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The purpose of this study is to develop a spatio-temporal neighbourhood-level house price index (STNL-HPI) incorporating a geographic information system (GIS) functionality that can be used to improve the house price indexation system.

By using the Malaysian house price index (MHPI) and application of geographically weighted regression (GWR), GIS-based analysis of STNL-HPI through an application called LHPI Viewer v.1.0.0, the stand-alone GIS-statistical application for STNL-HPI was successfully developed in this study.

The overall results have shown that the modelling and GIS application were able to help users understand the visual variation of house prices across a particular neighbourhood.

This research was only able to acquire data from the federal government over the period 1999 to 2006 because of budget limitations. Data purchase was extremely costly. Because of financial constraints, data with lower levels of accuracy have been obtained from other sources. As a consequence, a major portion of data was mismatched because of the absence of a common parcel identifier, which also affected the comparison of this system to other comparable systems.

Neighbourhood-level HPI is needed for a better understanding of the local housing market.

US studies show significant price effects when shares enter or leave an index during index revisions. Studies on other markets generally yield similar results with smaller price reactions. This study aims to examine the price effects resulting from revisions to the Australian S&P/ASX 100 and 300 indices.

The event study methodology is used to examine abnormal price and volume effects around the announcement dates and implementation dates of index revisions.

In contrast with studies on US index changes, this study shows no abnormal returns for additions to or deletions from the S&P/ASX 100 index and only a weak effect for the S&P/ASX 300, which showed a median abnormal return of  + 1.06 per cent on the implementation date for additions and −2.78 per cent for deletions.

These results give a cautionary warning to those who wish to speculate on the changes to index constituents on the Australian market, or other similar markets where the strength of the index effect has not been clearly quantified.

This study adds to the body of knowledge on the index effect by providing Australian evidence.

The purpose of this study is to extend the work of DeFusco, Ivanov and Karels by examining pricing deviation of DIA, SPY and QQQQ on intradaily basis.

The DIA is designed to be one hundredth of the DJIA, the SPY is designed to be one tenth of the S&P 500 and QQQQ is designed to be one fortieth of the NASDAQ 100. This feature of ETFs requires the estimation of the difference between the proportional level of the index and the price of the ETF, which is the ETF pricing deviation.

The paper finds that the DIA, SPY and QQQQ pricing deviations are 0.0429, −0.0743 and 0.4298, respectively. The findings indicate that the prices of DIA and QQQQ are on average lower than the underlying indexes. SPY is the exception having a price which is higher than the theoretical price of the S&P 500 index. The author finds that this is due to the increased demand for the SPY. Additionally, the paper provides an explanation for the large change (increase) in the pricing deviation of QQQQ after December 1, 2004 which DeFusco, Ivanov and Karels could not explain. On December 1, 2004 QQQQ trading was consolidated on NASDAQ. The paper finds negative growth in the volume of QQQQ after December 1, 2004 indicating decrease in popularity of this ETF. The decrease in popularity of QQQQ might explain the increase in its pricing deviation.

The paper uses high frequency data in the analysis of pricing deviation which might be artificially deflating standard errors and thus inflating the t‐test significance values.

The paper contributes to the ongoing search in the finance literature of precision ETF performance metrics.

The purpose of this paper is to construct a hedonic property price index in the segmented housing market.

Three different research questions are investigated. The first considers how to identify separate local housing markets, with the use of a regression‐tree approach, and the second concerns when it is possible to update a price index, with a recursive regression approach. Finally, the question about seasonal adjustment is investigated.

Overall, the hedonic approach is the best method to use. Moreover, the County of Stockholm is not one market in the sense that the market can be represented by only one property price index. It can be best described as a number of different sub‐markets where the property prices grow differently. The results suggest that there exist at least five different price indexes in the County of Stockholm. The results also support that recursive regressions are two appropriate methods to answer the research questions. Here, the empirical analysis suggests that the parameter estimates converge relatively fast toward the estimate using all observations.

The paper illustrates how to derive sub‐markets in the construction of a price index and when to update a price index series.

The introduction of new financial products, such as property derivatives, to the market has made the construction and quality of property price indexes more important. High quality price indexes are vital when it comes to, for example, pricing property derivatives. The paper facilitates this.

The main objective of this study is to initiate general building cost indicators to serve as cost indicators for the construction industry in Egypt. The two models (Egypt 1 and Egypt 2 Indices) developed for building the indices in this paper have been derived based on the “Engineering News Record” (ENR) Indices model with modifications to better suit the Egyptian market. Egypt 1 Indices is comprised of three indices which serve as a general cost indicator for the construction industry price movement in Egypt. Egypt 2 Indices is comprised of two indices which serve as a construction cost indicator for the reinforced concrete structures price movement in Egypt. The period analyzed in this research is 11 years (1988 through to 1998). The validation of index numbers produced showed that each index does indeed represent the respective type of building for which it was computed. Further, the analysis of Egypt Indices compared to the ENR Indices revealed that both indices exhibited trends that are generally similar from the year 1992 up to 1998.

While the classic futures pricing tool works well for capital markets that are less affected by sentiment, it needs further modification in China's case as retail investors constitute a large portion of the Chinese stock market participants. Their expectations of the rate of return are prone to emotional swings. This paper, therefore, explores the role of investor sentiment in explaining futures basis changes via the channel of implied discount rates.

Using Chinese equity market data from 2010 to 2019, the authors augment the cost-of-carry model for pricing stock index futures by incorporating the investor sentiment factor. This design allows us to estimate the basis in a better way that reflects the relationship between the underlying index price and its futures price.

The authors find strong evidence that the measure of Chinese investor sentiment drives the abnormal fluctuations in the basis of China's stock index futures. Moreover, this driving force turns out to be much less prominent for large-cap stocks, liquid contracting frequencies, regulatory loosening periods and mature markets, further verifying the sentiment argument for basis mispricing.

This study contributes to the literature by relying on investor sentiment measures to explain the persistent discount anomaly of index futures basis in China. This finding is of great importance for Chinese investors with the intention to implement arbitrage, hedging and speculation strategies.

The purpose of this paper is to use data on new apartment offerings in the municipality of Sao Paulo, Brazil to illustrate its main claim that the hedonic direct method using time dummies as well as the simple average method include cyclical behavior of observables and non‐observables in a house price index that may overestimate or underestimate the actual change in house prices, well beyond the composition effects.

The paper proposes the use of alternative characteristics hedonic functions to compute alternative Laspeyres house price indexes that differentiate the sources of observable shocks in the index. The decomposition allows for the inclusion of level and cyclical behavior of sets of aggregate variables into the index.

The appropriate house price index should filter out real shocks that potentially affect the real estate sector. An index should capture nominal variation and incorporating real variation biases the measurement. Thus, the index is intended and able to buffer the bias spillover into the rest of economy. In the limited sample from the city of Sao Paulo, Brazil, the main finding is that real shocks and US foreign shocks give an upward bias in the house price index, while nominal shocks give mostly a downward bias. Real shocks make the index incorporate gains that should not be incorporated into the index, thus providing a noisy picture of the nominal variation in house prices.

The key contribution of this paper is to provide a framework for the construction of a house price index that filters out real shocks that potentially affect the real estate sector. An index should capture nominal variation and incorporating real variation biases the measurement. Those biases can spillover to the rest of the economy is a detrimental way. Thus, the index is intended and able to buffer the bias spillover into the rest of economy.

The paper aims to describe, construct, and compare alternative price indices for real estate in Malta over the period 1980‐2010.

The paper utilises the technique of hedonic regression analysis to construct four hedonic price indices. One of the constructed indices is based the unconstrained hedonic methodology. Two other indices are variants of the constrained hedonic technique, while the fourth consists of an imputed hedonic index. The hedonic indices are then compared to other 12 conventional indices, namely the Laspeyres, Paasche and Fisher indices (constant weight and chain linked) that are constructed by utilizing the mean and median house prices pertaining to 14 different types of houses.

All indices are found to move closely together, growing between six and seven times between 1980 and 2010. The average annual compound growth rate of the 16 indices was found to be 6.5126 percent. The paper also shows how the estimated hedonic coefficients can be used to construct regional price indices for different combinations of housing characteristics.

The paper builds on previous work related to house prices in Malta. Its main contribution is the construction of hedonic indices that are based on advertised prices that span over a relatively long period of 31 years, together with the construction of constant weight and chain linked Laspeyres, Paasche and Fisher indices.

The purpose of this paper is to test whether temporal aggregation matters when constructing hedonic house price indices for developing markets using Ghana as a case study.

Monthly, quarterly, semi-yearly and yearly hedonic price indices are constructed and six null hypotheses are tested using the F-ratios to examine the temporal aggregation effect.

The results show that temporal aggregation may not be a serious issue when constructing hedonic house price indices for developing markets as a result of the smaller sample size which these markets normally have. At even 10 per cent significance level, none of the F-ratios estimated is statistically significant. Analysis of the mean returns and volatilities reveal that indices constructed at the lower level of temporal aggregation are very volatile, suggesting that the volume of transactions can affect the level of temporal aggregation, and so, the temporal aggregation level should not be generalised, as is currently observed in the literature.

The diversification importance of real estate and the introduction of real estate derivatives and home equity insurance as financial products call for the construction of robust and accurate real estate indices in all markets. While almost all empirical research recommends real estate price indices to be conducted at the lower level of temporal aggregation, these studies are largely conducted in developed markets where transactions take place frequently and large transaction databases exist. Unfortunately, little is known about the importance of temporal aggregation effect when constructing indices for developing real estate markets. This paper contributes to fill these gaps.

With the launch of CSI 300 Index Futures trading on April 16, 2010, China's stock market presents a more diversified trend, such as arbitrage, trends strategy entering the market rapidly. Therefore, the liquidity demand also presents a higher frequency, and the change is more complex than the original situation. In recent years, many literatures are engaged in high-frequency trading (HFT) related research, and an important concern is the impact of HFT on market volatility and liquidity. Is it playing the role of stabilizing the market, or bringing more noise and turmoil? Based on this, the purpose of this study is trying to study what kind of impact the HFT have on market liquidity before and after the launch of the CSI 300 Index Futures.

The paper uses the simultaneous equations model of price and net order flow proposed by Deuskar and Johnson and for the first time introduces an asymmetric identification through heteroskedasticity (ITH) method. The paper applies the method to the high-frequency data of CSI 300 Index and the Futures and classifies the buying and selling orders through volume clock. The price risks are decomposed into a component driven by the impact of liquidity demand shocks (flow-driven risks (FDRs)) and a component driven by external information (information-driven risks (IDRs)).

The empirical results show that the flow-driven risk of CSI 300 Index Futures is about 20 percent. In addition, before the introduction of the Index Futures, there is no asymmetric effect between liquidity demand shocks and price shocks existing in either CSI 300 Index or CSI 300 Index Futures. While after the introduction of stock Index Futures, the asymmetric effect in the both two markets emerges. The impact of the buying net order flows on the price is less than the impact of the selling net order flows on CSI 300 Index, whereas the impact of the buying net order flows on the price is larger than the impact of the selling net order flows on CSI 300 Index Futures. The paper further analyzes the relationship between liquidity and FDR and gets the conclusion that the reasons for the deterioration of the liquidity level are caused by the impact of the external information shocks, rather than the liquidity demand shocks. And entries of HFTs like arbitrage traders and hedge traders play a positive role in improving the liquidity level in the market.

The paper introduces an asymmetric ITH method for the first time and finds asymmetric effect of the net order flow on the return in both CSI 300 Index market and the corresponding Index Futures market.