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The purpose of this paper is to establish the flow-to-equity method, the free cash flow (FCF) method, the adjusted present value method and the relationships between these methods when the FCF appears as an annuity. More specifically, we depart from the two most widely used evaluation settings. The first setting is that of Modigliani and Miller who based their analysis on a stationary FCF. The second setting is that of Miles and Ezzell who worked with an FCF that represents an autoregressive possess of first order.

Inspired by recent observations in the literature concerning cash flows, discount rates and values in discounted cash flow (DCF) methods, we mathematically derive DCF valuation formulas for annuities.

The following relationships are established: (a) the correct discount rate of the tax shield when the free cash flow takes the form of a first-order autoregressive annuity, (b) the direct valuation of the tax shield from the free cash flow for a first-order autoregressive annuity, (c) the correct translation from the required return on unlevered equity to the levered equity, when the free cash flow is a stationary annuity and (d) direct calculation of the unlevered and levered firm values and the value of the tax shield for a stationary annuity.

Until now the complete set of formulas for the valuation of stochastic annuities by different DCF methods has not been established in the literature. These formulas are developed here. These formulas are important for practitioners and academics when it comes to the valuation of cash flows of finite lifetime.

The paper aims to examine the performance of Spanish mutual funds between 1999 and 2003.

The methodolgy uses the stochastic discount factor (SDF) framework across a variety of models developed in the recent asset pricing literature. This approach is a fairly recent innovation in the evaluation of investment performance.

The present work complements the research of Farnworth et al. and Fletcher and Forbes, adding a new issue to the SDF, the third co‐moment of asset returns. Recent asset pricing studies show the relevance of the component of an asset's skewness related to the market portfolio's skewness, the coskewness, and how it helps to explain the time‐variation of ex‐ante market risk premiums. It is found that the effects of adding coskewness to evaluate the performance is significant even when factors based on size, book‐to‐market and momentum are included.

The omission of a coskewness factor may lead to erroneous evaluations of a fund's performance, and therefore, issues such as the persistence of performance should be revised.

This paper explores, for the first time, the effects of incorporating a coskewness factor in the analysis of investment performance, both in an unconditional and a conditional framework using SDF models.

The author examines the impact these efficient factors have on factor model comparison tests in US returns using the Bayesian model scan approach of Chib et al. (2020), and Chib et al.(2022).

Ehsani and Linnainmaa (2022) show that time-series efficient investment factors in US stock returns span and earn 40% higher Sharpe ratios than the original factors.

The author shows that the optimal asset pricing model is an eight-factor model which contains efficient versions of the market factor, value factor (HML) and long-horizon behavioral factor (FIN). The findings show that efficient factors enhance the performance of US factor model performance. The top performing asset pricing model does not change in recent data.

The author is the only one to examine if the efficient factors developed by Ehsani and Linnainmaa (2022) have an impact on model comparison tests in US stock returns.

The purpose of this paper is to analyze how exchange ratios in mergers can be assessed when the companies economic capital valuation is carried out in a stochastic framework with financial assets and minimum guarantees.

The paper is a theoretical one. Its main objective is to present a quantitative model for exchange ratios accounting, introducing a stochastic pricing model in the presence of stochastic cash‐flows and representing contractual embedded real option such as minimum guarantees.

The paper presents a financial model to evaluate the differences in exchange ratios induced by stochastic capital reserves in the merging companies.

Stochastic cash‐flows in the economic capital of the merging companies set up a stochastic capital reserve which represents an additional value and could induce important differences in exchange ratios.

The model is fully applicable, also in the presence of embedded real options such as minimum guarantees, but requires the volatility of the underlying.

The paper should be useful under both a managerial and a theoretical use in order to evaluate stochastic exchange ratios.

We evaluate the performance of fixed income mutual funds using stochastic discount factors motivated by continuous-time term structure models. Time-aggregation of these models for discrete returns generates new empirical “factors,” and these factors contribute significant explanatory power to the models. We provide a conditional performance evaluation for US fixed income mutual funds, conditioning on a variety of discrete ex-ante characterizations of the states of the economy. During 1985–1999 we find that fixed income funds return less on average than passive benchmarks that do not pay expenses, but not in all economic states. Fixed income funds typically do poorly when short-term interest rates or industrial capacity utilization rates are high, and offer higher returns when quality-related credit spreads are high. We find more heterogeneity across fund styles than across characteristics-based fund groups. Mortgage funds underperform a GNMA index in all economic states. These excess returns are reduced, and typically become insignificant, when we adjust for risk using the models.

The purpose of this paper is to consider a discrete‐time, Markov, regime‐switching, affine term‐structure model for valuing bonds and other interest rate securities. The proposed model incorporates the impact of structural changes in (macro)‐economic conditions on interest‐rate dynamics. The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

The authors derive a simple way to give exponential affine forms of bond prices using backward induction. The authors also consider a continuous‐time extension of the model and derive exponential affine forms of bond prices using the concept of stochastic flows.

The methods and results presented in the paper are new.

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.

This paper shows that for a large class of single and multi‐factor term structure models, including the affine class, the market price of risk is directly related to the parameters of the stochastic processes of the underlying factors of the economy. It is shown that the market price of risk is proportional to the limit of the volatility of zero coupon bond returns. This means that the market price of risk is not entirely arbitrary. Not only it must be consistent with no arbitrage conditions, also it must be consistent with the parameters of stochastic processes of the factors that describe the economy. If the market price of risk is not correctly specified, then it could lead to profit opportunities of the type discussed in Backus et al (1996). Another consequence of our result is that in empirical tests of interest rate processes, the market price of risk should not be specified exogenously since its value is a function of the parameters of the model. We extend our result to forward processes. The market price of risk is shown to be a function of the volatility of the forward rate processes.

Due to disequilibrium between supply and demand in the option market, the option market‐maker is under exposure to certain risks because of their net option positions. This paper aims to pay attention to whether the risk award affects the option price and the shape of implied volatility in the market‐maker system.

The paper first eliminates the part of implied volatility explained by underlying asset's stochastic volatility‐jump price process, and second sorts out market investors' net demand data from TAIEX Options tick by tick deal data and then finally considers three market maker's risks – unhedgeable risk, capital constrain risk and asymmetric information risk, and how they affect implied volatility's level and slope.

Through the research in the TAIEX Option market, the paper finds that, under unhedgeable risk, net demand pressure has a significant impact on implied volatility. Especially, unhedgeable risk due to underlying asset's stochastic volatility has the best explanation for implied volatility level, and unhedgeable risk due to underlying asset's jump can explain implied volatility slope to some extent. Capital constrain risk and asymmetric information risk have an insignificant impact on implied volatility.

The findings in this study suggest that the risk award affects the option price and the shape of implied volatility in the market‐maker system and different risks have different effects on the level and slope of option implied volatility.

This paper finds the influence factors of the option price in the market‐maker system. It's useful for China's financial government and investors to learn the price tendency and regular pattern in the future China option market.

This is the first time that a net demand pressure based option pricing model is used, which is derived by Garleanu, Pedersen and Poteshman, to study the TAIEX Options' implied volatility. And the paper improves the methods eliminating the part of implied volatility explained by underlying asset's stochastic volatility‐jump price process.