomes.
... In the study, it is stated that in the 1970s, although stock markets were attractive in high inflation, returns were low, while in the 2000s, it is proved that high inflation also increases the risk of stocks. Chiang and Chen (2023) analysed the short-term relationship between stock returns and inflation in the US economy. A negative relationship was observed between stock returns and inflation in the total market. ...
This study delves into the intricate relationship between inflation and stock prices on Borsa Istanbul, with a particular focus on the turbulent post- COVID-19 era. While traditional assets like real estate have historically served as reliable inflation hedges, the emergence of Borsa Istanbul as a potential alternative warrants investigation, especially during the period 2019-2023. To assess the effectiveness of the Turkish stock market as an inflation hedge, we employ a rigorous econometric framework that extends beyond broad market indices to examine sector-specific responses. By adopting a Vector Autoregression (VAR) model, we capture the dynamic interplay between inflation and stock returns. Our analysis incorporates a comprehensive set of macroeconomic control variables spanning the period 2006Q1-2023Q4 and utilizes robust estimation techniques to account for potential structural breaks induced by the COVID-19 pandemic and unconventional economic policies. The primary objective of this study is to determine whether Borsa Istanbul stocks constitute an effective inflation hedge. In essence, our results suggest that the Turkish equity market has served as a safe haven for investors during inflationary periods. A deeper understanding of the relationship between inflation and equity markets is crucial for investors, policymakers, and financial market participants seeking to comprehend and manage inflation risks in emerging economies. In this context the study contributes to existing literature by providing empirical evidence on the inflation hedging capabilities of Borsa Istanbul stocks, particularly in the context of recent economic and geopolitical upheavals.
... In developed markets, studies have highlighted the interplay of monetary policy, inflation, and fiscal stimulus in shaping equity market responses. For instance, Beirne et al. (2020) observed that fiscal and monetary interventions helped stabilize financial conditions, particularly in Asian and European emerging economies, while Chiang and Chen (2023) found a negative relationship between inflation and aggregate stock returns in the US, except for the energy sector. Schrank (2024) notes that monetary policy changes during the crisis had pronounced effects on financial markets in Thailand, with gold providing limited safe-haven functionality compared to its historical performance. ...
This study addresses the confusion between Ordinary Least Squares (OLS) regression and Quantile Regression (QR) in analyzing the impact of macroeconomic variables on financial markets, specifically exchange rates, NSE Nifty returns, and gold prices. It also seeks to identify the key economic factors that influence these financial indicators, as the relationship between economic variables and market performance remains complex and multifaceted. To tackle these challenges, the study compares the effectiveness of both OLS and QR in capturing the impact of macroeconomic variables like inflation, interest rates, and foreign reserves on financial markets. The analysis proceeds by utilizing data from January 2019 to December 2023, sourced from the Reserve Bank of India (RBI), to assess monthly returns (MOM) of the selected financial indicators. A combination of descriptive statistics, Pearson correlation, and regression models is employed to explore the relationships between the variables. The study reveals that QR provides more nuanced insights, outperforming OLS by capturing the heterogeneity of effects across different market conditions, while OLS offers a more generalized view. Overall, the findings underscore the advantages of using Quantile Regression to better understand the conditional relationships between macroeconomic variables and financial market outcomes.
... Understanding the impact of energy prices on inflation is crucial for policy makers, businesses and households (Chiang, Chen, 2023;Garratt, Petrella, 2022;Kilian, Zhou, 2023;Zheng et al., 2023). To policymakers, anticipating and managing inflationary pressures is essential to maintain economic stability. ...
The relationship between energy commodity prices and inflation has important implications for fiscal policy and economic stability. The nature of energy commodities is multi-dimensional, serving both as basic raw materials in production processes and as critical consumer goods. This study focuses on estimating the impact of oil, natural gas and coal prices on inflation in Poland. Through the adoption of multiple regression models using quarterly data from Q2 2000 to Q3 2023, the study aims to estimate the impact of energy commodity prices, particularly oil, coal, and natural gas, on inflation in Poland and to answer the research question: What role do energy commodity prices play in shaping inflation in Poland? The empirical analysis revealed that oil and coal prices significantly influence inflation, reflecting Poland's energy dependency. Natural gas prices showed a limited impact due to lower consumption and mitigation policy measures. The significant impact of energy prices suggests that energy market developments should be closely monitored for their inflationary potential. The study offers valuable insights for policymakers in their efforts to effectively manage inflationary pressure. The article contributes to the literature by presenting the short-run relationship between inflation and energy commodity prices, covering long period of time with both financial, COVID-19 crisis and the Russian aggression in Ukraine.
... In the past, most studies have ignored the conditions for log approximations. Examples may include, but are not limited to, Duarte-Silva and Kimel (2024), Panagiotidis, Papapanagiotou, and Stengos (2024), Long, Chiah, Zaremba, and Umar (2024), Liu and Kang (2024), Wong (2023), Domenico, Livan, Montagna, and Nicrosini (2023), Blau, Griffith, and Whitby (2023), Chiang and Chen (2023), Simonato and Denault (2023), Ni and Wang (2023), Ausloos, Ficcadenti, Dhesi, and Shakeel (2021), etc. On the other hand, some studies like Tomlinson, Greenwood, and Mucha-Kruczyński (2024), and Herley, Orlowski, and Ritter (2023), used log return and showed that the mean and variance of the log returns are sufficiently close to zero. ...
It is rather a norm for researchers to directly use the log difference of an asset price to compute returns. Just like using ln(X+1) to avoid taking the natural logarithm of zero(s). However, this log returns are but a conditional approximation of the actual returns. Nonetheless, can log difference approximations and the ln(X+1) common practices produce BLUE estimates? Using the log return as an example, this study discusses the approximation nature and conditions for using the log difference approximation both for the interest regressor and control variables. These conditions are; that both the sample average and variance of the original series tend to zero. When these conditions are not met, the log difference approximation is, in fact, not a good approximation and biases OLS causal estimators. When the conditions are met, it produces unbiased, consistent but less efficient estimators. Thereby making the estimates less precise and less accurate. Nonetheless, this is true for a log differenced interest regressor(s) and control variables, when it correlates with the interest variable(s) and explains, in part, the dependent variable, even in large samples. Similarly, the common use of ln(X+1) biases the estimation of the true causal effect, even the intercept term, except when
X tends to infinity. A robust solution of using non-zero subsamples, against ln(X+1), produces unbiased and consistent estimators for the true causal effects under the causal assumptions. These biasedness, inconsistencies, and inefficiencies do not disappear in large samples. Finally, both ex-ante and ex-post test statistics are discussed, however, the ex-post estimation test statistic is recommended to confirm both the choice of using log difference approximation and that of using ln(X+1), in an empirical data causal regression analysis. Ideally, researchers should ensure the conditions for using the log difference approximation are met. Otherwise, these approximations and practices produce biased, inconsistent, and inefficient results, even in large samples, leading to misinformed policy implications.
... High inflation can create uncertainty, often leading to increased levels of volatility in stock markets and potentially slowing down economic activity. The relationship between market volatility and rising price levels has been widely studied (Geske & Roll, 1983;DeFina, 1991;Geetha et al., 2011;Chiang & Chen, 2023). ...
This paper investigates the factors influencing the number of monthly active users of E-Trading Apps from January 2017 until June 2021. As digital platforms increasingly facilitate retail investors’ access to financial markets, understanding the drivers behind user engagement is essential. Trading apps, defined as mobile applications that enable the buying and selling of financial instruments, have transformed the financial landscape, enhancing the role of retail investors. The analysis utilises a comprehensive panel dataset containing data from four major economies – the United States, United Kingdom, Germany and France. We find that monthly income is a significant predictor of E-Trading apps usage, suggesting that higher income levels drive greater retail participation in financial markets. However, variables such as unemployment rates, mortgage rates, and stock market returns did not show statistically significant effects. Additionally, we found a significant positive influence of the COVID-19 pandemic on user numbers, highlighting its role in boosting retail investor activity during the studied period. Overall, this paper emphasises the importance of both economic indicators, affecting the financial situation of consumers, and extraordinary events in shaping retail investor usage of E-Trading apps.
The interplay between stock market performance and economic risk is a central concern in financial economics, as macroeconomic variables have a considerable impact on investment decisions and stock pricing. This relationship is particularly critical for bank stocks, as their performance is a key indicator of a country’s financial health. While extensive research has explored bank stock returns in developed economies, there exists a significant gap in understanding this dynamic within developing countries like India, particularly amid macroeconomic fluctuations underscored by the COVID-19 pandemic. Given the substantial investments in bank stocks by Indian investors, this study aims to examine the impact of macroeconomic factors on Indian bank stock returns. The study employs quarterly data from 2013–14 to 2022–23, with macroeconomic data sourced from the CMIE Economic Outlook and bank stock returns data obtained from the Bloomberg database. Using an Ordinary Least Squares regression model, the findings reveal that interest rate (β = 0.3069), inflation (β = 0.1644), GDP (β = 0.1928) and COVID-19 (β = 0.5737) exert significant positive effects on bank stock returns, while the exchange rate (β = –0.7440) has a substantial negative impact. The results highlight the sensitivity of bank stock returns to macroeconomic volatilities, with the pronounced impact of the COVID-19 pandemic further highlighting the effects of economic crises. The findings emphasize the need for incorporating these factors into the bank stock returns model, offering valuable insights for investors, banks, and financial regulators. AcknowledgmentAleena Joseph is a recipient of the Indian Council of Social Science Research Doctoral Fellowship. The article is largely an outcome of the doctoral work sponsored by ICSSR. However, the responsibility for the facts stated, opinions expressed, and the conclusions drawn is entirely that of the authors.
Periods of high inflation generally cause uncertainty and risks in financial markets. In Turkey, the 2017-2023
period covers a time period characterized by frequent economic and financial fluctuations. High inflation in this
period affected many sectors in the country and created significant volatility in financial markets. BIST sector
indices were also affected by this economic environment and exhibited different volatile performances. In
particular, sectors such as energy, food and beverages are generally more affected by inflation, while sectors
such as services and technology have adapted more flexibly to economic fluctuations.
In this study, BIST Sector Indices: Food and Beverages, Electricity, Tourism and Technology indices over time
(2017-2023), i.e., high and low return periods, a univariate Markov Regime Switching (MRS) model is estimated.
According to the findings, the Food and Beverages index is stable in a particular market regime for a long period
of time and has a high probability of remaining in that regime once it is switched. For the Electricity index, the
index tends to remain in a particular market regime for a long time and can adapt quickly to changes in the
market. During periods of high inflation, the BIST-Tourism Index exhibited long-term stability and the low
volatility period covered a large period of time. This suggests that the tourism sector is resilient to economic
uncertainties and is more suitable for long-term planning. For the BIST-Technology Index, it is understood that
there is a long period of stability in a particular market regime and the period of low volatility lasts almost as long
as the period of high volatility. This suggests that the technology sector is resilient to economic uncertainties and
maintains its long-term stability.
The contribution of this study to the literature is that it reveals sector-specific long-term stability and volatility
characteristics to analyze the fluctuations of BIST sectoral indices during periods of high inflation. It provides
investors with important information about the different performance characteristics across sectors, allowing
them to formulate more effective strategies.
Jel Codes: C2, E31, E44, G1
Keywords: Macroeconomy, Inflation, BIST, Volatility
[This corrects the article DOI: 10.1007/s10479-022-04523-8.].
This paper analyses the volatility transmission between European Global Systematically Important Banks (GSIBs) and implied stock market volatility. A Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity model is applied to determine the dynamic correlation between returns of Europe’s GSIBs and the world’s most prominent measure of market “fear”, the CBOE Volatility Index (VIX). The results identify a higher negative co-relationship between the VIX and GSIB returns during the COVID-19 period compared with the Global Financial Crisis (GFC), with one-day lagged changes in the VIX negatively Granger-causing bank returns. The asymmetric impact of changes in implied volatility is examined by quantile regressions, with the findings showing that in the lower quartile–where extreme negative bank returns are present–jumps in the VIX are highly significant. This effect is more pronounced during COVID-19 than during the GFC. Additional robustness analysis shows that these findings are consistent during the periods of the Swine Flu and Zika virus epidemics.
What is the impact of interest rate and monetary policy on the stock market? Some studies find a positive impact of expansive monetary policy on stock prices others prove the opposite. This paper examines the effects of monetary expansion and interest rate changes on investment behavior on the stock market by illustrating two behavioral experiments with students. In our experiments the increase of money supply and the decrease of interest rates had a direct positive impact on share prices. These findings support the hypothesis that extreme expansive monetary policy with low, zero or negative interest rates encourage financial bubbles on the stock market. To avoid a crash the exit from such a policy must be slow. As happened in 1929, crashes can damage the financial system and the real economy. Central banks must take this into account in their monetary policy.
This study focusses on the negative relationship between inflation and stock returns (the puzzle of fisher hypothesis). Fama hypothesis examined the relationship between macroeconomic variable and stock return and found the strong relationship between the real output and stock prices. This study revisits Fama's hypothesis from the period 1990M1 to 2016M6 for emerging country perspective. The results documented that there is a significant negative relationship between inflation and output whereas positive between stock price and output.
This paper presents a critical review of 158 research articles to explore the relationship between stock return and inflation from 1930 to 2018, which provides a broad literature review and classification scheme. The results show that interest in the topic of inflation–return relation has surged during the above-mentioned period, and it is expected to remain as a prolific area of research in the forthcoming decade. The reviewed papers are classified based on the following themes: the sign of the relation, the geographical area of the study, the approach, and the applied financial methods. The majority of papers have reported the negative relationship between stock return and inflation, which means that the inflation might decrease the real component of stock return. In terms of geographical area, the authors find that the distribution of studies is prominently skewed to the developed economies, but this pattern has changed to a more diversified pattern in recent years. Also, it is found that the results in some of the papers are questionable due to applying inappropriate statistical methods such as linear regression. Finally, this paper suggests that sizable changes must be applied to the current practice of testing the relation between inflation and stock return, in order to develop more valid research. JEL: N20, G10, E31
This paper empirically investigates the relationship between real stock returns, inflation, and real activity using the Markov-switching dynamic regression (MS-DR) approach. The MS-DR allows multiple structural breaks in the estimation, and we can check regression coefficients separately in the recession and expansion periods. We selected two major developing countries (Mexico and South Africa) in order to reduce location bias. We use real stock returns, expected inflation, unexpected inflation, and real GDP growth in the estimations, and the ARFIMA model is used for unexpected inflation. The empirical results show that the relationship between real stock returns and inflation is negative only in the recession period. This regime-dependency is also tested with Eugene F. Fama’s (1981) proxy effect hypothesis, and it is found that the stock returns respond differently to inflation in a regime according to the regime- dependent proxy effect hypothesis. These findings suggest that the negative relationship puzzle in the empirical finance literature can be explained with the regime-dependency effect.
I use Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) models to estimate conditional stock market volatility using monthly data from Turkey and Canada. Following Engle and Rangel (2005), I look at the impact of inflation and find that the rate of inflation has high predictive power for stock market volatility in Turkey, whereas it is weaker, but still significant for Canada. The findings suggest that the higher the rate of inflation, the greater the stock market volatility, that is, higher rates of inflation are coincident with greater stock market risk. These results are also supported when the change in the rate of inflation is used as explanatory variable for predicting conditional volatility.
This study empirically assesses the relationship between real stock returns and inflationary trends in the Malaysian economy in the post-1997 Asian financial turmoil. Specifically, it attempts to test the relationship between real stock returns and inflation in the light of Fisher hypothesis that asserts the independence of real stock returns and inflation, and Fama (1981) proxy effect framework which states that the negative real stock returns-inflation is indirectly explained by a negative real economic activity-inflation and a positive real stock returns-real economic activity relationship. The findings show that real stock returns are independent of inflationary trends in accordance with the Fisher hypothesis, which implies that the Malaysian stock market provides a good hedge against inflation. Fama’s proxy hypothesis is then tested to check for the consistency of the relationships. The positive relationship between inflation and real economic activity and that between real stock returns and real economic activity that totally contradicts Fama’s proxy hypothesis are however found, to some extent, to be consistent with the explanation of the conventional macroeconomic theories of the Philip’s curve.
Stock returns, whether nominal or real, are commonly found to depend negatively on actual inflation, expected inflation and unexpected inflation. This runs contrary to the Fisher hypothesis generalised to apply to stocks, whereby stocks should be a hedge against inflation. However, another branch of finance, valuation theory, considers that the firm's equity is equal to the present value of future cash flows discounted at an appropriate market yield. Accordingly, if inflation is higher, the cash flows and the market yield are both adjusted upward, leaving the present worth unchanged. This present worth is the same if real (inflation-adjusted) cash flows are discounted at the real (inflation-adjusted) interest rate. Therefore valuation theory predicts that inflation is neutral on equity prices. This paper argues and presents evidence that this is indeed the case. When a fundamental variable, which is determined by a simple stock model, is included in the regressions, the effect of inflation on stock returns dissipates. Thus the observed negative relation between inflation and stock returns is due to a misspecification of the model. In reality, when the relation is properly formulated, inflation and stock returns are independent of each other.
This paper analyzes the Fisher effect using a panel of monthly data from January 1990 to December 2010 for three major countries: the United States, the United Kingdom, and Japan. Our empirical results contribute to the existing empirical literature in two ways. First, the study conducts panel cointegration tests and estimation. Second, it examines the validity of the Fisher hypothesis using short-term and long-term nominal interest rates. The empirical results show that the full Fisher effect holds from January 1990 to December 2010.
This paper hypothesizes that the relation between stock returns and inflation is caused by the equilibrium process in the monetary sector. More importantly, these relations vary over time in a systematic manner depending on the influence of money demand and supply factors. Post-war evidence from the United States, Canada, the United Kingdom and Germany indicates that the negative stock return-inflation relations are caused by money demand and counter-cyclical money supply effects. On the other hand, pro-cyclical movements in money, inflation, and stock prices during the 1930's lead to relations which are either positive or insignificant.
This paper examines the intertemporal relation between downside risk and expected stock returns. Value at Risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared with the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).
The "irrational exuberance" of the stock market in the late 1990s led to a discussion of the appropriate policy response by monetary authorities. Any response would be contingent on the stock market reaction to policy shocks. In this study, I employ a structural vector autoregression to estimate the response of the stock market returns to innovations in the federal funds rate. The role of the stock market in the Federal Reserve policy rule can also be examined empirically. 2006 The Southern Finance Association and the Southwestern Finance Association.
This paper analyses the co-movement between changes in expected inflation and U.S. stock sector returns utilizing a wavelet local multiple correlation approach, which records temporal evolution and potential correlation dynamics at various frequencies. Using daily data from January 2, 2003 to December 30, 2022, we find insignificant correlations in the short term but heterogeneous correlations in longer time periods. After the deflationary GFC period, quantitative easing has turned the long-term correlation negative in some sectors, and since COVID-19, the correlation has been positive. However, energy and materials are pro-inflation sectors in the medium and long term.
Purpose
The purpose of this study is to present evidence as to whether the use of gold or silver can be justified as an asset to hedge against policy uncertainty and COVID-19 in the Chinese market.
Design/methodology/approach
By using a GARCH model with a generalized error distribution (GED), this study specifies that the gold (or silver) return is a function of a set of economic and uncertainty variables, which include volatility from interest rate innovation, a change in economic policy uncertainty (EPU), a change in geopolitical risk (GPR) and volatility due to pandemic diseases, while controlling for stock market returns, inflation rates, economic growth and the Chinese currency value.
Findings
This study employs monthly data of gold and silver prices over the period from January 2002 to August 2021 to examine hedging behavior. Estimated results show that the gold return is positively correlated to the stock return and a rise in uncertainty from economic policy innovation, geopolitical risk, volatility due to US interest rate innovation as well as COVID-19 infection. This result suggests that gold cannot be used to hedge against a stock market decline, but can be used to hedge against uncertainty in general. However, the silver return only responds positively to a rise in uncertainty from the inflation rate and geopolitical risk. Evidence shows that silver returns are negatively correlated with stock returns, and display hedging characteristics. However, the evidence lacks statistically significance during the COVID-19 period, suggesting that the role of silver as a safe-haven asset against stock market turmoil is weak for this time period.
Research limitations/implications
More general nonlinear specifications can be developed. The tests may include different measures of uncertainty that interact with each other or with the lagged error terms. An implication of the model is that gold can be used to hedge against a broad range of uncertainties for economic policy change, political risk and/or a pandemic. However, the use of gold as an asset to hedge against a stock downturn in Chinese market should be done with caution.
Practical implications
This study has important policy implications as regards a choice in assets in formatting a portfolio to hedge against uncertainty. Specifically, this study presents empirical evidence on gold and silver return behavior and finds that gold returns respond positively to heightened uncertainty. Thus, gold is a good asset to hedge against uncertainty arising from policy innovations and infectious disease uncertainty.
Social implications
This paper provides insightful information on the choice of assets toward hedging against risk in the uncertainty market conditions. It provides information to investors and policy makers to use gold price movements as a signal for detecting the arrival of uncertainty. This study also provides information for demanding a risk premium for infectious disease.
Originality/value
This study empirically analyzes and verifies the role that gold serves as a safe haven asset to hedge against uncertainty in the Chinese market. This paper contributes to the literature by presenting evidence of risk/uncertainty premiums for holding gold against various sources of uncertainty such as economic policy uncertainty, geopolitical risk and equity market volatility due to US interest rate innovation and/or COVID-19. This study finds evidence that supports the use of a nonlinear specification, which demonstrates the interaction of uncertainty with the lagged change of infectious disease and helps to explain the gold/silver return behavior. Further, evidence shows that the gold return is positively correlated to the stock return. This finding contrasts with evidence in the US market. However, silver returns are negatively correlated with stock returns, but this correlation becomes insignificant during the period of COVID-19.
The bear Gulf Cooperation Council (GCC) sectoral equity markets in the midst of the COVID-19 pandemic presented us a test case to revisit the previously proclaimed refuge facets of gold and other precious commodities, as well as to find the resilience of these markets to global financial volatility. We further make a comparison of our findings with those obtained for the 2008 Global Financial Crisis (GFC) period. New evidence from our study based on bivariate Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity model confirms the potential of gold to serve as a weak safe haven amid both financial crises albeit with higher effectiveness during the early phase of the COVID-19 pandemic. As a whole, silver and crude oil couldn't offer sanctuary for GCC's sectoral equity markets. Further results show that unless hedged, returns of GCC equity markets are vulnerable to volatility and risk in the global financial markets.
This study investigates the impact of unexpected monetary growth (UΔM) and changes in U.S. monetary policy uncertainty (ΔMPU) on international stock returns while controlling for a change in equity market volatility (ΔEMV)and dividend yield (DY). Testing of North American stock market indices consistently shows that both UΔM and ΔMPU have significant negative impacts on stock returns, which extend the effects to one month lag. Further testing of Europe, Latin America and Asia market indices yields comparable qualitative results. The evidence confirms that an increase in the U.S. MPU is transmitted to international stock markets. This finding supports the international risk/uncertainty premium hypothesis. However, a rise in U.S. unexpected monetary growth as measured by UΔM has a less consistent effect in Latin American and Asian stock markets.
Purpose
This paper investigates the impact of a change in economic policy uncertainty ( Δ EPU t ) and the absolute value of a change in geopolitical risk ( | Δ GPR t | ) on the returns of stocks, bonds and gold in the Chinese market.
Design/methodology/approach
The paper uses Engle's (2009) dynamic conditional correlation (DCC) model and Chiang's (1988) rolling correlation model to generate correlations of asset returns over time and analyzes their responses to ( Δ EPU t ) and | Δ GPR t | .
Findings
Evidence shows that stock-bond return correlations are negatively correlated to Δ EPU t , whereas stock-gold return correlations are positively related to the | Δ GPR t | , but negatively correlated with Δ EPU t . This study finds evidence that stock returns are adversely related to the risk/uncertainty measured by downside risk, Δ EPU t and | Δ GPR t | , whereas the bond return is positively related to a rise in Δ EPU t ; the gold return is positively correlated with a heightened | Δ GPR t | .
Research limitations/implications
The findings are based entirely on the data for China's asset markets; further research may expand this analysis to other emerging markets, depending on the availability of GPR indices.
Practical implications
Evidence suggests that the performance of the Chinese market differs from advanced markets. This study shows that gold is a safe haven and can be viewed as an asset to hedge against policy uncertainty and geopolitical risk in Chinese financial markets.
Social implications
This study identify the special role for the gold prices in response to the economic policy uncertainty and the geopolitical risk. Evidence shows that stock and bond return correlation is negatively related to the ΔEPU and support the flight-to-quality hypothesis. However, the stock-gold return correlation is positively related to |ΔGPR|, resulting from the income or wealth effect.
Originality/value
The presence of a dynamic correlations between stock-bond and stock-gold relations in response to Δ EPU t and | Δ GPR t | has not previously been tested in the literature. Moreover, this study finds evidence that bond-gold correlations are negatively correlated to both Δ EPU t and | Δ GPR t | .
Purpose
Recent empirical studies by Antonakakis, Chatziantoniou and Filis (2013), Brogaard and Detzel (2015) and Christou et al. (2017) present evidence, which supports the notion that a rise in economic policy uncertainty (EPU) will lead to a decline in stock prices. The purpose of this paper is to examine US categorical policy uncertainty on stock returns while controlling for implied volatility and downside risk. In addition to the domestic impacts of policy uncertainty, this paper also presents evidence that changes in US policy uncertainty promptly propagates to the global stock markets.
Design/methodology/approach
This study uses a GED-GARCH (1, 1) model to estimate changes of uncertainties in US monetary, fiscal and trade policies on stock returns for the sample period of January 1990–December 2018. Robustness test is conducted by using different set of data and modeling techniques.
Findings
This paper contributes to the literature in several aspects. First, testing of US aggregate data while controlling for downside risk and implied volatility, consistently, shows that responses of stock prices to US policy uncertainty changes, not only display a negative effect in the current period but also have at least a one-month time-lag. The evidence supports the uncertainty premium hypothesis. Second, extending the test to global data reveals that US policy uncertainty changes have a negative impact on markets in Europe, China and Japan. Third, testing the data in sectoral stock markets mainly displays statistically significant results with a negative sign. Fourth, the evidence consistently shows that changes in policy uncertainty present an inverse relation to the stock returns, regardless of whether uncertainty is moving upward or downward.
Research limitations/implications
The current research is limited to the markets in the USA, eurozone, China and Japan. This study can be extended to additional countries, such as emerging markets.
Practical implications
This paper provides a model that uses categorical policy uncertainty approach to explain stock price changes. The parametric estimates provide insightful information in advising investors for making portfolio decision.
Social implications
The estimated coefficients of changes in monetary policy uncertainty, fiscal policy uncertainty and trade policy uncertainty are informative in assisting policymakers to formulate effective financial policies.
Originality/value
This study extends the existing risk premium model in several directions. First, it separates the financial risk factors from the EPU innovations; second, instead of using EPU, this study investigates the effects from monetary policy, fiscal policy and trade policy uncertainties; third, in additional to an examination of the effects of US categorical policy uncertainties on its own markets, this study also investigates the spillover effects to global major markets; fourth, besides the aggregate stock markets, this study estimates the effects of US policy uncertainty innovations on the sectoral stock returns.
We show that global political uncertainty, measured by the U.S. election cycle, on average, leads to a fall in equity returns in fifty non-U.S. countries. At the same time, market volatilities rise, local currencies depreciate, and sovereign bond returns increase. The effect of global political uncertainty on equity prices increases with the level of uncertainty in U.S. election outcomes and a country’s equity market exposure to foreign investors, but does not vary with the country’s international trade exposure. These findings suggest that global political uncertainty increases investors’ aggregate risk aversion, leading to a flight to safety.(JEL F30, F36, G12, G15, G18)
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.
We compare the performance of safe-haven assets during the Global Financial Crisis (GFC) and COVID-19 pandemic. First, regarding the GFC, we find, intermediate (weak) safe haven evidence for US dollar, Swiss franc and T-bonds (Gold, Silver and T-bills). Second, with regard
to COVID, we find gold is very risky in some settings, while silver has become extremely risky. Collectively, our findings suggest that the character of safe-haven assets has changed between the crises. Therefore, investors should exercise extreme care when investing in
potential safe-haven assets during times of market stress.
We construct a new measure of uncertainty about Federal Reserve policy actions and their consequences, a monetary policy uncertainty (MPU) index. We evaluate the information content of our index and document the usefulness of our index in bridging periods of conventional and unconventional policy making. We also estimate the aggregate effects of shocks to MPU on output, credit spreads, and other variables. Finally, we investigate the transmission channels of MPU, finding that heightened MPU leads to protracted declines in firm investment through both real options and financial frictions channels.
We study the feasibility of hedging stocks with oil. The Dynamic Conditional Correlation (DCC) approach allows for the calculation of optimal hedge ratios and corresponding hedge portfolio returns. Our results show that there are distinct economic benefits from hedging stocks with oil, although the effectiveness of hedging is both time-varying and market-state-dependent. The event of the Global Financial Crisis (GFC) is shown to affect the effectiveness of hedging. During the GFC, a positive jump in the hedge ratios occurs and hedge effectiveness increases. Among a set of common financial and macroeconomic drivers, we identify the implied volatility index VIX as being the most important. During times of global financial uncertainty, investors reduce stock positions more than commodity positions, thus VIX shocks negatively affect the portfolio returns of stock-oil hedges. The results also show that an appreciation of the U.S. dollar against the euro is associated with reduced hedge portfolio returns. From the GFC onwards, we document an increased significance of the gold price and the term spread in explaining hedge portfolio returns.
Any risk-return tradeoff analysis in aggregate equity markets relies on appropriate measures of risk, in most studies based on (co-)variance relations. Consequently, in integrated global markets, country-specific expected return is priced with a world price of covariance risk. This study relates domestic excess stock returns to the world downside risk. Evidence shows that downside tail risk (as a multiplier of volatility) has long memory cointegration properties; hence, the underlying risk aversion behavior in an integrated market is associated with the conditional quantile ratio, the correlation of stock returns, and the cointegrating coefficient of downside risk. Our empirical results based on G7 countries indicate that investors are averse to downside risk, which via Cornish–Fisher expansions is related to higher moment risk and interpretable in a utility-based decision framework.
The relationship between stock prices and the inflation can be either negative or positive, depending on the strengths of various theoretical channels at work. In this study, we examine the dynamic conditional correlations of stock prices and inflation in the United States over the period of 1791-2015 under a time-varying framework. The results of our empirical analysis reveal that correlations between the inflation and stock prices in the United States evolve heterogeneously overtime. In particular, the correlations are significantly positive in the 1840s, 1860s, 1930s and 2011, and significantly negative otherwise. The policy implications of these findings are then discussed.
We develop a new index of economic policy uncertainty (EPU) based on newspaper coverage frequency. Several types of evidence – including human readings of 12,000 newspaper articles – indicate that our index proxies for movements in policy-related economic uncertainty. Our US index spikes near tight presidential elections, Gulf Wars I and II, the 9/11 attacks, the failure of Lehman Brothers, the 2011 debt-ceiling dispute and other major battles over fiscal policy. Using firm-level data, we find that policy uncertainty is associated with greater stock price volatility and reduced investment and employment in policy-sensitive sectors like defense, healthcare, finance and infrastructure construction. At the macro level, innovations in policy uncertainty foreshadow declines in investment, output, and employment in the United States and, in a panel VAR setting, for 12 major economies. Extending our US index back to 1900, EPU rose dramatically in the 1930s (from late 1931) and has drifted upwards since the 1960s.
This paper examines the intertemporal capital asset pricing (Merton, 1973) for industry portfolio returns of 14 international markets. Using different multivariate GARCH models to estimate time-varying conditional covariances between industry excess returns and market excess returns by controlling for financial market volatility variables and the Fama-French-Carhart factors, we find positive evidence to support the tradeoff between industry excess return and the covariance risk for all advanced markets (except Germany), all Asian markets, and Argentina in Latin American markets. The evidence suggests that the positive risk-return relationship is more pronounced during the tranquil period.
A Structural VAR model is employed to investigate the effects of monetary and fiscal policy shocks on stock market performance in Germany, UK and the US. A significant number of past studies have concentrated their attention on the relationship between monetary policy and stock market performance, yet only few on the effects of fiscal policy on stock markets. Even more we know little, if any, on the effects of fiscal and monetary policies on stock market performance when the two policies interact. This study aims to fill this void. Our results show that both fiscal and monetary policies influence the stock market, via either direct or indirect channels. More importantly, we find evidence that the interaction between the two policies is very important in explaining stock market developments. Thus, investors and analysts in their effort to understand the relationship between macroeconomic policies and stock market performance should consider fiscal and monetary policies in tandem rather than in isolation.
The power of dividend yields to forecast stock returns, measured by regression R2, increases with the return horizon. We offer a two-part explanation. (1) High autocorrelation causes the variance of expected returns to grow faster than the return horizon. (2) The growth of the variance of unexpected returns with the return horizon is attenuated by a discount-rate effect - shocks to expected returns generate opposite shocks to current prices. We estimate that, on average, the future price increases implied by higher expected returns are just offset by the decline in the current price. Thus, time-varying expected returns generate ‘temporary’ components of prices.
This article examines the short and long-term relationships between stock prices, inflation, and output in 21 emerging capital markets. It also investigates whether the proxy hypothesis can explain the puzzling negative relation between stock returns and inflation. The study shows that in the short run the negative relationship between stock returns and inflation still persist for all countries except Malaysia, even after the effects of expected economic activity and inflation variability have been explicitly incorporated. Furthermore, the results of the generalised autoregressive conditional heteroscedastic (GARCH) model are consistent with the OLS results. These results reject the proxy-effect hypothesis in the short run. However, in the long run, cointegration tests verify a long-run equilibrium between stock prices, consumer price index, and the real economic activity. The findings support the Fisher effect and the proxy hypotheses in the long run only.
This paper investigates empirically the dynamics of investors' beliefs and Bayesian uncertainty about the state of the economy
as state variables that describe the time-variation in investment opportunities. Using measures of uncertainty constructed
from the state probabilities estimated from two-state regime-switching models of aggregate market return and of aggregate
output, I find a negative relationship between the level of uncertainty and asset valuations. This relationship shows substantial
cross-sectional variation across portfolios sorted on size, book-to-market, and past returns, especially conditional on the
state of the economy. I show that a conditional model with investors' beliefs and an uncertainty risk factor is remarkably
successful in explaining a large part of the cross-sectional variation in average portfolio returns. The uncertainty risk
factor retains its incremental explanatory power when compared to other conditional models such as the conditional CAPM.
Using monthly data from G7 and eight Asian countries, support is found for the Fisher hypothesis, as well as a positive relation between long-horizon nominal stock returns and expected inflation but not between long-horizon nominal stock returns and contemporaneous inflation. These empirical results complement and strengthen those of Boudoukh and Richardson. The MATLAB program and data to compute the results in this paper are available from http://kafuwong.econ.hku.hk/research/fisher/.
During the late 19th and early 20th centuries, the problems of the day were of a kind that led economists to concentrate on the allocation of resources and, to a lesser extent, economic growth, and to pay little attention to short-run fluctuations of a cyclical character. Since the Great Depression of the 1930s, this emphasis has been reversed. Economists now tend to concentrate on cyclical movements, to act and talk as if any improvement, however slight, in control of the cycle justified any sacrifice, however large, in the long-run efficiency, or prospects for growth, of the economic system. Proposals for the control of the cycle thus tend to be developed almost as if there were no other objectives and as if it made no difference within what general framework cyclical fluctuations take place. A consequence of this attitude is that inadequate attention is given to the possibility of satisfying both sets of objectives simultaneously.
IntroductionTypes of outliers in time seriesProcedures for outlier identification and estimationInfluential observationsMultiple outliersMissing-value estimationForecasting with outliersOther approachesAppendix
Outliers, level shifts, and variance changes are commonplace in applied time series analysis. However, their existence is often ignored and their impact is overlooked, for the lack of simple and useful methods to detect and handle those extraordinary events. The problem of detecting outliers, level shifts, and variance changes in a univariate time series is considered. The methods employed are extremely simple yet useful. Only the least squares techniques and residual variance ratios are used. The effectiveness of these simple methods is demonstrated by analysing three real data sets.
Whether common stocks provide a hedge against inflation has been long debated. This paper focuses on this question by investigating the relationship between inflation and stock returns in the short term and medium term and under different inflationary regimes using the UK data. Empirical evidence suggests that the UK stock market fails to hedge against inflation in the short term. However, in the medium term there is mixed results. Results from different inflationary regimes show that the relationship between inflation and returns varies in different regimes.
This article provides a test of the Fisher model, linking expected stock returns and inflation, based on international data. Since the Fisher model is ‘universal’ and calls for a slope of 1 in any country, we improve the testing power by conducting a joint test over eight countries. The pooling of data for several countries seems to reduce the small-sample bias. We test the Fisher model, using an instrumental variable approach, for holding-period horizons ranging from 1–12 months. The Fisher model is not rejected at any horizon: however, the magnitude of the slope coefficient lends stronger support at long horizons. This study using multi-country panel data provides evidence corroborating the finding of Boudoukh and Richardson (1993) that the Fisher model holds at long horizons (5 years), using 180 years of US data.
Previous research documents that US stock returns are related to the US monetary environment. The focus of this paper is to determine whether stock returns in foreign markets are associated with both local and US monetary environments. Consistent with the US market results, we find that foreign stock returns are generally higher in expansive US and local monetary environments than they are in restrictive environments. Further, these higher returns are generally not accompanied by increases in risk. Interestingly, several of the stock markets are more strongly related to the US monetary environment than to local monetary conditions. For seven of the 15 foreign countries examined, the local and US monetary environment explain 4% or more of the variation in monthly stock returns.
We apply a dynamic conditional-correlation model to nine Asian daily stock-return data series from 1990 to 2003. The empirical evidence confirms a contagion effect. By analyzing the correlation-coefficient series, we identify two phases of the Asian crisis. The first shows an increase in correlation (contagion); the second shows a continued high correlation (herding). Statistical analysis of the correlation coefficients also finds a shift in variance during the crisis period, casting doubt on the benefit of international portfolio diversification. Evidence shows that international sovereign credit-rating agencies play a significant role in shaping the structure of dynamic correlations in the Asian markets.
Several hypotheses have been proposed to explain the stock return–inflation relation. The Modigliani and Cohn’s inflation illusion hypothesis has received renewed attention. Another hypothesis is the two-regime hypothesis. We reexamine these hypotheses using long sample data of the US and international data. We find that the inflation illusion hypothesis can explain the post-war negative stock return–inflation relation, but it is not compatible with the pre-war positive relation. Using a structural VAR identification method, we show that there are two regimes with positive and negative stock return–inflation relations not only in each period of the US but also in every developed country we consider. This seems inconsistent with the inflation illusion hypothesis that predicts only a negative relation.
The expected market return is a number frequently required for the solution of many investment and corporate finance problems, but by comparison with other financial variables, there has been little research on estimating this expected return. Current practice for estimating the expected market return adds the historical average realized excess market returns to the current observed interest rate. While this model explicitly reflects the dependence of the market return on the interest rate, it fails to account for the effect of changes in the level of market risk. Three models of equilibrium expected market returns which reflect this dependence are analyzed in this paper. Estimation procedures which incorporate the prior restriction that equilibrium expected excess returns on the market must be positive are derived and applied to return data for the period 1926–1978. The principal conclusions from this exploratory investigation are: (1) in estimating models of the expected market return, the non-negativity restriction of the expected excess return should be explicity included as part of the specification: (2) estimators which use realized returns should be adjusted for heteroscedasticity.
This paper investigates the impact of monetary policy on stock returns in 13 OECD countries over the period 1972–2002. Our results indicate that monetary policy shifts significantly affect stock returns, thereby supporting the notion of monetary policy transmission via the stock market. Our contribution with respect to previous work is threefold. First, we show that our findings are robust to various alternative measures of stock returns. Second, our inferences are adjusted for the non-normality exhibited by the stock returns data. Finally, we take into account the increasing co-movement among international stock markets. The sensitivity analysis indicates that the results remain largely unchanged.
The intertemporal capital asset pricing model of Merton (1973) is examined using the dynamic conditional correlation (DCC) model of Engle (2002). The mean-reverting DCC model is used to estimate a stock’s (portfolio’s) conditional covariance with the market and test whether the conditional covariance predicts time-variation in the stock’s (portfolio’s) expected return. The risk-aversion coefficient, restricted to be the same across assets in panel regression, is estimated to be between two and four and highly significant. The risk premium induced by the conditional covariation of assets with the market portfolio remains positive and significant after controlling for risk premia induced by conditional covariation with macroeconomic, financial, and volatility factors.