Day-of-the-week effect on the VIX. A parsimonious representation

The study of significant deterministic seasonal patterns in financial asset returns is of high importance to academia and investors. This paper analyzes the presence of seasonal daily patterns in the VIX and S&P 500 returns series using a trigonometric specification. First, we show that, given the isomorphism between the trigonometrical and alternative seasonality representations (i.e., daily dummies), it is possible to test daily seasonal patterns by employing a trigonometrical representation based on a finite sum of weighted sines and cosines. We find a potential evolutive seasonal pattern in the daily VIX that is not in the daily S&P 500 log-returns series. In particular, we find an inverted Monday effect in the VIX level and changes in the VIX, and a U-shaped seasonal pattern in the changes in the VIX when we control for outliers. The trigonometrical representation is more robust to outliers than the one commonly used by literature, but it is not immune to them. Finally, we do not find a day-of-the-week effect in S&P 500 returns series, which suggests the presence of a deterministic seasonal pattern in the relation between VIX and S&P 500 returns.     

Some empirical evidence on the effects of U.S. monetary policy shocks on cross exchange rates

This paper examines the impact of U.S. monetary policy shocks on the cross exchange rates of sterling, yen and mark. The main finding of the paper is a ‘delayed overshooting’ pattern for all currency cross rates examined (sterling/yen, yen/mark and mark/sterling) following an unexpected U.S. monetary policy change, which in turn generates excess returns. We also provide evidence that the ‘delayed overshooting’ pattern in cross exchange rates is accompanied by asymmetric interventions by central banks in the foreign exchange markets under consideration triggered by a U.S. monetary policy shock.     

The day-of-the-week effect is weak: Evidence from the European real estate sector

The day-of-the-week effect for the securitized real estate indices is investigated by employing daily data at the global, European and country level for the period 1990 to 2010. We test for daily seasonality in 12 countries using both full sample and rolling-regression techniques. While the evidence for the former is in line with the literature, the results for the latter cast severe doubts concerning the existence of any persistent day-of-the-week effects. Once we allow our sample to vary over time, the average proportion of significant coefficients per day ranges between 15 % and 24 %. We show that higher average Friday returns evident in previous literature, remain significant in 21 % of the rolling samples. We conclude that daily seasonality in the European Real Estate sector is subject to the data mining and sample selection bias criticism.     

Seasonality and momentum across national equity markets

This paper examines seasonality and momentum jointly across national equity markets at the index level. We find that seasonality and momentum are almost uncorrelated and appear to arise from different global or local risk factors, rather than from different loadings on the same risk factors. Employing a trading strategy that integrates seasonality and momentum parametrically, we confirm our conclusion about the relationship between seasonality and momentum: while the pure seasonality and momentum strategies individually generate sizable and significant returns, the combination strategy significantly outperforms the pure strategies in a way that is quantitatively consistent with their lack of correlation.     

Model‐free evaluation of directional predictability in foreign exchange markets

We examine directional predictability in foreign exchange markets using a model‐free statistical evaluation procedure. Based on a sample of foreign exchange spot rates and futures prices in six major currencies, we document strong evidence that the directions of foreign exchange returns are predictable not only by the past history of foreign exchange returns, but also the past history of interest rate differentials, suggesting that the latter can be a useful predictor of the directions of future foreign exchange rates. This evidence becomes stronger when the direction of larger changes is considered. We further document that despite the weak conditional mean dynamics of foreign exchange returns, directional predictability can be explained by strong dependence derived from higher‐order conditional moments such as the volatility, skewness and kurtosis of past foreign exchange returns. Moreover, the conditional mean dynamics of interest rate differentials contributes significantly to directional predictability. We also examine the co‐movements between two foreign exchange rates, particularly the co‐movements of joint large changes. There exists strong evidence that the directions of joint changes are predictable using past foreign exchange returns and interest rate differentials. Furthermore, both individual currency returns and interest rate differentials are also useful in predicting the directions of joint changes. Several sources can explain this directional predictability of joint changes, including the level and volatility of underlying currency returns. Copyright © 2007 John Wiley & Sons, Ltd.     

A note on stock market seasonality: The impact of stock price volatility on the application of dummy variable regression model

This article provides both statistical analysis and empirical evidence that the dummy variable regression models extensively employed in the market seasonality literature may wind-up misleading results. We show that the estimates of the said model tend to reject the null hypothesis incorrectly once the stock returns exhibit higher volatility for the specified period under examination. Our empirical results suggest that the so-called “January effect” could be attributed to the application of inappropriate statistical method.     

Demographics and the long-horizon returns of dividend-yield strategies

This paper investigates the relationship between demographic changes and the long-run returns of dividend-yield investment strategies. We hypothesise that in a world where components of wealth are mentally treated as being non-fungible, the preference for high dividend-paying stocks by older investors means that the excess returns of high dividend-yielding stocks, relative to other stocks, should be positively related to demographic clientele variation. In particular, we find that, consistent with the behavioural life-cycle hypothesis, long-run returns of dividend-yield investment strategies are positively driven by changes in the proportion of the older population. Our results are robust when controlled for the Fama–French factors, inflation rate, consumption growth rate, interest rates, tax clienteles, time trend and alternative definitions of both dividend-yield strategies and demographic variation.     

Do interest rate options contain information about excess returns?

There is strong empirical evidence that long-term interest rates contain a time-varying risk premium. Options may contain valuable information about this risk premium because their prices are sensitive to the underlying interest rates. We use the joint time series of swap rates and interest rate option prices to estimate dynamic term structure models. The risk premiums that we estimate using option prices are better able to predict excess returns for long-term swaps over short-term swaps. Moreover, in contrast to the previous literature, the most successful models for predicting excess returns have risk factors with stochastic volatility. We also show that the stochastic volatility models we estimate using option prices match the failure of the expectations hypothesis.     

Asymmetric volatility spillover in the Tokyo stock exchange

This paper examines volatility transfers between size-based stock indexes from the Tokyo Stock Exchange. We use a bivariate EGARCH model to test for volatility spillover effects between large- and small-cap stock indexes. We find an asymmetric volatility spillover from large-cap stock returns to small-cap returns, but not vice versa. We also find a small-firm January effect, but not a June seasonality, in either large-and small-cap stock returns. Instead, we find that the conditional correlation between large- and small-cap indexes is time-varying, showing a tendency to increase during the month of June.(JEL G12, G15)     

Price gap anomaly in the US stock market: The whole story

This paper analyses the price gap anomaly in the US stock market (comprised of the DJI, S&P 500 and NASDAQ) covering the period 1928 to 2018. This paper aims to investigate whether or not price gaps create market inefficiencies. Price gaps occur when the current day’s opening price is different from the previous day’s closing price due orders placed before the opening of the market. Several hypotheses are tested using various statistical tests (Student’s t-test, ANOVA, Mann-Whitney test), regression analysis, and special methods, that is, the modified cumulative returns and the trading simulation approaches. We find strong evidence in favour of abnormal price movements after price gaps. We observe that during a gap day prices tend to change in the direction of the gap. A trading strategy based on this anomaly was efficient in that its results were not random, indicating that this market was not efficient. The momentum effect was found to be temporary and no evidence of seasonality in price gaps was found. Lastly, our results were also contrary to the myth that price gaps tend to get filled.     

我国旅游季节性规律的探索性研究——以北京、上海、云南、四川、福建、海南为例

旅游季节性作为一种明显但又可控性较差的旅游现象,受到国内外学界的广泛关注.我国受休假政策的影响,季节性表现的更加明显.目前由于统计数据的缺乏和不完整,国内对于我国季节性规律的整体性规律及大尺度、省际间的旅游季节性对比研究还比较少.本文首先从传统旅游人次及收入之外的全国宏观交通数据入手,试图分析我国整体性的旅游季节性分布规律.其次,基于面板数据的可得性,利用衡量旅游季节性集中性、强度、不均衡性的月度指数、季节性强度指数及基尼系数等一系列指标,分析各省市旅游季节性特点及淡旺季分布;从时空两个维度上对五个省市的旅游季节性进行对比,试图对我国旅游季节性规律做探索性研究.     

The persistence of the small firm/January effect: Is it consistent with investors’ learning and arbitrage efforts?

Using improved methodology and an expanded research design, we examine whether the small firm/January effect (Keim, D. B. (1983). Size-related anomalies and stock return seasonality: further empirical evidence. Journal of Financial Economics 12:13–32), is declining over time due to market efficiency. First, we find that January returns are smaller after 1963–1979, but have simply reverted to levels that existed before that time. Second, we show that the January effect is not limited to mature markets but also appears in firms trading on the relatively new NASDAQ exchange in the 1970s. Third, trading volume for small firms in December and January is not different from other months, implying that traders are not actively arbitraging the anomaly. Together, our results suggest that this anomaly continues to defy rational explanation in an efficient market.     

Risk sharing and counter-cyclical variation in market correlations

I present a consumption-based dynamic asset pricing model in which international market correlations vary counter-cyclically over time. The driving force in the model is the time-varying effective risk aversion induced by external habit formation. Market returns are driven by fundamental outputs and discount rates. When risk aversion is high, the effect of discount rates on market returns rises with the market price of risk. To the extent that countries share risk, the cross-country correlation of discount rates exceeds the cross-country correlation of fundamental outputs. In bad times, market correlations rise as returns are mostly driven by discount rates. Thus, consistent with the empirical evidence, periods of high risk aversion are associated with high market correlations and high market volatility. After calibration, my model is consistent with the observed variation in market correlations, as well as other features of asset prices including the equity premium and market volatility.     

Order imbalance and stock returns: Evidence from China

We investigate the relation between daily order imbalance and return in the Chinese stock markets of Shenzhen and Shanghai. Prior studies have found that daily order imbalance is predictive of subsequent returns. On the two Chinese exchanges we find the autocorrelation in order imbalances is similar to that of the New York Stock Exchange as reported by Chordia and Subrahmanyam [Chordia, T., & Subrahmanyam, A. (2004). Order imbalance and individual stock returns: Theory and evidence. Journal of Financial Economics, 72, 485–518]. We also find a strong contemporaneous relation between daily order imbalances and returns. However, we do not find evidence that order imbalances predict subsequent returns. We attribute the difference in predicative power to differences in trading mechanisms on the two exchanges and to differences in the share turnover rates.     

The maturity structure of term premia with time-varying expected returns

This paper analyzes the maturity structure of term premia using McCulloch’s US Treasury yield curve data from 1953–91, allowing expected returns to vary across time. One, 3, 6, and 12 month holding period returns on maturities up to 5 years are projected on 3 ex ante variables to compute time-varying expected returns, and simulations are employed to generate distributions of conditionally expected return premia. The likelihood of expected returns monotonically increasing in maturity (as implied by the liquidity preference hypothesis) is relatively high when the yield curve is steep and interest rates are high, and with longer holding periods, but low in other cases. The hypothesis that intermediate maturity bonds have the highest expected returns (a “hump-shaped” maturity-return pattern) around the onset of recessions does not receive much support.     

On the predictability of the distribution of excess returns in currency markets

This paper investigates the predictability of foreign exchange (FX) volatility and liquidity risk factors on returns to the carry trade, an investment strategy that borrows in currencies with low interest rates and invests in currencies with high interest rates. Previous studies have suggested that this predictability could have been spuriously accounted for due to the persistence of the predictors. The analysis uses a predictive quantile regression model developed by Lee (2016) that allows for persistent predictors. We find that predictability changes remarkably across the entire distribution of currency excess returns. Predictability weakens substantially in the left tail once persistence is accounted for, implying a moderate negative predictive relation between FX volatility risk and carry trade returns. By contrast, it becomes stronger in the right tail. Furthermore, we provide evidence that FX volatility risk still dominates liquidity risk after controlling for persistence. These findings suggest that the persistence of the predictors needs to be taken into account when one measures predictability in currency markets. Finally, out-of-sample forecast performance is also presented.     

The productivity effects of employee ownership within command economies: Evidence from Poland

The effects of employee ownership, broadly defined, are estimated for a sample of Polish producer co-operatives in three industries during 1976-8, i.e. when Poland was a centrally planned economy. The results indicate that, in general, increasing either worker participation in control and/or in economic returns provides positive effects on productivity. The pattern of the different effects of employee ownership varies significantly across sectors. This new evidence strongly suggests that workers within Soviet-type economies are responsive to economic incentives. Together with existing theoretical and empirical evidence for both Eastern and Western European firms, the findings suggest a larger role for employee ownership than typically either currently exists or that is under serious consideration in most restructuring economies.     

Differentiating employment prospects by industry and returns to job search in metropolitan areas

The role of differentiating employment prospects by the industry of the employer in the job seeker's calculation of the returns to search is analyzed. It is demonstrated that returns to search can vary systematically between metropolitan areas because of differing mixes of industry employment; it is argued that an increase in a measure of dispersion in the industry mix will tend to raise returns to job search. To test this hypothesis, cross sections of census data on unemployment rates of male experienced workers in each of the seven major occupational groups were analyzed. Statistically significant regression equations were obtained for three occupational groups (craftsmen, nonfarm laborers, and operatives); in all these cases the results supported the hypothesis of the paper.     

Crack spread option pricing with copulas

A copula-based approach for pricing crack spread options is described. Crack spread options are currently priced assuming joint normal distributions of returns and linear dependence. Statistical evidence indicates that these assumptions are at odds with the empirical data. Furthermore, the unique features of energy commodities, such as mean reversion and seasonality, are ignored in standard models. We develop two copula-based crack spread option models using a simulation approach that address these gaps. Our results indicate that the Gumbel copula and standard models (binomial, and Kirk and Aron (1995)) mis-price a crack spread option and that the Clayton model is more appropriate. We contribute to the energy derivatives literature by illustrating the application of copula models to the pricing of a heating oil–crude oil “crack” spread option.     

Risk premia and seasonality in commodity futures

We develop and estimate a multifactor affine model of commodity futures that allows for stochastic seasonality. We document the existence of stochastic seasonal fluctuations in commodity futures and that properly accounting for the cost‐of‐carry curve requires at least three factors. We estimate the model using data on heating oil futures and analyze the contribution of the factors to risk premia. Correctly specifying seasonality as stochastic is important to avoid erroneously assigning those fluctuations to other risk factors. We also estimate a nonlinear version of the model that imposes the zero lower bound on interest rates and find similar results.