Equity Price Volatility Research Articles

Risk-taking incentives and risk-talking outcomes

CEOs’ option-based compensation and discussions about political risk (risk-talking) in successive earnings conference calls are significantly positively associated. This effect is more significant in the subsample of firms with less equity price volatility and poor investment risk-taking (lower capital expenditure). Furthermore, seven out of eight components of risk-talking are positively related to CEOs’ option-based compensation. These findings suggest that CEOs with more options in compensation packages are likely to find discussing political risk during corporate earnings calls as a viable alternative to boost proxies of risk-taking outcomes (such as equity price volatility), especially when they perceive risk-taking expectations to be untenable.

A stochastic‐volatility equity‐price tree for pricing convertible bonds with endogenous firm values and default risks determined by the first‐passage default model

AbstractThis paper proposes a novel equity‐price‐tree‐based convertible bond (CB) pricing model based on the first‐passage default model under stochastic interest rates. By regarding equity values as down‐and‐out call options on firm values (FVs), at each tree node, we solve the implied FV and equity‐price volatility (EPV), and then endogenously settle the default probability (DP) and also the dilution effect subject to CB conversions with the implied FV and capital structure. Our model captures the stylized negative (positive) relationships between the stochastically evolving DP and FV or EP (EPV) that cannot be fully achieved by existing CB pricing models.

Time-frequency analysis of the comovement between wheat and equity markets

PurposeThis study aims to investigate the time-frequency comovement between wheat futures traded on three US markets (Chicago Board of Trade (CBOT), Kansas City Board of Trade (KCBOT) and Minneapolis Grain Exchange (MGE)) at different maturities and a global equity index.Design/methodology/approachAs they allow to trace transitional shifts over time and across different frequency bands, this paper relies on continuous wavelet tools to investigate the time-frequency comovement among wheat and global stock markets.FindingsThe results show an increase in wheat futures prices at all maturities and a weak integration level within each wheat market during the subprime crisis. Moreover, the wavelet power spectra maps show high wheat and equity price volatility at different time scales and for various subperiods. Furthermore, the continuous wavelet coherence highlights time-frequency-varying comovements between the markets considered, which become particularly high during times of crisis.Practical implicationsThe results provide market participants with a better understanding of the nature as well as the magnitude of the relationship between the global financial market and different wheat markets at different maturities and during tranquil and crisis periods. Indeed, from investors' perspective it is important to understand how markets are segmented or integrated during tranquil and crisis periods in order to better assess risks, diversify portfolios and implement more effective hedging strategies. As for regulators, a better understanding of the level of integration of different markets would further help refine macroprudential policies, and thus strengthen financial stability and resilience.Originality/valueThis paper enriches the existing literature by investigating the time-frequency comovement between wheat and a global equity market. Indeed, the dynamics between stock and wheat markets across different nearest to maturities have not been widely explored by previous studies.

Macro‐financial volatility under dispersed information

We provide a production‐based asset pricing model with dispersed information and small deviations from full rational expectations. In the model, aggregate output and equity prices depend on the higher‐order beliefs about aggregate demand and individual stochastic discount factors. We prove that equity price volatility becomes arbitrarily large as the volatility of idiosyncratic shocks diverges to infinity due to the interaction of signal extraction with idiosyncratic trading decisions, while aggregate output volatility falls. We propose a two‐step spectral factorization method that permits closed‐form solutions in the frequency domain applicable to a wide range of models with more hidden states than signals. Our model can quantitatively match output and equity volatilities observed in U.S. data.

Extreme high surface temperature events and equity-related physical climate risk

By matching the timing and geography of extreme high surface temperature (EHST) events in the United States to the location of firms' headquarters, we are able to measure the equity market's response to an exogenous shock deemed by climate scientists to relate proximately causally to equity-related physical climate risk. Measured as the cumulative excess return over EHST day 0 (the initial shock) to EHST day 20, we find that the equity market responds negatively to EHST events (−0.42%), and more negatively to costlier events (−1.38%) and those of longer duration (−0.68%). Firms in counties in the South and Southeast climate regions, the month of July, and the most recent decade of the study period (2008–2017) experience the most negative cumulative excess returns in response to EHST events. In addition, consistent with equity investors' recognition of physical climate risk, equity price volatility increases over EHST days 0–20, rising even more for costly and long-duration events. Our findings imply that the equity market recognizes but underprices physical climate risk, consistent with forming biased expectations of future equity returns.

Sensitivity of economic policy uncertainty to investor sentiment

Purpose This paper aims to explore the impact of investor sentiments on economic policy uncertainty (EPU). The analysis also considers the momentum effect, stock market returns volatility and equity pricing inefficiencies across markets, which, to the best of the authors’ knowledge, has not been addressed in the literature. The role of these control variables has collectively been considered to have important behavioral implications for international investors Design/methodology/approach Quantile regressions are used for estimation purpose, as it provides robust and more efficient estimates rather than those coming from the traditional regression model. Findings The momentum effect is negative and significant only at higher quantiles, while oil prices are positive and significant across all quantiles. The exchange rate exerts a negative and significant effect on EPU, whereas equity price volatility (i.e. investor sentiment) exerts a negative and significant impact on EPU in most of the quantiles. Research limitations/implications The results have important implications for international investors and policymakers, especially in terms of the breakdown of economic policy uncertainty across different sample markets. The breakdown of complete sample period into sub-samples acts as a robust analysis and documents the similarity of the results for the Asian and developed markets cases, but not in the case of the European markets. Practical implications The findings imply the importance of financial stability that impacts the accumulation of systemic risks and adds smoothness to the financial cycle in particular geographical areas. Originality/value The contribution of this paper is threefold. First, existing literature highlights and empirically tests the impact of economic policy uncertainty on different market, macro-economic and global control variables. The analysis, however, performs it in the reverse order, i.e. analyzing the impact of the momentum effect (investor sentiment variables), equity market inefficiencies and volatility (market variables) and exchange rates and Brent oil (control variables). Second, to check the sensitivity of economic policy uncertainty, the analysis analyzes a wide range of markets, segregated as emerging, developed and European regions over the sample period to generate region-wise implications. Finally, the analysis explores the relationship of aforementioned variables with economic policy uncertainty keeping in view the non-linear structure and prior evidence and investor sentiments and economic policy uncertainty in the regression model.

On Calibration and Simulation of Local Volatility Model with Stochastic Interest Rate

Local volatility model is a relatively simple way to capture volatility skew/smile. In spite of its drawbacks, it remains popular among practitioners for derivative pricing and hedging. For long-dated options or interest rate/equity hybrid products, in order to take into account the effect of stochastic interest rate on equity price volatility stochastic interest rate is often modelled together with stochastic equity price. Similar to local volatility model with deterministic interest rate, a forward Dupire PDE can be derived using Arrow-Debreu price method, which can then be shown to be equivalent to adding an additional correction term on top of Dupire forward PDE with deterministic interest rate. Calibrating a local volatility model by the forward Dupire PDE approach with adaptively mixed grids ensures both calibration accuracy and efficiency. Based on Malliavin calculus an accurate analytic approximation is also derived for the correction term incorporating impacts from both interest rate volatility and correlation, which integrates along a more likely straight line path for better accuracy. Eventually, the hybrid local volatility model can be calibrated in a two-step process, namely, calibrate local volatility model with deterministic interest rate and add adjustment for stochastic interest rate. Due to the lack of analytic solution and path-dependency nature of some products, Monte Carlo is a simple but flexible pricing method. In order to improve its convergence, we develop a scheme to combine merits of different simulation schemes and show its effectiveness.

The Macroeconomic Effects of International Uncertainty

This paper proposes a large-scale Bayesian vector autoregression with factor stochastic volatility to investigate the macroeconomic consequences of international uncertainty shocks in G7 countries. The curse of dimensionality is addressed by means of a global-local shrinkage prior that mimics certain features of the well-known Minnesota prior, yet provides additional flexibility in terms of achieving shrinkage. The factor structure enables us to identify an international uncertainty shock by assuming that it is the joint volatility process that determines the dynamics of the variance-covariance matrix of the common factors. To allow for first and second moment shocks we, moreover, assume that the uncertainty factor enters the VAR equation as an additional regressor. Our findings suggest that the estimated uncertainty measure is strongly connected to global equity price volatility, closely tracking other prominent measures commonly adopted to assess uncertainty. The dynamic responses of a set of macroeconomic and financial variables show that an international uncertainty shock exerts large effects on all economies and variables under consideration.

News shocks and asset price volatility in general equilibrium

We study equity price volatility in general equilibrium with news shocks about future productivity and monetary policy. As West (1988) shows, in a partial equilibrium present discounted value model, news about the future cash flow reduces asset price volatility. We show that introducing news shocks in a canonical dynamic stochastic general equilibrium model may not reduce asset price volatility under plausible parameter assumptions. This is because, in general equilibrium, the asset cash flow itself may be affected by the introduction of news shocks. In addition, we show that neglecting to account for policy news shocks (e.g., policy announcements) can potentially bias empirical estimates of the impact of monetary policy shocks on asset prices.

Asset price volatility and government revenue

This paper investigates the effect of commercial, residential property and equity price volatility on the variability of cyclically adjusted government revenue. We find significant evidence that asset price volatility increases the variability of government revenue. A 1% increase in equity price volatility increases government revenue variability by 0.37–0.44%. An increase in residential property price volatility increases revenue volatility by about 0.15–0.22%, whereas this effect diminishes to 0.11% in case of commercial property price. This evidence reflects the automatic increase of government revenue variability due to asset price movements and supports arguments in favour of adjusting fiscal variables for both business cycle and asset price changes. However, we also find evidence that equity price variability increases revenue variability even when government revenue is adjusted for both economic and asset price cycles, indicating the presence of more complicated dynamics between fiscal variables and asset price changes.

News Shocks and Asset Price Volatility in General Equilibrium

We study equity price volatility in general equilibrium with news shocks about future productivity and monetary policy. As West (1988) shows, in a partial equilibrium present discounted value model, news about the future cash flow reduces asset price volatility. We show that introducing news shocks in a canonical dynamic stochastic general equilibrium model may not reduce asset price volatility under plausible parameter assumptions. This is because, in general equilibrium, the asset cash flow itself may be affected by the introduction of news shocks. In addition, we show that neglecting to account for policy news shocks (e.g., policy announcements) can potentially bias empirical estimates of the impact of monetary policy shocks on asset prices.

Fiscal policy and asset price volatility

This paper investigates the relationship between volatility of different asset prices and the volatility of various indicators of fiscal policy (primary balance, spending and revenue). We find evidence that asset price volatility affects the volatility of fiscal policy stance in a positive and significant way. The effect comes primarily through residential property and equity price volatility on government revenue and spending. Increased volatility in commercial property prices is associated with increased variability of government revenue. Output growth volatility is the dominant determinant of revenue and primary balance variability, whereas bad budgetary conditions and the size of the public sector are the most significant determinants of spending variability. Trade openness leads to greater variability of government spending, revenue and primary balance to GDP ratios.

Asset price volatility and government revenue

This paper investigates the effect of commercial, residential property and equity price volatility on the variability of cyclically adjusted government revenue. We find significant evidence that asset price volatility increases the variability of government revenue. A 1 percent increase in equity price volatility increases government revenue variability by 0.37-0.44 percent. An increase in residential property price volatility increases revenue volatility by about 0.15-0.22 percent, whereas this effect diminishes to 0.11 percent in case of commercial property price. This evidence reflects the automatic increase of government revenue variability due to asset price movements and supports arguments in favour of adjusting fiscal variables for both business cycle and asset price changes. However, we also find evidence that equity price variability increases revenue variability even when government revenue is adjusted for both economic and asset price cycles, indicating the presence of more complicated dynamics between fiscal variables and asset price changes.

New Shocks and Asset Price Volatility in General Equilibrium

We study equity price volatility in general equilibrium with news shocks about future productivity and monetary policy. As West (1988) shows, in a partial equilibrium present discounted value model, news about the future cash flow reduces asset price volatility. We show that introducing news shocks in a canonical dynamic stochastic general equilibrium model may not reduce asset price volatility under plausible parameter assumptions. This is because, in general equilibrium, the asset cash flow itself may be affected by the introduction of news shocks. In addition, we show that neglecting to account for policy news shocks (e.g., policy announcements) can potentially bias empirical estimates of the impact of monetary policy shocks on asset prices.

The Effect of Asset Price Volatility on Fiscal Policy Outcomes

This paper examines the effect of asset price volatility on fiscal policy stance. We find that asset price volatility affects the volatility of discretionary fiscal policy in a positive and significant manner, which according to Fatas and Mihov (2003) has negative repercussions on output volatility and economic growth. Higher residential property price volatility amplifies both the volatility of government spending and the volatility of the discretionary fiscal policy stance. Equity price volatility increases the volatility of the fiscal policy stance, primarily via the government revenue channel.

Can Bank Supervisors Rely on Market Data? A Critical Assessment from a Swiss Perspective

Summary Market data, such as bond spreads or equity price volatility, are a complementary source to bank supervisory information. In Switzerland, meaningful market data are available for a number of banks which constitute a major part of the banking system. Notwithstanding some limitations (biases due to state guarantee for cantonal banks and potential ‘too-big-to-fail’ expectations for big banks) these market data are likely to play a supervisory role in the future. However, once the market expects supervisors to react to market data, these data become endogenous. This may jeopardize the very potential of market data to serve as policy guides.

Order Book Slope and Price Volatility

This paper investigates the information content of the limit order book in an order driven market, the Australian Stock Exchange (ASX). Specifically, we examine the informativeness of the order book slope in explaining the equity price volatility. By utilizing the order book slope as a proxy for the Difference of Opinion (DO), we document the following. Firstly, we find a negative contemporaneous relation between the order book slope and the price volatility for the constituent stocks of the ASX S&P20 index over the period between 1 July 2005 and 30 June 2006. Secondly, we observe that a decrease in the order book slope has a significantly larger impact on volatility than an increase in the order book slope. Next, our results provide supportive evidence for the informativeness of the order book slope to predict the future price volatility (especially the permanent component). Finally, we document that the removal of broker IDs in the ASX has little impact on the predictive power of the order book slope on the future volatility.

Asset Mispricing Due to Cognitive Dissonance

The behavior of equity prices is analyzed in a general equilibrium model where agents have preferences not only over consumption but also (implicitly) over their beliefs. To alleviate cognitive dissonance, investors endogenously choose to ignore information that conflicts too much with their ex ante expectations. Depending on the new information that is released, systematic overvaluation and undervaluation of equity prices arise, as well as too much and too little equity price volatility. The distortion in the asset pricing process is closely related to the precision of the information.

Aggregate consumption spending, the stock market and asymmetric error correction

In this study, we show how changes in wealth resulting from unanticipated changes in the value of equity holdings begin a process whereby households alter consumption growth in order to close the gap between actual and target spending. Because of changing uncertainty or equity price volatility over the stock market cycle, we found the time path of this adjustment to exhibit near-random walk behaviour during stock market downturns. Conversely, during ‘boom’ periods, e.g. when the value of equities held by households was greater than the threshold, the growth in consumer spending was quick to eliminate the disparity between actual and target spending.

Aggregate consumption spending, the stock market and asymmetric error correction

In this study, we show how changes in wealth resulting from unanticipated changes in the value of equity holdings begin a process whereby households alter consumption growth in order to close the gap between actual and target spending. Because of changing uncertainty or equity price volatility over the stock market cycle, we found the time path of this adjustment to exhibit near-random walk behaviour during stock market downturns. Conversely, during ‘boom’ periods, e.g. when the value of equities held by households was greater than the threshold, the growth in consumer spending was quick to eliminate the disparity between actual and target spending.