Price Equation Research Articles

A generalised approach to the study and understanding of adaptive evolution.

Evolutionary theory has made large impacts on our understanding and management of the world, in part because it has been able to incorporate new data and new insights successfully. Nonetheless, there is currently a tension between certain biological phenomena and mainstream evolutionary theory. For example, how does the inheritance of molecular epigenetic changes fit into mainstream evolutionary theory? Is niche construction an evolutionary process? Is local adaptation via habitat choice also adaptive evolution? These examples suggest there is scope (and perhaps even a need) to broaden our views on evolution. We identify three aspects whose incorporation into a single framework would enable a more generalised approach to the understanding and study of adaptive evolution: (i) a broadened view of extended phenotypes; (ii) that traits can respond to each other; and (iii) that inheritance can be non-genetic. We use causal modelling to integrate these three aspects with established views on the variables and mechanisms that drive and allow for adaptive evolution. Our causal model identifies natural selection and non-genetic inheritance of adaptive parental responses as two complementary yet distinct and independent drivers of adaptive evolution. Both drivers are compatible with the Price equation; specifically, non-genetic inheritance of parental responses is captured by an often-neglected component of the Price equation. Our causal model is general and simplified, but can be adjusted flexibly in terms of variables and causal connections, depending on the research question and/or biological system. By revisiting the three examples given above, we show how to use it as a heuristic tool to clarify conceptual issues and to help design empirical research. In contrast to a gene-centric view defining evolution only in terms of genetic change, our generalised approach allows us to see evolution as a change in the whole causal structure, consisting not just of genetic but also of phenotypic and environmental variables.

Drivers of smoked marine fish prices and challenges along the value chain

PurposeThe objectives of this paper are to analyze the drivers of smoked marine fish prices and examine the challenges along the value chain to inform policy.Design/methodology/approachThe study relies on cross-sectional data from 158 fish smokers, 100 wholesalers, and 120 retailers in Ghana. The challenges faced by the actors along the chain are identified and ranked using Kendall's coefficient of concordance. The three-stage least square estimation approach is employed to control for endogeneity resulting from the simultaneous equations for prices of different fish types and their substitutes.FindingsThe results reveal that marketing experience, the extent of competition, price of substitutes, payment terms, and variable cost items, such as transportation cost and storage charges, are key determinants of smoked fish prices along the value chain. Lack of access to credit is the main constraint to the marketing of smoked marine fish, irrespective of the actor or the fish type.Originality/valueMany studies have established the linkages between fish consumption, prices, and food security in the literature. However, there is a dearth of information on the responsiveness of fish prices to changes in the market and seller-specific factors to drive policy to stabilize prices along the value chain.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2021-0566

Schleiermacher and the transmission of sin

Understanding the pervasiveness of sin is central to Christian theology. The question of why humans are so sinful given an omniscient, omnipotent, and omnibenevolent God presents a challenge and a puzzle. Here, we investigate Friedrich Schleiermacher’s biocultural evolutionary account of sin. We look at empirical evidence to support it and use the cultural Price equation to provide a naturalistic model of the transmission of sin. This model can help us understand how sin can be ubiquitous and unavoidable, even though it is not biologically transmitted, and even if there is no historical Fall that precipitated the tendency to sin.

Valuation of ticket prices for first‐division football matches in the Spanish league

This paper measures the optimal prices of football tickets and investigates the pricing strategy of the first‐division teams in the Spanish league during the 2018/2019 season. The paper develops a dual hybrid model of supply and demand based on a hedonic price approach. Fans have multiple motivations to attend the stadium, such as the quality of the opposing teams, the pre‐match qualifying position, the schedule, the day of the match, the stadium facilities, and the atmosphere. Their final decision will be conditioned by the price set by the clubs. The data show a difference of almost 300% in ticket prices among clubs. The estimation results from a hedonic price equation reveal that an optimal pricing strategy is followed by only five out of 20 clubs in the league. We also quantify the percentage of overvaluation or undervaluation of ticket prices.

Price Determinants of Collectable U.S. Commemorative Stamps: An Examination of Philatelic Demand

Philately, the collecting of postage stamps, is a popular hobby throughout the world. Stamp collectors’ motivations vary from the simple pursuit of leisure and recreation to financial investment and speculation. This study explores the demand for vintage U.S. commemorative stamps by examining the determinates of retail prices across alternative categories of sellers. Using regression analysis and a cross-sectional sample of the first 250 commemorative stamps issued by U.S. postal authorities, we estimate price equations for representative national dealers, regional dealers, and for electronic auction sites. The results indicate that production quantities, age, and specific attributes of individual stamp issues are the primary determinants of retail price. However, the pricing structures across categories of sellers are significantly different in a hierarchical manner indicating that dealers may successfully segment the collectable stamp market across different types of collectors but alternative explanations for our conclusions cannot be excluded without additional research.

Pricing Options with Vanishing Stochastic Volatility

In the past years, there has been an extensive investigation of the class of stochastic volatility models for the evaluation of options and complex derivatives. These models have proven to be extremely useful in generalizing the classic Black–Scholes economy and accounting for discrepancies between observation and predictions in the simple log-normal, constant-volatility model. In this paper, we study the structure of an options market with a stochastic volatility that will eventually vanish (i.e., reaches zero) for very short periods of time with probability of one. We investigate the form of pricing measures in this situation, first in a simple binomial case, and then for a diffusion model, by constructing a weak approximation in discrete space and continuous time. The market described allows fleeting arbitrage opportunities, since a vanishing volatility prevents the construction of an equivalent measure, so that pricing contingent claims are, a priori, not obvious. Nevertheless, we can still produce a fair pricing equation. Let us note that this issue is not only of theoretical relevance, as the phenomenon of very low volatility has indeed been observed in the financial markets and the economy for quite a long time in the recent past.

Quantifying the Selective, Stochastic, and Complementary Drivers of Institutional Evolution in Online Communities.

Institutions and cultures usually evolve in response to environmental incentives. However, sometimes institutional change occurs due to stochastic drivers beyond current fitness, including drift, path dependency, blind imitation, and complementary cooperation in fluctuating environments. Disentangling the selective and stochastic components of social system change enables us to identify the key features of long-term organizational development. Evolutionary approaches provide organizational science with abundant theories to demonstrate organizational evolution by tracking beneficial or harmful features. In this study, focusing on 20,000 Minecraft communities, we measure these drivers empirically using two of the most widely applied evolutionary models: the Price equation and the bet-hedging model. As a result, we find strong selection pressure on administrative and information rules, suggesting that their positive correlation with community fitness is the main reason for their frequency change. We also find that stochastic drivers decrease the average frequency of administrative rules. The result makes sense when viewed in the context of evolutionary bet-hedging. We show through the bet-hedging result that institutional diversity contributes to the growth and stability of rules related to information, communication, and economic behaviors.

Decomposing Long Bond Returns: A Decentralized Theory

Classic bond pricing centralizes bond valuation across all maturities by specifying the dynamics of the short-term interest rate. This article develops a decentralized theory that prices each bond based purely on the near-term behavior of the bond’s own yield. The theory levers the domain expertise of an investor on a particular bond and allows the investor to make pricing and investment analysis on the bond without the shackles of an ambitious centralizing mandate. The theory decomposes the short-term return on a bond with respect to the variation of its own yield. Imposing no dynamic arbitrage on the return decomposition leads to a simple pricing equation relating the bond yield to the market pricing and conditional mean and variance forecasts of the yield’s near-term change. The article illustrates the theory’s applications in decentralized investment of a single bond and in the construction and investment of decentralized butterfly bond portfolios.

Product differentiation and the relative importance of wine attributes: U.S. retail prices

AbstractThis paper investigates the relative importance of various attributes, including varietal, brands, and geographic origin, in explaining retail wine prices for the United States market. We use a metric based on the Shapely value, from cooperative game theory, in the context of an empirical hedonic price equation estimated using a large sample of retail wine sales for home consumption over the period 2007–2019. We find that brands alone explain more than 70% of the variation in wine prices, but geographic origin and varietals retain additional explanatory power. Furthermore, information about the geographic origin appears to be a considerably more important attribute than varietals.

Host-parasite coevolution: Partitioning the effects of natural selection and environmental change using coupled Price equations.

George Price showed how the effects of natural selection and environmental change could be mathematically partitioned. This partitioning may be especially useful for understanding host–parasite coevolution, where each species represents the environment for the other species. Here, we use coupled Price equations to study this kind of antagonistic coevolution. We made the common assumption that parasites must genetically match their host's genotype to avoid detection by the host's self/nonself recognition system, but we allowed for the possibility that non‐matching parasites have some fitness. Our results show how natural selection on one species results in environmental change for the other species. Numerical iterations of the model show that these environmental changes can periodically exceed the changes in mean fitness due to natural selection, as suggested by R.A. Fisher. Taken together, the results give an algebraic dissection of the eco‐evolutionary feedbacks created during host–parasite coevolution.

Forecasting the behaviour of fractional Black-Scholes option pricing equation by laplace perturbation iteration algorithm

Financial derivatives plays a major role in all financial deals these days. Black–Scholes option pricing model gives a risk free analysis for investing in options. In the current work, a method called the Laplace Perturbation Iteration Algorithm is being applied on Fractional Black–Scholes Equation to obtain its fractional analytical solutions in series form to analyze its results for the European and American option pricing problem, quickly and accurately. Laplace Perturbation Iteration Algorithm incorporates Laplace transform and Perturbation Iteration Algorithm and forms an iterative scheme that derives the analytical solutions without any inconvenience. The Fractional Black–Scholes Equation analytical solution is obtained as a convergent power series of conveniently computed components. Four examples have been solved and their results have been discussed in this paper, in order to check the efficacy of Laplace Perturbation Iteration Algorithm.

Currency returns and systematic risk

We investigate the relationship between currency excess returns and Gross Domestic Product (GDP) in a Consumption Capital Asset Pricing Model. GDPs are observable systematic risk factors in our asset pricing equations. The correlation between the unobservable systematic factors is explored by Seemingly Unrelated Regressions estimations. The sample comprises the period from 1999:M01 to 2019:M12 and 48 countries. Results show that GDP growth risk is significant for most currency pairs and portfolios. We also find that they are priced in the cross-section of excess returns. Furthermore, currency returns are directly affected by regional business cycles (Europe, America, and Asia).

Price Equations for Understanding the Response of Ecosystem Function to Community Change

AbstractThe relationship between biodiversity and ecosystem function (BEF) remains unclear in many natural ecosystems, partially for lack of theoretical and analytical tools that match common characteristics of observational community data. The ecological Price equation promises to meet this need by organizing many different species-level changes into a few ecologically meaningful categories that sum to total ecosystem function change. Current versions of the ecological Price equation focus on species richness and presence-absence. However, abundance and relative abundance are better estimated in samples and are likely showing a stronger response to global change. Here, we present a novel, abundance-based version of the ecological Price equation in both discrete and continuous forms and explain the similarities and differences between this method and a related, previously developed richness-based method. We also present new empirical techniques for applying the Price equation to ecological data. Our two demonstration analyses reveal how additive effects of increasing abundance on total function are modified by concurrent selection effects due to shifts in species' composition as well as intraspecific change in species' per capita function. The ecological Price equations derived here complement existing approaches and together offer BEF researchers analytical tools and a unifying framework for studying BEF in observational community data.

A New Homotopy Transformation Method for Solving the Fuzzy Fractional Black–Scholes European Option Pricing Equations under the Concept of Granular Differentiability

The Black–Scholes option pricing model is one of the most significant achievements in modern investment science. However, many factors are constantly fluctuating in the actual financial market option pricing, such as risk-free interest rate, stock price, option underlying price, and security price volatility may be inaccurate in the real world. Therefore, it is of great practical significance to study the fractional fuzzy option pricing model. In this paper, we proposed a reliable approximation method, the Elzaki transform homotopy perturbation method (ETHPM) based on granular differentiability, to solve the fuzzy time-fractional Black–Scholes European option pricing equations. Firstly, the fuzzy function is converted to a real number function based on the horizontal membership function (HMF). Secondly, the specific steps of the ETHPM are given to solve the fuzzy time-fractional Black–Scholes European option pricing equations. Finally, some examples demonstrate that the new approach is simple, efficient, and accurate. In addition, the fuzzy approximation solutions have been visualized at the end of this paper.

INTEGRATION OF SOUTHEAST ASIAN STOCK MARKETS WITH THE WORLD STOCK MARKET: APPLICATION OF INTERNATIONAL ASSET PRICING MODEL

This study aims to determine the integration level of Southeast Asian stock market with the world stock market using an international capital asset pricing model. The countries that were sampled in this study were Indonesia, Malaysia, Philippines, Singapore and Thailand. The sample period starts from January 2000 until August 2016. This study uses an partially-segmented international capital asset pricing model by including the assumption of residual that were correlated between asset pricing equations. Because of this assumption, the seemingly unrelated regression (SUR) estimation method is more appropriately compared to the ordinary least square (OLS) method. The results of this study indicate that the integration level of Southeast Asian stock market varies. The Singapore and Thailand stock markets are fully integrated with the world stock market, the Indonesian and Malaysian stock markets are partially integrated with the world stock market, while the Philippine stock market is segmented with the world stock market. This finding shows the difference in the effectiveness of the stock market liberalization process in Southeast Asia

Rare species disproportionally contribute to functional diversity in managed forests

Functional diversity is linked with critical ecosystem functions, yet its relationship with numerical diversity, e.g. species richness, is not fully understood. The mechanisms linking changes of species richness, e.g. random and non-random species losses and gains, with changes of functional diversity become more relevant in the face of rapid environmental changes. In particular, non-random species changes including rare species may affect functional diversity, and the overall ecosystem function, disproportionately compared to random species changes including common species. In this study, I investigated how changes in numerical diversity of bird assemblages are related to functional diversity, and how the environment, and in particular forest management, influences such a relationship. I collected bird count data in the extensively-managed forest landscape of the Black Forest (Germany), at 82 sampling sites over three years. Data included species richness and abundance per site, and functional traits related to diet and habitat type for each species to compute functional diversity. By partitioning numerical diversity changes into five components using Price Equations, I calculated the contribution of random and non-random species losses and gains, and the abundance of common species, to functional diversity. Then I modelled these contributions as a function of several environmental variables describing broad forest conditions, and including forest management intensity. I found that, beside the major contribution of random species losses to functional diversity, non-random species losses also play a role, indicating that rare species that contribute more to functional diversity are often lost earlier than common species. The overall contribution to functional diversity of species losses is larger than that of species gains, pointing toward an ongoing simplification of the forest bird assemblage. Among all Price components, random species gains were influenced by management intensity, while other components were not influenced by any management variable. This highlight that potential conservation actions may not be effective in halting ecosystem functioning decline, as species gains do not result in increased functional diversity.

Good, Better, Best: How Evolution Optimizes Anatomy and Action

Good, Better, Best: How Evolution Optimizes Anatomy and Action

Methodology for Complete Decorrelation of Power Supply EM Side-Channel Signal and Sensitive Data

Electro-magnetic (EM) side channel attacks have become a serious threat to security of Internet-of-Things (IoT) devices. Power supply generated by voltage regulators is one of the most common attack targets due to its strong EM emanations. In this brief we derive analytical conditions for complete theoretical decorrelation of the power supply EM side-channel signal and the sensitive data. The output of the power supply converter is modelled as amplitude modulation (AM) of the load signal by the converter capacitance that acts as a carrier. By applying Price theorem (Papoulis and Pillai, 2002), we obtain the exact theoretical conditions that converter capacitance needs to fulfil in order to prevent EM side-channel attacks. The conditions are further adapted for practical implementation. When the proposed methodology is applied to AES measured traces, the correlation coefficient between the leaked signal and the sensitive data is 0.05. Such low correlation indicates the proposed methodology is a promising candidate against the attacks that exploit AM signals to extract sensitive data, such as, TEMPEST and active EM attacks. Test Vector Leakage Assessment (TVLA) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> -test detects no leaky points, thereby confirming circuit protection against differential and correlation EM attacks as well.

Disentangling Niche Theory and Beta Diversity Change.

AbstractBeta diversity describes the differences in species composition among communities. Changes in beta diversity over time are thought to be due to selection based on species' niche characteristics. For example, theory predicts that selection that favors habitat specialists will increase beta diversity. In practice, ecologists struggle to predict how beta diversity changes. To remedy this problem, we propose a novel solution that formally measures selection's effects on beta diversity. Using the Price equation, we show how change in beta diversity over time can be partitioned into fundamental mechanisms including selection among species, variable selection among communities, drift, and immigration. A key finding of our approach is that a species' short-term impact on beta diversity cannot be predicted using information on its long-term environmental requirements (i.e., its niche). We illustrate how our approach can be used to partition causes of diversity change in a montane tropical forest before and after an intense hurricane. Previous work in this system highlighted the resistance of habitat specialists and the recruitment of light-demanding species but was unable to quantify the importance of these effects on beta diversity. Using our approach, we show that changes in beta diversity were consistent with ecological drift. We use these results to highlight the opportunities presented by a synthesis of beta diversity and formal models of selection.

Code from: Price equations for understanding the response of ecosystem function to community change

Code from: Price equations for understanding the response of ecosystem function to community change