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In capital market, share prices of listed companies generally respond to accounting information. In 1995, Ohlson proposed a share valuation model based on two accounting indicators: company residual income and book value of net asset. In 2000, Zhang introduced the thought of option pricing and developed a new accounting valuation model. The purpose of this paper is to investigate the valuation deviation and the influence of some market transaction characteristics on pricing models.

The authors use listed companies from 1999 to 2013 as samples, and conduct comparative analysis with multiple regression.

The main findings are: first, the accounting valuation model is applicable to the capital market as a whole, and its pricing effect increases as years go by; second, in the environment of out capital market, the maturity of investors is one of important factors that causes the information content of residual income less than that of profit per share and lower pricing effect of valuation models; third, when the price earning (PE) of listed companies reaches certain level, the overall explanation capacity of accounting valuation models will become lower as PE gets higher; fourth, as for companies with higher turnover rate and more active transaction, the pricing effect of accounting valuation model is obviously lower; fifth, the pricing effect of accounting valuation models in a bull market is lower than in a bear market.

These findings establish connection between accounting valuation and market transaction characteristics providing an explorable orientation for the future development of accounting valuation theories and models.

The purpose of this paper is to investigate changes in the commercial real estate market dynamics as a function of and conditional to the shifts in market state-space environment that can influence agent responses.

The analytical design uses a comparative computational experiment to address the performance of property assets in the current market based on comparison with prior structural patterns. The latent variables developed across market sectors are used to test agent behavior contingent on the perspectives of capital asset pricing conditionals (CAPM) and a behavioral momentum/herd construct. The state-space momentum analysis can assist the comparative analysis of current levels and shifts in property asset performance given the issues that have arisen with the financial crisis of 2007-2009.

An analytic approach is employed framed by a situation-dependent model. This frame considers risk profiles characterizing the perspectives and preferences guiding a delineated market state. This perspective is concerned with the possibility of shifts in market momentum and representativeness conditioning investor expectations. It is observed that the current market (post-crisis) has changed significantly from the prior operations (despite the diversity observed in prior market states). The dynamics of initial findings required an additional test anchored to the performance of the general capital market and the real economy across time. This context supports the use of a modified CAPM model allowing the consideration of opportunity cost in a space-time dynamic anchored with the consideration of equity, debt, riskless asset and liquidity options as they varied for the representative agents operating per market state.

This paper integrates neoclassical and behavioral economic constructs. Combines asset pricing with prospect theory and allows the calculation of endogenous time-preferences, risk attitudes and formulation and testing of hyperbolic discounting functions.

The research shows that market structure and agent behavior since the financial crisis has changed from the investment and valuation perspectives operating as observed and measured from 1970 up to 2007. In contradiction to the long-term findings of Reinhart and Rogoff (2008), but in compliance with common perspectives and decision heuristics often employed by investors, this time things have changed! Discounting and expected rates of return are dynamic and are hyperbolic and not constant. Returns and investment for property assets are situational (market state-space specific) and offer a distinct asset class, not appropriately estimated by many of the traditional financial models.

Assist in supporting insights to measure in errors and equations that result in inefficient resource allocation and beta discounting that supports the financial crisis created by assets subject to long-term decision needs (delta function).

The paper offers a combination and comparison of neoclassic asset pricing using a modified CAPM (two-pass) approach within the structural frame of Kahneman and Tversky’s (1979) prospect theory. This technique allows the consideration of the effects of present bias, beta-delta functions and the operation of the Allais Paradox in market states that are characterized by gains and losses and thus risk aversion and risk seeking behavior. This ability for differentiation allows for the development of endogenous time-preferences and hyperbolic discounting factors characteristic of commercial property investment.

The purpose of this paper is to investigate the strategy that a turnaround in the USA will portend a turnaround in the UK's economy and property market. For this strategy to operate, it is assumed that the capital and property markets in and between the two nations are highly integrated with endogenous pricing functions.

Given the endogenous assumptions of the conjectured research statement, tests of integration (or segmentation) between two capital and property markets are conducted. Correlation, tracking error analysis, and a multiple systematic risk factor model are used to test the pricing relationships. The methodological form employs variant macroeconomic variable pricing models (MVM) of alternative combinations of systematic affects operating across and between the national markets.

Pricing integration is noted between the UK and US capital markets, while the property markets are economically and statistically segmented. Opportunities for arbitrage based on different prices/returns for equivalent risk exposures are statistically observed between the UK and USA. The effect is that systematic pricing between the two markets cannot be addressed solely by diversification options. This infers a potential for arbitrage (statistically, strategically or in practice) is possible, given that systematic risk exposures between the two markets are not equivalently priced across cyclical phases. In this context it is inferred that the probable measure of pricing differences across the two markets is more than a cyclical lag effect.

The paper delineates the degrees of integration/segmentation in the UK and US property and capital markets as a function of systematic risks in changing economic conditions. These differences support the existence of statistical arbitrage and the specification of investment behaviour as a function of differencing pricing expectations. These findings can assist in the formulation of investment and hedging strategies to assist in managing international portfolios subject to cyclical market exposures. This paper contributes to an understanding of and foundation for testing the nature and impact of cycles on property investment performance as a function of pricing changes.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

The purpose of this paper is to test a discrete time asset pricing model where a non‐marketable asset (human capital), along with other factors predicting stock returns, explain risk return relationship. The paper will add to the literature on risk return relationship with human capital by investigating the hypothesis that human capital is a significant factor affecting stock prices.

The dynamic inter‐linkages of factors representing financial and human components of wealth in predicting stock returns is tested in the Indian market for the period of 1996:04 to 2005:06. The procedures employed include Granger causality tests, impulse response functions and seemingly unrelated regression estimates.

Empirical findings validate the model that including human capital as a proxy for aggregate wealth in the economy can better predict stock prices than the standard empirical capital asset pricing model. There is a Granger cause relationship between security prices and labor income and it is further concluded that labor and dividend are significant factors affecting security prices.

This is one of the first papers to study the human capital aspect in predicting stock returns in the Indian market. In addition, the paper provides important insights into the causal relationship of human capital and market return in explaining the risk return relationship.

Financial asset return series usually exhibit nonnormal characteristics such as high peaks, heavy tails and asymmetry. Traditional risk measures like standard deviation or variance are inadequate for nonnormal distributions. Value at Risk (VaR) is consistent with people's psychological perception of risk. The asymmetric Laplace distribution (ALD) captures the heavy-tailed and biased features of the distribution. VaR is therefore used as a risk measure to explore the problem of VaR-based asset pricing. Assuming returns obey ALD, the study explores the impact of high peaks, heavy tails and asymmetric features of financial asset return data on asset pricing.

A VaR-based capital asset pricing model (CAPM) was constructed under the ALD that follows the logic of the classical CAPM and derive the corresponding VaR-β coefficients under ALD.

ALD-based VaR exhibits a minor tail risk than VaR under normal distribution as the mean increases. The theoretical derivation yields a more complex capital asset pricing formula involving β coefficients compared to the traditional CAPM.The empirical analysis shows that the CAPM under ALD can reflect the β-return relationship, and the results are robust. Finally, comparing the two CAPMs reveals that the β coefficients derived in this paper are smaller than those in the traditional CAPM in 69–80% of cases.

The paper uses VaR as a risk measure for financial time series data following ALD to explore asset pricing problems. The findings complement existing literature on the effects of high peaks, heavy tails and asymmetry on asset pricing, providing valuable insights for investors, policymakers and regulators.

This paper has used account-level data of corporate and retail borrowers, assessed their credit risk through the risk-neutral principle and examined its implication on loan pricing.

It derives the capital charge and credit risk-premium for expected and unexpected losses through a risk-neutral approach. It estimates the risk-adjusted return on capital as the pricing principle for loans. Using GMM regression, the article has assessed the determinants of risk-based pricing.

It has been found that risk-premium is not reflected in the current loan pricing policy as per Basel II norms. However, the GMM estimation on RAROC can price risk premium and probability of default, LGD, risk weight, bank beta and capital adequacy, which are the prime determinants of loan pricing. The average RAROC for retail loans is more than that of corporate loans despite the same level of risk capital requirement for both categories of loans. The robustness tests indicate that the RAROC method of loan pricing and its determinants are consistent against the time and type of borrowers.

The RAROC method of pricing effectively assesses the inherent risk associated with loans. Though the empirical findings are confined to the sample bank, the model can be used for any bank implementing the Basel principle of risk and capital assessments.

The article has developed and validated the model for estimating RAROC, as per Basel II guidelines, for loan pricing that any bank can use.

It has developed the risk-based loan pricing model for retail and corporate borrowers. It has significant practical utility for banks to manage their risk, reduce their losses and productively utilise the public deposits for societal developments.

The article empirically validated the risk-neutral pricing principle using a unique 1,520 retail and corporate borrowers dataset.

The purpose of this paper is to present a methodology based on the transactional asset pricing approach (TAPA) and to illustrate the application of TAPA within the context of professional property valuation.

The TAPA is a novel analytical valuation methodology recasting the traditional derivations of the income approach techniques, including DCF, from a transactional perspective based on the principle of inter-temporal transactional equity, instead of the conventional investor-specific view originating from I. Fisher (1907, 1930).

The authors present DCF analysis as a specific case of a more general TAPA approach to valuation under the income method. This also leads to novel analytical derivations of the Direct income capitalization, Gordon, Inwood, Hoskold and Ring models. Based on the TAPA framework, the authors also research the value-enhancing effects of benchmark market volatility on the subject property value and conclude that such effects can be statistically significant depending on the DCF analysis period.

The research has a direct bearing on time-variable discount rate forecasting capabilities, as it uses a time-variant structure for the discount rates.

Using the US Case-Shiller and BLS rental indices as a valuation benchmark, the paper contains an example of applying the general TAPA framework to value a notional property under a TAPA’s DCF version. Such property valuations can be easily replicated in practice – especially in the context of equitable/fair value determination under the International Valuation Standards Council valuation standards.

TAPA is a deductive principles-based theory of asset valuation especially fit for the transactional and illiquid asset valuation contexts – thus enabling a more efficient pricing for such assets in a sense of reflecting the transactional interests of the parties more closely than achievable under the conventional valuation methods.

TAPA is an original filiation of research with roots going as far back as Aristotelian Catallactics. It contains analytical formalizations of certain transactional equity principles.

Daniel and Titman (1997) contend that the Fama‐French three‐factor model’s ability to explain cross‐sectional variation in expected returns is a result of characteristics that firms have in common rather than any risk‐based explanation. The primary aim of the current paper is to provide out‐of‐sample tests of the characteristics versus risk factor argument. The main focus of our tests is to examine the intercept terms in Fama‐French regressions, wherein test portfolios are formed by a three‐way sorting procedure on book‐to‐market, size and factor loadings. Our main test focuses on ‘characteristic‐balanced’ portfolio returns of high minus low factor loading portfolios, for different size and book‐to‐market groups. The Fama‐French model predicts that these regression intercepts should be zero while the characteristics model predicts that they should be negative. Generally, despite the short sample period employed, our findings support a risk‐factor interpretation as opposed to a characteristics interpretation. This is particularly so for the HML loading‐based test portfolios. More specifically, we find that: the majority of test portfolios tend to reveal higher returns for higher loadings (while controlling for book‐to‐market and size characteristics); the majority of the Fama‐French regression intercepts are statistically insignificant; for the characteristic‐balanced portfolios, very few of the Fama‐French regression intercepts are significant.