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Market links (and price discovery) between financial assets and lead–lag relationships are topics of interest for financial economists, financial managers and analysts. The lead–lag relationship analysis should consider both short and long-term investors. From a portfolio diversification perspective, the first type of investor is generally more interested in determining the co-movement of financial assets at higher frequencies, which are short-run fluctuations, while the latter concentrates on the relationship at lower frequencies, or long-run fluctuations. The paper aims to discuss these issues.

For this study, a technique was employed known as the wavelet approach, which has recently been imported to finance from engineering sciences to study the co-movement dynamics between global sukuk and bond markets. Data cover the period from January 2010 to December 2015.

The results indicate that: there is no unidirectional causality from developed market bond indices to Malaysia and Dow Jones indices, which is promising for fixed-income investors of a developed market; and in relation to emerging markets, the Malaysian sukuk market has a bidirectional causality with Indonesia, Malaysia, India and South Korea bond indices but not China bond indices, while in terms of the Dow Jones sukuk index, there is no unidirectional causality between the listed emerging markets and the sukuk index except Indonesia’s market during the sample period.

This analysis provides evidence regarding the timely and appropriate measure of correlation changes and the behaviour of sukuk and bond indices globally, which is beneficial to the management of sukuk and bond portfolios.

The evidence hitherto unexplored, which was produced by the application of a wavelet cross-correlation amongst the selected sukuk and bond indices, provides robust and useful information for international financial analysts as well as long and short-term investors.

The purpose of this paper is to examine the lead‐lag relationships between the National Stock Exchange (NSE) Nifty stock market index (in India) and its related futures and options contracts, and also the interrelation between the derivatives markets.

The paper uses serial correlation of return series and autoregressive moving average (ARMA) model for studying the lead‐lag relationship between hourly returns on the NSE Nifty index and its derivatives contracts like futures, call and put options. Further, the lead‐lag relation between hourly returns of the derivatives contracts among themselves is also studied using ARMA models.

The ARMA analysis shows that the NSE Nifty derivatives markets tend to lead the underlying stock index. The futures market clearly leads the cash market although this lead appears to be eroding slightly over time. Although the options market leads the cash overall, there is some feedback between the two with the underlying index leading at times. Further, it is found that the index call options lead the index futures more strongly than futures lead calls, while the futures lead puts more strongly than the reverse.

The results imply that the derivative contracts on NSE Nifty lead the underlying cash market. Thus, the derivative markets are indicative of futures price movements and this will certainly be helpful to potential investors to design their risk‐return portfolio while investing in stocks and derivatives contracts.

This paper is an original piece of work towards exploring the lead‐lag relation between NSE Nifty and the derivative contracts. The issue of price discovery on futures and spot markets and the lead‐lag relationship are topics of interest to traders, financial economists, and analysts.

The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets.

The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method.

The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices.

China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior.

Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead–lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock.

It turns out that the lead–lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time.

One limitation of this paper is that it studies China’s stock market only; however, different conclusions could be drawn for other financial markets or mature stock markets.

As for the implications, the new tool could improve the prediction accuracy of the model, thus have practical significance for stock selection and dynamic portfolio management.

This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.

This study examines the lead-lag relationship between KOSPI200 and the volatility index based on the implied volatility from the KOSPI200 options. The sample period covers from January 2, 2003 to June 30, 2004. Both daily and minute-by-minute data were used for the lead-lag analysis. The study also determines whether the response of volatil ity index to KOSPI200 is symmetric or not. The most important findings may be summarized as follows.

First, there is no lead-lag relationship between the change in volatility index and the KOSPI200 returns on a daily basis. However, on a minute-by-minute basis, volatility index leads KOSPI200 for the group of largest increases in volatility index, and the opposite is true for the group of largest decreases and least changes in volatility index. The option market appears to react more quickly to volatility increases, while the stock market seems more sensitive to volatility decreases. Second, the volatility increase in response to the stock market decline is more severe than the volatility decrease in response to the stock market rise for daily data. This evidence of asymmetry suggests that volatility index plays a role of investors’fear gauge. Our results show no asymmetric response of volatility index to stock market movements for weekly data.

This paper aims to investigate informational efficiency of stock, options and credit default swap (CDS) markets. Previous research suggests that informed traders prefer equity option and CDS markets over stock markets to exploit their informational advantage. As a result, equity and credit derivative markets contribute more to price discovery compared to stock markets.

In this study, the authors investigate the dynamics behind informed investors’ trading decisions in European stock, options and CDS markets. This allows to identify the predictive explanatory power of the unique information contained in each market with respect to future stock, CDS and option market movements.

A lead-lag relation is found between the CDS market and the other markets, in which changes in CDS spreads are able to consistently forecast changes in stock prices and equity options’ implied volatilities, indicating how the fast-growing CDS market seems to play a special role in the price discovery process. Moreover, in contrast to results of US studies, the stock market is found to forecast changes in the other two markets, suggesting that investors also prefer stock market involvement to exploit their information advantages before moving to CDS and option markets. Interestingly, these patterns have only emerged during the recent financial crisis, while before the crisis, the option market was found to be of major importance in the price discovery process.

The authors are the first to study the lead-lag relationship among European stock, option and CDS markets for a large sample period covering the financial crisis.

The dynamics between five-year US Treasury bonds and interest rate swaps are examined using bivariate threshold autoregressive (BTAR) models to determine the drivers of spread changes and the nature of the lead–lag relation between the two instruments. This model is able to identify the economic – or threshold – value that market participants consider significant before realigning their portfolios. Specifically, three different regimes are identified: when the swap spread in the previous week is either high or low, the Treasury bond market leads the swap market. However, when the swap spread is low, none of the markets leads each other. Thus, yield movements are shown to be governed by the direction and magnitude of the change in the swap spread, which in turn provides an economic insight into the rebalancing between swap and bond portfolios.

The purpose of this paper is to address a key issue fundamental to the operation of land and housing markets, that is, the relationship between land and house prices. The study identifies possible causation between established house and vacant allotment prices using the metropolitan area of Adelaide, Australia as a case study.

A key outcome of the study is the construction of a Site Adjusted Land Price Index against which a Quality Adjusted House Price Index is compared.

The results show that there is a lagged effect of land prices on house prices and that this is significant at an interval of eight lag periods. The results also imply that the lead lag relationship between established house and vacant allotment prices is not unidirectional. This suggests that, while a change in house prices leads to a change in land prices in the short-run, the long-run position is for increasing land prices to lead to a delayed increase in house prices.

Rising house prices do not simply and solely reflect a shortage of land. There are suggested effects both immediate from house to land and delayed from land to house, particularly in a rising market.

The lead lag relationships of both indexes are tested using Granger causality estimates to assess whether theoretical Ricardian concepts still hold in a modern urban land market.

The volatility of bitcoin (BTC) and time horizon is the center point for investment decisions. However, attention is not often drawn to the relationship between BTC and equity indices. Thus, the purpose of this paper is to investigate the volatility and time frequency domain of BTC with stock markets.

The authors analyse six actively traded VIX Exchange Traded Products (ETPs) including 1x long, −1x inverse and 2x leveraged products. The authors assess their impact on the VIX Futures index benchmark.

Long-run causal relations between daily price movements in ETPs and futures are established, and the impact of rebalancing activity of leveraged and inverse ETPs evidenced through causal relations in the last 30 min of daily trading.

High frequency lead lag relations are observed, demonstrating opportunities for arbitrage, although these tend to be short-lived and only material in times of market dislocation.

The causal relations between VXX and VIX Futures are well established with leads and lags generally found to be short-lived and arbitrage relations holding. The authors go further to capture 1x long, −1x inverse as well as 2x leveraged ETNs and the corresponding ETFs, to give a broad representation across the ETP market. The authors establish causal relations between inverse and leveraged products where causal relations are not yet documented.