Is idiosyncratic volatility priced in cryptocurrency markets?

This paper investigates how idiosyncratic volatility is priced in the cross-section of cryptocurrency returns. By conducting both portfolio-level analysis and Fama-MacBeth regression analysis, we demonstrate that idiosyncratic volatility is positively related to the expected returns of cryptocurrencies. This finding is not subsumed by effects of size, momentum, liquidity, volume, and price and is robust to different weighting schemes, holding periods, and sample sizes. Besides, we find no evidence of temporal relation between idiosyncratic volatility and returns in cryptocurrency markets.     

Is idiosyncratic volatility priced in commodity futures markets?

This article investigates the relationship between expected returns and past idiosyncratic volatility in commodity futures markets. Measuring the idiosyncratic volatility of 27 commodity futures contracts with traditional pricing models that fail to account for backwardation and contango leads to the puzzling finding that idiosyncratic volatility is significantly negatively priced cross-sectionally. However, idiosyncratic volatility is not priced when the phases of backwardation and contango are suitably factored in the pricing model. A time-series portfolio analysis similarly suggests that failing to recognize the fundamental risk associated with the inexorable phases of backwardation and contango leads to overstated profitability of the idiosyncratic volatility mimicking portfolios.     

Are regime-shift sources of risk priced in the market?

In this paper we develop a discrete-time pricing model for European options where the log-return of the underlying asset is subject to discontinuous regime shifts in its mean and/or volatility which follow a Markov chain. The model allows for multiple regime shifts whose risk cannot be hedge out and thus must be priced in option market. The paper provides estimates of the price of regime-shift risk coefficients based on a joint estimation procedure of the Markov regime-switching process of the underlying stock and the suggested option pricing model. The results of the paper indicate that bull-to-bear and bear-to-crash regime shifts carry substantial prices of risk. Risk averse investors in the markets price these regime shifts by assigning higher transition (switching) probabilities to them under the risk neutral probability measure than under the physical. Ignoring these sources of risk will lead to substantial option pricing errors. In addition, the paper shows that investors also price reverse regime shifts, like the crash-to-bear and bear-to-bull ones, by assigning smaller transition probabilities under the risk neutral measure than the physical. Finally, the paper evaluates the pricing performance of the model and indicates that it can be successfully employed, in practice, to price European options.     

Is information risk priced? Evidence from abnormal idiosyncratic volatility

We propose a new, price-based measure of information risk called abnormal idiosyncratic volatility (AIV) that captures information asymmetry faced by uninformed investors. AIV is the idiosyncratic volatility prior to information events in excess of normal levels. Using earnings announcements as information events, we show that AIV is positively associated with informed return run-ups, abnormal insider trading, short selling, and institutional trading during pre-earnings-announcement periods. We find that stocks with high AIV earn economically and statistically larger future returns than stocks with low AIV. Taken together, our findings support the notion that information risk is priced.     

Are extreme returns priced in the stock market? European evidence

This paper revisits some recently found evidence in the literature on the cross-section of stock returns for a carefully constructed dataset of euro area stocks. First, we confirm recent results for US data and find evidence of a negative cross-sectional relation between extreme positive returns and average returns after controlling for characteristics such as momentum, book-to-market, size, liquidity and short term return reversal. We argue that this is the case because these stocks have lottery-like characteristics, which is attractive to certain investors. Also, these stocks tend to be very volatile so that arbitrageurs are discouraged from correcting potential mispricing. As a consequence, these stocks are often overpriced and hence face lower expected returns. Second, when we control for extreme returns, the recently found negative relationship between idiosyncratic risk and future returns is less robust. In our models, after adding maximum returns, the relationship is insignificant and sometimes even positive. We also find that idiosyncratic skewness and coskewness play an important role for asset pricing, as predicted by several theoretical models.     

Is consumption risk priced in the stock market?

The paper examines whether the risk in the consumption of stockholders caused by incomplete consumption insurance is priced in the cross-section of average stock returns. Using Taylor series expansion of the average marginal utility of consumption, we show that the risk in the consumption of stock market participants can be decomposed into two components, insurable (hedgeable using financial assets) and uninsurable (caused by incomplete consumption insurance) consumption risks. We argue that the growth rate of average consumption may be viewed as a proxy for the insurable component of consumption risk, while the growth rates of the rescaled higher-order cross-sectional consumption distribution moments may be regarded as a multivariate proxy for uninsurable risk in consumption. Exploiting microlevel household quarterly consumption data from the US Consumer Expenditure Survey, we find that both components of consumption risk are significantly priced when the limited stock market participation is taken into account. Neither the insurable and uninsurable components of consumption risk nor the Fama–French risk factors are rejected as capturing important components of systematic risk when tested against each other in an integrated multifactor asset pricing model.     

Is idiosyncratic asymmetry priced in commodity futures?

In this article, we use a recently introduced asymmetry measure, IE, to measure the idiosyncratic asymmetry of commodity futures returns and find that idiosyncratic asymmetry negatively and significantly predicts commodity futures returns cross sectionally. Furthermore, we find that a long–short trading strategy based on idiosyncratic asymmetry generates significant abnormal returns, which cannot be explained by traditional risk factors in commodity futures and persists up to 12 months. Moreover, idiosyncratic asymmetry appears to be a priced factor in commodity futures with significant risk premium. Finally, we confirm that IE is better at capturing the pricing effect of idiosyncratic asymmetry than the traditional skewness measure.     

How is illiquidity priced in the Chinese stock market?

This study investigates the liquidity premium in the Chinese stock market. We found that the expected stock returns increase monotonically with the quintile sort on characteristic liquidity with descending patterns. The characteristic liquidity premium ranges from 0.82% to 1.28% per month, which is much higher than that of their US counterparts. Moreover, our multivariate decomposition approach highlights that characteristic illiquidity premiums can be explained mainly by size, idiosyncratic volatility and momentum. The net systematic liquidity premium reaches 0.84% per month, driven mainly by commonality beta. The finding shows that a liquidity-based strategy forecasts cross-section and time-series expected returns.     

What drives volatility persistence in the foreign exchange market?

We propose a new empirical specification of volatility that links volatility to the information flow, measured as the order flow in the market, and to the price sensitivity to that information. The time-varying market sensitivity to information is estimated from high-frequency data, and movements in volatility can therefore be directly related to movements in order flow and market sensitivity. Empirically, the model explains a large share of the long-run variation in volatility. Importantly, the time variation in the market's sensitivity to information is at least as relevant in explaining the persistence of volatility as the rate of information arrival itself. This may be evidence of a link between changes over time in the aggregate behavior of market participants and the time-series properties of realized volatility.     

Does the weather affect stock market volatility?

This paper investigates the empirical association between stock market volatility and investor mood-proxies related to the weather (cloudiness, temperature and precipitation) and the environment (nighttime length). Overall, our results suggest that cloudiness and length of nighttime are inversely related to historical, implied and realized measures of volatility. The strength of association seems to vary with the location of an exchange on Earth with respect to the equator. Weather deviations from seasonal norms and dummies representing extreme weather conditions do not offer additional explanatory power in our datasets.     

Where are the sources of stock market mispricing and excess volatility?

Using a simple dividend model, we illustrate and synthesize the sources of stock market mispricing and excess volatility based upon two hypotheses—inflation illusion and heterogeneous beliefs. Our theoretical framework posits that equity mispricing arises when investors have subjective expectations about discount rates or dividend growth rates. We then analyze the sources of equity mispricing and market excess volatility under a VAR framework. Empirically, we find that both inflation illusion and heterogeneous beliefs explain equity mispricing. However, heterogeneous beliefs play a more important role in explaining stock mispricing in the long run. We also find that heterogeneous beliefs cause excess volatility, but inflation illusion does not. Therefore, dispersion in investors’ beliefs is a better explanation of stock market mispricing than the investors’ inability to properly discount future cash flows.     

Do liquidity and idiosyncratic risk matter? Evidence from the European mutual fund market

This paper examines the interaction of idiosyncratic risk, liquidity and return across time in determining fund performance, as well as across investment style portfolios of European mutual funds. This study utilizes a unique data set including returns for equity mutual funds registered in six European countries. Overall, using monthly data, we find that both liquidity and idiosyncratic risk are relevant in determining mutual fund returns. Our results are robust across different model specifications. We show that model specifications up to six factors are useful as these risk factors capture different aspects in the cross-section of mutual funds returns. The evidence regarding mutual funds subgroups is strongly in favor of the significance of liquidity, and idiosyncratic risk to a lesser extent, as risk factors. Even if liquidity and idiosyncratic risk are considered at the same time, one factor is not significantly decreasing the importance of the other factor.     

Does knowing the volatility states affect the market risk premium?

Mayfield (J Financ Econ 73:465–496, 2004) has devised a method for estimating the market risk premium, based on a variant of Merton’s ICAPM wherein volatility is specified as a two-state Markov process. In this study, we assess Mayfield’s key assumption that investors know the current volatility state with certainty, via empirical testing of the assumption of exogenous Markov-switching in Mayfield’s model. We detect strong evidence of endogenous switching. This indicates that investors infer the current volatility state, as opposed to simply observing it. We also find that the risk premium estimates are affected by the switching type.     

Are capital controls in the foreign exchange market effective?

One of the reasons for governments to employ capital controls is to obtain some degree of monetary independence. In this paper we test whether capital controls can reduce the link between exchange rates fluctuations and cross border interest differentials. Recent capital control proxies are used in order to determine the date of capital account liberalization for a panel of Western European and emerging countries. Results show that capital controls have a very limited effect on observed deviations from interest parities, even when accounting for the political risk associated with capital controls.     

Are there arbitrage gaps in the UK gilt strips market?

Evidence in financial markets of an opportunity for pure arbitrage, and therefore a violation of the law of one price, is considered an anomaly to be noted. This paper reports an apparent violation of the law of one price between UK government gilts and their separately traded principal and coupon strips over a sample period of nearly 14 years. There are persistent price differences, and hence opportunities for arbitrage, after allowance for the bid-ask spread; the strips package tends to be overpriced in relation to the corresponding gilt. The price differences may, in part, be due to a lack of liquidity and stale prices in the strips market.     

Can tail risk explain size,book‐to‐market,momentum, and idiosyncratic volatility anomalies?

We examine the impact of tail risk on the return dynamics of size, book‐to‐market ratio, momentum and idiosyncratic volatility sorted portfolios. Our time‐series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value, high idiosyncratic volatility and low momentum stocks exhibit negative and statistically significant tail risk betas. Our cross‐sectional analyses at the individual stock level suggest that tail risk helps in explaining the four pricing anomalies, particularly size and idiosyncratic volatility anomalies.     

A note on the time–series relationship between market industry concentration and market volatility

Using cross-sectional regression analysis, previous studies provide conflicting results regarding the relationship between market industry concentration and market volatility. This paper investigates this relationship in the time–series. Using data from twenty one developed markets and the world market, we find that this relationship is significant and positive in about 61% of the markets: the more concentrated the market, the more volatile the market. We also find that, in 70% of the markets, there exists a causal relationship between market industry concentration and market volatility and the direction of causality runs from the former to the latter. Our results suggest that market industrial structure is a significant factor in explaining market volatility.     

Is gold the best hedge and a safe haven under changing stock market volatility?

We evaluate the role of gold and other precious metals relative to volatility (Volatility Index (VIX)) as a hedge (negatively correlated with stocks) and safe haven (negatively correlated with stocks in extreme stock market declines) using data from the US stock market. Using daily data from November 1995 to November 2010, we find that gold, unlike other precious metals, serves as a hedge and a weak safe haven for US stock market. However, we find that VIX serves as a very strong hedge and a strong safe haven during our sample period. We also find that in periods of extremely low or high volatility, gold does not have a negative correlation with the US stock market. Our results show that VIX is a superior hedging tool and serves as a better safe haven than gold during our sample period. We highlight the practical significance of our results for financial market participants by conducting a portfolio analysis.     

Are conditional illiquidity risks priced in China? A cross-sectional test

In this study, we theoretically derive conditional illiquidity risks from the conditional liquidity-adjusted capital asset pricing model (CLCAPM) that we propose by incorporating funding illiquidity into the LCAPM, and we examine whether they are priced empirically in China's A-share market. We provide new evidence of the positive premiums of conditional illiquidity risks even after controlling for mispricing signals and sentiment. The finding suggests that conditional illiquidity risk could be an alternative channel to explain the cross-section of stock returns. Moreover, investors could obtain higher premiums as compensation for their tolerance of more highly conditional illiquidity risks during high market volatility (low market returns) periods.     

Are candlestick technical trading strategies profitable in the Japanese equity market?

We show that candlestick charting, the oldest known form of technical analysis, is not profitable in the Japanese equity market over the 1975–2004 period. Candlestick technical analysis, which was developed in Japan in the 1600s, is deeply intertwined with Japanese culture and is very popular in Japan. However, there is no evidence candlestick technical trading strategies add value in either the entire 30 year period, in three 10 year sub-periods or in bull or bear markets.