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Our objective is to spell out accounting’s economic roles. Our thesis is that earnings and other accounting outputs help firms function more efficiently. Within the firm, accounting information makes contracts work better and aids managerial decisions in the absence of available prices. In capital market exchanges, accounting information ameliorates information asymmetry, thereby enabling price discovery and reducing trading costs. We argue that accounting information is useful in stewardship and valuation despite its limitations. For pedagogical purposes, we first examine the attributes of accounting earnings as produced and received in the market without delving into how the preparers’ incentives influence the fineness of information produced or its properties. Readers can view this discussion as a reduced-form analysis of accounting earnings and their relation to stock prices. After mapping this landscape, we then present a strategic analysis of accounting earnings. This analysis recognizes that accounting information affects users’ and producers’ decisions, which, combined with self-interested behavior, influences the properties of the accounting information produced and affects how it is used in valuation, contracting, and firms’ investment decisions. Shareholder value is our primary efficiency measure, and we also discuss regulatory, social, and contract efficiency. We note that shareholder value maximization and stakeholder protection are not at odds and that accounting information facilitates firms’ commitment to stakeholder protection, which, in turn, leads to more value creation for shareholders.  “The Economics of Accounting is a refreshing and long overdue analysis of the role of accounting in the economy. The authors step back from the deluge of partial results in the literature – most of which is focused on the capital market – and provide the reader with a fine perspective on why accounting exists, what it affects, and in turn what affects the shape it takes. The book should be required reading for all doctoral students and, I suspect, many of their supervisors.” – Ray Ball, Sidney Davidson Distinguished Service Professor of Accounting, University of Chicago “The Economics of Accounting provides an engaging and accessible analysis of the crucial significance of accounting in today’s financial systems. It explores the integral role of accounting in producing information for firm valuation and managerial decision-making. Moreover, it demonstrates accounting’s essential function in shaping and evaluating the agency relationship among shareholders, managers, and other stakeholders. Overall, this insightful work nicely illustrates the economic role of accounting.” – Antoinette Schoar, Stewart C. Myers-Horn Family Professor of Finance and Entrepreneurship, Massachusetts Institute of Technology

This paper provides the first evidence of a moral hazard in signaling in an entrepreneurial finance context by examining token offerings or initial coin offerings (ICOs). Entrepreneurs' ability to signal quality is crucial to succeeding in the competition for growth capital. However, the absence of institutions verifying endogenous signals may induce a moral hazard in signaling. Consistent with this hypothesis, an artificial linguistic intelligence indicates that token issuers systematically exaggerate information disclosed in whitepapers. Exaggerating entrepreneurs raise more funds in less time, suggesting that investors do not see through this practice initially. Eventually, the crowd learns about the exaggeration bias through trading with other investors. The resulting investor disappointment causes the cryptocurrency to depreciate and the probability of platform failure to increase.

This paper presents an overview of the European mutual fund industry and investigates mutual fund performance using a survivorship bias controlled sample of 506 funds from the 5 most important mutual fund countries. The latter is done using the Carhart (1997) 4-factor asset-pricing model. In addition we investigate whether European fund managers exhibit "hot hands", persistence in performance. Finally the influence of fund characteristics on risk-adjusted performance is considered. Our overall results suggest that European mutual funds, and especially small cap funds are able to add value, as indicated by their positive after cost alphas. If we add back management fees, 4 out of 5 countries exhibit significant out-performance at an aggregate level. Finally, we detect strong persistence in mean returns for funds investing in the United Kingdom. Our results deviate from most US studies that argue mutual funds under-perform the market by the amount of expenses they charge.

Equity ownership in the United States no longer reflects the dispersed share ownership of the canonical Berle-Means firm. Instead, we observe the reconcentration of ownership in the hands of institutional investment intermediaries, which gives rise to what we call “the agency costs of agency capitalism.” This ownership change has occurred because of (i) political decisions to privatize the provision of retirement savings and to require funding of such provision and (ii) capital market developments that favor investment intermediaries offering low cost diversified investment vehicles. A new set of agency costs arise because in addition to divergence between the interests of record owners and the firm’s managers, there is divergence between the interests of record owners – the institutional investors – and the beneficial owners of those institutional stakes. The business model of key investment intermediaries like mutual funds, which focus on increasing assets under management through superior relative performance, undermines their incentive and competence to engage in active monitoring of portfolio company performance. Such investors will be “rationally reticent” – willing to respond to governance proposals but not to propose them. We posit that shareholder activists should be seen as playing a specialized capital market role of setting up intervention proposals for resolution by institutional investors. The effect is to potentiate institutional investor voice, to increase the value of the vote, and thereby to reduce the agency costs we have identified. We therefore argue against recent proposed regulatory changes that would undercut shareholder activists’ economic incentives by making it harder to assemble a meaningful toe-hold position in a potential target.

We show that, consistent with economic incentives, analysts from sell-side firms generally recommend "glamour" (i.e., positive momentum, high growth, high volume, and relatively expensive) stocks. Naive adherence to these recommendations can be costly, because the level of the consensus recommendation adds value only among stocks with favorable quantitative characteristics (i.e., high value and positive momentum). Among stocks with unfavorable quantitative characteristics, higher consensus recommendations are associated with worse subsequent returns. In contrast, the quarterly change in the consensus recommendation is a robust return predictor that appears to contain information orthogonal to a large range of other predictive variables.

Spanish Abstract: Se presentan las cuentas de resultados y los balances de Madera Inc y se explica del modo más sencillo posible el significado de cada cuenta. Se plantean las siguientes preguntas: ¿Qué significa el beneficio? ¿Es lo que “ganan” los accionistas, lo que “gana” la empresa, lo que “gana” alguien? ¿Qué significan los fondos propios? ¿Son fondos? ¿De quién? También se compara la cuenta de resultados y el balance con las cuentas anuales que hacen casi todas las familias. English Abstract: We explain in the easiest way the meaning of the different accounts of the P&L and Balance Sheet of Madera Inc. We also make some questions: What is net income? Is it money? What is Net Worth? Is it money? We also compare the P&L and Balance Sheet with the accounting of many families.

Trend-following strategies take long positions in assets with positive past returns and short positions in assets with negative past returns. They are typically constructed using futures contracts across all asset classes, with weights that are inversely proportional to volatility, and have historically exhibited great diversification features especially during dramatic market downturns. However, following an impressive performance in 2008, the trend-following strategy has failed to generate strong returns in the post-crisis period, 2009-2013. This period has been characterised by a large degree of co-movement even across asset classes, with the investable universe being roughly split into the so-called Risk-On and Risk-Off subclasses. We examine whether the inverse-volatility weighting scheme, which effectively ignores pairwise correlations, can turn out to be suboptimal in an environment of increasing correlations. By extending the conventionally long-only risk-parity (equal risk contribution) allocation, we construct a long-short trend-following strategy that makes use of risk-parity principles. Not only do we significantly enhance the performance of the strategy, but we also show that this enhancement is mainly driven by the performance of the more sophisticated weighting scheme in extreme average correlation regimes.

Despite theoretical and intuitive reasons for a credit risk premium, past research has found little supporting empirical evidence. This is primarily due to biases in computing credit excess returns which improperly account for term risk. Using data spanning 80 years in the U.S., and nearly 20 years in Europe, we find strong evidence of credit risk premium after correctly adjusting for term risk. The credit risk premium is not spanned by other known risk premia and exhibits time variation related to economic growth and aggregate default rates. These results have important implications for asset pricing and investment decisions.

Fintech has been playing an increasing role in shaping financial and banking landscapes. Banks have been concerned about the uneven playing field because fintech lenders are not subject to the same rigorous oversight. There have also been concerns about the use of alternative data sources by fintech lenders and the impact on financial inclusion. In this paper, we explore the advantages/disadvantages of loans made by a large fintech lender and similar loans that were originated through traditional banking channels. Specifically, we use account-level data from the Lending Club and Y-14M bank stress test data. We find that Lending Club’s consumer lending activities have penetrated areas that could benefit from additional credit supply, such as areas that lose bank branches and those in highly concentrated banking markets. We also find a high correlation with interest rate spreads, Lending Club rating grades, and loan performance. However, the rating grades have a decreasing correlation with FICO scores and debt to income ratios, indicating that alternative data is being used and performing well so far. Lending Club borrowers are, on average, more risky than traditional borrowers given the same FICO scores. The use of alternative information sources has allowed some borrowers who would be classified as subprime by traditional criteria to be slotted into “better” loan grades and therefore get lower priced credit. Also, for the same risk of default, consumers pay smaller spreads on loans from the Lending Club than from traditional lending channels.

The Capital Asset Pricing Model (CAPM) predicts a positive relation between risk and return, but empirical studies find the actual relation to be flat, or even negative. This paper provides a broad overview of explanations for this ‘volatility effect’ that have been proposed in different streams of literature, and categorizes each explanation according to the CAPM assumption it relates to. Interestingly, various explanations relate to investor behavior that is rational given exogenous incentive structures or constraints, which may explain why the volatility effect has been so persistent over time. We argue that although the CAPM may be bad at explaining reality, addressing the reasons for its failure could actually be a normative arbitrage opportunity.

This paper deals with estimating model parameters in graphical models. We reformulate it as an information geometric optimization problem and introduce a natural gradient descent strategy that incorporates additional meta parameters. We show that our approach is a strong alternative to the celebrated EM approach for learning in graphical models. Actually, our natural gradient based strategy leads to learning optimal parameters for the final objective function without artificially trying to fit a distribution that may not correspond to the real one. We support our theoretical findings with the question of trend detection in financial markets and show that the learned model performs better than traditional practitioner methods and is less prone to overfitting.

Much of capital market research in accounting over the past 20 years has assumed that the price adjustment process to information is instantaneous and/or trivial. This basic assumption has had an enormous influence on the way we select research topics, design empirical tests, and interpret research findings. In this discussion, I argue that price discovery is a complex process, deserving of more attention. I highlight significant problems associated with a naive view of market efficiency, and advocate a more general model involving noise traders. Finally, I discuss the implications of recent evidence against market efficiency for future capital market research in accounting.

The “real” price of gold in the U.S. is historically high, relative to its history as an actively tradable asset. But what about the real price of gold in other countries? It turns out that, in our impressionistic sample of 23 countries, the real price of gold is high everywhere. The real price of gold is high in “troubled” countries as well as in “safe” countries. If the real price of gold is a barometer of perceived troubles then there is trouble everywhere. Or, alternatively, gold is just expensive everywhere. This research is motivated by our earlier paper, Erb and Harvey (2012), The Golden Dilemma.

This paper analyzes the performance of portfolio strategies that invest in no-load, open-end U.S. domestic equity mutual funds, incorporating predictability in (i) manager skills, (ii) fund risk-loadings, and (iii) benchmark returns. Predictability in manager skills is found to be the dominant source of investment profitability -- long-only strategies that incorporate such predictability considerably outperform prior-documented "hot-hands" and "smart-money" strategies, and generate positive and significant performance with respect to the Fama-French and momentum benchmarks. Specifically, these strategies outperform their benchmarks by 2-4% per year through their ability to time industries over the business cycle. Moreover, they choose individual funds that outperform their industry benchmarks to achieve an additional 3-6% per year. Overall, our findings indicate that industries are important in locating outperforming mutual funds, and that active management adds much more value than documented by prior studies.

In this note we propose a simple two-factor multi-curve model where Fed-fund, SOFR and LIBOR rates are modeled jointly. The model is used to price the newly quoted SOFR futures as well as Eurodollar futures. We then derive pricing formulas for SOFR-based swaps, and show how the valuations of LIBOR-based swaps as well as LIBOR-SOFR basis swaps are impacted by the introduction of a new LIBOR fallback.

The credit crisis was sparked by a shock to fundamentals, housing prices failed to rise, which led to a collapse of trust in credit markets. In particular, the repurchase agreement market in the U.S., estimated to be about $12 trillion, larger than the total assets in the U.S. banking system ($10 trillion), became very illiquid during the crisis due to the fear of counterparty default, leaving lenders with illiquid bonds that they did not want, believing that they could not be sold. As a result, there was an increase in repo haircuts (the initial margin), causing massive deleveraging. I investigate this indirectly, by looking at the breakdown in the arbitrage foundation of the ABX.HE indices during the panic. The ABX.HE indices of subprime mortgage-backed securities are derivatives linked to the underlying subprime bonds. Introduced in 2006, the indices aggregated and revealed information about the value of the subprime mortgage-backed securities and allowed parties to buy protection against declines in subprime value via credit derivatives written on the index or tranches of the index. When the ABX prices plummeted, the arbitrage relationships linking the credit derivatives linked to the index and the underlying bonds broke down because liquidity evaporated in the repo market. This breakdown allows a glimpse of the information problems that led to illiquidity in the repo markets, and the extent of the demand for protection against subprime risk.

In order to value a firm or a project, it is necessary to construct estimated financial statements and free cash flows. In this teaching note we will present a spreadsheet model - EXCEL© - for forecasting financial statements in a consistent way and without using what is known as plugs. The simplest and coarse form of a plug in forecasting financial statements is to match the financial statements (in particular the Balance Sheet) creating a line or item to account for any difference that arises between total assets and liabilities plus debt in order to make the Balance Sheet to check. If total assets are greater than total liabilities plus equity, then the plug is a new line in the liabilities side. If lower, the plug is a line in the assets side. This is no only inappropriate, but it can hide mistakes when working with complex models such as those used by valuation analysts. We illustrate the procedure with an example that has some complexities. These complexities are explained in Section One. The purpose of this note is that the reader, following the instructions, could complete the example. Then, the readers are encouraged to read actively by constructing the financial statements for themselves on a spreadsheet. The relevant financial statements are: the Balance Sheet (BS), the Income statement (IS) and the Cash Budget (CB). The construction of the financial statements starts from policies and/or targets (i.e. accounts receivable policy or target) and input data that is specific for the firm or from the macroeconomic environment. With these targets or policies and data we can construct the financial statements. For valuation purposes, the balance sheet and the income statements are important but may be insufficient if we wish to construct the cash flow using the direct method. For that reason we construct the CB. From the table of parameters we construct tables that will be used in the construction of the main financial statements. In the main text we describe some complexities such as price-demand elasticity, the effect of book value leverage on the real growth and on accounts payable policy. We introduce the effect of accounts receivable policy on growth as well. We reproduce Excel© spreadsheet and in the last two columns we include the formulation than the reader should replicate and copy for the forecasting period. There are a few exceptions, but they will be announced.

This paper explores historical return and risk properties of equity-hedged options across the S&P 500 option surface. We evaluate returns by estimating alpha to the S&P 500 index, and we quantify risk using three metrics: return volatility, losses under stress tests, and conditional value at risk. We show that analyzing option risk-adjusted alphas using different risk metrics leads to significantly different conclusions. We find that the most compensated options to sell on the S&P 500 surface per unit of stress-test loss are front-month options with strikes near-the-money and moderately below the index level. We apply these results to evaluate return expectations for short volatility strategies, potential added return from option selection, and implications for variance swaps.

We provide a first comprehensive structuring of the literature applying machine learning to finance. We use a probabilistic topic modeling approach to make sense of this diverse body of research spanning across the disciplines of finance, economics, computer sciences, and decision sciences. Through the topic modelling approach, a Latent Dirichlet Allocation technique, we are able to extract the 14 coherent research topics that are the focus of the 5,204 academic articles we analyze from the years 1990 to 2018. We first describe and structure these topics, and then further show how the topic focus has evolved over the last two decades. Our study thus provides a structured topography for finance researchers seeking to integrate machine learning research approaches in their exploration of finance phenomena. We also showcase the benefits to finance researchers of the method of probabilistic modeling of topics for deep comprehension of a body of literature, especially when that literature has diverse multi-disciplinary actors.

We develop an ex-ante measure of expected stock returns based on analyst price targets. We then show that ex-ante measures of volatility, skewness, and kurtosis implied from stock option prices are positively related to the cross section of ex-ante expected stock returns. While expected returns are related to both the systematic and unsystematic components of volatility, only the unsystematic components of skewness and kurtosis are related to the cross section of expected stock returns after controlling for other variables known to be related to the cross section of expected stock returns or analyst forecast bias.

The strategy of buying safe low-beta stocks while shorting (or underweighting) riskier high-beta stocks has been shown to deliver significant risk-adjusted returns. However, it has been suggested that such “low-risk investing” delivers high returns primarily due to its industry bet, favoring a slowly changing set of stodgy, stable industries and disliking their opposites. We refute this. We show that a betting against beta (BAB) strategy has delivered positive returns both as an industry-neutral bet within each industry and as a pure bet across industries. In fact, the industry-neutral BAB strategy has performed stronger than the BAB strategy that only bets across industries and it has delivered positive returns in each of 49 U.S. industries and in 61 of 70 global industries. Our findings are consistent with the leverage aversion theory for why low beta investing is effective.

Three main approaches for examining the effect of accounting information in financial markets have emerged in the last three decades. We formally define information content, valuation relevance, and value relevance. Respectively, these approaches are based on Beaver (1968), Ball and Brown (1968), and tests of association between market values and accounting numbers. We systematically compare and contrast these paradigms to highlight their relative strengths and weaknesses, and to identify possible reasons why one method provides different results from another. Implementing these research methods using data from the last three decades, we show that information content has remained constant while valuation relevance and value relevance have both declined. We find that our conclusions are robust with respect to return volatility, non-linearities of the valuation model used, earnings composition, and the earnings expectation model used. We conclude that the unrecognized disclosures released concurrently with earning sare likely to have contributed to this divergence.

Most businesses hold cash, often in the form of low-risk or riskless investments that can be converted into cash at short notice. The motivations for holding cash vary across firms. Some hold cash to meet operating needs whereas others keep cash on hand to weather financial crises or take advantage of investment opportunities. In the first part of this paper, we will begin by looking at the extent of cash holdings at publicly traded firms and some of the motives for the cash accumulation. We will also look at how best to value these cash holdings in both discounted cash flow and relative valuation models. In the second part of the paper, we will turn to a trickier component - cross holdings in other companies. We will begin by looking at the way accountants record these holdings and the implications for valuation. We will then consider how to incorporate the value of these cross holdings in a full information environment, followed by approximations that work when information about cross holdings is partial or missing.

Abstract. This paper describes how an efficient and exact Monte-Carlo simulation of the Hull-White model could be performed. For that purpose the joint conditional distribution of the short interest rate and the discount factor is derived. The proposed approach can be straightforward extended to the multifactor Gaussian affine term structure models.

Spam messages are ubiquitous and extensive interdisciplinary research has tried to come up with effective countermeasures. However, little is known about the response to unsolicited e-mail, partly because spammers do not disclose sales figures. This paper correlates incoming spam messages that promote the investment in particular equity securities with financial market data. We use multivariate regression models to measure the impact of stock spam on traded volume and conduct an event study to find effects on market valuation. In both cases we have found evidence for significant reactions to spam campaigns in the short run. Theoretical and practical implications of the findings are addressed.