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The purpose of this paper is to examine the risk neutral and non-risk neutral pricing of Singapore Real Estate Investment Trusts (S-REITs) via comparing the average of the individual ratios (of deviation between expected and observed closing price/observed closing price) with the ratio (of standard deviation/mean) for closing prices via the binomial options pricing tree model.

If the ratio (of standard deviation/mean) ratio > the ratio (of deviation between expected and observed closing price/observed closing price), then the deviation of closing prices from the expected risk neutral prices is not significant and that the S-REIT is consistent with risk neutral pricing. If the ratio (of deviation between expected and observed closing price/observed closing price) is greater, then the S-REIT is not consistent with risk neutral pricing.

Capitacommercial Trust (CCT), Capitamall Trust (CMT) and Keppel Real Estate Investment Trust (REIT) have large positive differences between the two ratios (39.86, 30.79 and 18.96 percent, respectively), implying that these S-REITs are not trading at risk neutral pricing. Suntec REIT has a small positive difference of 2.35 percent between both ratios, implying that it is trading at risk neutral pricing. Ascendas REIT has the largest negative difference between the two ratios at −4.24 percent, to be followed by Mapletree Logistics Trust at −0.44 percent. Both S-REITs are trading at risk neutral pricing. The analysis shows that CCT, CMT and Keppel REIT exhibit risk averse pricing.

Results are consistent with prudential asset allocation for viable S-REIT portfolio investing but that not all these S-REITs exhibit strong market efficiency in their pricing.

Pricing may be risk neutral over a certain period but investor sentiments, fear of risks and speculative activities could affect an S-REIT’s risk neutrality.

With enhanced risk diversification activities, the S-REITs should attain risk neutral pricing.

Virtually no research of this nature has been undertaken for S-REITS.

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.

Nowadays, uncertainty in market demand poses considerable risk to the retailers that supply the market. On the other hand, the risk-averse behaviors of retailers toward risk may have evolved over time. Considering a supply chain including a manufacturer and a population of retailers, the authors intend to investigate how the population of retailers tends to evolve toward risk-averse behavior. Moreover, this study aims to evaluate the effects of wholesale-retail price of manufacturer on evolutionary stable strategy (ESS) of the retailers.

Due to market uncertainty, a supply chain with a population of risk-averse and risk-neutral retailers was investigated. The wholesale pricing strategy is determined by a manufacturer acting as a leader, while retailers who make order quantity decisions act as followers. An integrated Cournot duopoly equilibrium and evolutionary game theory (EGT) approach has been used to model this situation.

A numerical real-world case study using Iran Khodro Company is analyzed by applying the proposed EGT approach. The study provides managerial insights to the manufacturer as well as retailers in developing their strategies. Results showed that risk behavior of retailers significantly affects optimal wholesale/retail price, profits and ESS. In the long term, the retailers tend to have a risk-neutral behavior to gain more profit. In the short term, if a retailer choses risk-averse strategy, in the long term, it will change its strategy to obtain more profit and remain in the competitive market.

The contributions in this research are fourfold. First, ESS concept to investigate the risk-averse or risk-neutral attitudes of the retailers was used. Second, the uncertain risk behavior of the competing retailers was considered. Third, the effect of varying wholesale pricing was investigated. Fourth, the equilibrium wholesale and retail prices have been obtained by considering uncertainty demand and risk.

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

This paper investigates the relative importance of the skewness and kurtosis of the risk neutral distribution for pricing KOSPI200 options. The skewness and kurtosis are estimated from non parametric method of Bakshi, Kapadia, and Madan (2003) and the parametric method of Corrado and Su (1996). We show that the skewness of the risk neutral distribution is more important factor than the kurtosis irrespective of the estimation method, the definition of pricing errors, the moneyness, the type of options and a period of time.

Reviews previous research on the timing of employee stock option exercise decisions and share price performance before and after insider trading. Analyses the 1992‐1993 exercise behaviour of top executives at 65 large US firms using the Black‐Scholes (1973) value (less anticipated dividends) as a benchmark to compare with the intrinsic value (market price minus exercise price) at the date of exercise. Finds options are exercised when the two values are roughly equal, i.e. that executives’ decisions are not risk‐averse or biased by private information. Also shows a tendency for the subsequent change in share prices to be lower when the intrinsic value is less than the Black‐Scholes value at the time of exercise. Considers consistency with other research and the implications of the findings.

This paper reports findings from a series of laboratory asset markets. Although stakes in these markets are modest, asset prices display a substantial equity premium (risky assets are priced substantially below their expected payoffs) – indicating substantial risk aversion. Moreover, the differences between expected asset payoffs and asset prices are in the direction predicted by standard asset-pricing theory: assets with higher beta have higher returns. This work suggests ways to separate the effects of risk aversion from competing explanations in other experimental environments.

The topic of volatility measurement and estimation is central to financial and more generally time-series econometrics. In this chapter, we begin by surveying models of volatility, both discrete and continuous, and then we summarize some selected empirical findings from the literature. In particular, in the first sections of this chapter, we discuss important developments in volatility models, with focus on time-varying and stochastic volatility as well as nonparametric volatility estimation. The models discussed share the common feature that volatilities are unobserved and belong to the class of missing variables. We then provide empirical evidence on “small” and “large” jumps from the perspective of their contribution to overall realized variation, using high-frequency price return data on 25 stocks in the DOW 30. Our “small” and “large” jump variations are constructed at three truncation levels, using extant methodology of Barndorff-Nielsen and Shephard (2006), Andersen, Bollerslev, and Diebold (2007), and Aït-Sahalia and Jacod (2009a, 2009b, 2009c). Evidence of jumps is found in around 22.8% of the days during the 1993–2000 period, much higher than the corresponding figure of 9.4% during the 2001–2008 period. Although the overall role of jumps is lessening, the role of large jumps has not decreased, and indeed, the relative role of large jumps, as a proportion of overall jumps, has actually increased in the 2000s.

Many governments are taking measures in support of small and medium-sized enterprises (SMEs) to mitigate the economic impact of the COVID-19 outbreak. This paper presents a theoretical model for evaluating various government measures, including insurance for bank loans, interest rate subsidy, bridge loans and relief of tax burdens.

This paper distinguishes a firm's intrinsic value and book value, where a firm can lose its intrinsic value when it encounters cash-flow crunch. Wang transform is applied to (1) calculating the appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs, (2) describing the frailty distribution for SMEs and (3) defining banks' underwriting capability and overlap index in risk selection.

Government support for SMEs can be in the form of an appropriate level of interest rate subsidy payable to incentivize banks to issue more loans to SMEs and to extend the loan maturity of current debt to the SMEs.

More available data on bank loans would have helped strengthen the empirical studies.

This paper makes policy recommendations of establishing policy-oriented banks or investment funds dedicated to supporting SMEs, developing risk indices for SMEs to facilitate refined risk underwriting, providing SMEs with long-term tax relief and early-stage equity-type investments.

The model highlights the importance of providing bridge loans to SMEs during the COVID-19 disruption to prevent massive business closures.

This paper provides an analytical framework using Wang transform for analyzing the most effective form of government support for SMEs.