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“Where do I find the Consumer Price Index?” “What was last year's unemployment rate?” “How do I locate data on the number of 1979 cars sold?” The above questions are among a multitude that a reference librarian might be asked concerning business statistics. To find the answers to these questions, the librarian may use a variety of sources.

The purpose of this paper is to explore the forecasting effectiveness of Black-Scholes (BS) focussing parity analysis of time series econometric and implied volatility (IV) numerical techniques.

To analyze the comparative competitiveness of econometric time series and IV models this paper consolidated the study with their inter-relations leading toward multilayered moneyness-maturity correlation of model and market option prices, thoroughly determined the moneyness-maturity combinations of error metrics of Nifty index options.

Out of six models tested and critically examined here, the paper procures only a single model, IV, which best caters to the requirements of option traders and as a result the paper ended up that only IV supports to multifarious moneyness-maturity dimension of option pricing of Nifty index options. The analysis also confirms that the standard VIX is not a reliable tool for determining the base price of Nifty index options (via BS). As the IV landmarks during the most dynamic phase of Indian capital market which is a touchstone to justify the quality of any model, the paper can deduce that IV could continue to perform in hardships of financial contraction par smoothly and effectively.

The final outcome of this research which ended successfully in exploring a dominant model, guided successfully through the most volatile period of Indian economy can be used to safe guard investor's faith and to figure a design which could compete on the canvass of option pricing.

As equity market is always subject to highly unpredictable conditions and may keep on experiencing it through all times to come, the unified objective of research is to find out the most impeccable volatility model to meet out the requirements of option practitioners, specifically contributing upto the satisfaction and expected results during tumultuous period.

The main purpose of this paper is to explore the listing behaviours of agents and sellers. In particular, the paper analyzes listing prices and the predicting power of the house features described in advertisements, to improve their use in real estate valuations. In Italy, selling prices are not public information and therefore listing prices play a key role for market analyses and are used by real estate companies and appraisers for estimating house values.

A traditional hedonic model was used to measure the overall contribution to listing price of the characteristics described in advertisements. The analysis was performed both on houses put on the market by agents and on houses put on the market by sellers. Listing price distributions and their deviation from normality were analyzed. Furthermore, a hedonic analysis was performed, which consisted of two steps. First, the coefficient of determination for any characteristic was computed. Second, the overall contribution to the listing price of the characteristics described in advertisements was measured.

The analysis shows the presence of factors which affect listing prices and which are not revealed to buyers in real estate advertisements. On the other hand, the presence of characteristics that do not affect the listing price but are described in advertisements was also found. Furthermore, agents and sellers showed different behaviours. While the marginal contributions of each characteristic estimated on a sample of houses put on the market by agents were significant, the analysis reveals that listing prices of houses put on the market by sellers are not explained by the house features.

To the best of the authors’ knowledge, this is the first study to propose a hedonic approach to exploring the major determinants of listing prices of houses on sale on the Italian market. The listing behaviour of agents and sellers and the predicting power of the observable characteristics could address the use of listing prices in real estate valuations. At the same time, the potential presence of unobservable factors that affect the listing price could be a source of bias in estimating the value of houses.

This paper aims to present the dynamics of housing prices in Italian cities based on unpublished data with regional details from the late 1960s, half-yearly base, for all main Italian cities measuring the average prices for three city dimensions: city centre, sub-centres and outskirts or suburbs. It estimates the Italian long-term house price index, city based in real terms, and shows a combination of methods to deal with large time-series data.

This paper builds long-term cycles based on the city (real) data by estimating the common components of cointegrated time series and extracting the unobservable signals to build real house price index for sub-regions in Italy. Three different econometric methodologies are used: Johansen cointegration test and VAR models to identify the long-term pattern of prices at the estimated aggregate level; principal components to obtain the common (permanent and transitory) components; and signal extraction in ARIMA time series–model-based approach method to extract the unobserved time signals.

Results show three long-term cycle-trends during the period and identify several one-direction causal non-permanent relationships among house prices from different Italian areas. There is no evidence of convergence among regional’s house prices suggesting that the Italian housing prices converge inside the local market with only short diffusion effects at larger regional level.

Data are measured as the average price in squared meters, and the resulting index is not quality controlled.

The long-term trends on housing prices serve to implement further research and know deeply the evolution of Italian housing prices.

This paper contains new and unknown information about the evolution of housing prices in Italian regions and cities.

Diagrams are ubiquitous in economics and are uncontestably among the most used, if not the most important workhorses of economists, though they come in many forms. This essay examines the different uses of graphs and diagrams in the pioneering work of two Victorian economists, Stanley Jevons and Alfred Marshall. We stress the difference between their use as representations and as visual reasoning tools, a difference that became obscured in the twentieth century with the rise of econometrics.

This chapter enquires into the contribution of two British writers, Herbert Somerton Foxwell and Henry Riverdale Grenfell, who elaborated upon the hints provided by Jevons towards a description of long waves in the oscillations of prices. Writing two decades after Jevons, they witnessed the era of high prices turning into the great depression of the last quarter of the nineteenth century, the causes of which they saw in the end of bimetallism. Not only did they take up Jevons’s specific explanation of the long fluctuations, but they also based their discussion upon graphical representation of data and incorporated in their treatment a specific trait (the superposition principle) of the ‘waves’ metaphor emphasized by the Manchester statisticians in the 1850s and 1860s. Their contribution is also interesting for their understanding of crises versus depressions at the time of the emergence of the interpretation of oscillations as a cycle, which they have only partially grasped – as distinct from the approach of later long wave theorists.

This paper investigates the role of the border in Canadian and U.S. prices, based on a sample of highly disaggregated city-level retail prices. It finds substantial short-run differences in cross-border prices. While most of these are eliminated over time, long-run differences in the cross-border prices remain. These long-run cross-border differences average just over 20%, compared to mean long-run intranational price gaps of 7–9%. Short-run price differences are eliminated at similar rates in the cross-border and intranational data. Evidence from national average prices suggests the gap between cross-border prices has not narrowed during the recent depreciation of the Canadian dollar.

All enterprises, whether multimillion‐dollar corporations or small mom and pop businesses, have their ups and downs over the course of time. In the event of a single business failure, the effect on the local economy would likely be minimal. In the unfortunate event of multiple business failures or a recession, however, the negative effects on the local economy could be severe. To forecast and predict business fluctuations such as recessions, economists employ economic or cyclical indicators. These are trends based upon statistical data collected regularly on various aspects of the economy (e.g., employment, income, prices, industrial production, and manufacturing inventory).

The purpose of this study is to examine the influence of underwriter reputation on the valuation of Malaysian initial public offerings (IPOs).

This study employed cross-sectional multiple regression models to analyse the relationship between underwriter reputation and IPO valuation that included 466 IPOs listed on Bursa Malaysia from 2000 to 2017.

The results revealed that underwriter reputation had a significant negative association with IPO valuation. Firms that engaged the services of reputable underwriters had their IPO offer prices set lower than the intrinsic values during the listing. After incorporating firms' size, this study found a positive relationship between underwriter reputation and IPO valuation. Big firms (high quality) hired reputable underwriters for certification purposes as issuers were aware that the cost of hiring a reputable underwriter would be justified by increased transparency after listing. Therefore, firms that engaged reputable underwriters had approximately fair values since issuers assumed that the price would be close to the intrinsic value following enhanced transparency post-listing.

Future studies should focus on other non-financial factors, such as auditor reputation.

The present study provides new insights into the certification role of underwriters in valuing IPOs in the Malaysian market.

The paper proposes a statistical approach to investigate the role played by each house characteristic on the selling process. The paper aims to compare the impact of building characteristics, apartment characteristics and location on the bargaining outcome based on a case study in the Italian real estate market.

The paper first measures the overall contribution of characteristics and location to prices and bargaining outcome. Second, it studies the association between each characteristic and list price – the starting point of the selling process – and between each characteristic and selling price, i.e. the price agreed on to close a transaction. In order to focus on bargaining, the paper computed the association between each characteristic and bargaining outcome.

Structural characteristics empirically showed low association with bargaining outcome. In contrast, the paper found that location had a significant impact on the bargaining: location is the most important factor in negotiation. On the other hand, location amenities and disamenities may be attractive or unattractive depending on the buyers, and this could influence the bargaining outcome.

The paper findings confirm that factors influencing house prices are not always important factors in negotiation, in line with the literature on negotiation. Hedonic analysis showed the importance of house characteristics to explain house prices. Nevertheless, structural characteristics did not explain bargaining outcome variation. The findings also support the importance of a geographical segmentation to improve price prediction and bargaining outcome variation.