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The lack of transaction data has been identified as one of the major obstacles for the empirical evaluation of real option. Quigg’s study in 1993 was one of the first to empirically estimate the premium for the option of waiting to develop using data from 2,700 land sales in Seattle. This study modified Quigg’s methodology and applied it to estimate the premium for the option of waiting to develop based on a sample of data from 2,286 property transactions in the UK collected over a 14‐year sample period from 1984 to 1997. Based on a one‐factor contingent claim valuation model, we found that the average premiums for the timing options were 28.78 percent for office sector, 25.75 percent for industrial sector and 16.06 percent for retail sector. We also tested the robustness of the theoretical‐based land value estimates in explaining the market‐based land values. The regression results showed a statistically significant relationship in logarithm form between the market‐based residual land value and the model‐based land values (with embedded timing option), with R² of 0.75, 0.79 and 0.82 for office, industrial and the retail sectors respectively.

This chapter analyses the ability of some structural models to predict corporate bankruptcy. The study extends the existing empirical work on default risk in two ways. First, it estimates the expected default probabilities (EDPs) for a sample of bankrupt companies in the USA as a function of volatility, debt ratio, and other company variables. Second, it computes default correlations using a copula function and extracts common or latent factors that drive companies’ default correlations using a factor-analytical technique. Idiosyncratic risk is observed to change significantly prior to bankruptcy and its impact on EDPs is found to be more important than that of total volatility. Information-related tests corroborate the results of prediction-orientated tests reported by other studies in the literature; however, only a weak explanatory power is found in the widely used market-to-book assets and book-to-market equity ratio. The results indicate that common factors, which capture the overall state of the economy, explain default correlations quite well.

This paper examines the time‐series behaviour of house prices for the four Asian markets, namely, Hong Kong, Singapore, Tokyo and Taipei, by using structural time‐series methodology. The paper assumes two types of trend models to characterise and compare the long‐run movement of house prices. It also examines the cyclical pattern hidden in the series. The long‐run trend rate in these markets ranged between approximately 1.6 and 3.2 per cent per annum. Hong Kong, Singapore and Taipei have relatively higher figures, which could be expected in light of the rapidly growing economies. Surprisingly, their cyclical patterns were fairly similar, although causes of the cycles differed. The markets were found to have stochastic cycles of around one year, two to four years and seven to ten years, which were consistent with previous findings on real business cycles commonly observed internationally in other macroeconomic time series. However, the found stochastic nature suggests all these markets are not in a steady state and is still changing.

Analyses the diversification effects of the portfolio holdings of ten selected listed property investment companies on the co‐movement of the stock prices for an 11‐year period from 1983 to 1994. The long‐term common trends in the sample securitized property companies are tested using the bivariate and the Johansen’s multivariate cointegration methodologies. The empirical evidence does not reject the hypothesis that prediction of the price variation of one stock based on the change in the price of another comparable stock is possible in the long term. Also, the price convergence process was not dependent on whether two companies are practising the same diversification and/or specialisation policies. However, there is evidence that companies with large portfolio holdings can influence the stock prices of property companies with smaller portfolio holdings. This implies that arbitraging the small stocks by reading the price movement of the large firms could give possible abnormal returns to the investor.

The main theme of this volume is credit risk and credit derivatives. Recent developments in financial markets show that appropriate modeling and quantification of credit risk is fundamental in the context of modern complex structured financial products. Moreover, there is a need for further developments in our understanding of this important area. In particular modeling defaults and their correlation has been a real challenge in recent years, and still is. This problem is even more relevant after the so-called subprime crisis that hit in the summer of 2007. This makes the volume very timely and hopefully useful for researchers in the area of credit risk and credit derivatives.

This paper aims to explore the role of the financial intelligence unit in Tanzania in fighting against money laundering and its predicate offences, examine its potential in controlling the problem and describe factors that undermine its efficacy.

The doctrinal research approach is used to analyse Tanzania’s anti-money laundering law and appraise its effectiveness in facilitating operations of the financial intelligence unit in fighting against money laundering and its predicate offences. The law-in-context approach is applied to interrogate the anti-money laundering law and describe non-law factors that impinge on the efficiency of Tanzania’s financial intelligence unit.

The law vests the financial intelligence unit with powers to perform a number of functions that are significant in fighting against money laundering and its predicate offences in Tanzania. The unit has been instrumental in curbing money laundering. The efficacy of this anti-money laundering agency, which is at its infancy stage, is emasculated by law-related, institutional and non-law factors. These factors undercut the potency of the agency.

There is a need for Tanzania to undertake policy, legislative and institutional reforms to augment the efficacy of the financial intelligence unit. The reforms should be implemented concurrently with other measures, which will enhance the country’s anti-money money laundering regime.

This paper applies the legal and non-law perspectives to evaluate the effectiveness of the financial intelligence unit as an essential component of Tanzania’s anti-money laundering regime. It proposes law-related and non-law approaches to augment the efficiency of the unit and the country’s anti-money laundering regime in general.