Cross-sectional implications of dynamic asset pricing with stochastic volatility and ambiguity aversion

Building on recent research that highlights the importance of macroeconomic volatility and ambiguity aversion in explaining the dynamics of stock returns, in this paper we propose a dynamic asset pricing model that simultaneously accounts for stochastic macroeconomic volatility and ambiguity, assuming that investors deal with uncertainty about the mechanics of macroeconomic fluctuations using first-release consumption and revisions to aggregate consumption on vintage data. Our results show that the proposed model captures a large fraction of the cross-sectional variation of excess returns for a wide range of market anomaly portfolios. Furthermore, while the price of risk for ambiguity is positive and significant for the vast majority of assets under study, macroeconomic volatility yields ambiguous outcomes, although it significantly increases the explanatory power of the model for specific assets. Our results suggest that macroeconomic volatility and ambiguity complement each other in explaining the cross-sectional behavior of stock returns.     

股票价格低于每股净资产的影响因素分析——来自中国A股上市公司的经验证据

破净指股票价格跌破每股净资产,是股票价格与每股净资产关系的一种极端表现。本文以1 059家A股上市公司为样本,采用修正的Ohlson模型,分组对股价破净的影响因素进行研究。结果发现:对于业绩为正的非ST企业而言,公司规模大、上市时间早、机构投资者持股比例低的国有企业容易破净;ST企业的股票价格虽下跌,但其重组捷径和壳资源改变了投资者的预期,使ST企业不破净或较少破净。     

Impact of value-at-risk models on market stability

Financial institutions around the world use value-at-risk (VaR) models to manage their market risk and calculate their capital requirements under Basel Accords. VaR models, as any other risk management system, are meant to keep financial institutions out of trouble by, among other things, guiding investment decisions within established risk limits so that the viability of a business is not put unduly at risk in a sharp market downturn. However, some researchers have warned that the widespread use of VaR models creates negative externalities in financial markets, as it can feed market instability and result in what has been called endogenous risk, that is, risk caused and amplified by the system itself, rather than being the result of an exogenous shock. This paper aims at analyzing the potential of VaR systems to amplify market disturbances with an agent-based model of fundamentalist and technical traders which manage their risk with a simple VaR model and must reduce their positions when the risk of their portfolio goes above a given threshold. We analyse the impact of the widespread use of VaR systems on different financial instability indicators and confirm that VaR models may induce a particular price dynamics that rises market volatility. These dynamics, which we have called `VaR cycles’, take place when a sufficient number of traders reach their VaR limit and are forced to simultaneously reduce their portfolio; the reductions cause a sudden price movement, raise volatility and force even more traders to liquidate part of their positions. The model shows that market is more prone to suffer VaR cycles when investors use a short-term horizon to calculate asset volatility or a not-too-extreme value for their risk threshold.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

How Do Alphas and Betas Move? Uncertainty,Learning and Time Variation in Risk Loadings*

I employ a parsimonious model with learning, but without conditioning information, to extract time‐varying measures of market‐risk sensitivities, pricing errors and pricing uncertainty. The evolution of these quantities has interesting implications for macroeconomic dynamics. Parameters estimated for US equity portfolios display significant low‐frequency fluctuations, along patterns that change across size and book‐to‐market stocks. Time‐varying betas display superior predictive accuracy for returns against constant and rolling‐window OLS estimates. As to the relationship of betas with business‐cycle variables, value stocks’ betas move pro‐cyclically, unlike those of growth stocks. Investment growth, rather than consumption, predicts the betas of value and small‐firm portfolios.     

Valuation under imperfect information: Bayesian learning from the performance of the firm and the market

This paper develops a valuation model for a project or firm in the presence of uncertainty about the mean of the probability distribution of the cash flows generated by the project. Its major point is that in the presence of parameter uncertainty the value of the project is smaller than in the case where the mean cash flows is perfectly known. The second point is that when there is a known covariance between project cash flows and aggregate market cash flows investors can learn about the unknown mean cash flows by observing the market. This is referred to as ‘learning from the market’.     

Dynamic interaction of risk–return trade-offs between oil market and China’s stock market: An analysis from the risk preferences perspective

The risk–return trade-off refers to the compensation required by investors for bearing risks, which can be viewed as the risk preference of investors in a market. The current study investigates the dynamic interdependence of risk–return trade-offs between China’s stock market and the crude oil market from the perspective of risk preference of investors, which is designed to explore the transmission process of investors’ risk preference in both markets. Specifically, this study applies the time-varying parameter GARCH-M model, namely TVP-GARCH-M model, to characterize the time-dependent risk–return trade-offs (investors’ risk preferences) in the crude oil and China’s stock markets, then examines their relationship through Granger causality tests. Results show that a variation in risk preferences of the oil market investors can dramatically cause a variation in risk preferences of the Chinese stock market investors, while the risk preference of investors in the Chinese stock market does not lead to that in the crude oil market, which is in accordance with expectations. The dynamic effect of investors’ risk appetite in the crude oil market is further examined by the TVP-VAR model. The findings of this work suggest that there generally exists a positive impact of investors’ risk preference in the oil market and that the effect is time-varying to a greater degree during the short and medium term. Moreover, responses of the Chinese stock market investors’ risk preference were more significant during the 2008 financial crisis. Additionally, the empirical results remain robust when applying alternative crude oil prices and China’s stock prices.     

Heterogenous beliefs with sentiments and asset pricing

We present a dynamic equilibrium model with two irrational investors: an extrapolator and a contrarian, whose beliefs regarding the growth rate of dividend stream are biased by their sentiments. The key contribution is to connect two disagreements with the degree of irrationality of investors and to provide novel insights into the predictability of stock return. We show that the higher level of sentiment disagreement is, the more stock price is overvalued. However, the future stock price will decline because the extrapolator’s sentiment will cool down over time. Therefore, the sentiment disagreement negatively predicts future return. At the meanwhile, our model not only shows that the survey expectations about cashflows increase the variations in asset price and dampen the corresponding volatility, but also helps to explain the mixed results about the relationship between the investors’ belief dispersions and stock return predictability.     

Risk decomposition,estimation error,and naïve diversification

How to achieve adequate diversification is important in portfolio construction. Efficient markets should not reward an investor for taking on risk that can be diversified away. Hence, when minimizing risk exposure, investors need to measure what part of total portfolio risk is systematic and what part can be diversified away. I examine several methods for decomposing total portfolio risk into systematic and diversifiable components and then carry out simulations to compare cross-sectional distributions of estimated and true risk as number of stocks increases in portfolios constructed using naïve diversification. Ordinary least squares estimators of diversifiable risk are relatively robust, and their cross-sectional distributions closely track the cross-sectional distributions of the corresponding true diversifiable risk. Other proposed estimators of diversifiable risk as well as all estimators of systematic risk have cross-sectional dispersion much greater than the corresponding true risk although, with one exception, bias is small. Results are relatively robust to the choice of method for generating market returns and to the underlying asset pricing model but not to random security betas. The simulation analysis also shows that risk and magnitude of shocks due to diversifiable risk are not negligible, even for 300-stock portfolios.     

Asset price volatility and banks

This paper examines the operation of Diamond–Dybvig banks when depositors have access to the asset market. Previous studies have shown that banks are redundant in this environment since it is impossible to prevent the strategic withdrawals. This paper shows that the strategic withdrawals can be prevented if the market risk, due to asset price volatility, is considered. Banks provide deterministic returns to the depositors since the aggregate withdrawals are predictable, and therefore, banks can choose the portfolio such that no asset liquidation is involved. However, an individual consumer with stochastic liquidity need is vulnerable to the price volatility if he holds the asset directly. Therefore, banks improve the consumers’ welfare by providing the insurance against not only the liquidity shock but also the market risk. Banks are not redundant.     

Aggregate stock market behavior and investors’ low risk aversion

This paper studies whether investors’ high risk aversion can be avoided in a representative-agent model that is able to explain aggregate stock market behavior in the US financial market. We present a consumption-based asset pricing model with a representative agent who has a ‘catching up with the Joneses’ preference to show that high risk aversion can be avoided in a representative-agent model that can help explain many of the empirically observed properties of the aggregate stock market return, including the equity premium and risk-free rate puzzles, the predictability of long-horizon stock returns, and the ‘leverage effect’ in return volatility.     

LONG‐RUN RISKS IN THE TERM STRUCTURE OF INTEREST RATES: ESTIMATION

This paper estimates a model in which persistent fluctuations in expected consumption growth, expected inflation, and their time‐varying volatility determine asset price variation. The model features Epstein–Zin recursive preferences, which determine the market price of macro risk factors. Analysis of the US nominal term structure data from 1953 to 2006 shows that agents dislike high uncertainty and demand compensation for volatility risks. Also, the time variation of the term premium is driven by the compensation for inflation volatility risk, which is distinct from consumption volatility risk. The central role of inflation volatility risk in explaining the time‐varying term premium is consistent with other empirical evidence including survey data. In contrast, the existing long‐run risks literature emphasizes consumption volatility risk and ignores inflation‐specific time‐varying volatility. The estimation results of this paper suggest that inflation‐specific volatility risk is essential for fitting the time series of the US nominal term structure data. Copyright © 2012 John Wiley & Sons, Ltd.     

Regulatory risk, market uncertainties, and firm financing choices: Evidence from U.S. Electricity Market Restructuring

Based on the universe of rate-regulated electric utilities in the U.S., we examine why firms alter their financing decisions when transitioning from a regulated to a competitive market regime. We find that the significant increase in regulatory risk after the passage of the Energy Policy Act, state-level restructuring legislations, and divestiture policies have reduced leverage by 15 percent. Policies that encouraged competition, and hence increased market uncertainty, lowered leverage by another 13 percent on average. The ability to exercise market power allowed some firms to counter this competitive threat. In aggregate, regulatory risk and market uncertainty variables reduce leverage between 24.6 and 26.7 percent. We also confirm findings in the literature that firms with higher profitability and higher asset growth have lower leverage, and those with more tangible assets are more levered. Firms with greater access to internal capital markets and those with a footloose customer segment use less debt, while those actively involved in trading power in the wholesale market use more debt.     

Cost of equity for Canadian and U.S. sectors

A two-stage CAPM approach is used to generate cost-of-equity estimates and sources of their uncertainty for 10 GICS sectors in Canada and the U.S. under the assumption of relatively integrated North American economies and equity markets. The estimated cost of equity for the Canadian sectors is, on average, about the same as that of the U.S. sectors, but with a higher estimation error. The estimation error of the market risk premium is the most important uncertainty component for the equity cost estimates, except for Canadian Utilities where beta uncertainty is the most important component. Beta and interaction effects play a relatively more important role in Canada due to relatively more volatile sector betas in Canada. Our study suggests that: (1) Canadian cost of equity should be estimated in an integrated market rather than a segmented market and (2) higher importance should be given to estimating the dynamics of betas for the Canadian sectors.     

Retail investors’ trading and stock market liquidity

The paper investigates the relation between retail investors’ participation in trading and aggregate stock market liquidity. The findings show a positive and significant relation between retail investors’ trading and stock market liquidity. Examination of the determinants of retail investors’ trading reveals that, on average, retail investors with more diversified trading activity tend to trade when liquidity is higher, the frequency of their arrival to the market is not affected by the level of liquidity, and retail investors are willing to trade at a lower liquidity level as sellers than as buyers. Moreover, retail investors’ trading does not create price noise at the aggregate market level. Overall, the evidence suggests that retail investors contribute to market quality.     

Economic policy uncertainty and stock market sector time-varying spillover effect: Evidence from China

This paper investigates the volatility spillover effect among the Chinese economic policy uncertainty index, stock markets, gold and oil by employing the time-varying parameter vector autoregressive (TVP-VAR) model. Three main results are obtained. Firstly, the optional consumption, industry, public utility and financial sectors are systemically important during the sample period. Secondly, among the four policy uncertainties, the uncertainty of fiscal policy and trade policy contributes more to the spillover effect, while the uncertainty of monetary policy and exchange rate policy contributes less to the spillover effect. Thirdly, during COVID-19, oil spillovers from other sources dropped rapidly to a very low point, it also had a significant impact on the net volatility spillover of the stock market. This paper can provide policy implication for decision-makers and reasonable risk aversion methods for investors.     

Uncertainty-driven labor market fluctuations

This paper explores uncertainty shocks as a driving force in a search and matching model of the labor market. Uncertainty takes the form of a noisy component in a firm׳s initial signal about job productivity. Greater uncertainty dampens job creation by increasing the risk of making the costly mistake of investing in jobs that will turn out to be unprofitable. Thus, uncertainty shocks can cause labor market downturns: lower vacancy rates, lower job-finding rates, and higher unemployment. Numerical simulations examine the level of volatility and the cross-correlations and autocorrelations of key U.S. labor market indicators that result from fluctuations driven by changes in uncertainty.     

What drives dynamic connectedness of the U.S equity sectors during different business cycles?

The study investigates (i) the time-varying and directional connectedness of nine equity sectors through intra- and inter-sector volatility spillover periods and (ii) assesses the impact of state variables on aggregate volatility spillovers. The study finds about 76% of volatility linkage is associated with cross-sector volatility transmissions. Aggressive sectors, which are sensitive to macroeconomic risk, play the net volatility transmission role. Defensive sectors that are largely immune to macroeconomic risk play the net volatility receiving role. The intensity and direction of volatility transmissions among the sectors vary with economic expansion and recession periods. Over time, some sectors switching from net transmitting to net receiving role and vice versa. Macro and financial market uncertainty variables significantly impact volatility spillover at lower volatility spillover (economic expansion period) and higher volatility (economic recession periods) volatility spillover quantiles. Political signals are seemingly more imprecise and uninformative during economic expansion or low quantiles, intensifying volatility spillover. Overall, the causal effects of macro, financial, and policy uncertainty variables on aggregate volatility spillover are asymmetric, nonlinear, and time-varying. The study's result supports the cross-hedging and financial contagion views of volatility transmission across nine US equity sectors.     

Heterogeneous relationship between IPO return and risk across idiosyncratic variance characteristics

This paper analyzes the levels and changes in the post-IPO stock return volatility and provides insights into market responses to the presence of firm-specific risk. First, we document a negative relation between initial idiosyncratic volatility level and the post-IPO volatility change in that initially low volatility firms have more volatility increase and vice verse. This evidence suggests fundamental firm-specific changes after the IPO. Further, we find that underpricing and short-run post-IPO returns are positively related to the initial and corresponding idiosyncratic risk level. This finding suggests that underpricing compensates investors for acquiring costly information and firm-specific risk information is being incorporated into offer prices. Finally, we find that higher long-run post-IPO performance is related to both lower initial risk level and decreasing risk in the first year after the IPO.     

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.