Some Financial Problems in the Light of EMM Results:Asset Pricing and Efficient Portfolio Allocation

Discussing results in asset pricing and efficient portfolio allocation,we show that mixed success and errors in these results often follow from a lack of information about the asset return distribution and wrong assumptions about its properties.Some mistakes in asset pricing come from the assumption of symmetry in return distributions.Some errors in efficient portfolio allocation follow from Markowitz’s approach when applying it to portfolio optimization of skewed asset returns.The Extended Merton model(EMM),generating skewed return distributions,demonstrates that(i)in skewed asset returns,the variance is not an adequate measure of risks and(ii)positive skewness in the asset returns comes together with a high default probability.Thus,the maximization of the mean portfolio returns and skewness with controlled variance used in mainstream papers can critically increase portfolio risks.We present the new settings of the optimal portfolio allocation problem leading to less risky efficient portfolios than the solutions suggested in all previous papers.

The term structure of Sharpe ratios and arbitragefree asset pricing in continuous time

Motivated by financial and empirical arguments and in order to introduce a more flexible methodology of pricing,we provide a new approach to asset pricing based on Backward Volterra equations.The approach relies on an arbitrage-free and incomplete market setting in continuous time by choosing non-unique pricing measures depending either on the time of evaluation or on the maturity of payoffs.We show that in the latter case the dynamics can be captured by a time-delayed backward stochastic Volterra integral equation here introduced which,to the best of our knowledge,has not yet been studied.We then prove an existence and uniqueness result for time-delayed backward stochastic Volterra integral equations.Finally,we present a Lucas-type consumption-based asset pricing model that justifies the emergence of stochastic discount factors matching the term structure of Sharpe ratios.

An impact assessment of the COVID‑19 pandemic on Japanese and US hotel stocks

This study proposes two new regime-switching volatility models to empirically analyze the impact of the COVID-19 pandemic on hotel stock prices in Japan compared with the US,taking into account the role of stock markets.The first model is a direct impact model of COVID-19 on hotel stock prices;the analysis finds that infection speed negatively affects Japanese hotel stock prices and shows that the regime continues to switch to high volatility in prices due to COVID-19 until September 2021,unlike US stock prices.The second model is a hybrid model with COVID-19 and stock market impacts on the hotel stock prices,which can remove the market impacts on regime-switching volatility;this analysis demonstrates that COVID-19 negatively affects hotel stock prices regardless of whether they are in Japan or the US.We also observe a transition to a high-volatility regime in hotel stock prices due to COVID-19 until around summer 2021 in both Japan and the US.These results suggest that COVID-19 is likely to affect hotel stock prices in general,except for the influence of the stock market.Considering the market influence,COVID-19 directly and/or indirectly affects Japanese hotel stocks through the Japanese stock market,and US hotel stocks have limited impacts from COVID-19 owing to the offset between the influence on hotel stocks and no effect on the stock market.Based on the results,investors and portfolio managers should be aware that the impact of COVID-19 on hotel stock returns depends on the balance between the direct and indirect effects,and varies from country to country and region to region.

Does the EVA valuation model explain the market value of equity better under changing required return than constant required return?

Through the Economic-Value-Added(EVA)valuation model,the expected market value of equity can be determined by adding the book value of equity with the present value of expected EVAs under the assumption of constant required return and constant return on equity.The equation of EVA valuation model has taken its shape under the assumption of constant required return and constant return on equity.However,a large body of empirical evidence indicates that required rate of return never remain constant.The EVA-valuation model formulated under constant required return cannot be implemented under the scenario of changing required return.In this study,we explored whether the EVA valuation model could be implemented under changing required return by making any changes in the model and found that it could be implemented under the scenario of changing required return by replacing the book value of the equity of the existing model with the present value of required earnings or normal market earnings.We further examined whether the explanatory ability of the EVA valuation model under the assumption of changing required return is better than that of the valuation model under the assumption of constant required return.Relative information content analyses were conducted by considering sample of the intrinsic value of equities determined by valuation models and the market value of equities of 69 large-cap,88 mid-cap,and 79 small-cap companies.The results showed that the EVA-based valuation model with changing normal market return outperformed the EVA-based valuation model with constant required return.

Contingent convertible lease modeling and credit risk management

The main objective of this study is to determine a lease agreement to finance an investment project and a solution for managing credit risk.This study investigates three types of contingent leases to reduce the costs associated with bankruptcy and compensate for the lessor’s position.A leasing defaultable contract allows the lessor to obtain the rent that will be recovered if the lessee defaults.A leasing convertible contract can be automatically converted into shares when certain default conditions related to the cash flows generated by the firm are met.These conditions are triggered by the ratio of the firm’s value and leasing payments.A Defaultable-Convertible-Leasing contract with a payback option grants the lessor the right but not the obligation to convert the remaining lease payments into stocks or to break up the contract and pick up the rented equipment when the firm reaches the default threshold.These contracts are motivated by contributing to the range of risk-management strategies by adding more flexibility to standard leasing contracts and contingent rents.Closed-form securities pricing solutions are set forward in a dynamic model for firms with existing assets and a growth option financed by shares and a contingent lease.Risk-neutral pricing theory and the backward induction method are used to determine the pricing of corporate securities.Numerical analysis shows that leasing convertible contracts and defaultable-convertible contracts with payback options impact the service value of the leased asset,maturity,and inefficiencies resulting from insolvency and asset substitution.An optimal conversion rate reduces inefficiencies,thus making the leasing convertible contract and defaultable-convertible-leasing contract with payback option a reliable solution to ensure business continuity and loss coverage of the leasers upon default.

Implications of Fama-French Models and Critical Evaluation of Cost of Equity Approach in Explanation of Variations in Expected Stock Returns

CAPM theory that solves relationship between asset return and asset risk for potential investment project by CML and SML,is illustrated in the first section as an introduction of further analysis of corporate valuation techniques.Fama and French three factor model is perceived as a revision of CAPM,although it stills has severe weaknesses.CAPM theory solves relationship between asset return and asset risk for potential investment project by CML and SML.

Can news-based economic sentiment predict bubbles in precious metal markets?

This study examines the role of market sentiment in predicting the price bubbles of four strategic metal commodities(gold,silver,palladium,and platinum)from January 1985 to August 2020.It is the first to investigate this topic using sentiment indices,including news-based economic and consumer-based sentiments developed using different methods.We observed the role of sentiment as a reliable indicator of future bubbles for some metal commodities and found that bubbles were regularly concomi-tant with bearish sentiments for gold and platinum.Moreover,gold and palladium were the only commodities that experienced a bubble during the COVID-19 pandemic.Overall,our findings suggest inclusion of sentiment to the model that predicts the price bubbles of precious metals.

Discount Rate of China’s New Energy Power Industry

Under the dual pressures of energy crisis and environmental pollution,China’s new energy power industry has become a focal point for environmental management and requires greater investment.In this context,as a significant input of investment projects,discount rate requires a well-calibrated evaluation because new energy power investment projects are highly capital intensive.The main objective of this paper is to evaluate the discount rate of China’s new energy power industry.First,we use Moving Average to correct the parameters of capital asset pricing model(CAPM)and weighted average cost of capital,which extends the literature on the avoidance of CAPM noise information problem.Second,we study the industry-level annual discount rates of mainly China’s new energy power industries,including hydropower,nuclear power,wind power,and photovoltaic power industries for the period of 2014-2019.The results show that discount rates in China’s new energy power industries evolved differently between the years of 2014-2019 with average annual discount rates being 7.56%,5.83%,5.60%,and 8.64%,for the hydropower,nuclear power,wind power,and photovoltaic power industries,respectively.In 2019,the four annual discount rates were highest for the photovoltaic power industry(8.66%),followed by hydropower(7.17%),wind power(5.72%),and nuclear power industry(5.26%).Forecasting to 2020 from the 2019 evaluation base period,the discount rates are 6.37%,5.00%,6.57%,and 9.05%for the photovoltaic power,hydropower,wind power,and nuclear power industries,respectively.Under the different capital structures,their forecasts for the photovoltaic power,hydropower,wind power,and nuclear power industries in 2020 are,respectively,within[4.35%,9.24%],[3.92%,7.10%],[4.58%,10.40%],[5.46%,14.81%].We also discussed more details on capital structure and forecast period of discount rates for China’s new energy power industries.Our analysis shows that it is necessary to establish a new energy power industry database and steadily promote the implementation of policies.

A Binomial Model of Asset and Option Pricing with Heterogeneous Beliefs

This paper provides a difference-in-opinions equilibrium framework for pricing asset and option in a multi-period binomial economy with heterogeneous beliefs.Agents agree to disagree about their beliefs on the probability and asset return in each state of nature.By constructing a consensus belief,we examine the impact of heterogeneous beliefs on market equilibrium.We show that agents'wealth shares are expected to remain the same under the consensus belief,although they are expected to increase under their own beliefs.Also large disagreement leads to lower risk premium,while high disagreement on the future return in up state(down state)leads to lower(higher)risk-free rate and expected return for the risky asset.Furthermore,under the consensus belief,the implied volatility of the call options exhibits some observed patterns widely documented in option markets.

Analysis of High Frequency Data in Finance:A Survey

This study examines the use of high frequency data in finance,including volatility estimation and jump tests.High frequency data allows the construction of model-free volatility measures for asset returns.Realized variance is a consistent estimator of quadratic variation under mild regularity conditions.Other variation concepts,such as power variation and bipower variation,are useful and important for analyzing high frequency data when jumps are present.High frequency data can also be used to test jumps in asset prices.We discuss three jump tests:bipower variation test,power variation test,and variance swap test in this study.The presence of market microstructure noise complicates the analysis of high frequency data.The survey introduces several robust methods of volatility estimation and jump tests in the presence of market microstructure noise.Finally,some applications of jump tests in asset pricing are discussed in this article.

Investors’ Social Network and Return

Restricted by the availability of investors’account data,existing studies know little about the reasons for differences in investors’return in financial markets.Given this,this paper,based on the unique account data,reveals that the differences in investors’return are correlated to their locations in the social network.Conclusions are as follows.(1)Investors’social network constructed based on the submission time of completed orders describes the information diffusion process of financial markets.Information diffuses from the center of the network to the edge,and investors’return depends on their position in the network.(2)Investors’social network affects their return through the positive spillover mechanism of their behavior.Wealthy investors are in the center of the social network,the stronger the information sharing,the higher the status in the network,the higher the return;while retail investors are on the edge of the social network,and when their network centrality is certain,they even suffer return penalty for information sharing.(3)The speed of information diffusion in investors’social network has an important impact on asset pricing.Stocks’volatility,return,and liquidity are high in financial markets with an intermediate level of information diffusion speed.This paper puts forward new reasons for differences in investors’return from the perspective of investors’social network,and holds that big data in the capital market deserve further exploration with the social network method.

Financialisation in emerging economies:a systematic overview and comparison with Anglo-Saxon economies

Financialisation research has originally focussed on the US experience,but the concept is now increasingly applied to emerging economies(EMEs).There is a rich literature stressing peculiarities of individual country experiences,but little systematic comparison across EMEs.This paper fills this gap,providing an overview of the debate and identifying six financialisation interpretations for EMEs.These different interpretations stress(1)financial deregulation,(2)foreign financial inflows,(3)asset price volatility,(4)the shift from bank-based to market-based finance,(5)business debt,and(6)household indebtedness.We construct and compare measures of the six financialisation interpretations across a sample of 17 EMEs from Latin America,emerging Europe,Africa and Asia,contrasting them with the US and UK,two financialised economies.We find considerable variation in financialisation experiences of EMEs.Asset price volatility is found across the continents.Asia has been more exposed to capital inflows,stock markets have gained importance and private sector debt has risen.In emerging Europe financial deregulation has been more pronounced with lower levels but strong increases in household debt.The picture is similar in South Africa,the African EME in the sample,where household debt is comparatively high.Financialisation in Latin America is weaker according to our measures.