Tokenization promises to convert lumpy, illiquid real-world assets into divisible, transferable claims, yet secondary markets for these instruments remain thin and trading is infrequent. Standard asset pricing models, including the capital asset pricing model and its liquidity-adjusted extensions, were not designed for assets whose holders derive consumption, access, or governance value directly from ownership. This paper develops a conceptual asset pricing framework for utility-backed non-fungible tokens (NFTs) and tokenized real-world assets by augmenting the liquidity-adjusted capital asset pricing model with a utility (convenience) yield. The framework decomposes the required pecuniary return into a risk-free rate, a systematic liquidity-risk premium, an amortized illiquidity level premium that scales with transaction costs and turnover, and a utility-yield offset that lowers the return investors require in cash. Two analytical implications follow. First, utility backing compresses observed pecuniary returns without eliminating the underlying illiquidity premium. Second, where utility flows covary positively with illiquidity, estimates that regress pecuniary returns on liquidity proxies understate the gross illiquidity premium. An illustrative calibration, with parameter ranges drawn from the empirical tokenization literature, quantifies the mechanism rather than estimating it. The framework yields testable predictions and implications for valuation and disclosure.
The explosive popularity of blockchain-based gaming has brought non-fungible tokens (NFTs) into the fray, as tradable collectibles that connote not only monetary worth but an experience as well. In contrast to traditional in-game items, gaming NFTs exist in two domains of use, on-chain marketplaces and off-chain ecosystems, providing new twists to their valuation. This paper analyzes the approach, issues, and possible developments of the NFT gaming collectibles valuation by consolidating the knowledge in economics, data science, and digital games research. We then present a taxonomy of value drivers, gameplay utility, rarity, provenance, community effects, and tokenomics, to develop a conceptual background. We then compare the relative advantages and (*) disadvantages of popular valuation methods, including hedonic pricing models, repeat-sales indices, machine learning, and liquidity-adjusted approaches. We also identify structural issues of this nascent market, including wash trading, fragmentation of liquidity, evolving product utility, mutability of metadata, and regulatory uncertainty. Critical synthesis helps us see how valuation practices are susceptible to abuse on both sides: how we can abuse the market, but also how we can design the technical aspects of markets to cheat. Lastly, we discuss research directions in the form of standardized benchmarks, dynamic valuation frameworks, interoperability-adjusted models, and integrity checks. The paper will contribute to both the academic and practice worlds as it will provide a reproducible course of action by scholars, game development companies, investors, and marketplaces interested in designing open and sustainable valuation methods for the gaming NFTs.
Smart contracts upgradeability is a critical requirement for modern decentralized applications based on blockchain technology, but its implementation remains a technical challenge due to the immutable nature of smart contracts. The Proxy Pattern has become the most widely used solution for implementing upgradability into smart contracts, but it comes with some limitations such as implementation complexity and strict memory layout inheritance. This paper introduces an alternative approach based on dynamic routing with Router Contract, which enables modular upgradeability through centralized address management, offering greater flexibility at the cost of requiring external state persistence. Furthermore, a hybrid architecture is proposed, combining both Proxy Pattern and Router Contract approaches to achieve dual-layer upgradeability – supporting both state-preserving updates and full module replacements. The paper offers a comprehensive evaluation of upgradeability strategies and proposes a versatile solution for evolving smart contract systems.
Bitcoin treasury companies have taken stock markets by storm amassing billions of dollars worth of tokens in hundreds of entities. The paper discusses, how leverage - whether created through corporate debt or investors using stock as loan collateral - fuels this trend. The extension of the binary-choice Kelly criterion to incorporate uncertainty in the form of the Kullback-Leibler divergence or more generally Bregman divergence is also briefly discussed.
This paper introduces a novel multi-objective optimization framework for sustainable portfolio rebalancing under uncertainty. The model simultaneously targets return maximization, downside risk control, and liquidity preservation, addressing the complex trade-offs faced by investors in volatile markets. Unlike traditional static approaches, the framework allows for dynamic asset reallocation and explicitly incorporates nonlinear transaction costs, offering a more realistic representation of trading frictions. Key financial parameters—including expected returns, volatility, and liquidity—are modeled using interval arithmetic, enabling a flexible, distribution-free depiction of uncertainty. Risk is measured through semi-absolute deviation, providing a more intuitive and robust assessment of downside exposure compared to classical variance. A core innovation lies in the behavioral modeling of investor preferences, operationalized through three strategic configurations, pessimistic, optimistic, and mixed, implemented via convex combinations of interval bounds. The framework is empirically validated using a diversified cryptocurrency portfolio consisting of Bitcoin, Ethereum, Solana, and Binance Coin, observed over a six-month period. The simulation results confirm the model’s adaptability to shifting market conditions and investor sentiment, consistently generating stable and diversified allocations. Beyond its technical rigor, the proposed framework aligns with sustainability principles by enhancing portfolio resilience, minimizing systemic concentration risks, and supporting long-term decision-making in uncertain financial environments. Its integrated design makes it particularly suitable for modern asset management contexts that require flexibility, robustness, and alignment with responsible investment practices.
Romario Desouza Daniel Mangiwa, Revina Siregar, Sri Anum Sari, Neli Agustina
Ethereum is one of the leading cryptocurrencies utilizing blockchain technology for peer-to-peer financial transactions. This study aims to forecast Ethereum's price using the Autoregressive Integrated Moving Average (ARIMA)model. Historical price data from January 1, 2023, to January 15, 2025, covering 534 periods, was analyzed. The ARIMA (0,1,9) model was selected based on AIC, SC, and Adjusted R-squared criteria, with forecast evaluation showing a Mean Absolute PercentageError (MAPE) of 15.01% and a Root Mean Squared Error (RMSE) of 649.702. Forecast results indicate an upward trend in Ethereum's price over the next 30 periods, with fluctuations being less pronounced compared to historical data. The study concludes that ARIMA provides reasonably accurate short-term predictions, although forecasting errors increase with longer prediction periods. These findings can serve as a reference for investors in developing short-term investment strategies for Ethereum.
The accelerating shift toward a digital economy, driven by advancements in technology, has fundamentally transformed the nature of assets, markets, and business models. In this changing environment, Fair Value Accounting (FVA) — which aims to measure assets and liabilities based on current market conditions — faces unprecedented challenges and opportunities. The emergence of digital assets such as cryptocurrencies, non-fungible tokens (NFTs), and decentralized finance (DeFi) products has exposed limitations in traditional valuation frameworks, highlighting issues related to market volatility, illiquidity, and the absence of standardized valuation practices. At the same time, technological innovations like artificial intelligence (AI), big data analytics, and blockchain technology offer new tools that can enhance the accuracy, transparency, and timeliness of fair value measurements. This paper critically examines the future trajectory of fair value accounting in a digitalized world, identifies the major obstacles in valuing digital assets, and explores the role of emerging technologies in addressing these gaps. By analyzing global regulatory responses and proposing strategic reforms, this study provides insights into how accounting standards must evolve to maintain relevance, reliability, and comparability in financial reporting. Ultimately, the paper argues for a proactive transformation of FVA practices, integrating dynamic digital valuation methods while preserving the core principles of accountability, transparency, and investor protection in an increasingly complex economic landscape.
In the ever evolving landscape of decentralized finance automated market makers (AMMs) play a key role: they provide a market place for trading assets in a decentralized manner. For so-called bluechip pairs, arbitrage activity provides a major part of the revenue generation of AMMs but also a major source of loss due to the so-called 'informed orderflow'. Finding ways to minimize those losses while still keeping uninformed trading activity alive is a major problem in the field. In this paper we will investigate the mechanics of said arbitrage and try to understand how AMMs can maximize the revenue creation or in other words minimize the losses. To that end, we model the dynamics of arbitrage activity for a concrete implementation of a pool and study its sensitivity to the choice of fee aiming to maximize the revenue for the AMM. We identify dynamical fees that mimic the directionality of the price due to asymmetric fee choices as a promising avenue to mitigate losses to toxic flow. This work is based on and extends a recent article by some of the authors.
Decentralized autonomous organizations (DAOs) are emerging innovative organizational structures, enabling collective coordination, and reshaping digital collaboration. Despite the promising and transformative characteristics of DAOs, the potential technological advancements and the understanding of the business value that organizations derive from implementing DAO characteristics are limited. This research applies a systematic review of DAOs' business applicability from an open systems perspective following a best-fit framework methodology. Within our approach, combining both framework and thematic analysis, we discuss how the open business principles apply to DAOs and present a new DAO business framework comprising of four core business elements: i) token, ii) transactions, iii) value system and iv) strategy with their corresponding sub-characteristics. This paper offers a preliminary DAO business framework that enhances the understanding of DAOs' transformative potential and guides organizations in innovating more inclusive business models (BMs), while also providing a theoretical foundation for researchers to build upon.
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.
C. Vinoth Kumar, Poongundran Selvaprabhu, Nivetha Baska, Vivek Menon U · 7 authors
The Know Your Customer (KYC) process is a fundamental prerequisite for any financial institution’s compliance with the regulatory framework. Blockchain technology has emerged as a revolutionary solution to enhance the effectiveness of the KYC procedure. It ensures that the KYC process is transparent, secure, and immutable, thereby offering a robust solution to combat fraudulent activities. The potential of blockchain technology in revolutionizing the KYC process has been acknowledged globally. Blockchain technology provides a decentralized platform for storing customer data, enabling financial institutions to access the information seamlessly. Using ethereum blockchain technology in KYC procedures can enhance the efficiency of financial institutions, significantly reducing the time and cost associated with the process. This work aims to provide a viable and sustainable solution to the challenges that banks experience in implementing KYC procedures and onboarding new customers. The proposed solution involves the central bank maintaining a comprehensive register of all registered banks while closely monitoring their adherence to the existing regulations governing KYC and customer acquisition.
Non-fungible tokens (NFTs), one of the most talked about technological innovations within Web 3.0 discourse, has stirred awe and confusion in the recent months. While interest in NFTs has grown rapidly in the marketing and the broader business literatures, the question of their value remains a theoretical puzzle. The mystery created by the millions of dollars paid for some NFTs while others are virtually worthless hampers our understanding of what constitutes the value of an NFT. Thus, an appreciation of NFT valuation can advance our theory of value, with implications for businesses. In an attempt to shed light on what drives the value of an NFT we develop a theoretical framework involving a typology of value construction and value perception for NFTs based on two main dimensions––legitimacy (extrinsic vs performative) and groundedness (connection to people, places, or times). We specify four types of NFTs based on subjective and objective dimensions that extend and enrich our theory of the value. We then detail further elements shaping NFT valuation. Finally, we offer advice on how to make sense of value construction and perceptions of NFTs. While our paper is mostly about object valuation, we briefly consider person, culture, and situation factors that also affect valuation. But since the market is agnostic with regard to such factors, we emphasize the NFT object. We end the paper by outlining a research agenda that can push research on NFT forward as crypto and metaverse markets develop.
Victor von Wachter, Johannes Rude Jensen, Ferdinand Regner, Omri Ross
The smart contract-based markets for non-fungible tokens (NFTs) on the Ethereum blockchain have seen tremendous growth in 2021, with trading volumes peaking at 3.5b in September 2021. This dramatic surge has led to industry observers questioning the authenticity of on-chain volumes, given the absence of identity requirements and the ease with which agents can control multiple addresses. We examine potentially illicit trading patterns in the NFT markets from January 2018 to mid-November 2021, gathering data from the 52 largest collections by volume. Our findings indicate that within our sample 3.93% of addresses, processing a total of 2.04% of sale transactions, trigger suspicions of market abuse. Flagged transactions contaminate nearly all collections and may have inflated the authentic trading volumes by as much as 149,5m for the period. Most flagged transaction patterns alternate between a few addresses, indicating a predisposition for manual trading. We submit that the results presented here may serve as a viable lower bound estimate for NFT wash trading on Ethereum. Even so, we argue that wash trading may be less common than what industry observers have previously estimated. We contribute to the emerging discourse on the identification and deterrence of market abuse in the cryptocurrency markets.
Cryptocurrency and blockchain has conjointly become trending buzzwords in the business\nworld today. As the blockchain technology has become older and more researched, its areas\nof usage have broadened far beyond payment solutions like Bitcoin. In venture financing,\nblockchain has been used to establish a prominent fundraising tool, called initial coin offerings\n(ICO). An ICO is a crowdfunding method resembling initial public offerings, where ventures\nissue a blockchain based token, subject to public sale. ICO has become a lucrative financing\nmethod for blockchain affiliated ventures.\nThe hype around cryptocurrency has led to increased ICO attention. Everyone can invest in an\nICO, and thus, it has become a popular investment opportunity. This thesis looks at ICOs as\ninvestment objects, with the aim to find out what an investor should consider before investing.\nAdditionally, we assess whether ICOs are profitable financial instruments relative to its close\nsubstitutes, and evaluate measures to avoid scams.\nThe study is based on 104 companies that have had ICOs, and analyzes what factors influence\nboth ICO success rate, and post-ICO capital gains. Our results indicate that hype and pricing\nis influential on the outcome of an ICO, which in turn is important for subsequent price\nmovements. We have also observed that venture capital seed funded companies performed\nbetter in the ICO aftermath. By further using the results, we have also found that investors\nmay use these parameters when investing in an ICO to outperform both our benchmark\ncryptocurrency Ethereum, and other ICOs.
Trading securities is a process that requires multiple trusted intermediaries to ensure that the trade is done correctly. The securities industry is therefore very slow and expensive; the central securities depository (CSD) being one of the main contributors to the disruption. In an effort to fix this, financial institutions has recently started looking into the blockchain technology; the innovation behind the cryptocurrency Bitcoin. Bitcoin is a digital currency that can be traded peer-to-peer without the need for a trusted intermediary. If this concept could be used when trading securities it would simplify the process, making the settlement-time near instant. In addition to the speedup, it would also save the industry a lot of money since many processes could be automated. The purpose of this paper is to provide an overview of the blockchain technology and its applications in the finance industry. The focus is on how a blockchain could be used to reduce the responsibility of the central securities depository as much as possible, and especially on how corporate actions could be automated. The goal is to answer these questions: Is blockchain a suitable platform for a decentralized corporate actions solution? Whatare the benefits and drawbacks of using a blockchain versus a traditional centralized solution? The aim is to provide an evaluation of the usage of blockchains in finance, with extra focus on the CSD and corporate actions
Stewart C. Myers President of American Finance Association 1983 This paper's title is intended to remind you of Fischer Black's well-known note on “The Dividend Puzzle,” which he closed by saying, “What should the corporation do about dividend policy? We don't know.” 6 I will start by asking, “How do firms choose their capital structures?” Again, the answer is, “We don't know.” The capital structure puzzle is tougher than the dividend one. We know quite a bit about dividend policy. John Lintner's model of how firms set dividends 20 dates back to 1956, and it still seems to work. We know stock prices respond to unanticipated dividend changes, so it is clear that dividends have information content—this observation dates back at least to Miller and Modigliani (MM) in 1961 28. We do not know whether high dividend yield increases the expected rate of return demanded by investors, as adding taxes to the MM proof of dividend irrelevance suggests, but financial economists are at least hammering away at this issue. By contrast, we know very little about capital structure. We do not know how firms choose the debt, equity or hybrid securities they issue. We have only recently discovered that capital structure changes convey information to investors. There has been little if any research testing whether the relationship between financial leverage and investors' required return is as the pure MM theory predicts. In general, we have inadequate understanding of corporate financing behavior, and of how that behavior affects security returns. I do not want to sound too pessimistic or discouraged. We have accumulated many helpful insights into capital structure choice, starting with the most important one, MM's No Magic in Leverage Theorem (Proposition I) 31. We have thought long and hard about what these insights imply for optimal capital structure. Many of us have translated these theories, or stories, of optimal capital structure into more or less definite advice to managers. But our theories don't seem to explain actual financing behavior, and it seems presumptuous to advise firms on optimal capital structure when we are so far from explaining actual decisions. I have done more than my share of writing on optimal capital structure, so I take this opportunity to make amends, and to try to push research in some new directions. A static tradeoff framework, in which the firm is viewed as setting a target debt-to-value ratio and gradually moving towards it, in much the same way that a firm adjusts dividends to move towards a target payout ratio. An old-fashioned pecking order framework, in which the firm prefers internal to external financing, and debt to equity if it issues securities. In the pure pecking order theory, the firm has no well-defined target debt-to-value ratio. Recent theoretical work has breathed new life into the pecking order framework. I will argue that this theory performs at least as well as the static tradeoff theory in explaining what we know about actual financing choices and their average impacts on stock prices. I have arbitrarily, and probably unfairly, excluded “managerial” theories which might explain firms' capital structure choices.1 I have chosen not to consider models which cut the umbilical cord that ties managers' acts to stockholders' interests. I am also sidestepping Miller's idea of “neutral mutation.”2 He suggests that firms fall into some financing patterns or habits which have no material effect on firm value. The habits may make managers feel better, and since they do no harm, no one cares to stop or change them. Thus someone who identifies these habits and uses them to predict financing behavior would not be explaining anything important. The neutral mutations idea is important as a warning. Given time and imagination, economists can usually invent some model that assigns apparent economic rationality to any random event. But taking neutral mutation as a strict null hypothesis makes the game of research too tough to play. If an economist identifies costs of various financing strategies, obtains independent evidence that the costs are really there, and then builds a model based on these costs which explains firms' financing behavior, then some progress has been made, even if it proves difficult to demonstrate that, say, a type A financing strategy gives higher firm value than a type B. (In fact, we would never see type B if all firms follow value-maximizing strategies.) There is another reason for not immediately embracing neutral mutations: we know investors are interested in the firm's financing choices, because stock prices change when the choices are announced. The change might be explained as an “information effect” having nothing to do with financing per se—but again, it is a bit too easy to wait until the results of an event study are in, and then to think of an information story to explain them. On the other hand, if one starts by assuming that managers have special information, builds a model of how that information changes financing choices, and predicts which choices will be interpreted by investors as good or bad news, then some progress has been made. So this paper is designed as a one-on-one competition of the static tradeoff and pecking-order stories. If neither story explains actual behavior, the neutral mutations story will be there faithfully waiting. A firm's optimal debt ratio is usually viewed as determined by a tradeoff of the costs and benefits of borrowing, holding the firm's assets and investment plans constant. The firm is portrayed as balancing the value of interest tax shields against various costs of bankruptcy or financial embarassment. Of course, there is controversy about how valuable the tax shields are, and which, if any, of the costs of financial embarassment are material, but these disagreements give only variations on a theme. The firm is supposed to substitute debt for equity, or equity for debt, until the value of the firm is maximized. Thus the debt-equity tradeoff is as illustrated in Fig. 1. Costs of adjustment. If there were no costs of adjustment, and the static tradeoff theory is correct, then each firm's observed debt-to-value ratio should be its optimal ratio. However, there must be costs, and therefore lags, in adjusting to the optimum. Firms can not immediately offset the random events that bump them away from the optimum, so there should be some cross-sectional dispersion of actual debt ratios across a sample of firms having the same target ratio. The static-tradeoff theory of capital structure. Large adjustment costs could possibly explain the observed wide variation in actual debt ratios, since firms would be forced into long excursions away from their optimal ratios. But there is nothing in the usual static tradeoff stories suggesting that adjustment costs are a first-order concern—in fact, they are rarely mentioned. Invoking them without modelling them is a cop-out. Any cross-sectional test of financing behavior should specify whether firms' debt ratios differ because they have different optimal ratios or because their actual ratios diverge from optimal ones. It is easy to get the two cases mixed up. For example, think of the early cross-sectional studies which attempted to test MM's Proposition I. These studies tried to find out whether differences in leverage affected the market value of the firm (or the market capitalization rate for its operating income). With hindsight, we can quickly see the problem: if adjustment costs are small, and each firm in the sample is at, or close to its optimum, then the in-sample dispersion of debt ratios must reflect differences in risk or in other variables affecting optimal capital structure. But then MM's Proposition I cannot be tested unless the effects of risk and other variables on firm value can be adjusted for. By now we have learned from experience how hard it is to hold “other things constant” in cross-sectional regressions. Of course, one way to make sense of these tests is to assume that adjustment costs are small, but managers don't know, or don't care, what the optimal debt ratio is, and thus do not stay close to it. The researcher then assumes some (usually unspecified) “managerial” theory of capital structure choice. This may be a convenient assumption for a cross-sectional test of MM's Proposition I, but not very helpful if the object is to understand financing behavior.3 But suppose we don't take this “managerial” fork. Then if adjustment costs are small, and firms stay near their target debt ratios, I find it hard to understand the observed diversity of capital structures across firms that seem similar in a static tradeoff framework. If adjustment costs are large, so that some firms take extended excursions away from their targets, then we ought to give less attention to refining our static tradeoff stories and relatively more to understanding what the adjustment costs are, why they are so important, and how rational managers would respond to them. But I am getting ahead of my story. On to debt and taxes. Debt and taxes. Miller's famous “Debt and Taxes” paper 27 cut us loose from the extreme implications of the original MM theory, which made interest tax shields so valuable that we could not explain why all firms were not awash in debt. Miller described an equilibrium of aggregate supply and demand for corporate debt, in which personal income taxes paid by the marginal investor in corporate debt just offset the corporate tax saving. However, since the equilibrium only determines aggregates, debt policy should not matter for any single taxpaying firm. Thus Miller's model allows us to explain the dispersion of actual debt policies without having to introduce non-value-maximizing managers.4 Trouble is, this explanation works only if we assume that all firms face approximately the same marginal tax rate, and that is an assumption we can immediately reject. The extensive trading of depreciation tax shields and investment tax credits, through financial leases and other devices, proves that plenty of firms face low marginal rates.5 Given significant differences in effective marginal tax rates, and given that the static tradeoff theory works, we would expect to find a strong tax effect in any cross-sectional test, regardless of whose theory of debt and taxes you believe. Figure 2 plots the net tax gain from corporate borrowing against the expected realizable tax shield from a future deduction of one dollar of interest paid. For some firms this number is 46 cents, or close to it. At the other extreme, there are firms with large unused loss carryforwards which pay no immediate taxes. An extra dollar of interest paid by these firms would create only a potential future deduction, usable when and if the firm earns enough to work off prior carryforwards. The expected realizable tax shield is positive but small. Also, there are firms paying taxes today which cannot be sure they will do so in the future. Such a firm values expected future interest tax shields at somewhere between zero and the full statutory rate. In the “corrected” MM theory 28 any tax-paying corporation gains by borrowing; the greater the marginal tax rate, the greater the gain. This gives the top line in the figure. In Miller's theory, the personal income taxes on interest payments would exactly offset the corporate interest tax shield, provided that the firm pays the full statutory tax rate. However, any firm paying a lower rate would see a net loss to corporate borrowing and a net gain to lending. This gives the bottom line. There are also compromise theories, advanced by D'Angelo and Masulis 12, Modigliani 30 and others, indicated by the middle dashed line in the figure. The compromise theories are appealing because they seem less extreme than either the MM or Miller theories. But regardless of which theory holds, the slope of the line is always positive. The difference between (1) the tax advantage of borrowing to firms facing the full statutory rate, and (2) the tax advantage of lending (or at least not borrowing) to firms with large tax loss carryforwards, is exactly the same as in the “extreme” theories. Thus, although the theories tell different stories about aggregate supply and demand of corporate debt, they make essentially the same predictions about which firms borrow more or less than average. The net tax gain to corporate borrowing. So the tax side of the static tradeoff theory predicts that IBM should borrow more than Bethlehem Steel, other things equal, and that General Motors' debt-to-value ratio should be more than Chrysler's. Costs of financial distress. Costs of financial distress include the legal and administrative costs of bankruptcy, as well as the subtler agency, moral hazard, monitoring and contracting costs which can erode firm value even if formal default is avoided. We know these costs exist, although we may debate their magnitude. For example, there is no satisfactory explanation of debt covenants unless agency costs and moral hazard problems are recognized. The literature on costs of financial distress supports two qualitative statements about financing behavior.6 Risky firms ought to borrow less, other things equal. Here “risk” would be defined as the variance rate of the market value of the firm's assets. The higher the variance rate, the greater the probability of default on any given package of debt claims. Since costs of financial distress are caused by threatened or actual default, safe firms ought to be able to borrow more before expected costs of financial distress offset the tax advantages of borrowing. Firms holding tangible assets-in-place having active second-hand markets will borrow less than firms holding specialized, intangible assets or valuable growth opportunities. The expected cost of financial distress depends not just on the probability of trouble, but the value lost if trouble comes. Specialized, intangible assets or growth opportunities are more likely to lose value in financial distress. Firms prefer internal finance. They adapt their target dividend payout ratios to their investment opportunities, although dividends are sticky and target payout ratios are only gradually adjusted to shifts in the extent of valuable investment opportunities. Sticky dividend policies, plus unpredictable fluctuations in profitability and investment opportunities, mean that internally-generated cash flow may be more or less than investment outlays. If it is less, the firm first draws down its cash balance or marketable securities portfolio.7 If external finance is required, firms issue the safest security first. That is, they start with debt, then possibly hybrid securities such as convertible bonds, then perhaps equity as a last resort. In this story, there is no well-defined target debt-equity mix, because there are two kinds of equity, internal and external, one at the top of the pecking order and one at the bottom. Each firm's observed debt ratio reflects its cumulative requirements for external finance. The pecking order literature. The pecking order hypothesis is hardly new.8 For example, it comes through loud and clear in Donaldson's 1961 study of the financing practices of a sample of large corporations. He observed 13 that “Management strongly favored internal generation as a source of new funds even to the exclusion of external funds except for occasional unavoidable ‘bulges’ in the need for funds.” These bulges were not generally met by cutting dividends: Reducing the “customary cash dividend payment… was unthinkable to most managements except as a defensive measure in a period of extreme financial distress” (p. 70). Given that external finance was needed, managers rarely thought of issuing stock: Though few companies would go so far as to rule out a sale of common under any circumstances, the large majority had not had such a sale in the past 20 years and did not anticipate one in the foreseeable future. This was particularly remarkable in view of the very high Price-Earnings ratios of recent years. Several financial officers showed that they were well aware that this had been a good time to sell common, but the reluctance still persisted. (pp. 57–58). Of course, the pecking order hypothesis can be quickly rejected if we require it to explain everything. There are plenty of examples of firms issuing stock when they could issue investment-grade debt. But when one looks at aggregates, the heavy reliance on internal finance and debt is clear. For all non-financial corporations over the decade 1973–1982, internally generated cash covered, on average, 62 percent of capital expenditures, including investment in inventory and other current assets. The bulk of required external financing came from borrowing. Net new stock issues were never more than 6 percent of external financing.9 Anyone innocent of modern finance who looked at these statistics would find the pecking order idea entirely plausible, at least as a description of typical behavior. Writers on “managerial capitalism” have interpreted firms' reliance on internal finance as a byproduct of the separation of ownership and control: professional managers avoid relying on external finance because it would subject them to the discipline of the capital market.10 Donaldson's 1969 book was not primarily about managerial capitalism, but he nevertheless observed that the financing decisions of the firms he studied were not directed towards and that to explain decisions would have to start by the “managerial of corporate finance. This is given the of finance theory in the it is not so that financing by a pecking order against interests. financing with I to the pecking order story because I could think of no theoretical for it that would in with the theory of modern finance. An could be made for internal financing to avoid issue costs, and if external finance is needed, for debt to avoid the still higher costs of But issue costs in do not seem large enough to the costs and benefits of leverage in the static tradeoff story. However, recent work based on information gives predictions in line with the pecking order The is based on a paper by and although I will down that paper's to the firm has to in order to some valuable investment be this net value and be what the firm will be if the opportunity is The firm's what and are, but investors in capital markets do they see only a of values The information is as from the information capital markets are and MM's Proposition I in the sense that the stock of debt to assets is if information to investors is constant. 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However, there are cases in which the value of is always less for debt than for For example, if the firm can issue debt, is and the firm never a valuable investment Thus, the to issue debt is as good as cash in the if default risk is the value of will be less for debt than for equity if we make the of Thus, if the has information it is to issue debt than This assumes that new or debt would be if the managers' information is so that any security issue would be In this the firm want to make as large as to take advantage of new If stock would seem than debt The rule seems to debt when investors the and equity, or some other when they The trouble with this strategy is you in investors' If you know the firm will issue equity only when it is and debt you will to equity unless the firm has its is, unless the firm has so much debt that it would face costs in issuing Thus investors would the firm to follow a pecking this is too The model just would need of out before it could actual behavior. I have it just to how models based on information can predict the two of the pecking order the for internal the for debt over equity if external financing is I will now what we know about financing behavior and try to make sense of this in of the two I with about financing behavior, and then a few from evidence or personal Of even based on good statistics have been to away under so with external investment are by debt issues and internally-generated stock issues a relatively as has this is what many managers they are to This is what the pecking order hypothesis in the first However, it might also be explained in a static tradeoff theory by adding significant costs of equity issues and the tax of capital gains to This would make external equity relatively It would explain why companies target dividend low enough to avoid having to make stock It would also explain why a firm whose debt ratio target not immediately issue back debt, and a more debt-to-value ratio. Thus firms might take extended excursions their debt that the static tradeoff hypothesis as usually rarely this of adjustment But the costs of seems small. It is thus hard to explain extended excursions a firm's debt target by an static tradeoff firm could quickly issue debt and back if personal income taxes are important in explaining firms' apparent for internal equity, then difficult to explain why external equity is not strongly is, why most firms gradually to lower target payout ratios and the cash to of security Firms try to stock issues when security prices are Given that they external they are more likely to issue stock than stock prices have than they have For example, past stock were one of the variables in study of firms' choices between new debt and new equity and have similar behavior in the This is to static tradeoff If firm value the debt-to-value ratio and firms ought to issue debt, not equity, to their capital The is to the pecking order There is no reason to that the information is more when stock prices are if there were such a investors would have learned it by and would the firm's issue There is no way firms can take advantage of of new equity in a rational against and growth opportunities. Firms holding valuable intangible assets or growth opportunities to borrow less than firms holding tangible assets. For example, and a significant relationship between of investment in and research and and the of borrowing. They also a significant positive relationship between the rate of capital and and the of borrowing. the same by a different for a firm's and growth opportunities was the difference between the market value of its debt and equity securities and the cost of its tangible assets. The higher this he the less the firm's debt-to-value ratio. There is plenty of evidence that the of borrowing is determined not just by the value and risk of the firm's but also by the type of assets it For example, without this the static tradeoff theory would specify all target debt ratios in of not book Since many firms have market values far in of book values if book values are in current we ought to see at least a few such firms operating at very high book debt of we do This to make as as we that book values reflect assets-in-place assets and values reflect and growth opportunities as well as Thus, firms do not set target book debt ratios because the values are for the values of assets in Masulis has that stock prices on average, when a firm