THE EFFECT OF THE SEC'S ORDER-HANDLING RULES ON NASDAQ

We study the effect of the implementation of new Securities and Exchange Commission order-handling rules—the Limit Order Display Rule, the Quote Rule, and the Actual Size Rule—on NASDAQ's quoting and trading behavior. We find that the number of reported quotes increases and the bid-ask spread decreases following the implementation of the new rules. The decreased quoted depth associated with placement of individual investors' limit orders—the Limit Order Display Rule—outweighs the increased quoted depth associated with displaying institutional quotes—the Quote Rule. Further, the number of trade executions increases while the average trade size decreases. The volatility of trade-to-trade and midpoint returns decreases for the initial group of stocks subject to the rules, but not for the two subsequent groups.     

FURTHER EXAMINATION OF PRICE DISCOVERY ON THE NYSE AND REGIONAL EXCHANGES

I re‐examine price discovery on the New York Stock Exchange (NYSE) and regional exchanges. I employ three common‐trend cointegration models to analyze the equilibrium dynamics between the NYSE and regional exchanges for the thirty Dow stocks. The overall results show that whether the regional exchanges free‐ride on the NYSE in obtaining equilibrium prices depends on whether trade prices or quotes are examined. The regional exchanges play a significant (though less important) role in the price‐discovery process for trade prices. However, the contributions of regional exchanges in price discovery of quotes are negligible. I explain the inconsistency between the results using quotes and those using trades. I also highlight the problems of using either quotes or trades in examining this free‐riding hypothesis and suggest future research on the different informativeness of trades on the NYSE and regional exchanges. JEL classification: G20, C32.     

Trades and Quotes: A Bivariate Point Process

This article formulates a bivariate point process to jointlyanalyze trade and quote arrivals. In microstructure models,trades may reveal private information that is then incorporatedinto new price quotes. This article examines the speed of thisinformation flow and the circumstances that govern it. A jointlikelihood function for trade and quote arrivals is specifiedin a way that recognizes that an intervening trade sometimescensors the time between a trade and the subsequent quote. Modelsof trades and quotes are estimated for eight stocks using Tradeand Quote database (TAQ) data. The essential finding for thearrival of price quotes is that information flow variables,such as high trade arrival rates, large volume per trade, andwide bid–ask spreads, all predict more rapid price revisions.This means prices respond more quickly to trades when informationis flowing so that the price impacts of trades and ultimatelythe volatility of prices are high in such circumstances.     

Retail Trading and IPO Returns in the Aftermarket

Using trade size from the Trade and Quote (TAQ) data set as a proxy for individual versus institutional trading, this paper finds that the effects of trading of these two types of investors on initial public offering (IPO) returns on the first trading day depend on the hotness of the IPO. My regression results reveal that IPOs’ open-to-close returns are positively related to small trade participation, small trade purchases, and small trade order imbalance in the hot IPO sample, but not in the cold and neutral IPO samples. In addition, the aftermarket prices of cold and neutral IPOs are primarily driven by the trading of institutional investors, who are less likely to be driven by sentiment.     

An empirical study of auction revenue rankings: the case of municipal bonds

Using a novel dataset of 386 first‐price municipal bond auctions held in California, I perform counterfactual revenue comparisons, based on the theoretical result of Milgrom and Weber (1982). I show that the revenue in the second‐price auction is nonparametrically identified, and the counterfactual revenue in the English auction can be bounded in an informative way. These results form a basis for nonparametric estimation of counterfactual revenue differences. I find that the revenue gain from using the English auction would be in the range of 11%—19% of the gross underwriting spread, and that most of it would already be captured by using the second‐price auction. The recent explosive growth of Internet English auctions, administered by Grant Street Group, provides external support to the claim that auction design matters in this market.     

The Implied Longevity Yield: A Note on Developing an Index for Life Annuities

I develop an index for tracking the dynamic behavior of life (pension) annuity payouts over time, based on the concept of self‐annuitization. Our implied longevity yield (ILY) value is defined equal to the internal rate of return (IRR) over a fixed deferral period that an individual would have to earn on their investable wealth if they decided to self‐annuitize using a systematic withdrawal plan. A larger ILY number indicates a greater relative benefit from immediate annuitization. I use age 65—with a 10‐year period certain—compared against the same annuity at age 75 as the standard benchmark for the index, and calibrate to a comprehensive time series of weekly (Canadian) life annuity quotes from 2000 through 2004. I find that during this period the ILY varied from 5.45 percent to 6.90 percent for males and from 5.00 percent to 6.42 percent for females and was highly correlated with a duration‐weighted average yield of 10‐year and long‐term Government of Canada bonds. I believe our ILY metric can help promote and explain the benefits of acquiring lifetime payout annuities by translating the abstract‐sounding longevity insurance into more concrete and measurable financial rates of return.     

MOMENTUM: DOES THE DATABASE MAKE A DIFFERENCE?

We examine discrepancies between the Center for Research in Security Prices (CRSP) and Trade and Quote (TAQ) databases by examining the returns of momentum strategies using each database. Momentum portfolios constructed from CRSP prices earn significant profits whereas similar portfolios using TAQ prices show losses. Adjusting TAQ prices with the TAQ dividends file or with the cumulative distribution factor provided by CRSP does not eliminate all differences. There are significant discrepancies in the way CRSP and TAQ record newly listed and delisted stocks. We document the residual (after all filters) price differences between the two databases and provide filters to adjust TAQ data for long sample periods and large sample sizes. Our filtering procedures allow for the possibility of examining intraday patterns in momentum profits.     

ADVERSE SELECTION,INVENTORY‐HOLDING COSTS,AND DEPTH

We examine whether specialist depth quotes are related to the adverse‐selection and inventory‐holding‐cost components of the spread. Consistent with theory that predicts an inverse relation between depths and informed trading risk, we find that depth quotes are strongly inversely related to the adverse‐selection component of the spread. We also find that depth quotes are inversely related to the inventory‐holding‐cost component, though this relation is weaker than the relation between depths and adverse selection. Our evidence suggests cross‐sectional variation in depths is driven primarily by variation in informed trading risk, as proxied for by the adverse‐selection component, rather than by inventory concerns. JEL classification: G10, G14     

CLIENTELE TRADING IN RESPONSE TO PUBLISHED INFORMATION: EVIDENCE FROM THE DARTBOARD COLUMN

We present an analysis of clientele trading effects in response to the widespread dissemination of public information. Employing analyst recommendations published in the Wall Street Journal's Dartboard column as the informational stimulus and the NYSE's trades and quotes (TAQ) transactions database as the data resource, we document that investors in different trading clienteles exhibit dramatically different trading responses to identical innovations in the informational environment.     

Universal features of price formation in financial markets: perspectives from deep learning

Using a large-scale Deep Learning approach applied to a high-frequency database containing billions of market quotes and transactions for US equities, we uncover nonparametric evidence for the existence of a universal and stationary relation between order flow history and the direction of price moves. The universal price formation model exhibits a remarkably stable out-of-sample accuracy across a wide range of stocks and time periods. Interestingly, these results also hold for stocks which are not part of the training sample, showing that the relations captured by the model are universal and not asset-specific.

The universal model—trained on data from all stocks—outperforms asset-specific models trained on time series of any given stock. This weighs in favor of pooling together financial data from various stocks, rather than designing asset- or sector-specific models, as is currently commonly done. Standard data normalizations based on volatility, price level or average spread, or partitioning the training data into sectors or categories such as large/small tick stocks, do not improve training results. On the other hand, inclusion of price and order flow history over many past observations improves forecast accuracy, indicating that there is path-dependence in price dynamics.     

WITHDRAWN SPIN‐OFFS: AN EMPIRICAL ANALYSIS

We examine market reaction to corporate spin‐offs that are eventually withdrawn. These spin‐offs do not experience the significant positive share price response reported for spin‐offs generally. The overall market reaction to both the initial spin‐off announcement and the withdrawal announcement is not significant. When a reason is provided for withdrawing a spin‐off, there is a significant positive market reaction; otherwise, there is a significant negative reaction. Firms that withdraw a spin‐off without stating a reason experience significant deterioration in industry‐adjusted operating performance in the three years following the withdrawal. These results indicate the market can anticipate the viability of withdrawn spin‐offs at the time of the initial announcement. JEL classification: G34     

Resource Allocation Auctions within Firms

There is growing interest in the use of markets within firms. Proponents have noted that markets are a simple and efficient mechanism for allocating resources in economies in which information is dispersed. In contrast to the use of markets in the broader economy, the efficiency of an internal market is determined in large part by the endogenous contractual incentives provided to the participating, privately informed agents. In this paper, we study the optimal design of managerial incentives when resources are allocated by an internal auction market, as well as the efficiency of the resulting resource allocations. We show that the internal auction market can achieve first‐best resource allocations and decisions, but only at an excessive cost in compensation payments. We then identify conditions under which the internal auction market and associated optimal incentive contracts achieve the benchmark second‐best outcome as determined using a direct revelation mechanism. The advantage of the auction is that it is easier to implement than the direct revelation mechanism. When the internal auction mechanism is unable to achieve second‐best, we characterize the factors that determine the magnitude of the shortfall. Overall, our results speak to the robust performance of relatively simple market mechanisms and associated incentive systems in resolving resource allocation problems within firms.     

Smooth and bid-offer compliant volatility surfaces under general dividend streams

Abstract

Given bid-offer quotes for a set of listed vanilla options, a fundamental need of option market makers is to interpolate and extrapolate the available quotes to a full arbitrage-free surface. We propose a methodology which directly controls the trade-off between smoothness and bid-offer compliance of the resulting volatility surface. Unlike previous literature, the method applies simultaneously to all listed maturities and aims to smooth the implied risk-neutral densities. Additionally, we consider asset dynamics which allow for general dividend streams—continuous, discrete yield and discrete cash—a modelling aspect of key importance in option markets.     

Efficiency out of disorder: Contested ownership in incomplete contracts

In many situations, irreconcilable disagreements between players lead to costly ownership disputes over assets—for example, in case of joint ownership. This article studies the role of such disputes in a situation where two players have to make a transaction‐specific investment and when contracts are incomplete. I show that potentially contested ownership may mitigate the inefficiency of investments due to the incompleteness of contracts generating an exchange surplus that comes closer to the first‐best surplus as compared to any other ex ante distribution of ownership typically discussed in the literature following the influential work by Grossman, Hart, and Moore. If the contest is an all‐pay auction, each player makes a transaction‐specific investment as if he or she owns the asset. This article can explain why shared ownership—as for example in equity joint ventures, family firms, start‐up partnerships, and so on—is an important part of today's corporate landscape.     

Drivers of Shareholder Returns in Tech Industries (or How to Make Sense of Amazon's Market Value)

Earnings according to GAAP do a notoriously poor job of explaining the current values of the most successful high‐tech companies, which in recent years have experienced remarkable growth in revenues and market capitalizations. But if GAAP earnings fail to account for the values of such companies, are there other measures that do better? The authors address this question in two main ways. They begin by summarizing the findings of their recent study of both the operating and the stock‐market performance of 169 publicly traded tech companies (with market caps of at least $1 billion). The aim of the study was to identify which of the many indicators of corporate operating performance—including growth in revenues, EBITDA margins, and returns on equity—have had the strongest correlation with shareholder returns over a relatively long period of time. The study's main conclusion is that investors appear to be looking for signs of neither growth nor efficiency in using capital alone, but for an optimal mix or balancing of those goals. And that mix, as the study also suggests, is captured in a cash‐flow‐based variant of “residual income” the authors call “residual cash earnings,” or RCE. In the second part of their article, the authors show how and why RCE does a much better job than reported net income or EPS of explaining the current market value of Amazon.com , one of the best‐performing tech companies in the world. Mainly by treating R&D spending as an investment of capital rather than an expense, RCE reveals the value of a company that is distinguished by both the amount and the productivity of its ongoing investment—both of which have been obscured by GAAP.     

Real Options: Meeting the Georgetown Challange

In response to the demand for a single, generally accepted real options methodology, this article proposes a four‐step process leading to a practical solution to most applications of real option analysis. The first step is familiar: calculate the standard net present value of the project assuming no managerial flexibility, which results in a value estimate (and a “branch” of a decision tree) for each year of the project's life. The second step estimates the volatility of the value of the project and produces a value tree designed to capture the main sources of uncertainty. Note that the authors focus on the uncertainty about overall project value, which is driven by uncertainty in revenue growth, operating margins, operating leverage, input costs, and technology. The key point here is that, in contrast to many real options approaches, none of these variables taken alone is assumed to be a reliable surrogate for the uncertainty of the project itself. For example, in assessing the option value of a proven oil reserve, the relevant measure of volatility is the volatility not of oil prices, but of the value of the operating entity—that is, the project value without leverage. The third step attempts to capture managerial flexibility using a decision “tree” that illustrates the decisions to be made, their possible outcomes, and their corresponding probabilities. The article illustrate various kinds of applications, including a phased investment in a chemical plant (which is treated as a compound option) and an investment in a peak‐load power plant (a switching option with changing variance, which precludes the use of constant risk‐neutral probabilities as in standard decision tree analysis). The fourth and final step uses a “no‐arbitrage” approach to form a replicating portfolio with the same payouts as the real option. For most corporate investment projects, it is impossible to locate a “twin security” that trades in the market. In the absence of such a security, the conventional NPV of a project (again, without flexibility) is the best candidate for a perfectly correlated underlying asset because it represents management's best estimate of value based on the expected cash flows of the project.     

More on a statistical analysis of log-periodic precursors to financial crashes

In this paper, we extend the existing empirical evidence on the relationship between the state of the limit order book (LOB) and order choice. Our contribution is twofold: first, we propose a sequential ordered probit (SOP) model which allows studying patient and impatient traders’ choices separately; second, we consider two pieces of LOB information, the best quotes and the book beyond the best quotes. We find that both pieces of LOB information explain the degree of patience of an incoming trader and, afterwards, its order choice. Nonetheless, the best quotes concentrate most of the explanatory power of the LOB. The shape of the book beyond the best quotes is crucial in explaining the aggressiveness of patient (limit order) traders, while impatient (market order) traders base their decisions primarily on the best quotes. Patient traders’ choices depend more on the state of the LOB on the same side of the market, while impatient traders mostly look at the state of the LOB on the opposite side. The aggressiveness of both types of traders augments with the inside spread. However, patient (impatient) traders submit more (less) aggressive limit (market) orders when the depth of the own (opposite) best quote and the length of the own (opposite) side of the book increase. We also find that higher depth away from the best ask (bid) quote may signal that this quote is ‘too low (high)’, causing incoming impatient buyers (sellers) to be more aggressive and incoming patient sellers (buyers) to be more conservative.     

Optimal state‐contingent regulation under limited liability

We consider an optimal regulation model in which the regulated firm's production cost is subject to random, publicly observable shocks. The distribution of these shocks is correlated with the firm's cost type, which is private information. The regulator designs an incentive‐compatible regulatory scheme, which adjusts itself automatically ex post given the realization of the cost shock. We derive the optimal scheme, assuming that there is an upper bound on the financial losses that the firm can sustain in any given state. We first consider a two‐type, two‐state case, and then extend the results to the case of a continuum of firm types and an arbitrary finite number of states. We show that the first‐best allocation can be implemented if the state of nature conveys enough information about the firm's type and/or the maximal loss that the firm can sustain is sufficiently large. Otherwise, the solution is characterized by classical second‐best features.     

END‐OF‐DAY PRICING IN THE U.S. TREASURY MARKET: A COMPARISON OF GovPX AND THE FEDERAL RESERVE BANK OF NEW YORK

We compare end‐of‐day indicative U.S. Treasury prices from GovPX and the Federal Reserve Bank of New York (FRBNY). We find that the two sources rarely quote identical prices, and differences are not simply due to noise or rounding. The average bid price differential is 2 cents for notes and bonds, but it is only ¹/₁₀ of 1 cent for bills. Bid‐ask spreads in both sources appear to be largely artificial and contain limited information. Finally, we find that the end‐of‐day indicative FRBNY bid prices are closer to true intraday GovPX market quotes than end‐of‐day indicative quotes provided by GovPX itself.