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The purpose of this paper is to outline a new approach to risk management that will create an innovative marketplace mechanism to deal with risk.

The paper discusses current risk management practice and proposes a novel new approach to risk management with an example.

This paper proposes the creation of a restructured mortgage product to transfer the home price volatility risk explicitly to investors and portfolio managers.

This paper proposes product innovation to transfer risk. The idea is original and is a conceptual viewpoint aimed at urging the industry to implement the concept. The recent credit crisis highlights the problem of unhedged home price volatility born by individual borrowers. As borrowers are not equipped to hedge this risk, it is important to restructure the mortgage to explicitly transfer the risk of home price volatility to investors and mortgage lenders.

Large-scale farm management in China has developed rapidly in recent years. Large-scale farmers face substantial operating risks, requiring extensive price risk management. However, the agricultural insurance and futures markets in China are incomplete. This study aims to analyze the price-risk-management behaviors of large-scale farmers under incomplete market conditions, with a focus on the interconnections between large scale farmers' subjective preferences (risk preferences, time preferences), liquidity constraints and their price risk management.

The authors construct an analysis framework to reveal the impact of large-scale farmers' risk preferences, time preferences and liquidity conditions on their price-risk-management behaviors under incomplete market conditions. Using data from field surveys and subjective preference experiments involving 409 large-scale grain farmers in China, an empirical analysis was conducted using the bivariate probit model.

The results show that risk-averse farmers will use risk transfer (such as contract farming) and risk diversification (such as multi-period sales) to avoid price risk. However, farmers subject to liquidity constraints and strong time preferences will not choose risk diversification, and the interaction between time preferences and liquidity constraints will strengthen this decision. The larger the farm-management scale, the greater the impact.

The authors focus on rapidly developed large-scale farm management in China. Appropriate price risk management is required by large-scale farmers due to their substantial operating risks. Considering the incomplete conditions of agricultural insurance and futures markets, the results of this study will help identify behavioral characteristics of large-scale farmers and optimize their price-risk-management strategies, further stabilizing large-scale farm management.

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.

We examine the behavior of the Russian stock market as one of the leading indices of economic health, reflecting investors’ expectations about future returns. The sample period includes the global financial crisis, a recovering period, and the recent crisis in the Russian economy 2014–2015.

We assume that the Russian stock market strongly depends on the global market, but the market is not fully integrated. This chapter investigates whether specific risk factors such as high dependence of the Russian economy on oil prices and currency volatility are priced in the Russian stock market, using International CAPM with time-variant parameters and conditional heteroskedasticity. The results show that the global financial crisis has had a profound negative impact on the Russian market, and that the expected return and liquidity has declined. The risk of investing in the Russian market is estimated as higher than in the developed market and even in other emerging markets after the global recession. We find that oil price exposure and currency risk to be priced in the Russian stock market and indicate that international investors require higher compensation for bearing these risks. The price of the currency risk has decreased since the implementation of the floating exchange rate regime by the Central Bank of Russia in 2014, but still significant.

Some opportunities to overcome the present stagnation and drive for a sustainable development are discussed.

Steel price uncertainty exposes pipeline projects that are inherently capital intensive to the risk of cost overruns. The current study proposes a hedging methodology for tackling steel pipeline price risk by deploying Asian option contracts that address the shortcomings of current risk mitigation strategies.

A stepwise methodology is introduced, which uses a closed-form formula as an Asian option valuation method for calculating this total expenditure. The scenario analysis of three price trends examines whether or not the approach is beneficial to users. The sensitivity analysis then has been conducted using the financial option Greeks to assess the effects of changes in volatility in the total price of the option contracts. The total price of the Asian options was then compared with those of the European and American options.

The results demonstrate that the Asian option expenditure was about 1.87% of the total cost of the case study project. The scenario analysis revealed that, except for when the price followed a continuous downward pattern, the use of this type of financial instrument is a practical approach for steel pipeline price risk management.

This approach is founded on a well-established financial options theory and elucidates how pipeline project participants can deploy Asian option contracts to safeguard against steel price fluctuations in practice.

Although the literature exists about the theory and application of financial derivative instruments for risk management in other sectors, their application to the construction industry is infrequent. In the proposed methodology, all participants involved in fixed price pipeline projects readily surmount the risk of exposure to material price fluctuations.

Whether stock returns are linked to exchange rate changes and whether foreign exchange risk is priced in a domestic context are less conclusive and thus still subject to a great debate. The purpose of this paper is to provide new empirical evidence on these two inter‐related issues, which are critical to investors and corporate risk management.

This paper applies two different econometric approaches: Nonlinear Seemingly Unrelated Regression (NLSUR) via Hansen's Generalized Method of Moment (GMM) and multivariate GARCH in mean (MGARCH‐M) to examine the exchange rate exposure and its pricing.

Using industry data for Japan, similar to previous studies, foreign exchange risk is not priced based on the test of an unconditional two‐factor asset pricing model. However, strong evidence of time‐varying foreign exchange risk premium and significant exchange rate betas are obtained based on the tests of conditional asset pricing models using MGARCH‐M approach where both conditional first and second moments of industry returns and risk factors are estimated simultaneously.

The strong empirical evidence found in this study implies that corporate currency hedging not only results in more stable cash flows for a firm, but also reduces its cost of capital, and hence is justifiable.

This paper conducts an in‐depth investigation regarding the exchange rate exposure and its pricing by utilizing two different econometric approaches: NLSUR via Hansen's GMM and MGARCH‐M. In doing so, a more reliable conclusion about the exchange rate exposure and its pricing can be drawn.

The purpose of this paper is to demonstrate how crop price insurance premium can be calculated using an option pricing model and how insurers can transfer underwriting risks in the futures market.

Based on data from spot and futures market in China, this paper develops an improved B-S model for the calculation of crop price insurance premium and tests the possibility of hedging underwriting risks by insurance firms in the futures market.

The authors find that spot price of crops in China can be estimated with agricultural commodity futures prices, and can be taken as the insured price for crop price insurance. The authors also find that improved B-S model yields better estimation of crop price insurance premium than traditional B-S model when spot price does not follow geometric Brownian motion. Finally, the authors find that hedging can be one good alternative for insurance firms to manage underwriting risks.

This paper develops an improved B-S model that is data-driven in nature. Insured price of the crop price insurance, or the exercise price used in the B-S model, is estimated from a co-integration model built on spot and futures market price series. Meanwhile, distributional patterns of spot price series, one important factor determining the applicability of B-S model, is factored into the improved B-S model so that the latter is more robust and friendly to data with varied distributions. This paper also verifies the possibility of hedging of underwriting risks by insurance firms in the futures market.