The determinants of the model-free positive and negative volatilities

In this paper we analyze the role of macroeconomic and financial determinants in explaining stock market volatilities in the U.S. market. Both implied and realized volatility are computed model-free and decomposed into positive and negative components, thereby allowing us to compute directional volatility risk premia. We capture the behaviour of each component of implied volatility and risk premium in relation to their different determinants. The negative implied volatility appears to be linked more towards financial conditions variables such as uncertainty and geopolitical risk indexes, whereas positive implied volatility is driven more by macro variables such as inflation and GDP. There is a clear shift in importance from macro towards financial determinants moving from the pre towards the post financial crisis. A mixed frequency Granger causality approach uncovers causality relationships between volatilities and risk premia and macro variables and vice versa, a finding which is not detected with a conventional low frequency VAR model.     

Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields

We propose a Nelson–Siegel type interest rate term structure model where the underlying yield factors follow autoregressive processes with stochastic volatility. The factor volatilities parsimoniously capture risk inherent to the term structure and are associated with the time-varying uncertainty of the yield curve’s level, slope and curvature. Estimating the model based on US government bond yields applying Markov chain Monte Carlo techniques we find that the factor volatilities follow highly persistent processes. We show that yield factors and factor volatilities are closely related to macroeconomic state variables as well as the conditional variances thereof.     

Riding the swaption curve

We conduct an empirical analysis of the term structure in the volatility risk premium in the fixed income market by constructing long-short combinations of two at-the-money straddles for the four major swaption markets (USD, JPY, EUR and GBP). Our findings are consistent with a concave, upward-sloping maturity structure for all markets, with the largest negative premium for the shortest term maturity. The fact that both delta–vega and delta–gamma neutral straddle combinations earn positive returns that seem uncorrelated suggests that the term structure is affected by both jump risk and volatility risk. The results seem robust for macroeconomic announcements and the specific model choice to estimate the risk exposures for hedging.     

Identifying volatility risk premia from fixed income Asian options

Fixed income options are frequently adopted by companies to hedge interest rate risk. Their payoff dependence on the cumulative short-term rate makes them particularly informative about interest rate volatility risk. Based on a joint dataset of bonds and Asian interest rate options, we study the interrelations between bond and volatility risk premia in a major emerging fixed income market. We propose a dynamic term structure model that generates an incomplete market compatible with a preliminary empirical analysis of the dataset. Approximation formulas for at-the-money Asian option prices avoid the use of computationally intensive Fourier transform methods, allowing for an efficient implementation of the model. The model generates a bond risk premium strongly correlated with a widely accepted emerging market benchmark index (EMBI-Global), and a negative volatility risk premium, consistent with the use of Asian options as insurance in this market.     

What do asset prices have to say about risk appetite and uncertainty?

Building on intuition from the dynamic asset pricing literature, we uncover unobserved risk aversion and fundamental uncertainty from the observed time series of the variance premium and the credit spread while controlling for the conditional variance of stock returns, expectations about the macroeconomic outlook, and interest rates. We apply this methodology to monthly data from both Germany and the US. We find that the variance premium contains a substantial amount of information about risk aversion whereas the credit spread has a lot to say about uncertainty. We link our risk aversion and uncertainty estimates to practitioner and “academic” risk aversion indices, sentiment indices, financial stress indices, business cycle indicators and liquidity measures.     

International linkages and macroeconomic news effects on interest rate volatility — Australia and the US

We examine international linkages between daily time series of US and Australian 3-month treasury bills and 10-year government bonds from 1987–1995, paying particular attention to the effects of macroeconomic announcements in both countries. The two countries' interest rate data are modeled by a bivariate exponential generalized autoregressive conditional heteroscedasticity (EGARCH) formulation. The results suggest that market participants believed the Reserve Bank of Australia targeted the consumer price index (CPI), while the Federal Reserve targeted economic activity. Monetary policy announcements had significant effects on interest rates, as well as on their volatility in the short term. US macroeconomic activity announcements significantly moved Australian interest rates, particularly at the short end. Australian interest rates moved significantly in response to the previous day's US interest rate shocks. The conditional volatility of the Australian interest rate changes was also significantly influenced by lagged US interest rate shocks, as well as by surprises in US macroeconomic announcements. Some macroeconomic news announcements raised conditional volatilities, while others reduced them. Overall, there was a remarkable and complex array of linkages between the two countries.     

Linear‐Rational Term Structure Models

We introduce the class of linear‐rational term structure models in which the state price density is modeled such that bond prices become linear‐rational functions of the factors. This class is highly tractable with several distinct advantages: (i) ensures nonnegative interest rates, (ii) easily accommodates unspanned factors affecting volatility and risk premiums, and (iii) admits semi‐analytical solutions to swaptions. A parsimonious model specification within the linear‐rational class has a very good fit to both interest rate swaps and swaptions since 1997 and captures many features of term structure, volatility, and risk premium dynamics—including when interest rates are close to the zero lower bound.     

The macroeconomic determinants of technology stock price volatility

Stock prices reflect the value of anticipated future profits of companies. Since business cycle conditions impact the future profitability of firms, expectations about the business cycle will affect the current value of firms. This paper uses daily and monthly data from July 1986 to December 2000 to investigate the macroeconomic determinants of US technology stock price conditional volatility. Technology share prices are measured using the Pacific Stock Exchange Technology 100 Index. One of the novel features of this paper is to incorporate a link between technology stock price movements and oil price movements. The empirical results indicate that the conditional volatilities of oil prices, the term premium, and the consumer price index each have a significant impact on the conditional volatility of technology stock prices. Conditional volatilities calculated using daily stock return data display more persistence than conditional volatilities calculated using monthly data. These results further our understanding of the interaction between oil prices and technology share prices and should be of use to investors, hedgers, managers, and policymakers.     

Preference heterogeneity and asset prices: An exact solution

We introduce a general equilibrium model of a multi-agent, pure-exchange economy and find a set of conditions that enable us to obtain explicit closed-form solutions to the equilibrium interest rate, stock price, risk premium and stock market volatility when investors have heterogenous risk aversions. Because the market is dynamically complete, full risk sharing obtains and a representative agent can be constructed, though the risk aversion of this agent fluctuates over time with the state of the economy, as the relative wealth distribution of the individual investors changes. We show that preference heterogeneity can cause asset prices to be significantly more volatile than the underlying dividends and that it can lead to leverage-like effects in volatility, in the sense that volatility increases after stock-market declines.     

A consumption-based model of the term structure of interest rates

This paper proposes a consumption-based model that accounts for many features of the nominal term structure of interest rates. The driving force behind the model is a time-varying price of risk generated by external habit. Nominal bonds depend on past consumption growth through habit and on expected inflation. When calibrated to data on consumption, inflation, and the aggregate market, the model produces realistic means and volatilities of bond yields and accounts for the expectations puzzle. The model also captures the high equity premium and excess stock market volatility.     

Macroeconomic risks and REITs returns: A comparative analysis

We study the relationship between the excess returns of REITs and volatilities of macroeconomic factors in developing markets (Bulgaria and South Africa) and a ‘benchmark’ developed market (USA). As expected, our results generally indicate that conditional volatilities of macroeconomic risks, extracted through the GARCH (1,1) process, are time-varying. GARCH coefficients are largely significant for excess returns and retained principal components implying conditional time-varying volatility. We use the GMM to examine the linkage between volatilities of macroeconomic variables and REITs returns. The general result here is that macroeconomic risk cannot explain excess returns on REITs. However, we document a positive relationship between variability in REITs returns and the real economy for the US. US REITs portfolio managers and investors should be wary of fluctuations in these variables as they may accentuate volatility in REITs returns.     

Empirical analysis of real and financial volatilities on stock excess returns: evidence from Taiwan industrial data

This paper tests the relation between stock excess returns and risk factors measured by volatility. The sources of the volatility are based on the volatility of macroeconomic factors and time-series volatility. To model the macroeconomic fundamentals, we divide the risk into real and financial volatilities pertinent to Taiwan's economic environment. By examining the data of indusry excess returns and market excess returns, we find evidence to reject the hypothesis that the stock excess returns are independent of the real and financial volatilities.     

Information in the Term Structure of Yield Curve Volatility

Using a novel no‐arbitrage model and extensive second‐moment data, we decompose conditional volatility of U.S. Treasury yields into volatilities of short‐rate expectations and term premia. Short‐rate expectations become more volatile than premia before recessions and during asset market distress. Correlation between shocks to premia and shocks to short‐rate expectations is close to zero on average and varies with the monetary policy stance. While Treasuries are nearly unexposed to variance shocks, investors pay a premium for hedging variance risk with derivatives. We illustrate the dynamics of the yield volatility components during and after the financial crisis.     

The Effect of Temporal Risk Aversion on Optimal Consumption,the Equity Premium,and the Equilibrium Interest Rate

This paper demonstrates that temporal risk aversion makes smoothing consumption over time less attractive, while the usual risk aversion makes it more attractive. As temporal risk aversion increases, the equilibrium interest rate decreases and the equity premium increases. This paper also shows a striking and novel result that an increase in time impatience can lead to either a decrease or an increase in the interest rate, depending on the nature of the nonseparability.     

Modeling volatility and changes in the swap spread

We investigate the determinants of changes in U.S. interest rate swap spreads using a model that explicitly allows for volatility interactions between swaps of different terms to maturity. Changes in the swap spread are found to be positively related to interest rate volatility, to changes in the default risk premium in the corporate bond market, and to changes in the liquidity premium for government securities. Swap spread changes are negatively related to changes in the level of interest rates and changes in the slope of the term structure. We also find that there is a strong and significant volatility interaction among spreads for swaps of different maturities and that the process for the conditional variance of the spread is highly persistent across all maturities.     

Volatility,the Macroeconomy,and Asset Prices

How important are volatility fluctuations for asset prices and the macroeconomy? We find that an increase in macroeconomic volatility is associated with an increase in discount rates and a decline in consumption. We develop a framework in which cash flow, discount rate, and volatility risks determine risk premia and show that volatility plays a significant role in explaining the joint dynamics of returns to human capital and equity. Volatility risk carries a sizable positive risk premium and helps account for the cross section of expected returns. Our evidence demonstrates that volatility is important for understanding expected returns and macroeconomic fluctuations.     

Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors

I use Stochastic Discount Factors to examine the sources of the idiosyncratic volatility premium. I find that non-zero risk aversion and firms’ non-systematic coskewness determine the premium on idiosyncratic volatility risk. The firm’s non-systematic coskewness measures the comovement of the asset’s volatility with the market return. When I control for the non-systematic coskewness factor, I find no significant relation between idiosyncratic volatility and stock expected returns. My results are robust across different sample periods and firm characteristics.     

A new approach to measuring riskiness in the equity market: Implications for the risk premium

We introduce a new approach to measuring riskiness in the equity market. We propose option implied and physical measures of riskiness and investigate their performance in predicting future market returns. The predictive regressions indicate a positive and significant relation between time-varying riskiness and expected market returns. The significantly positive link between aggregate riskiness and market risk premium remains intact after controlling for the S&P 500 index option implied volatility (VIX), aggregate idiosyncratic volatility, and a large set of macroeconomic variables. We also provide alternative explanations for the positive relation by showing that aggregate riskiness is higher during economic downturns characterized by high aggregate risk aversion and high expected returns.     

Time-varying risk aversion and asset prices

This paper uses a variant of the consumption-based representative agent model in Campbell and Cochrane [Campbell, J.Y., Cochrane, J.H., 1999. By force of habit: Consumption-based explanation of aggregate stock market behavior. Journal of Political Economy 107, 205–251] to study how investors’ time-varying risk aversion affects asset prices. First, we show that a countercyclical variation of risk aversion drives a procyclical conditional risk premium. Second, we show that with a small value for the volatility of the log surplus consumption ratio, a large value of risk aversion may not determine whether the equity premium and the risk-free rate puzzles can be resolved or not. Third, we show that countercyclical risk aversion may not help explain the predictability of long-horizon stock returns, the univariate mean-reversion of stock prices and the “leverage effect” in return volatility.     

Risk,uncertainty, and asset prices

We identify the relative importance of changes in the conditional variance of fundamentals (which we call “uncertainty”) and changes in risk aversion in the determination of the term structure, equity prices, and risk premiums. Theoretically, we introduce persistent time-varying uncertainty about the fundamentals in an external habit model. The model matches the dynamics of dividend and consumption growth, including their volatility dynamics and many salient asset market phenomena. While the variation in price–dividend ratios and the equity risk premium is primarily driven by risk aversion, uncertainty plays a large role in the term structure and is the driver of countercyclical volatility of asset returns.