Maximal Extractable Value (MEV) refers to a maximum value block producers can extract from an Ethereum block by reordering, inserting, or censoring transactions. Pair trading is an investment strategy which involves identifying two closely related assets and taking simultaneous long and short positions in them. This strategy aims to generate returns by exploiting price disparities between the two assets, regardless of the broader market’s direction. The purpose of this study is to examine whether pair trading opportunities can be used as a Maximal Extractable Value extraction method on Ethereum Network. The study expands on the existing literature on Maximal Extractable Value by analyzing new kind of extraction method. This study analyzes decentralized exchange transactions between September 2022 and September 2023 to determine the applicability of pair trading logic as a Maximal Extractable Value extraction method. Pair trading opportunities are identified from the transactions following methodology of pair trading literature and pair trading strategy is found to be profitable over a long period, while individual opportunities tend to make a loss. The strategy is also found to remain profitable during the collapse of FTX, bankruptcy of Silicon Valley Bank, exploitation of Curve which were periods of increased market distress. The majority of the opportunities are relatively time sensitive with the median entry window for positions lasting for slightly over 10 minutes, and the median position must be held being 16 minutes before the position reverts or diverges. The study does not find unambiguous evidence of pair trading opportunities’ characteristics changing under increased market distress. Similarly, the study does not find competition among MEV searchers for the pair trading opportunities having increasing or decreasing trend during the observation period.
This article introduces the LP forward contract, a derivative replicating the payoff of a liquidity position (LP) at a future date without intermediate yield. It provides tools for mitigating directional risks and managing impermanent loss. The framework applies the Black-Scholes model to the crypto space, offering closed-form solutions for LP forwards and dynamic hedging strategies. It breaks down HODL portfolios into impermanent loss-hedging portfolios and LP forward contracts, quantifying yield farming costs and enhancing risk management for liquidity providers. This approach aligns the interests of Web3 projects and investors, promoting sustainable growth in DeFi.
NFT-based projects, while being risky, represent great business opportunities for existing businesses and start-ups.In this paper, we propose the use of the Real Options Valuation (ROV) method in evaluating their investment decisions, in which flexibility is defined as the capability to wait for making the investment.The real option model is developed under the assumption that the opportunity to invest is available for a limited time horizon.The resulting partial differential equation for the value of the option to wait can be solved through a convenient approximation that computes the ratio between project value and investment costs. Using several numerical examples, this paper examines how the input parameters entering the valuation model affect the value of its outputs: the value of the flexibility to invest and the ratio at which investment decision becomes optimal. Unlike in a static Net Present Value decision, the examples based on the ROVmethod show that the ratio of the project value to the investment cost must be substantial to justify the investment.In our hypothetical examples, the initial ratio between project value and investment cost, their respective volatility, and the time horizon have a great influence on the decision to invest.
Naielly Lopes Marques, Leonardo Lima Gomes, Luiz Eduardo Teixeira Brandão
ABSTRACT This article proposes an investment model for a renewable energy generator that allows it to earn the right to issue Renewable Energy Certificates (RECs) and sell them through quarterly sales auctions promoted by the blockchain. Blockchain technology can further promote the RECs market, as it enables tokenization and distribution of certificates. We did not find articles in the literature that analyze the decision to invest in decentralized autonomous organizations (DAOs) that have rules for issuing and trading RECs specified in smart contracts, which are executed and validated by the blockchain. This article contributes to the literature on blockchain technology applications in the renewable energy market by proposing issuing and selling RECs tokens through a DAO. The relevance of this research is that it shows that simple real option pricing methods can help decision-makers evaluate investment opportunities under uncertainty and flexibility. The tokenization and distribution of RECs via blockchain can promote transaction agility, reduce or eliminate bureaucracy in the means of payment, and increase the security and transparency of transactions. We propose a model for issuing and selling RECs in smart contracts. We assume that the generator has the flexibility to invest now or in one year to enter the platform, considering the energy generated in one year by a single typical 4MW wind turbine. Our model assumes that the price of the REC token follows an inverse demand function subject to stochastic shocks. The results contribute to the understanding of the performance dynamics of digital products under uncertainty and flexibility and show that distributed ledger technology (DLT) may be a viable alternative for renewable energy incentives.
Novriana Sumarti, Febi A. D. F. Suryawan, Ahmad R. Sumitro
This paper develop an approach to evaluate Bitcoin Mining Project using Real Option Method. In evaluating a project not yet being run, there is opportunity made available to the manager of company to expand or abandon the project if some particular conditions would occur in the time period being projected. The methods are based on Binomial Tree with varying time of Learning Option. Having evaluated the project for five years, it concludes that the project with Real Option methods can increase the value of the project.
Francisco López Herrera, División de Investigación, Facultad de Contaduría y Administración, Universidad Nacional Autónoma de México, Ciudad de México, México., Luis Guadalupe Macías-Trejo, Oscar V. De la Torre-Torres
Este artículo muestra los resultados de un análisis del desempeño de ocho de los criptoactivos más importantes entre la gran variedad que actualmente existe en el mercado. Se estudia su riesgo de mercado con base en métricas ampliamente utilizadas para activos financieros. El análisis se complementa con la evaluación de su desempeño dentro de portafolios formados con criterios convencionales. Se encuentra un comportamiento bastante heterogéneo entre los activos estudiados, sugiriendo que tal comportamiento obedece a las características específicas de cada uno de ellos, más que a las características comunes como una clase específica de activos.
Purpose This paper aims to examine the applicability of real options methodology with respect to developing internal transfer pricing mechanisms. A pervasive theme in existing models is their inability to handle the dynamic and volatile nature of today’s business environment, as well as their lack of objective managerial flexibility. The authors address these and other issues and develop a transfer pricing mechanism based on Black–Scholes and the binomial options pricing methodology, which is better suited in today’s dynamic business environment. Design/methodology/approach The authors use a conceptual approach in developing theoretical justifications and show, practically, how a transfer price can be developed using two different real options pricing models. Findings The authors find that real options transfer price mechanism (real options framework [ROF]) can effectively deal with many of the issues that permeate a modern organization with complex multi-dimensional operations. The authors argue that uncertainty and behavioral issues commonly associated with setting transfer prices are better handled using a transfer pricing mechanism that preserves flexibility at the business unit level, the managerial level and the firm level. The approach allows for different managerial styles in both centralized and decentralized sub-units within the same organization. The authors argue that an open multi-dimensional framework using real options is suitable under conditions of uncertainty and managerial opportunism. Practical implications ROF-based transfer pricing may be significant in that firms can use it as a tool to manage an organization by setting the prices centrally and at the same time allowing managers to select the transfer price that best suits their specific situation and operating conditions. This may result in a more efficient and more profitable organization. Originality/value The contribution of the paper is the melding of the ROF from the finance literature with the accounting problem of setting a transfer price for items lacking a competitive market price. The authors also contribute to existing research by explicitly developing a framework that values managerial flexibility, takes into account uncertainty and considers the behavioral aspects of the transfer pricing process. The authors establish the conditions under which a generic real options model is a feasible alternative in determining a transfer price.
This thesis examines how Distributed Ledger Technologies (DLTs) could be utilized in capital markets in general and in the Nordic capital market in particular. DLTs were introduced with the so called cryptocurrency Bitcoin in 2009 and has in the last few years been of interest to various financial institutions as a means to streamline financial processes. By combining computer scientific concepts such as public-key cryptography and consensus algorithms DLTs make it possible to keep shared databases with limited trust among the participators and without the use of a trusted third party. In this thesis various actors on the Nordic capital market were interviewed and their stance on DLTs were summarized. In addition to this a Proof of Concept of a permissioned DLT application for ownership registration of securities was constructed. It was found that all the interviewees were generally optimistic about DLTs potential to increase the efficiency of capital markets. The technology needs to be adopted to handle the capital markets demand for privacy and large transaction volumes, but there is a general agreement among the interviewees that these issues will be solved. The biggest challenge for an adoption of DLTs seem to lie in that of finding a common industry-wide standard.
Decentralized generation on the owners premises can be used on-site which we call auto-consumption. In a system with energy based (volumetric) network charges this reduces network income and in turn causes higher network charges on remaining usage with redistributional effects among customers. We estimate the effect from PV auto-consumption in Germany to be small in many network areas but significant in others leading to significant regional unequality. The effect may be self-enforcing and could increase strongly with pronounced shares of PV and auto-consumption. Further analysis should address the causal links to inform modifications to network charging for higher cost causality in power systems with high shares of (renewable) decentralized generation. Meanwhile a higher fixed component in network charges could be a pragmatic way to mitigate effects and serve a more equal participation of auto-consumers in network financing.
Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC) and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS) flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.
Performing a valuation exercise of decentralized companies that explore and exploit natural resources (such as Pemex) interpreted from the perspective of a “Special Purpose Vehicle” (SPV), modeled as structured debt, allowing a deeper analysis when the entity does not own the generating assets of its operating cash flow when capital has a negative book value, the generation of free cash flows is negative and it is subject to tax royalty payments that do not allow for deductibility of debt. Moreover, given its high tax burden and that it is forced to issue debt to finance their capital investments, it is unclear whether it can generate resources to meet its labor and/or financial liabilities, particularly if energy prices would fall. These obligations are modeled as options. In summary, this exercise helps to identify key factors in its operations and finances
Listed real estate companies, just like all other listed companies around the world, have to publish quarterly as well as annual reports, informing the public and especially the share and stake holders about the current development of the company. These reports are always awaited with great anticipation. Will there be bad news or good news in the report? And if there is bad news, is it as bad as suspected or better and vise versa are good financial news as good as everybody expected. Depending on this news, changes in the stock price are expected, as well as observed changes in stock price are often explained with an interpretation of the content of the reports. It is commonly expected and believed that bad news have a negative effect on the performance and vise versa with god news. As obvious as it seems, so difficult it is to proof, as god and bad is not an absolute definition but rather a relative one in the eye of the beholder. An interesting question arising from this is, if the publication of financial reports have an general impact, meaning ìalwaysî significantly positive or negative, basically regardless of the content. In order to verify whether the publication of these reports has an effect, an event study shall observe abnormal returns around the time of the publication. Further options are to test if relatively late / early publication has an effect ñ a problem here will be the definition of the ìnormalî time of publication ñ and if the timing within the week or the timing with regard to the period of the year have an influence. // ï The aim of this study is to find out whether a general effect (always positive or always negative) on stock performance can be observed caused by the publication of financial reports, although it is commonly expected to depend upon the content; ï Does it matter whether the reports are published relatively early or relatively late; ï Does timing matter with regard to day of the week or period of the year // On a scientific level, the contribution of this study lies in analyzing whether behavioral effects influence the stock performance of listed real estate companies. From a professional point of view, implications for an optimized investment strategy can be obtained as well as implications for the optimal information strategy of listed real estate companies with regard to their stock performance.
This paper studies the effects of stock market valuation on research investment, the rate of innovation, and welfare. In the presence of financing constraints for R&D investment, episodes of high market valuation can ease these constraints and raise the economy-wide investment in R&D and the rate of innovation. If the decentralized equilibrium rate of innovation is inefficiently low, then such episodes may lead to an increase in aggregate welfare even if the higher valuation is not entirely justified by fundamentals. We present a Schumpeterian-style growth model with a costly financial intermediation process to characterize the relationship between market value, entry of new firms, and the aggregate rate of innovation. We use the model to measure the welfare consequences of a stock market run-up that may only partly be justified by fundamentals. In particular, we apply the model to the US economy in the 1990s and calibrate the impact of the NASDAQ boom on the rate of innovation, growth and welfare. The welfare effect depends on the underlying change in fundamentals. We find that with an acceleration in US trend productivity growth from a pre-1995 rate of 1.4% to a rate of 2.0% per annum, the NASDAQ boom will have resulted in a net welfare gain of 0.55%. If the new growth rate is as high as 3%, the net gain was 1.35% of the present discounted value of consumption.