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We consider a real discrete pricing problem in network revenue management for FlixBus. We improve the company's current pricing policy by an intermediate optimization step using booking limits from standard deterministic linear programs. We pay special attention to computational efficiency. FlixBus' strategic decision to allow for low-cost refunds might encourage large group bookings early in the booking process. In this context, we discuss counter-intuitive findings comparing booking limits with static bid price policies. We investigate the theoretical question whether the standard deterministic linear program for network revenue management does provide an upper bound on the optimal expected revenue if customer's willingness to pay varies over time.

This article provides a simple explanation of the asymptotic concavity of the price impact of a meta-order via the microstructural properties of the market. This explanation is made more precise by a model in which the local relationship between the order flow and the fundamental price (i.e. the local price impact) is linear, with a constant slope, which makes the model dynamically consistent. Nevertheless, the expected impact on midprice from a large sequence of co-directional trades is nonlinear and asymptotically concave. The main practical conclusion of the proposed explanation is that, throughout a meta-order, the volumes at the best bid and ask prices change (on average) in favor of the executor. This conclusion, in turn, relies on two more concrete predictions, one of which can be tested, at least for large-tick stocks, using publicly available market data.

With IATA's New Distribution Capability (NDC), booking classes and fares filed into Global Distribution Systems will no longer be necessary, and the task of airline revenue management (RM) will shift from optimizing the availability of fares to generate optimal offered prices for each seat product (restricted, semi-flexible, flexible, …) which the airline sells. We will show how the marginal revenue transformation theory can be extended into the classless RM environment and introduce a network optimization algorithm based on this. The optimizer takes the forecasted price–demand curve of each origin–destination (OD) product as input and uses dynamic programming to calculate a bid price vector on each leg, which is in turn used to calculate the offered prices for each OD product. We will also discuss how the new method could be used in practice by an airline RM department to provide predictable and self-consistent prices.

Using unique seasoned equity offering (SEO) investor bid data in China, we examine the impact of analyst optimism bias on SEO investors’ bids and the subsequent SEO discount. After accounting for information asymmetry and analyst coverage, our findings suggest that SEO investor bid prices are positively correlated with analyst optimism bias, suggesting that SEO investors are misled. The higher SEO bid price translates into a lower SEO discount. Our findings are robust to alternative measures of earnings forecasts, additional control variables, and SEO discounts. Additional evidence suggests that, when institutional investor ownership is lower or an SEO firm is less transparent, the positive correlation is more prominent. At last, we find the long-run SEO performance is negatively correlated with the analyst optimism bias. Our findings imply that analysts play more than one role in SEO pricing. In addition to lowering information asymmetry, analysts also mislead SEO investors by providing optimistically biased earnings forecasts.

This paper studies an intermediated market for a homogeneous good with middlemen who hold inventories of the good. Using a directed search approach, I investigate a steady state equilibrium. Under market frictions and competition, the ask price of middlemen includes a retail premium for the immediacy service to buyers and the bid price includes a wholesale premium charged to sellers for guaranteed sale. It is shown that the middlemen enhance the economy-wide eciency, and that the bid-ask spread can be non-monotone in the middlemen’s inventory capacity. The simple model provided here has wide applicability and oers economic insights into many empirically relevant forms of middlemen, especially in the context of financial intermediaries, international trade and retail stores.

In the process of deepening market-oriented reform, the most important thing in China is building a national unified electricity market system under a high renewable energy penetration scenario. The new round of market-oriented reform proposes to establish an inter-provincial electricity-trading arrangement. Due to imperfect market mechanisms and immature inter-provincial electricity markets, we investigate the electricity market operation system of the national unified electricity market. Existing transmission commitments, trading cycles, market participants, strategic bids, and clearing and settlement mechanisms are analyzed for inter-provincial medium- and long-term markets. For security reasons of interchange schedules, we propose a novel inter-provincial market-clearing model based on static security regions, which consider inter-provincial electricity transmissions and direct current power flows. The proposed market-clearing model is simulated and verified in a 3-bus system and an IEEE 30-bus system. The proposed clearing model and rational market theory are conducive not only to promoting renewable energy consumption but also to improving the linkages between inter-provincial medium- and long-term markets.

If bidding in a pure common-value auction is costly and bidders do not know how many others are also bidding, all equilibria are in mixed strategies. Participation is probabilistic, and bid prices are dispersed. The symmetric equilibrium is unique and yields simple analytic expressions. We use them to, for example, show that bid prices exhibit negative skew-ness. The expressions are further used to estimate the model based on bidding on a Standard & Poor’s 500 security. We find that the number of bidders declined over time, making liquidity supply fragile.

Large-scale renewable photovoltaic (PV) and battery energy storage system (BESS) units are promising to be significant electricity suppliers in the future electricity market. A bidding model is proposed for PV-integrated BESS power plants in a pool-based day-ahead (DA) electricity market, in which the uncertainty of PV generation output is considered. In the proposed model, we consider the market clearing process as the external environment, while each agent updates the bid price through the communication with the market environment for its revenue maximization. A multiagent reinforcement learning (MARL) called win-or-learn-fast policy-hill-climbing (WoLF-PHC) is used to explore optimal bid prices without any information of opponents. The case study validates the computational performance of WoLF-PHC in the proposed model, while the bidding strategy of each participated agent is thereafter analyzed.

We investigate the puzzle of why bid–ask spreads of options are so large by focussing on the price impact component of the spread. We propose a structural vector autoregressive model for trades in the option market to analyze whether they move the underlying price and/or the underlying’s volatility. Our model captures cross-option strategies by pooling order flows across contracts after a decomposition into exposure to the underlying asset and its volatility. While our estimates confirm that S&P500 option trades indeed significantly move the underlying and the volatility, the economic magnitudes are very small. Hence, large bid–ask spreads of options remain a puzzle.

Do option investors rationally exercise their options? Numerous studies report evidence of irrational behavior. In this paper, we pay careful attention to intraday option quotes and reach the opposite conclusion. An exercise boundary violation (EBV) occurs when the best bid price for an American option is below the option’s intrinsic value. Far from being unusual, we show that EBVs occur very frequently. Under these conditions, the rational response of an investor liquidating an option is to exercise the option rather than sell it. Empirically, we find that the likelihood of early exercise is strongly influenced by the existence and duration of EBVs. Not only do these results reverse standard theory on American option valuation and optimal exercise strategy, but they also suggest that the ability to avoid selling at an EBV price creates an additional source of value for American options that is unrelated, and in addition to, dividend payments. This additional value may help explain why American options appear overpriced relative to European options.

In large part of the world, rivers are polluted with sewage, industrial and agricultural wastes. The objective of this study is to determine farmers’ willingness to pay to improve the water quality of the Aksu River in Kahramanmaras Province. For this purpose, a survey was conducted with 236 farmers in the study area and the contingent valuation method and binomial probit model were used to evaluate river quality. As a result of the analysis, it is determined that average farm size was 188.2 decares, average annual income was $ 40377.56 and 87.3% of the respondents want to do good agricultural practices, which is a form of production that does not harm the environment, human and animal health. Model results showed that the region (polluted and not polluted area) and the use of fertilizers according to soil analysis results affect farmers’ willingness to pay positively. On the other hand, the education level of farmers and bid price have a negative effect on the willingness to pay. As a result of the analysis, it is determined that the farmers wanted to pay $8.03 per decare to improve the river water quality.

Green industrial policies around renewable energy (RE) are growing increasingly prevalent in emerging economy contexts as a means to foster low-carbon industrialization pathways. However, policymakers often face a tradeoff in their policy designs. In this paper, we focus on the tradeoff between minimizing the cost of low-carbon energy generation to fuel traditional input-intensive industrialization strategies, and implementing potentially costly measures to build local industries around low-carbon energy technologies. Specifically, we utilize the cases of Mexico and South Africa to investigate how each country’s distinct prioritization of these two objectives led to a divergence of their RE auction designs and outcomes. Specifically, using data on the involvement of local and foreign actors in Mexican and South African RE projects, policy documents, and interviews with public and private stakeholders in the two countries, we show how each country’s policy design shaped RE market and bid price developments, and the formation of local RE value chains. We find that the prioritization of low-cost RE generation can result in a greater reliance on existing foreign value chains and capital, without building the local capabilities that could result in greater long-term benefits for the market. We further discuss the implications of our results for policymakers, focusing on providing recommendations for RE industrial policy design in general, and the calibration of local content incentives in particular.

This paper explores whether and how media serves as an information intermediary in the capital market and predicts value creation from mergers and acquisitions (M&As). Using a sample of 288 M&A deals in the U.S. market from 2000 to 2015, this paper examines whether pre-merger news about acquirers correlates to M&A performance. The empirical evidence shows that a positive media attitude before merger announcements has predictive power for stock returns in both the short and long run. Moreover, media pessimism is associated with higher bid premiums, meaning that acquirers must raise the bid price to offset the negative effects produced by the media. These findings suggest that media news contains information relevant to M&A performance and thus has implications for shareholder wealth.

A model of a decentralized market is developed that features search frictions, advertised prices and bargaining. Sellers can post ask prices to attract buyers through a process of directed search, but ex post there is the possibility of negotiation. Similarly, buyers can advertise negotiable bid prices to attract sellers. Even when transaction prices often differ from quoted prices, bid and ask prices play a crucial role in directing search and reducing trading frictions. The theory endogenizes the direction of search and provides insight about the prevalence of posted prices in the absence of full commitment by market participants to transact at the advertised price.

This article analyzes auctions that can feature two bidding rounds for the sale of a single good. In the first round, the seller, after analyzing the received bids, may elect to have k bidders rebid. The highest bidder in the second round then acquires the asset at the highest bid price. We use a sample of 67 properties that sold through this auction process. The 40 hotels in this sample are matched to a control group of 157 hotel properties that were sold in the conventional manner in order to develop a hedonic model for “conventional” sale prices. Using this model, we find that the double round auction mechanism increases the seller's expected revenue significantly: Specifically, in our sample, we estimate that the expected value of a double round auction bid is 8.4% higher than the estimated price if the property were sold using traditional methods. In addition, we show that the average bid is not significantly different from the estimated sale price. We further find (controlling for property characteristics) that the average bid increases by 3.7% from the first to the second round.

This paper investigates the information content of the limit order book on future volatility in the crude oil futures market. We propose a time-weighted limit order book slope that incorporates the duration of each bid and ask update. When volatility is expected to increase around weekly announcements on physical crude oil inventory, we observe that the limit order book slope decreases significantly. We also show that the time-weighted limit order book slope is informative about price volatility one day ahead. Overall, our findings illustrate the importance of the limit order book as a conduit for volatility information.

The purpose of this paper is to examine Malaysian motorists’ willingness to pay for Chinese lucky plate numbers. Regression analyses reveal that the Chinese bidders are more likely to win and pay significantly more for the Chinese lucky numbers than their non-Chinese counterparts. Consistent with resale motive considerations, the non-Chinese bidders impose the same discount for unlucky numbers as their Chinese counterparts but do not pay a premium for the lucky numbers. We also document the influence of peer effects on the winning bid price. Specifically, Chinese bidders tend to pay more for the same plate numbers won by their peers in the previous auction, whereas both Chinese and non-Chinese bidders are less averse to the unlucky numbers if there are precedents of such ownership among their peers. Overall, our findings suggest that policymakers and marketers need to be sensitive to the subtle differences in the cultural cues of consumers in a multiracial society such as Malaysia.

This paper presents bid and ask formulas for cap and floor contracts prices byusing Wang transform under a Liouville fractional Vasicek (LfVasicek) interest rate model. To do this, the parameters of the model are calibrated by using the Newton-Raphson (NR) method. Then the standard and Liouville fractional versions of the Vasicek model are compared by the Bayes information criterion (BIC). Finally, we obtain the bid-ask boundaries for interest rate amount and cap and foor prices.

International audience; In most over-the-counter (OTC) markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while mitigating the risk associated with holding inventory in a volatile market. Many market-making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multiasset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multiasset market making by using a factor model. Moreover, we generalize existing market-making models by the addition of an important feature: the existence of different transaction sizes and the possibility for the market makers in OTC markets to answer different prices to requests with different sizes.

In this study, we consider a one-period financial market with a dealer/broker and an infinite number of investors. While the dealer who trades on his own account (with proprietary trading) simultaneously sets both the transaction fee and the asset price, the broker who brings investors' orders to the market (with no proprietary trading) sets only the transaction fee, given that the price is determined according to the market-clearing condition among investors. We analyze the impact of proprietary trading on the asset price, transaction fee, trading volume, and the welfare of investors. We find that the bid and ask prices set by the dealer who can engage in proprietary trading are more favorable to average investors. As a result, both the trading volume and the transaction fee increase, and social welfare improves.

We consider a procurement auction, where each supplier has private costs and submits a stepped supply function. We solve for a Bayesian Nash equilibrium and show that the equilibrium has a price instability in the sense that a minor change in a supplier’s cost sometimes result in a major change in the market price. In wholesale electricity markets, we predict that the bid price of the most expensive production unit can change by 1-10% due to price instability. The price instability is reduced when suppliers have more steps in their supply functions for a given production technology. In the limit, as the number of steps increases and the cost uncertainty decreases, the Bayesian equilibrium converges to a pure-strategy NE without price instability, the Supply Function Equilibrium (SFE).

Using a unique investor bid price database of a uniform-price auction pricing mechanism of SEOs in China, we seek answers to two research questions: how does value uncertainty relate to investor bid prices (weighted average and standard deviation) and to the subsequent SEO pricing in an auction price mechanism? What is the underlying transmission mechanism between value uncertainty and SEO discounts? Our findings suggest that: (1) the weighted average of investor bid prices is negatively correlated with value uncertainty, indicating an information cost effect; (2) the dispersion of bids (proxied by standard deviation of bid prices) is positively correlated with value uncertainty, indicating the presence of a heterogeneous investor beliefs effect; and (3) SEO discounts are negatively correlated with the weighted average bid price and with the bid price standard deviation. The magnitude of this impact on the SEO discounts, however, is larger for the weighted average bid price than the standard deviation, suggesting that the information cost effect outweighs the heterogeneous investor beliefs effect. Moreover, we find that investor bid prices (weighted average and standard deviation) form part of the transmission mechanism shaping the relationship between value uncertainty and SEO discounts. Our findings are robust to a battery of robustness checks.

We disentangle bid- and ask-side liquidity using 11 years of comprehensive NYSE limit order book data and document that this has important implications for understanding the determinants, commonalities and pricing of liquidity. First, the ask- but not bid-side liquidity of financial stocks deteriorates during the 2008 short selling ban. Second, bid-side (ask-side) liquidity decreases (increases) in lagged short- and long-term returns, indicating persistent contrarian behavior in limit orders. Third, liquidity commonality increases during the financial crisis, more so on the bid than on the ask side. Finally, ask- but not bid-side illiquidity predicts daily returns, while both forecast monthly returns.

Prior studies suggest that income smoothing may be used as an earnings management tool by managers, and is associated with stock price declines when companies subsequently break smoothing patterns. We contend that investors' negative reaction in these situations is also driven by their magnified concerns about firm information risk, in addition to their decreased earnings expectations. Consistent with this argument, we find that bid-ask spreads around unexpected loss announcements are greater when preceded by higher levels of income smoothing. Furthermore, total spreads before the loss announcements were not greater for firms that exhibited higher income smoothing but had not reported earlier losses. This suggests that investors had difficulties seeing through managerial opportunistic motives before the unexpected loss announcements. Additionally, we find that institutional ownership and sell-side analyst coverage appear to moderate the positive association between income smoothing and bid-ask spreads, consistent with the monitoring role institutional investors and financial analysts play in constraining managerial opportunism. We also detect a significant decrease in the extent of income smoothing following loss announcements. Overall, our results are consistent with the view that income smoothing may be viewed by investors as being motivated by managerial opportunism instead of as communicating the true earnings results. Further analysis suggests that pursing a moderate amount of volatility in reported earnings may be the optimal financial reporting policy.

We have seen many times over the years where bid prices drop precipitously in the last few days of the booking process, thus potentially opening up cheap seats at a time when passengers with the greatest willingness to pay are shopping. The research question studied here is whether an airline can effectively apply a bid price floor or freeze, in the last week or two of the booking process to increase revenue in a competitive environment with four competing airlines. This paper will provide the answer to the above question in the Passenger Origin–Destination Simulator (PODS) Network U10 (a large international network with 572 origin–destination markets, including a low-cost carrier). The results show how challenging it is to find a combination of O–D optimization method, overbooking level, and time-frame that are effective. In fact, only unbucketed dynamic programming (vector) and overbooking with a floor or freeze in the last 7 days is consistently revenue positive.

The Simultaneous Multiple Round Ascending Auction (SMRA) pioneered by Milgrom, Wilson and McAfee in 1994 has become a defacto standard auction mechanism for the award of radio spectrum for commercial mobile services around the world. The winning bid price in such SMRA spectrum auctions is of interest as it determines the valuation of the scarce resource by the mobile operators, and also indicates the revenue accrued to the governments as auction proceeds. We examine, using a cross-country panel dataset, the determinants of spectrum prices, of all the SMRA auctions held in about 25 countries during 1994–2019. Our findings indicate that reserve prices fixed by the auctioneer as the starting price of auctions and the competition in the auction are the two variables that significantly affect the winning bid prices positively in SMRA auctions. The effect of reserve prices is more pronounced in regional auctions held in countries such as the U.S. and India. Further, the larger the amount of spectrum put on auction, lesser is the winning bid price, thereby indicating the traditional supply-demand relationship. Based on these findings, we provide policy prescriptions on fixing appropriate reserve prices, providing a clear visibility of spectrum availability, and increasing competition in mobile services for effective use of scarce radio spectrum.

This paper examines the impact of currency volatilities on the average monthly spreads in ADRs and their underlying local shares. We employ a novel estimator for spreads based on two-day-period high and low values of a comprehensive universe of stocks over fifteen years using dynamic panel data estimation. Surprisingly, we find that currency volatility has a larger impact on spreads of ADRs than on their underlying local shares. This adds novel information to the well-documented evidence that local shares and exchange rate variations are the primary drivers of ADR returns. FX implied volatility accounts for about 16.6% of the variance in our sample. We also observe that, on average, ADR spreads are smaller than the spreads on their corresponding underlying shares. We posit that size matters and therefore provide measures of the economic significance of all our estimated results.

The National Institute of Food and Agriculture (NIFA) provided a grant to establish a wood-based cellulosic biofuels industry in the US Pacific Northwest. Whether the industry will be sustainable depends largely on social acceptability in general and market acceptability of the biofuels among the public in particular. We conducted contingent valuation surveys of general public in the US states of Oregon and Washington to determine people's willingness to pay (WTP) for wood-based cellulosic biofuels and the factors that influence their WTP decisions. Oregon has an existing cellulosic biorefinery, while Washington's biorefineries are only being planned, allowing us to conduct an ex-ante (Washington) versus ex-post (Oregon) WTP comparison. We sent out mail surveys to 2828 valid mailing addresses between May and July of 2015 and received 757 completed surveys. We used the distribution-free Turnbull estimator to estimate the expected WTP and logistic regression to determine the relative strength of predictors on WTP. About one fifth (18.8%) of the respondents were willing to pay some premium for wood-based cellulosic biofuels. The mean WTP amount was $0.19 ± $0.03/gal. (95% confidence interval: $0.17 to $0.21), which equates to a 6.4% price premium on top of the market price for gasoline. Logistic regression results showed that the offered bid price, knowledge on biofuels, age and religious affiliation of respondents were statistically significant predictors of WTP decisions. No significant differences in ex-ante versus ex-post WTP were observed. We also discussed the policy implications of these results for sustainable management of the wood-based cellulosic biofuels industry.

To estimate the bid-ask spread, we propose a new method that resembles the Roll measure (1984) but has some key advantages: it is fully independent of bid-ask bounces and benefits from a wider information set, namely, close, high, and low prices, which are readily available. Assessed against other low-frequency estimates, our estimator generally provides the highest cross-sectional and average time-series correlations with the TAQ effective spread benchmark. Moreover, it delivers the most accurate estimates for less liquid stocks. Finally, our estimator improves the measurement of systematic liquidity risk and commonality in liquidity for individual stocks and sorted portfolios.The appendix to "A Simple Estimation of Bid-Ask Spreads from Daily Close, High, and Low Prices" to is available at the following URL: http://ssrn.com/abstract=2809692.

The Financial Industry Regulatory Authority began collecting transaction data from broker-dealers in 2011 as a step toward enhancing its understanding of securitization markets. We use transaction data to document the importance of the interdealer network structure to market quality. Some dealers are relatively central in the network and trade with many dealers, while others are peripheral. Core dealers receive relatively lower and less dispersed spreads than peripheral dealers. We develop a model in which core and peripheral dealers trade with different customer clienteles and argue that the presence of relatively sophisticated customers in securitization markets explains these facts.

Much empirical evidence shows that stock short-selling costs and bans have significant effects on option prices. We reconcile these findings by providing a dynamic analysis of option prices with costly short-selling and option market makers. We obtain simple, closed-form, unique option bid and ask prices that represent option market makers’ expected hedging costs, and are weighted averages of well-known benchmark prices (Black–Scholes, Heston). Our analysis delivers rich implications that support the empirical evidence on the effects of short-selling costs and bans on option prices, as well as uncovering several novel predictions. We also apply our methodology to corporate bonds, which have option-like payoffs.

This experiment studies belief updating under ambiguity, using subjects' bid and ask prices for an asset with ambiguous payoff distribution. Bid and ask quotes allow for distinguishing between the two main paradigms of updating under ambiguity–full Bayesian updating and maximum likelihood updating. We find substantial heterogeneity in subjects' reaction to information. The majority of subjects (54%) chose quotes that were in line with full Bayesian updating, while another, non-negligible, group (35%) behaved like maximum likelihood updaters.

We study the manipulation of prices in a dynamic version of the Glosten and Milgrom (1985) model with a long-lived informed trader. We clarify the conditions under which a unique equilibrium exists and show that when the equilibrium is unique, bid and ask prices are monotonically increasing functions of the market maker’s belief about the value of the asset. We also characterize the situations in which this equilibrium involves manipulation of prices by the informed trader. Finally, we describe a computational method to find equilibria in the model, and simulation results confirm and extend our theoretical findings.

In the hospitality industry, an allotment is a block of pre-negociated “rooms” which have been bought by a tour operator. In the context of campsites, allotments represent a significant share of the mobile homes sales. For the campsite owner, dealing with tour operator allotment requests is a poisoned chalice. On one hand these pre-booked sales are more or less a guarantee of selling a good share of its inventory. On the other hand, the discount level is so high that selling the whole inventory through allotments could potentially ruin the business. Hence, a balance must be found between allotment contracts and estimated direct sales to final customers (at full price, or lightly discounted price). The purpose of the present paper is to show that the stochastic optimisation problem at stake is highly combinatorial and that algorithmic approaches relying on continuous relaxations of the demand (“bid price”) behave poorly. For multi-site allotment optimisation with service level requirements from tour operators, we developed a Lagrange decomposition technique based on local Markov Decision Process solvers that outperforms classic "fluid displacement" approaches. We provide experimental results on instances with 200 campsites 20,000 mobile homes and 15 tour operators inspired from a leading European actor of the campsite industry.

In this study we examine on intradaily basis (milliseconds) the largest 100 ETFs’ bid-ask spread components in the period March 21, 2014 to April 17, 2014. We document that ETFs have lower proportion of adverse selection in the bid-ask spread relative to stocks, which also means that the order processing cost component is higher in ETFs. This suggests that uninformed investors prefer to trade ETFs relative to individual stocks. The data in our study also suggests a U-shaped form of the adverse selection component across four categories of ETF trading volume and not a monotone decreasing relation from lowest to highest trading volume ETFs. Fixed-income ETFs have the highest adverse selection component coefficient whereas real estate ETFs have the lowest. Additionally, mutual fund structured ETFs have lower adverse selection component coefficient than the trust structured ETFs. We also document that ETFs with more quotes have lower adverse selection; whereas ETFs with higher average bid price, higher expense ratio and trust structuring of the ETF have higher adverse selection component of the bid-ask spread.

The literature on patent license auctions in oligopoly assumed that the auctioneer reveals the winning bid and stressed that this gives firms an incentive to bid high in order to signal an aggressive output strategy in a downstream Cournot market game, and conversely bid low to signal acquiescent pricing in a Bertrand market game. The present paper examines the information revealed by publishing the winning or the losing or no bid, assuming an oligopoly with differentiated goods. We rank disclosure rules and find that it is not optimal for the innovator to disclose the winning bid, regardless of the mode of competition.

This paper investigates the way in which intraday bid-ask spreads are related to trading volume, volatility, skewness, as well as kurtosis for commodity futures on copper, aluminum, gold, and rubber in China. We show that bid-ask spreads are generally negatively related to trading volume and skewness, but positively related to volatility and kurtosis. In addition, the effects of trading volume, volatility, and skewness are stronger than those of kurtosis. Moreover, using a threshold regression model, we document that these relations exhibit asymmetries with regard to good versus bad news, large versus small volatility, positive versus negative skewness, as well as high versus low kurtosis. While these asymmetric effects vary across futures, we find some common patterns, and provide economic explanations for the observed asymmetric relations.

Making accurate accept/reject decisions on dynamically arriving customer requests for different combinations of resources is a challenging task under uncertainty of competitors' pricing strategies. Because customer demand may be affected by a competitor's pricing action, changes in customer interarrival times should also be considered in capacity control procedures. In this article, a simulation model is developed for a bid price-based capacity control problem of an airline network revenue management system by considering the uncertain nature of booking cancellations and competitors' pricing strategy. An improved bid price function is proposed by considering competitors' different pricing scenarios that occur with different probabilities and their effects on the customers' demands. The classical deterministic linear program (DLP) is reformulated to determine the initial base bid prices that are utilized as control parameters in the proposed self-adjusting bid price function. Furthermore, a simulation optimization approach is applied in order to determine the appropriate values of the coefficients in the bid price function. Different evolutionary computation techniques such as differential evolution (DE), particle swarm optimization (PSO), and seeker optimization algorithm (SOA), are utilized to determine these coefficients along with comparisons. The computational experiments show that promising results can be obtained by making use of the proposed metaheuristic-based simulation optimization approach.

Market makers in some financial markets often make offsetting trades and have significant market power. We develop a market making model that captures these market features as well as other important characteristics such as information asymmetry and inventory risk. In contrast to the existing literature, a market maker in our model can optimally shift some trades with some investors to other investors by adjusting bid or ask. As a result, we find that consistent with empirical evidence, expected bid–ask spreads may decrease with information asymmetry and bid–ask spreads can be positively correlated with trading volume.

This article investigates two practical concerns with bid-price control origin–destination (OD) revenue management (RM) systems. First, we examine forecast decrementing methods for the common situation where demand forecast generation is decoupled from booking policy optimization. Second, we explore the impacts of two bounding schemes designed to eliminate bid price declines close to departure. Using the Passenger Origin–Destination Simulator (PODS), we find (i) more sophisticated forecast decrements increase revenue compared with the traditional approach when combined with advanced forecasting methods incorporating passenger willingness to pay and (ii) bid price bounds increase revenue with standard forecasting methods but decrease revenue with advanced forecasting methods.

With a panel VAR of 10 Euro area countries, we studied the budgetary determinants of government bond yield spreads vis-à-vis Germany between 1999Q1 and 2012Q4. We find that rising bid ask, VIX and debt differentials increase yield spreads; and improvements in the budget balance, higher growth prospects and depreciation lower the spreads. Moreover, rises in public wages or in social expenditure increase spreads, while increases in direct and indirect taxes lower the yield spreads. In the post-2007Q3 crisis period, rising expenditure components (except subsidies) increased spreads. info:eu-repo/semantics/publishedVersion

First version: 28th May, 2014, This version: 28th August, 2014, This paper aims to extend the existing evidence on the investment value of green buildings to international markets, specifically the residential market in Japan. Using a unique transaction database of condominiums in the Tokyo metropolitan area and a hedonic analytical framework, we find that green buildings command a small but significant premium on both the asking and transaction prices. This finding is consistent with results from other countries. As far as we are aware, this is also the first study of green buildings’ economic value based on a hedonic model incorporating buyer characteristics. However, further analysis reveals that this premium is primarily driven by wealthy households that exhibit a higher willingness-to-pay for eco-labelled condominiums, both as a total amount and as a fraction of the total sales price. We therefore conclude that eco-labels are perceived as a luxury good in the Japanese housing market rather than a way to save money on lower utility bills., 基盤研究(S) = Grants-in-Aid for Scientific Research (S)

Trading or transaction costs are one of the most important attributes of any trading system and can be divided into two major groups: explicit (visible) and implicit (hidden). In this paper, we investigate the impact of the bid-ask spreads, a form of hidden cost, on the results of backtesting (and, therefore, the potential impact on real-time trading) of an automated trading system based on genetic programming. We concentrate on the nature (fixed or floating) of bid-ask spreads (hereafter ‘spread’) and demonstrate that the effectiveness of an automated trading system more significantly degrades in the case of floating spreads compared to fixed spreads. We investigate four fixed spreads (one, two, five and ten pips) and a floating spread with a median value of two pips and demonstrate that the floating spread with a mean value of 0.02 USD results in significantly worse performance than a fixed spread of 0.1 USD. ‘Floating spreads’ in this paper is a term used for market-determined continuously changing bid-ask spreads.

This paper aims to indicate the best daily proxy for unobserved liquidity in the presence of extreme movements on the market. We apply copulas to investigate the dependence between benchmarks based on intraday prices and proxies based on daily data. We focus on the tail dependence between both types of measures. Our results show that when the market experiences extreme illiquidity, the Closing Quoted Spread (CQS) based on daily closing bid and ask prices is superior to other percent-cost low-frequency proxies. We find the highest tail dependence coefficients for CQS and either the Percent Effective Spread or the Percent Quoted Spread.

This paper examines market quality for the E-Mini S&P 500 futures around Federal Reserve announcements. I document that the release of the Federal Open Market Committee (FOMC) statement induces significantly “higher than normal” volatility and trading volume. The bid–ask spread is significantly higher in the minutes preceding the release, but it returns to its “normal” level immediately after the release. Using order-level data, I show that market depth behind the best bid and ask quotes is much lower on event days, hitting an intraday low immediately before the FOMC release at values on average about 20 percent of the level observed in control days.

The authors present an analytical model of a first-price sealed-bid cattle auction in which a spot and coordinated markets are interconnected. The model reveals that the conventional wisdom that market coordination negatively affects the bid price in the spot market is an oversimplification. The relationships between key market variables impact bids and bid shading in complex ways. While captive supplies can lead to lower spot prices, the price reductions do not necessarily stem from an increase in market power due to contracting. The model emphasizes the importance of several variables for future empirical studies.

This paper studies the role of foreign exchange market intervention in the price discovery process of the USD–JPY market. Using the tick-by-tick bid and ask quotes from the Electronic Broking Services (EBS), we find that Japanese official intervention affects the relative contributions of bid and ask quotes to price discovery of the USD–JPY exchange rate. The empirical results show that bid quotes usually respond to information more promptly than ask quotes, as measured by information share on a daily basis. The asymmetry in price-discovery efficacy of bid and ask quotes, however, declines in magnitude on days in which Japanese monetary authorities intervene in the USD–JPY market.

This study argues that the structure of bid-ask spreads is asymmetric across the business cycle. During expansion, investors tend to be overconfident, leading to a higher spread component due to information asymmetry. On the other hand, during recession, the markets are more volatile, leading to a higher spread component due to order processing costs. With TAIEX futures contracts as a sample, it is found that the spread component due to information asymmetry is significantly higher in times of expansion than in times of recession, while the spread component due to order processing cost is significantly higher in times of recession than in times of expansion.

This paper investigates the relationship between the use of the fair value option for liabilities (FVO) under IAS 39 and information asymmetry across investors as reflected in bid-ask spreads. Using a sample of European banks for 2006–2010, we find descriptive evidence that banks using FVO exhibit lower bid-ask spreads, relative to non-adopters. We also document that lower bid-ask spreads are still present when the control group of non-adopters is held constant while the treatment group is reduced to adopters that recognise fair value changes attributable to own credit risk changes. Moreover, the comparison of adopters with own credit risk fair value changes to other adopters shows that the recognition of these fair values is not associated with higher bid-ask spreads. Stressing the limitations of our research and highlighting the existence of alternative plausible explanations, our findings appear not to support claims that recognising fair value changes attributable to changes in the own credit risk is detrimental to the transparency of financial statements.

Purpose – This paper aims to present a positive analysis of the bidding process for private finance initiative (PFI) projects. The analysis attempts to unravel how value for money (VFM) changes in the bidding process and what factors influence this change. Bidding theory postulates that the winning bid price drops from the effect of competition when the number of bid-participating firms increases. Design/methodology/approach – An instrumental variable analysis was conducted using a two-stage least-squares method to remove the influence of endogeneity in the number of bid participants, which, according to prior research and surveys of business operators, possibly explains some of the VFM change. The results were considered robust because no observable change was found in the positive effect of the number of participant firms. Findings – This paper provides positive evidence of the relationship between the number of firms and the bidding result. The analysis shows that the number of bid-participating firms clearly has a significant positive effect on VFM change. Specifically, competition lowers the winning bid amount in line with the theoretical proposition. Originality/value – This study confirms previous research based on bidding data of Japanese PFI projects, a segment not sufficiently researched so far. Further, increasing the number of participant firms, up to a maximum of six, is shown to raise the VFM, a result consistent with the fact that five major construction companies play a leading role in Japanese PFI projects.