Non-traded Assets Research Articles

Can machine learning methods predict beta?

ABSTRACT It is common to estimate equity betas for private firms or non-traded assets through a comparable company analysis (CCA) of peer firms. Previous literature has questioned the accuracy of those estimates. We test if Machine Learning (ML) algorithms can provide superior forecasts. In out-of-sample tests from 1990 to 2021, we find that ML predictions reduce the mean absolute error by over 42% relative to the CCA. The improved accuracy of ML is most pronounced for smaller, younger firms with different capital structure from their peer group, suggesting potential large improvements are possible by applying ML methods to private firm valuation.

The no-arbitrage pricing of non-traded assets

The no-arbitrage pricing of non-traded assets

The No-arbitrage Pricing of Non-traded Assets

The No-arbitrage Pricing of Non-traded Assets

Putting Credit Factor Investing into Practice

Implementing established corporate bond factors in real-world portfolios poses many challenges for investors. First, the investment universe is reduced by non-tradable assets. In this article, the authors avoid investing into these bonds by constructing a tradability measure based on past transaction data. A realistic strategy to implement should target bonds that are being traded in the market. Second, factor performance is typically measured against a benchmark. To allow for a fair comparison, the authors limit the deviation between the portfolio and the benchmark in key dimensions. Consequently, not only bonds with the best signals can be included in the portfolio. Overall, this reduced universe, along with other restrictions and higher transaction costs than on the equity side, leads to a substantial performance decrease. Nevertheless, the authors show that factor investing in credit is still a successful strategy if it is approached with realistic expectations and common pitfalls are avoided. Their enhanced approach translates signals into usable trading strategies, outperforming the benchmark with an information ratio of 1.1 (1.4) for investment grade (high yield).

Equilibrium policy portfolios when some investors are restricted from holding certain assets

PurposeThe authors analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. They study how the existence of non-tradable assets impacts optimal asset allocation decisions of investors who own such assets and of investors who do not have access to non-tradable assets.Design/methodology/approachIn this theoretical analysis, the authors analyze a model with tradable and non-tradable asset classes whose cash flows are jointly normally distributed. There are two types of investors, with and without access to non-tradable assets. All investors have constant absolute risk aversion preferences. The authors derive closed form solutions for optimal investor demand and equilibrium asset prices. They calibrated the model using US data for listed equity, bonds and private equity. Further, the authors illustrate the sensitivities of quantities and prices with respect to the main parameters.FindingsThe study finds that the existence of non-tradable assets has a large impact on optimal asset allocation. Investors with (without) access to non-tradable assets tilt their portfolios of tradable assets away from (toward) assets to which non-tradable assets exhibit positive betas.Practical implicationsThe model provides important insights not only for investors holding non-tradable assets such as private equity but also for investors who do not have access to non-tradable assets. Investors who ignore the effect of non-tradable assets when reverse-engineering risk premia from asset covariances and market capitalizations might severely underestimate the equity risk premium.Originality/valueThe authors provide the first comprehensive analysis of the equilibrium effects of non-tradability of some assets on optimal policy portfolios. Thus, this paper goes beyond analyzing the effects of market imperfections on individual portfolio choices.

Can Business Groups Survive Institutional Advancements? Examining the Role of Internal Market for Non-Tradable, Intangible Assets

Business groups are observed everywhere except in the U.S. and U.K.; their global presence is widely acknowledged. The most successful explanation for this preponderance has been based on the relative efficiency of business groups’ internal market vis-à-vis the external market conventionally observed in underdeveloped or emerging economies. Unsurprisingly, this view cannot explain why business groups also prosper in advanced economies where their internal market is thought to no longer match efficient external markets. This study addresses this contradiction by drawing attention to non-tradable, intangible assets and putting forward an institution-free, micro-level explanation. Specifically, we reason that the external market for organizational capabilities is bound to be missing regardless of institutional advancements and economic development due to human beings’ innate cognitive limits and information and behavioral uncertainties, while business groups’ internal markets may overcome these limits via their distinctive organizing mechanism underpinned by group identity, solidarity, mutual trust, shared organizational architecture, and enhanced communicability. In other words, business groups can outperform the external market in coordinating and facilitating exchanges of non-tradable assets and organizational capabilities in particular that are becoming increasingly crucial for successful competition. Using panel data of large business groups in Korea during the periods between 2003 and 2016, we confirm that affiliation with business groups and accessing their internal market enhances technological capability. Thus, this study extends our understanding of business groups beyond the institution-based explanation.

The Covariance Structure between Liquid and Illiquid Assets

The traditional methods of estimating investment risk based on the observed variation of asset prices falter on sparsely traded assets owing to the lack of price quotes. The price variance of illiquid assets such as private equity, loans, or real estate is, if calculable at all, not meaningful. Nor does the observed covariance between illiquid assets indicate a degree of proximity in the price behavior. The author proposes a cross-sectional approach instead, taking the price dispersion across assets as an estimate of variance and using the so-called cross dispersion of covariance. The covariance matrix computed in this way over traded and nontraded assets seems coherent with the (sub)matrix computed over time on traded assets. The cross-sectional matrix sets a universal framework for managing portfolios invested in traded and nontraded assets, making all-encompassing risk assessments possible.

Near-optimal asset allocation in financial markets with trading constraints

We develop a dual-control method for approximating investment strategies in multidimensional financial markets with convex trading constraints. The method relies on a projection of the optimal solution to an (unconstrained) auxiliary problem to obtain a feasible and near-optimal solution to the original problem. We obtain lower and upper bounds on the optimal value function using convex duality methods. The gap between the bounds indicates the precision of the near-optimal solution. We illustrate the effectiveness of our method in a market with different trading constraints such as borrowing, short-sale constraints and non-traded assets. We also show that our method works well for state-dependent utility functions.

Forecasting betas with random forests

ABSTRACT It is common to estimate equity betas for private firms or non-traded assets through a comparable company analysis, and we test if the Random Forest algorithm can provide superior forecasts. In out-of-sample tests from 1992 to 2018, we find that Random Forest forecasts produce substantially lower average errors and mean absolute errors every year.

LOCALLY RISK-MINIMIZING HEDGING FOR EUROPEAN CONTINGENT CLAIMS WRITTEN ON NON-TRADABLE ASSETS WITH COMMON JUMP RISK

This article investigates the optimal hedging problem of the European contingent claims written on non-tradable assets. We assume that the risky assets satisfy jump diffusion models with a common jump process which reflects the correlated jump risk. The non-tradable asset and jump risk lead to an incomplete financial market. Hence, the cross-hedging method will be used to reduce the potential risk of the contingent claims seller. First, we obtain an explicit closed-form solution for the locally risk-minimizing hedging strategies of the European contingent claims by using the Föllmer–Schweizer decomposition. Then, we consider the hedging for a European call option as a special case. The value of the European call option under the minimal martingale measure is derived by the Fourier transform method. Next, some semi-closed solution formulae of the locally risk-minimizing hedging strategies for the European call option are obtained. Finally, some numerical examples are provided to illustrate the sensitivities of the optimal hedging strategies. By comparing the optimal hedging strategies when the underlying asset is a non-tradable asset or a tradable asset, we find that the liquidity risk has a significant impact on the optimal hedging strategies.

A semigroup approach to generalized Black-Scholes type equations in incomplete markets

In this paper we will study an option pricing problem in incomplete markets by an analytic point of view. The incompleteness is generated by the presence of a non- traded asset. The aim of this paper is to use the semigroup theory in order to prove existence and uniqueness of solutions to generalized Black-Scholes type equations that are non-linearly associated with the price of European claims written exclusively on non-traded assets. Then, we derive analytic expressions of the solutions. An approximate representation in terms of a generalized Feynman-Kac type formula is derived in cases where an explicit closed form solution is not available. Numerical examples are also given (see Appendix E) where theoretical approximations and numerical tests reveal a remarkable agreement.

A linear goal programming method to recover risk neutral probabilities from options prices by maximum entropy

We develop a new methodology to retrieve risk neutral probabilities (equivalent martingale measure) with maximum entropy from quoted option prices. We assume the no arbitrage hypothesis and model the efficient market hypothesis by means of a maximum entropic risk neutral distribution. The method is free of parametric assumption except for the simulation of the distribution support, for which purpose we can choose any stochastic model. Firstly, we innovate in the minimization of a different f-divergence than Kullback–Leibler’s relative entropy, resulting in the total variation distance. We minimize it by means of linear goal programming, thus guaranteeing a fast numerical resolution. The method values non-traded assets finding a RNP minimizing its f-divergence to the maximum entropy distribution over a simulated support—the uniform distribution—calibrated to the benchmarks prices constraints. Our second innovation is that in an incomplete market, we can increase the f-divergence from its minimum to obtain any asset price belonging to the interval satisfying the non-existence of an arbitrage portfolio, without presupposing any utility function for the decision maker. We exemplify our methodology by means of synthetic and real-world cases, showing that our methodology can either price non-traded assets or interpolate and extrapolate a volatility surface.

Time-Varying Background Risk Over the Great Recession

Based on a theory of portfolio choice with non-tradable assets, we estimate perceived background risks immediately before and after the Great Recession from a large representative panel survey of U.S. households. Background risks related to human capital, residential property and proprietary business all reduce risk-taking, but these effects decline over the Great Recession. These declines are driven by perceptions of increased stock market risk rather than changes in covariances between returns on non-tradable assets and stocks. Perceptions of risk-adjusted stock market performance remained unchanged. Our results help to explain why household stock market participation rose following the Great Recession

Policy Portfolios When Some Assets are Non-Tradeable

Asset managers usually define a policy portfolio to provide a long-term benchmark. According to the CAPM, the policy portfolio should be the value weighted market portfolio of all assets. However, the practical implementation of such a policy portfolio is not straightforward. First, it is non-trivial to determine the market value weights of tradable assets. Second, even if one ignores human capital as a component of the market portfolio, there are large parts of the asset universe which are difficult to trade, such as non-listed equity. While some investors are endowed with such illiquid assets or are able to pay the (fixed) costs associated with accessing them, other investors are effectively precluded from holding such assets. In this paper we analyze the equilibrium effects of non-tradable assets on optimal policy portfolios. We find that the existence of non-tradable assets implies that investors do not hold the market portfolio. Investors with (without) access to non-tradable assets tilt their portfolios away from (towards) assets to which non-tradable assets exhibit positive betas.

Does country background risk matter to the strategic asset allocation of sovereign wealth funds?

On the basis of background risk theory (Gollier 2001), this paper discusses the country background assets of sovereign wealth funds (SWFs), establishes the optimal strategic asset allocation model with consideration for background risk, and proves that the rebalanced weight of each asset is negatively correlated with the covariance of background assets and financial assets. Considering both the national foreign currency reserve assets and future payment obligations of international import goods as background risk, this paper uses China's SWF as a sample, partitions global equity markets according to MSCI country and industry indices, utilizes market implied expected return and market models to estimate the expected return of those investable assets, and finally determines the optimal strategic asset allocation of SWFs. The theoretical modeling methods in this paper can be extended to solve SWFs' asset allocation problems with non-tradable assets and to help optimize the portfolio allocation decisions of individual investors with heterogeneous background risks.

An Actuarial Approach to Reload Option Valuation for a Non-tradable Risk Assets under Jump-diffusion Process and Stochastic Interest Rate

We use an actuarial approach to estimate the valuation of the reload option for a non-tradable risk asset under the jump-diffusion processes and Hull-White interest rate. We verify the validity of the actuarial approach to the European vanilla option for non-tradable assets. The formulas of the actuarial approach to the reload option are derived from the fair premium principle and the obtained results are arbitrage. Numerical experiments are conducted to analyze the effects of different parameters on the results of valuation as well as their differences from those obtained by the no-arbitrage approach. Finally, we give the valuations of the reload options under different parameters.

International Cost of Capital Estimation: The No-Arbitrage Method

This study summarizes problems associated with existing international cost of capital (ICC) estimation methods; adapts long-existing arbitrage pricing methods to ICC estimation to a setting where ICC is to be estimated for a privately-held asset not traded in the capital markets; and then presents a semi-realistic example of ICC estimation for such non-traded assets under the NA method. The study contributes to the literature by more clearly defining the ICC estimation problem; provides a heretofore absent clear theoretical basis for ICC estimation; explains critical aspects of developing accurate, reliable ICC estimates; and provides a general solution to the identified problems with existing ICC estimation methods.

Valuation Reports in the Context of Banking Resolution: What are the Challenges?

The paper discusses the problem of valuation in bank resolution. In an overview over the most relevant principles of valuation theory, the paper notes the difficulties inherent in valuing risks and illiquidity in holding non-traded assets. Subsequently, the paper briefly reviews the resolution of Banco Popular Espanol, and then discusses the need for clarification of the no-investor-worse-off principle, the relation between the price in a sale of business and the presumed outcome in an insolvency procedure, and the difficulties attached to assessing the value of an illiquid asset that is held. The paper concludes with a discussion of the need for time, for valuation and in resolution, warns against a moratorium on withdrawals and payouts, and argues that time pressures would be much reduced if funding in resolution was provided for.

CORPORATE FINANCE IN RENEWABLE ENERGY INVESTMENTS A REVIEW ABOUT THEORY AND PRACTICE

This paper examines key topics in corporate finance relevant for valuating renewable energy (RE) investments - typically a non-traded asset (NTA) and an asset type often ignored by many valuation literatures. We begin by discussing principal valuation methods from the academic financial literature, and draw on empirical survey demonstrating their relevance in practice. The key discussed topics include the applied methods in capital budgeting, cost of equity estimation, and risk analysis and mitigation. In each topic, we suggest how adequate the methods are to be applied for valuing RE investments, based on the nature of such investment projects, before rounding off the topics with a project valuation adjustment and risk management framework we propose. This paper lays the groundwork for further research as it presents work-in-progress, followed by the data collection phase with a survey amongst investors and financial advisors within the researched population. Therefore, empirical results will be presented at a later stage. We conclude with a theoretical and research agenda for future work.

From Utility Indifference Pricing to Risk Premium Pricing for a Contingent Claim on a Non-Tradable Asset

Pricing a contingent claim on a non-tradable asset (e.g. a management warrant package in an LBO) cannot be done with standard hedging based option pricing theory. Common alternatives are utility indifference pricing, suggested by various authors, or risk premium pricing (using the option pricing methodology with the asset drift modified for a risk premium), often favored by practitioners. The purpose of this note is to point out that the two approaches are in fact conceptually equivalent, in the sense that the utility function risk aversion in the first method can be mapped into a risk premium in the second method.