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The purpose of this paper is to examine the behavior of buyers and sellers in making housing decision and analyses the mechanisms of the seller‐buyer interaction affecting house sale prices.

The research methodology relies on a cross‐sectional telephone survey and the statistical analysis of housing transactions in Hong Kong.

The list price is unimportant to the formation of the sale price. Rather buyer‐seller interactions affect housing prices. The list price is positively related to the number of revisions, and the size of reduction, in the list price, and the list period, but negatively related to the sale‐to‐list‐price ratio. Overpriced properties trigger larger price reductions, noticeably, in the first round of negotiation, and stay on the market longer. Short negotiation periods and time‐till‐sale, and a sale at a marginal reduction in the list price is expected by market participants and conforms with the historical sales data. Hence, market expectations are generally fulfilled and support rationality in a steady market.

There are sample size limitations, which might bias the results and weaken the generalizability. The limited housing transactions may not be representative of the population at large.

When the market conditions are moderate, offering the property for sale at close to its current market value would determine the best possible selling price.

Telephone surveys on home buyer‐seller interactions and critical analysis of sale records are extremely rare in Hong Kong. The paper illustrates how, in times of moderate economic conditions and housing prices, the strategic negotiation process will rationally bring the selling price close to the market value price.

The conception of markets as interfaces connecting semi-autonomous systems of producers and customers has led to an extensive use of social network analysis. So far, the network focus has been on connections among people, paying less attention to the crucial role played by connections between cultural elements (e.g., concepts, representations, ideas) in the way markets are formed and sustained. Such connections constitute “semantic networks” and are the focus of the present article. We attend to them by developing a network view of the cultural dimension of markets and apply it in an empirical setting where culture plays a crucial role – luxury watchmaking – to illustrate the impact of market semantic networks on a major outcome: price.

The purpose of this paper is to report the results of a study concerning how fundamental-motivated investors, and their subsequent impact on the path of prices, affect the severity of price bubbles in an experimental laboratory asset market.

In a laboratory experiment, asset markets are manipulated by systematically replacing inexperienced human traders with automated traders programmed to submit bids and asks at fundamental value.

When traders in a market are automated to invest on fundamentals, deviations from fundamental value are initially suppressed, but reappear when automated traders cease to influence prices. A significant reduction in the severity of the resulting bubble may be attributed to the interaction of automated traders and humans through the initial path of prices when controlling for changes in liquidity. This reduction corresponds to reduced autocorrelation in the time series of returns.

This paper represents the first attempt (to the authors’ knowledge) to extend the intervention approach of the seminal paper by Smith et al. (1988) to systematically study the extent to which manipulation of initial path of prices impacts the formation and magnitude of bubbles in the laboratory.

For more than 40 years, researchers have examined an exhaustive set of attributes as price determinants in tourism and hospitality. In extending this rich research stream, this study aims to propose and empirically assess a new set of hotel attributes, namely, faith-based attributes that allow tourists to continue following the activities and rituals guided by their religions while on vacation.

Using the Bayesian quantile regression for the first time in the field of hotel pricing, the hedonic pricing models examine both internal and external faith-based attributes, namely, halal services, which cater to the needs of Muslim tourists, in a sample of 805 hotels across the top three non-Muslim country destinations (Singapore, Thailand and Japan).

By exploring the effects of faith-based (halal) attributes available in hotels located in the biggest cities of the above-mentioned destinations, this study provides evidence for the significant role of faith-based (halal) attributes in determining hospitality prices.

This study’s findings offer a resource for several implications for tourism and hospitality scholars, practitioners and policymakers, especially within the field of Muslim/halal tourism, to develop action plans and strategies.

This study is the first to introduce a novel set of faith-based hospitality attributes and empirically assess their impact on hospitality price formation. Additionally, it contributes to the hedonic pricing method by being the first to use the Bayesian quantile regression.

The purpose of this paper is to study the influence of different quantitative (traditionally used) and qualitative variables, such as the possible negative effect in determined periods of certain socio-political factors on share price formation.

We first analyse descriptively the evolution of the Ibex-35 in recent years and compare it with other international benchmark indices. Bellow, two techniques have been compared: a classic linear regression statistical model (GLM) and a method based on machine learning techniques called Extreme Gradient Boosting (XGBoost).

XGBoost yields a very accurate market value prediction model that clearly outperforms the other, with a coefficient of determination close to 90%, calculated on validation sets.

According to our analysis, individual accounts are equally or more important than consolidated information in predicting the behaviour of share prices. This would justify Spain maintaining the obligation to present individual interim financial statements, which does not happen in other European Union countries because IAS 34 only stipulates consolidated interim financial statements.

The descriptive analysis allows us to see how the Ibex-35 has moved away from international trends, especially in periods in which some relevant socio-political events occurred, such as the independence referendum in Catalonia, the double elections of 2019 or the early handling of the Covid-19 pandemic in 2020.

Compared to other variables, the XGBoost model assigns little importance to socio-political factors when it comes to share price formation; however, this model explains 89.33% of its variance.

El propósito de este artículo es estudiar la influencia de diferentes variables cuantitativas (tradicionalmente usadas) y cualitativas, como la posible influencia negativa en determinados períodos de ciertos factores sociopolíticos, sobre la formación del precio de.

Primero analizamos de forma descriptiva la evolución del Ibex-35 en los últimos años y la comparamos con la de otros índices internacionales de referencia. A continuación, se han contrastado dos técnicas: un modelo estadístico clásico de regresión lineal (GLM) y un método basado en el aprendizaje automático denominado Extreme Gradient Boosting (XGBoost).

XGBoost nos permite obtener un modelo de predicción del valor de mercado muy preciso y claramente superior al otro, con un coeficiente de determinación cercano al 90%, calculado sobre las muestras de validación.

De acuerdo con nuestro análisis, la información contable individual es igual o más importante que la consolidada para predecir el comportamiento del precio de las acciones. Esto justificaría que España mantenga la obligación de presentar estados financieros intermedios individuales, lo que no ocurre en otros países de la Unión Europea porque la NIC 34 solo obliga a realizar estados financieros intermedios consolidados.

El análisis descriptivo permite ver cómo el Ibex-35 se ha alejado de las tendencias internacionales, especialmente en periodos en los que se produjo algún hecho sociopolítico relevante, como el referéndum de autodeterminación de Cataluña, el doble proceso electoral de 2019 o la gestión inicial de la pandemia generada por el Covid-19.

En comparación con otras variables, el modelo XGBoost asigna poca importancia a los factores sociopolíticos cuando se trata de la formación del precio de las acciones; sin embargo, este modelo explica el 89.33% de su varianza.

This research paper aims to examine the relationships among the factors associated with changing shopping environment, consumer knowledge and reference price.

A self administered online survey was used to collect data (final sample size was 265). After checking for non‐response bias, data was factor analyzed and checked for reliability and validity. Hypotheses were tested using structural Equation Modeling procedure.

Product search opportunity is associated with product and price knowledge. Price volatility is negatively associated with internal reference price. Further, consumers' price comparison propensity and price knowledge positively influence external reference price. Finally, price volatility has a significant negative influence on consumer knowledge and IRP orientation.

The sampling frame is a major limitation, in addition to not including variables such as product type and other measures of price volatility. Future research should expand the sampling frame and include other variables as well as other aspects of price volatility.

These findings provide insights into advertised price claims in the information rich internet age. Managers also benefit from the finding that the internet, particularly price comparison, influences external reference price. Consequently, managers must be cautious with their advertised price claims and not exaggerate the value of offerings or cost savings too much.

This topic is important because retailers extensively use reference price or price comparison to increase consumers' perception of the product value. However, not much research attention has been given to this topic.

This paper examines whether there are differences in the nature of the price discovery process across established versus emerging stock markets using a twenty-country sample.

The authors analyse security returns for traces of predictability or non-randomness using variance ratio tests, Granger-Causality models and runs tests.

The findings pinpoint at predictabilities which seem inconsistent with market efficiency, and they suggest that the inherent cause of predictability differs across groups.

The authors present empirical evidence which may be used to attain a deeper understanding of the links between predictability and market efficiency, in view of the conflicting evidence in prior literature.

Whilst the pricing process in emerging markets may be hindered by delayed adjustments, in case of established markets it seems that there is a higher tendency for price reversals which could be due to prior over-reactions.

This study presents evidence of substantial differences in predictability across developed and emerging markets which was gleaned through the rigorous application of different empirical tests.

The article makes a comprehensive study of the development of social economic thought in the history of economic doctrines. Traces of social economic development are dated back to the Physiocrats and moral philosophers and reference is made to the early Arab works in the developments of these social economic doctrines. The social economic thought in the classical school of economic theory is critically studied. It is shown that with the advancement of economic theory in the hands of the neoclassical school and its latter‐day developments social economic doctrines receded from mainstream economics. The contemporary social economists in North America have fallen into the trap of these neoclassical approaches applied to the study of social economic phenomena. The article also shows that similar neoclassical and ethically neutral traces continue in the works of the mixed economy theorists, institutionalists, macroeconomists, monetarists, rational expectations hypothesists, public and social choice theorists of all types. Thus, the whole gamut of mainstream economics is shown to be trapped in an epistemological and methodological quandary as to how ethical phenomena are to be treated rationally in the framework of economic theory.

This paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.

The income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.

The gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.

Investors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.

Ratio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.

The graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.

A consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

The study aims to propose an appraisal procedure based on the preferences stated by a sample of potential consumers and producers which makes it possible to obtain the hypothetical demand and supply curves and to estimate the most likely market value and transaction quantities for housing markets with unrevealed prices.

The procedure is divided into two steps: the first is aimed at selecting the alternatives that are most likely to meet the market’s preference by applying discrete choice (DC) analysis; the second makes it possible to estimate the potential demand and supply curves for the preferable alternatives singled out through DC analysis by using contingent valuation methods.

The results obtained considering only the hypothetical demand or the hypothetical supply differ by an average of 10 per cent from the actual sale price. Conversely, the values detected as the intersection of the hypothetical demand curve and the hypothetical supply curve, fall into variation margins that can be considered fully acceptable in real estate appraisal

As opposed to the applications performed in international real estate operations where reference is made solely to the potential demand estimate, the described procedure estimates the transaction value as the intersection between the hypothetical demand and supply curves, for the purposes of keeping account of the conditions that generally occur in the real market. Furthermore, it is possible to detect the incidence of the characteristics in market price formation, and to identify the market share of possible alternative assets and estimate the optimal quantity to be produced.