Lag Relationship Research Articles

Is Eurasian snow cover in October a reliable statistical predictor for the wintertime climate on the Iberian Peninsula?

ABSTRACTIn this study, the recently found lead–lag relationship between Eurasian snow cover increase in October and wintertime precipitation totals on the Iberian Peninsula is re‐visited and generalized to a broad range of atmospheric variables on the synoptic and local scale. To this aim, a robust (resistant to outliers) method for calculating the index value for Eurasian snow cover increase in October is proposed. This ‘Robust Snow Advance Index’ (RSAI) is positively correlated with the wintertime (DJF) frequency of cyclonic and westerly flow circulation types over the Iberian Peninsula, while the corresponding relationship with anticyclonic and easterly flow types is negative. For both cases, an explained variance of approximately 60% indicates a strong and highly significant statistical link on the synoptic scale.Consistent with these findings, it is then shown that the lead–lag relationship equally holds for the DJF‐mean conditions of (1) precipitation amount, (2) diurnal temperature range, (3) sun hours, (4) cloud cover and (5) wind speed on the local scale. To assess if these target variables can be skillfully hindcast, simple linear regression is applied as a statistical forecasting method, using the October RSAI as the only predictor variable. One‐year out cross‐validation yields locally significant hindcast correlations of up to approximately 0.8, obtaining field significance for any of the five target variables mentioned above. The validity for a wide range of atmospheric variables and the consistency of the local‐ and synoptic‐scale results affirm the question posed in the title.

A Closer Look at the U.S. Housing Market: Modeling Relationships among Regions

This article investigates the dynamic interactions among nine U.S. regional housing markets by estimating the multivariate cointegration model using both autoregressive (AR) and moving average (MA) representations over the period from 1975 to 2010. Long‐run results indicate that the extent of convergence among the regional housing markets substantially increased over time and more so after the housing bubble burst in the latter part of 2006. Common stochastic trend analysis reveals that the housing regions of New England, Mid‐Atlantic and the Pacific were the primary regional drivers that led the regions toward long‐run equilibrium during the 1975 to 2006 subperiod. Further analysis indicates that the relationships among the regions cannot be attributed to trends in two important macroeconomic fundamentals: regional per capita income and regional GDP. Finally, short‐run analysis reveals substantial lead lag relationships among all the markets.

Information Efficiency of U.S. Restaurant Stocks that are Cross-Listed in Germany

We study relationships between stock returns on U.S. and German exchanges for U.S. restaurant companies. Specifically, we examine whether information asymmetry affect how much stock returns in Germany lag stock returns of the same company on U.S. markets. German and U.S. investors differ in information access because of differing stock exchange listing requirements. Our main goals are to examine if (a) stock returns of U.S. underlying shares lead stock returns of cross-listed shares on the Open Market because of information asymmetry and (b) the lead–lag relationship is more evident among shares involuntarily cross-listed on the Open Market than securities voluntarily cross-listed on the EU Regulated Market because of differences in regulation in information disclosure. We estimated cross-autocorrelations using vector autoregressions and tested the hypotheses with the Wald test. The results, in general, support both hypotheses.

Speed of information adjustment in Indian stock indices

This study attempts to analyse the speed at which information gets incorporated into the various stock indices in India. Four alternate speed estimators viz., the AR (1) model, the ARMA (1, 1) model, the ARMA (1, X) model, and the cross-covariance estimator were calculated to estimate the rate at which information is adjusted. The lead–lag relationships between indices with varied characteristics were also analysed. It was observed that the Sensex and the Nifty indices, the constituents of which are large capitalisation stocks, led the smaller indices till 2009. This was disturbed in 2010 and 2011, especially by bank indices.

MO‐F‐WAB‐02: Constancy of Time Lag Relationship Between External and Internal Signal in Abdominal Tumor Sites

Purpose: To investigate constancy, within a treatment session, of the time lag relationship between implanted markers in abdominal tumors and an external motion surrogate. Methods: Six gastroesophageal junction and three pancreatic cancer patients (IRB‐approved protocol) received a respiration‐correlated CT (RCCT), and two cone‐beam CTs (CBCT), one before and one after the treatment. Time between initial and final scan varied from about 1 to 3 h. Each patient had at least one implanted fiducial marker near the tumor. In all scans, abdominal displacement (Varian RPM) was recorded as the external motion signal. In‐house software tracked fiducials, representing internal signal, in CBCT projection images and amplitude‐sorted RCCT. For each set of projection images, time lag between internal and external signals was found by maximizing the correlation coefficient in each breathing cycle and averaging over all cycles. For the RCCT, these quantities were calculated for the 1 –2 cycles during which the fiducial was imaged. Results: Mean ± standard deviation in time lag, over all scans and patients, was 0.10 ± 0.07 s (range 0.01 – 0.36 s). External signal lagged the internal in 20/27 scans. Change in time lag between pre‐and post‐RT CBCT was 0.06 ± 0.07s (range 0.01 – 0.22 s), corresponding to 3.1 ± 3.7% (range 0.6 – 10.8%) of the gate width (range 1.6 – 3.1 s). Including the RCCT scan, change in time lag increased to 6.5 ± 5.4% (range 0.2 – 16.1%) of the gate width, and in three patients, change in time lag exceeded 10% of the gate width. Conclusion: Time lag between internal and external signal is small compared to the treatment gate width in all patients. Change in time lag within a treatment session, inferred from pre to post‐RT measurements is also small, suggesting that a single measurement at the session start is adequate.NIH/NCI award R01 CA126993 and a research grant from Varian.

The dynamic interactions among the stock, bond and insurance markets

This paper explores the lead–lag relationships and the dynamic linkages among stock, insurance and bond markets in the developed countries. This is the first empirical study which sheds light on the extent and magnitude of the association among these financial markets used by the Granger causality test of Toda and Yamamoto (1995), generalized impulse response approach, and generalized variance decomposition in a multivariate setting. Our empirical results illustrate that there are indeed various patterns of dynamic relationships. The direction of causality appears to differ across countries. While investigating these interactive relationships under unexpected shocks, there is a one-way significant influence between the life insurance premium and long-run interest rate. These empirical findings serve as valuable applications not only for investors to diversify their risk away as well as to earn the abnormal return, but also for policy-makers to allocate resources more efficiently.

Compensation incentives of credit rating agencies and predictability of changes in bond ratings and financial strength ratings

Over the past decade there has been mixed evidence on the lead–lag relation between issuer-paid and investor-paid credit rating agencies. We investigate the lead–lag relationship for changes in bond ratings (BRs) and financial strength ratings (FSRs), for the US insurance industry, where FSRs impose market discipline. First, we find that changes in issuer-paid BRs are led by changes in investor-paid BRs, even over a period that issuer-paid agencies have improved their timeliness. Second, information flows in both directions between changes in issuer-paid BRs and FSRs. Third, issuer-paid FSRs are predictable by investor-paid BRs. Fourth, the lead effect of investor-paid downgrades is economically significant as it is associated with an unconditional, post-event, 30-day cumulative abnormal return of −4%. This return is a result of investor-paid downgrades in BRs, which predict more downgrades in the following 90days (same period return of −11%).

Price Lead-Lags in Indian Stock and Futures Market - A Wavelet Based Study

This paper examines the relationship between the stock and futures markets in terms of cointegration (Johnson Cointegration) and lead lag relationship (Wavelet Approach). We applied the Maximum Overlap Discrete Wavelet Transform (MODWT) method to stock and futures prices of 12 near month contracts during the period April 2011 and March 2012. The study included 13 Scripts across sectors which are included both in BSE Sensex and Nifty 50. Empirical results show that stock and futures are cointegrated in the long run and there is either feedback relationship or futures lead across time scales and also we have seen in some scripts there is no lead lag neither contemporaneously nor in different time scales.

The asymmetric price adjustment between REIT and stock markets in Asia-Pacific markets

This paper applies the threshold error correction model to examine the relationship for real estate investment trusts (REITs) and stock, and their asymmetric adjustment behaviors in six Asian/Pacific financial markets: Australia, Japan, Singapore, Taiwan, Korea, and Hong Kong. Our results show that there has been long-term equilibrium in REIT and stock indices in most of these markets. To earn exceptional profits, it is recommended that investors can sell (buy) the REITs when the indices of REITs are lower (higher) than equilibrium in Australia, Singapore and Taiwan; on the other hand, they should sell (buy) when the REIT market goes up (down) in Hong Kong and Japan. A causality test revealed that previous information about stocks predicted changes in the REITs in all the Asian/Pacific markets. One can also find that the lead–lag relationships are significant. The threshold EC model predicts two-way causality under both the regimes for the financial markets in most countries during all the sample periods. In addition, the adjustment speeds for the stock indices are faster than that for the REIT indices as disequilibrium occurs. This paper also finds that the previous mentioned trading strategies generally remained the same during the period of sub-prime mortgage crisis. However, the threshold EC model predicts one-way causality for both the regimes for the financial markets in most countries during this crisis period. In addition, we also find that the severe shock in REIT markets led investors in Australia and Taiwan to be more conservative during this period. The REIT indices had more effect on stock indices after the sub-prime mortgage crisis. According to the empirical results, we can infer that the degree of market imbalance and the occurrence of the sub-prime mortgage crisis induce the changes in the investment behavior of market participants.

The simulation of water vapor transport in East Asia using a regional air–sea coupled model

A regional air–sea coupled model (RegCM3‐POM) is used, and the ability of the model to simulate June, July, and August (JJA) moisture transport is verified. The coupled model (RegCM3‐POM) has better performances than the uncoupled model (RegCM3) in the simulation of the JJA mean water vapor characteristics from 1979 to 2002 and its interannual variations. The differences of water vapor between RegCM3‐POM and RegCM3 are mainly caused by different winds in the middle and low troposphere. The simulated circulation pattern of RegCM3‐POM is more similar to the Climate Forecast System Reanalysis (CFSR) data than that of the uncoupled model. The simulated geopotential height and the gradient of geopotential height in the coupled model are more accurate than those in the uncoupled model. The real‐time and lead–lag relationship between geopotential height and sea surface temperature (SST) in RegCM3‐POM is consistent with that between the height of CFSR data and HadISST (Hadley Center Sea Ice and Sea Surface Temperature data). Thus, the simulated water vapor in the lower troposphere and the vertically integrated moisture transport are more accurate in the coupled model than in RegCM3. In addition, the correlation coefficients between moisture transport and SST in RegCM3 are positive in South China Sea, corresponding to SST forcing; the correlation coefficients in RegCM3‐POM are negative, which is consistent with that between the vapor transport in CFSR data and HadISST. Thus, the air–sea coupled model represents more accurately than the uncoupled model the relationship between SST and moisture transport.

Investigating the dynamics of, and interactions between, Shanghai office submarkets

The Shanghai office market has developed rapidly over the past two decades. As a consequence of this development, two, apparently distinct, office submarkets, Puxi and Pudong have developed in central Shanghai. This raises the issue as to whether the Shanghai office market can be viewed as a homogeneous entity or whether there is imperfect substitutability across office locations within the city. The latter case raises the possibility of the existence of office submarkets. In this paper, we examine intra-metropolitan rental dynamics in the Puxi and Pudong submarkets, identifying any interrelationships between these markets, and consider whether they form distinct office submarkets. We find no interaction between the two submarkets. Further, we find no evidence of lead–lag relationships between the two submarkets. Finally, when we test for convergence in rental performance between the two submarkets, the tests reveal that we can reject the null of no convergence.

Preliminary Studies on Predicting the Tropical Indian Ocean Sea Surface Temperature through Combined Statistical Methods and Dynamic ENSO Prediction

AbstractThe sea surface temperature (SST) in the Indian Ocean affects the regional climate over the Asian continent mostly through a modulation of the monsoon system. It is still difficult to provide an a priori indication of the seasonal variability over the Indian Ocean. It is widely recognized that the warm and cold events of SST over the tropical Indian Ocean are strongly linked to those of the equatorial eastern Pacific. In this study, a statistical prediction model has been developed to predict the monthly SST over the tropical Indian Ocean. This model is a linear regression model based on the lag relationship between the SST over the tropical Indian Ocean and the Nino3.4 (5°S–5°N, 170°W–120°W) SST Index. The predictor (i.e., Nino3.4 SST Index) has been operationally predicted by a large size ensemble El Nino and the Southern Oscillation (ENSO) forecast system with coupled data assimilation (Leefs_CDA), which achieves a high predictive skill of up to a 24-month lead time for the equatorial eastern P...

Are Algorithmic Trades Informed? An Empirical Analysis of Algorithmic Trading around Earnings Announcements

This study examines the impact of corporate earnings announcements on trading activity and speed of price adjustment, analyzing algorithmic and non–algorithmic trades during the immediate period pre– and post– corporate earnings announcements. We confirm that algorithms react faster and more correctly to announcements than non–algorithmic traders. During the initial surge in trading activity in the first 90 seconds after the announcement, algorithms time their trades better than non–algorithmic traders, hence algorithms tend to be profitable, while non–algorithmic traders make losing trades over the same time period. During the pre announcement period, non–algorithmic volume imbalance leads algorithmic volume imbalance, however, in the post announcement period, the direction of the lead–lag relationship is exactly reversed. Our results suggest that as algorithms are the fastest traders, their trading accelerates the information incorporation process.

Climate change during the past 1000 years: a high‐temporal‐resolution multiproxy record from a mire in northern Finland

AbstractWe present a record of peatland development in relation to climate changes and human activities from the Palomaa mire, a remote site in northern Finland. We used fine‐resolution and continuous sampling to analyse several proxies including pollen (for vegetation on and around the mire), testate amoebae (TA; for mire‐wetness changes), oxygen and carbon isotopes from Sphagnum cellulose (δ18O and δ13C; for humidity and temperature changes), peat‐accumulation rates and peat‐colour changes. In spite of an excellent accumulation model (30 14C dates and estimated standard deviation of sample ages <1 year in the most recent part), the potential to determine cause–effect (or lead–lag) relationships between environmental changes and biotic responses is limited by proxy‐specific incorporation processes below the actively growing Sphagnum surface. Nevertheless, what emerges is that mire development was closely related to water‐table changes rather than to summer temperature and that water‐table decreases were associated with increasing peat‐accumulation rates and more abundant mire vegetation. A rapid fen‐to‐bog transition occurred within a few years around AD 1960 when the water table decreased beyond the historical minimum, supporting the notion that mires can rapidly shift into bogs in response to allogenic factors. Copyright © 2012 John Wiley & Sons, Ltd.

The Improvement of a Prediction Study of Transactions Based on E-Commerce Site Search Data

The search behavior of E-commerce consumers is conscious. And their shopping is another kind of consciousness behavior. In the shopping process of e-commerce website, these two consciousness behavior were joined together. So, the phenomenon reflects some trends and patterns, reflect the relationship between e-commerce site search volume and trading volume. This paper will attempt to establish the model of a theoretical framework, which explored the first - lag relationship between the amount of e-commerce site search and e-commerce transaction volume, by stepwise method which obtain comprehensive search index, and then which complete the empirical analysis, obtain the prediction result. The results showed that: there are a higher correlation between the search data and trading volume of e-commerce site; after adding a synthesis of the search index, the model fit increased to 0.901, which significantly improve the prediction result of the model. At the same time, the model has a stronger timeliness, which can more timely predict e-commerce transactions.

Futures price dynamics of CO2 emission allowances

We analyze the pricing and lead–lag relationship between spot and futures prices of CO2 emission allowances in the EU emission trading scheme. We show that the cost-of-carry hypothesis between spot and futures prices holds for the trial period. In this period we focus on how fast a deviation from equilibrium due to shocks is restored. We derive testable restrictions on the loading coefficients and the short term dynamics within a vector error correction model. Previous studies in this field did not take into account the effects of lagged differences in the determination of the speed of adjustment. The results indicate that deviations from equilibrium are restored faster for the futures price series maturing in 2006 than for the futures price series maturing in 2007. Furthermore, we conduct an impulse response analysis using local projections with conditional confidence bands. Finally, we give an outlook for the Kyoto commitment period which is already running. In this time period so far we find that the cost-of-carry hypothesis does not hold.

Short sales and put options: Where is the bad news first traded?

Although the literature provides strong evidence supporting the presence of informed trading in both the option and the short equity markets, it is not clear which market attracts more informed trading. Using a unique dataset that covers intraday transaction data in the option and short equity markets, we investigate informed trading in a cross-market environment by explicitly studying the lead–lag relationship between the put net trade volume and short sales of the underlying stock. Our high frequency analysis shows that in general short sales contain more information. However, put options become more informative before the release of negative earnings announcements.

Lead lag Relationship: Analysis of KSE

This research paper finds the lead lag relationship between the firms listed on the KSE-100 index. Lead lag relationship is analyzed between large and small capitalization portfolios. Moreover, up market and down-market conditions are also explored for finding out the lead lag relationship in the KSE-100 index. Autoregressive Conditional Heteroskedasticity model is used for finding out the effect of symmetric and asymmetric betas on small cap portfolio returns. The results show that there is no lead lag relationship between small cap portfolios and large cap portfolios when the market is not divided into up and down markets. For the asymmetric beats, the analysis shows that there is lead lag relationship between small cap portfolio returns and lagged large cap portfolio returns in the up market. On the other hand, large cap portfolio returns lead small cap portfolio returns in the down market.

Are Algorithmic Trades Informed? - An Empirical Analysis of Algorithmic Trading Around Earnings Announcements

This study examines the impact of corporate earnings announcements on trading activity and speed of price adjustment, analyzing algorithmic and non–algorithmic trades during the immediate period pre– and post– corporate earnings announcements. We confirm that algorithms react faster and more correctly to announcements than non–algorithmic traders. During the initial surge in trading activity in the first 90 seconds after the announcement, algorithms time their trades better than non–algorithmic traders, hence algorithms tend to be profitable, while non–algorithmic traders make losing trades over the same time period. During the pre announcement period, non–algorithmic volume imbalance leads algorithmic volume imbalance, however, in the post announcement period, the direction of the lead–lag relationship is exactly reversed. Our results suggest that as algorithms are the fastest traders, their trading accelerates the information incorporation process.

Futures mispricing, order imbalance, and short-selling constraints

The aim of the research is to determine how the lifting of price restrictions on short sales and security-lending sales affects market efficiency, liquidity and arbitrage opportunities. The study examines trading behaviors of large and small traders separated by their transaction costs and shows the lifting of price restrictions strengthens the correlation between extreme order imbalance and extreme mispricing. Also, autocorrelations of the underpricing and overpricing persist longer, in particular for big traders, and so do those of buy-side and sell-side order imbalances. However, the outcomes for the post-lifting market efficiency are mixed. This paper provides evidence that lifting price restrictions enhances informed trading and the lead–lag relationship between mispricing and order imbalance in the cash and futures markets.