Pure jump Lévy processes for asset price modelling

The goal of the paper is to show that some types of Lévy processes such as the hyperbolic motion and the CGMY are particularly suitable for asset price modelling and option pricing. We wish to review some fundamental mathematic properties of Lévy distributions, such as the one of infinite divisibility, and how they translate observed features of asset price returns. We explain how these processes are related to Brownian motion, the central process in finance, through stochastic time changes which can in turn be interpreted as a measure of the economic activity. Lastly, we focus on two particular classes of pure jump Lévy processes, the generalized hyperbolic model and the CGMY models, and report on the goodness of fit obtained both on stock prices and option prices.     

Multivariate asset models using Lévy processes and applications

In this paper, we propose a multivariate asset model based on Lévy processes for pricing of products written on more than one underlying asset. Our construction is based on a two-factor representation of the dynamics of the asset log-returns. We investigate the properties of the model and introduce a multivariate generalization of some processes which are quite common in financial applications, such as subordinated Brownian motions, jump-diffusion processes and time-changed Lévy processes. Finally, we explore the issue of model calibration for the proposed setting and illustrate its robustness on a number of numerical examples.     

What causes home asset bias and how should it be measured?

Many explanations of home asset bias involve intuitions that should affect the data inputs used by investors in optimizing portfolios: (1) transaction costs affecting expected returns, (2) perceived riskiness of foreign assets affecting standard deviations, and (3) omitted assets affecting correlations. Only the first area has been examined empirically. We examine the empirical feasibility of the second and third explanations, as well as whether combining explanations can fully account for home asset bias. We find that no single set of adjustments can explain home asset bias by itself. Combining adjustments is promising but the implied correlation structure among asset returns is puzzling.     

What is the impact of wealth shocks on asset allocation?

I test the assumption of constant relative risk aversion using U.S. macroeconomic data and analyse the role of wealth shocks in generating transitory changes in asset portfolio composition. I show that the risky asset share exhibits cyclical behavior and it is significantly (and positively) affected by unexpected variation in wealth. Therefore, the empirical evidence suggests that risk aversion is counter-cyclical. I also find that the portfolio share of housing wealth falls when the agent is faced with a positive wealth shock, i.e. housing is a hedge against unfavorable wealth fluctuations. Finally, considering a variety of wealth definitions, the results show that: (i) wealth effects are stronger for direct holdings of risky assets than for indirect holdings, which highlights that investors do not typically trade some assets such as pension or mutual funds; (ii) although significant, wealth effects on asset allocation are mainly temporary as agents quickly rebalance the asset portfolio composition (i.e. there is weak evidence of inertia or slow adjustment in asset allocation); and (iii) changes in expected returns partially explain the variation in risky asset allocation.     

Dynamic asset–liability management in a Markov market with stochastic cash flows

This paper provides a general model to investigate an asset–liability management (ALM) problem in a Markov regime-switching market in a multi-period mean–variance (M–V) framework. Emphasis is placed on the stochastic cash flows in both wealth and liability dynamic processes, and the optimal investment and liquidity management strategies in achieving the M–V bi-objective of terminal surplus are evaluated. In this model, not only the asset returns and liability returns, but also the cash flows depend on the stochastic market states, which are assumed to follow a discrete-time Markov chain. Adopting the dynamic programming approach, the matrix theory and the Lagrange dual principle, we obtain closed-form expressions for the efficient investment strategy. Our proposed model is examined through empirical studies of a defined contribution pension fund. In-sample results show that, given the same risk level, an ALM investor (a) starting in a bear market can expect a higher return compared to beginning in a bull market and (b) has a lower expected return when there are major cash flow problems. The effects of the investment horizon and state-switching probability on the efficient frontier are also discussed. Out-of-sample analyses show the dynamic optimal liquidity management process. An ALM investor using our model can achieve his or her surplus objective in advance and with a minimum variance close to zero.     

The αVG model for multivariate asset pricing: calibration and extension

Luciano and Semeraro proposed a class of multivariate asset pricing models where the asset log-returns are modeled by a multivariate Brownian motion time-changed by a multivariate subordinator which consists of the weighted sum of a common and an idiosyncratic subordinator. In the original setting, Luciano and Semeraro imposed some constraints on the subordinator parameters such that the multivariate subordinator is of the same subordinator sub-class as its components, leading to asset log-returns of a particular Lévy type. This restriction leads to marginal characteristic functions which are independent on the common subordinator setting. In this paper, we propose to extend the original model by relaxing the constraints on the subordinator parameters, leading to marginal characteristic functions which become a function of the whole parameter set. Under this generalized version, the volatility of the log-returns depends on both the common and idiosyncratic subordinator settings, and not only on the idiosyncratic one, which makes the generalized model more in line with the empirical evidence of the presence of both an idiosyncratic and a common component in the business clock. For the numerical study, we compare the calibration fit of both univariate option surfaces and market implied correlations for a period extending from the 2nd of June 2008 until the 30th of October 2009 under the two model settings and assess the calibration risk arising from different calibration procedures by pricing traditional multivariate exotic options. In particular we show that the decoupling calibration procedure fails to accurately replicate the market dependence structure under the original model for highly correlated asset returns and we propose an alternative methodology which rests on a joint calibration of the univariate and the dependence structure and which leads to an accurate fit of the market reality under both the generalized and original models.     

Searching for a listed infrastructure asset class using mean–variance spanning

This study examines the portfolio-diversification benefits of listed infrastructure stocks. We employ three different definitions of listed infrastructure and tests of mean–variance spanning. The evidence shows that viewing infrastructure as an asset class is misguided. We employ different schemes of infrastructure asset selection (both traditional asset classes and factor exposures) and discover that they do not provide portfolio-diversification benefits to existing asset allocation choices. We also find that defining and selecting infrastructure investments by business model as opposed to industrial sectors can reveal a very different investment profile, albeit one that improves the mean–variance efficient frontier since the global financial crisis. This study provides new insights into defining and benchmarking infrastructure equity investments in general, as well as into the extent to which public markets can be used to proxy the risk-adjusted performance of privately held infrastructure investments.     

An empirical analysis of differences in Black and White asset and liability combinations☆

This study analyzes data from the 1992 Survey of Consumer Finances and finds significant differences in asset and liability combinations between Black and White households. In addition, White households are identified as having significantly greater net worth and financial assets relative to Black households. We are unable to show that the net worth of Black households is constrained by barriers in financial markets. Our study investigates how this difference in net worth could engender different financing decisions. We find that Black households are significantly more risk averse in their choice of assets. Further, we find that Black households typically pay higher rates for several types of credit instruments, even though they self identify as conducting significantly more extensive searches in the financial markets. JEL classification: D10; D31; J15     

Demographics and asset returns: does the dynamics of population ageing matter?

The empirical connection between the population age-structure and financial asset returns has been so far investigated with special focus on the US, whereby weak or disparate results are obtained. This paper aims to assess whether this connection is affected by the demographic dynamics. To this end the analysis is based on a stylized overlapping generation model and on the empirical investigation for Italy, which is experiencing one of the most pronounced ageing in the world and, specifically, steeper than the US one. Following the approach used for the US, stock returns and Government bond yields are regressed over demographic and/or control variables using annual data over 1958–2004. Results for Italy are more clear-cut and thus support the importance of the country-specific age-dynamics in explaining the impact of demographics on financial markets.     

Valuation of asset and volatility derivatives using decoupled time-changed Lévy processes

In this paper we propose a general derivative pricing framework that employs decoupled time-changed (DTC) Lévy processes to model the underlying assets of contingent claims. A DTC Lévy process is a generalized time-changed Lévy process whose continuous and pure jump parts are allowed to follow separate random time scalings; we devise the martingale structure for a DTC Lévy-driven asset and revisit many popular models which fall under this framework. Postulating different time changes for the underlying Lévy decomposition allows the introduction of asset price models consistent with the assumption of a correlated pair of continuous and jump market activity rates; we study one illustrative DTC model of this kind based on the so-called Wishart process. The theory we develop is applied to the problem of pricing not only claims that depend on the price or the volatility of an underlying asset, but also more sophisticated derivatives whose payoffs rely on the joint performance of these two financial variables, such as the target volatility option. We solve the pricing problem through a Fourier-inversion method. Numerical analyses validating our techniques are provided. In particular, we present some evidence that correlating the activity rates could be beneficial for modeling the volatility skew dynamics.     

What does futures market interest tell us about the macroeconomy and asset prices?

Economists have traditionally viewed futures prices as fully informative about future economic activity and asset prices. We argue that open interest could be more informative than futures prices in the presence of hedging demand and limited risk absorption capacity in futures markets. We find that movements in open interest are highly pro-cyclical, correlated with both macroeconomic activity and movements in asset prices. Movements in commodity market interest predict commodity returns, bond returns, and movements in the short rate even after controlling for other known predictors. To a lesser degree, movements in open interest predict returns in currency, bond, and stock markets.     

Marcos M. López de Prado: Machine learning for asset managers

Financial Markets and Portfolio Management -     

A nonparametric approach to measuring the sensitivity of an asset’s return to the market

In the market model the return on an asset is modeled as a linear function of the return on a market index with slope parameter beta. The coefficient beta is often used as a measure of the sensitivity of the asset’s return to the market and to measure the component of the variance of the return that is explained by the market. However, both of these interpretations require the additional assumption that the error term in the market model has mean 0 conditional on the return on the market index, an assumption that is often difficult to verify in practice. In this paper, a nonparametric version of the market model is proposed that does not require such an assumption. This nonparametric model replaces the beta coefficient of the market model with a “beta curve” describing the relationship between the asset’s return and that of the market locally near a given value of the market return. The proposed model is applied to stock returns, as well as to returns on mutual funds. Corresponding tests of the market model are given and it is shown that the nonparametric model often provides an improvement over the standard parametric market model.     

Sports betting as a new asset class—current market organization and options for development

New asset classes are originally distributed via over the counter channels; mostly negotiated, traded, and settled on a bilateral and ad-hoc basis. Subsequently, the demand for organized market services grows alongside trading volumes, number of market participants, and distribution reach. This paper focuses on sports betting as a new asset class and uses the analogies between the development of traditional and new asset classes as a framework to extend market organization. The first section motivates sports betting as a new asset class based on its economic relevance. In Sect. 2, the European market is described by product design, distribution platforms, and regulatory environment. In Sect. 3, we discuss the dimensions of market model, technology, and regulation as prerequisites to develop organized markets. Against this background, we compare the value chain in financial and sports betting markets to identify and describe three options for development: a regulated market environment, an inter-bookmaker platform, and central counterparty clearing services.

The real effect of banking crises: Finance or asset allocation effects? Some international evidence

This paper analyzes whether the decline in economic growth that follows a banking crisis occurs because of a reduction in the amount of credit available (finance effect) or a worsening in the allocation of investable resources (asset allocation effect). We use a sample of more than 2500 industrial firms in 18 developed and developing countries that experienced 19 systemic banking crises between 1989 and 2007. The results indicate that banking crises negatively affect firms’ intangible investments, which intensifies the economic downturn. The negative growth effect produced by the worsening of the investment allocation is stronger in countries with highly developed financial systems and institutions.     

How do firms react to the prohibition of long-lived asset impairment reversals? Evidence from China

New Chinese Accounting Standards (CAS) released on February 15, 2006, prohibit the reversal of long-lived asset impairments, effective for reporting periods beginning January 1, 2007 and later. This development in the Chinese market provides a unique experimental setting to directly investigate how firms react to the ban on previously-allowed long-lived asset impairment reversals, especially firms that use impairment charges as “cookie jar reserves.” By contrasting write-off recognition and reversal across the pre- and post- new CAS announcement regimes, we show that firms listed on Chinese stock exchanges recognized less impairment charges during the “transition” period—after announcement of the new standard and before the effective date—than in pre-announcement periods. Meanwhile, firms with substantial previous write-downs reversed more impairment charges to achieve their earnings targets in the transition period. The new CAS also constraints “big bath” reporting by loss firms. As US GAAP prohibits these reversals and IFRS allows them, our empirical evidence depicts firms’ possible reactions in other regimes contemplating doing away with such reversals.     

The optimal asset allocation of the main types of pension funds: a unified framework

The existing literature deals with the optimal investment strategy of defined benefit (DB) or defined contribution (DC) pension plans. This article’s objective is to compare the optimal policies of different types of pension plans. This is done by first defining an original framework, which is based on the distinction between the nature of the guarantee—which can be internal or external—offered by or to a pension fund. This framework allows to establish links between optimization programs of DC, DB and targeted money purchase schemes. The case of an internal guarantee appears as a standard portfolio insurer’s problem. The second kind of guarantee, not analyzed in the literature yet with regard to the resulting optimal policy, is characterized by the existence of an option in the final wealth definition. Four funds are present in the internal guarantee optimal allocation: the speculative component, the preference independent guarantee- and contribution-hedge terms and the preference dependent state variable-hedge fund. The external guarantee program, solved with an original method using the principles of standard options theory, yields an optimal policy incorporating the delta of the option embodied in the final wealth definition. The conclusion is that the resulting optimal portfolio policy becomes riskier.

Do asset impairments and the associated disclosures resolve uncertainty about future returns and reduce information asymmetry?

The objective of this study is to provide insights into how Australian listed firms are implementing AASB 136 Impairments of Assets. Our first concern is whether uncertainty about future returns and information asymmetry motivates the recognition of asset impairments. We find no evidence that the recognition of asset impairments is associated with higher uncertainty about future returns. Furthermore, we find no evidence that the recognition of asset impairments is associated with higher information asymmetry. Our second concern is whether asset impairments and the associated disclosures provide information that reduces uncertainty about future returns and information asymmetry. While we find some evidence that asset impairments are associated with decreases in information asymmetry before the financial crisis, during the financial crisis, asset impairments are associated with increases in both measurement uncertainty and information asymmetry.