Acquisition Pricing Research Articles

The Impact of CEO Optimism on Acquisition Pricing and Completion

The Impact of CEO Optimism on Acquisition Pricing and Completion

How does the power structure affect the acquisition price and inventory decisions in the reverse supply chain

With growing concerns about environmental sustainability, reverse supply chains play a crucial role in recycling, remanufacturing, and reducing waste. Investigating the power structure’s impact on decisions related to acquisition prices and inventory management can provide insights into the integration of sustainable practices. This study analyzes a reverse supply chain with a supplier and a remanufacturer, in which the supplier provides the remanufacturer with sorted used cores. We investigate the acquisition pricing and inventory decisions under different power structures (supplierled Stackelberg model, remanufacturer-led Stackelberg model) through game theory analysis. We first establish the centralized model to explore optimal acquisition decisions and profit of the total system. Then we evaluate the acquisition quantity, wholesale prices, the profit of supplier and remanufacturer in the supplier-led model and in the remanufacturer-led model. Finally, the impact of power structure on the performance of supplier and remanufacturer are explored by numerical analysis, as well as the supply chain system. Our significant findings show that (i) the total profit of the supplier-led and remanufacturer-led reverse supply chain are less than the centralized model due to the double marginalization; (ii) the remanufacturer-led reverse supply chain is superior to the supplier-led model reverse supply chain; (iii) the selected grades in the supplier-led model is proved the same as that in the remanufacturer-led model, which could not been affected by the wholesale price; (iv) the greater the inventory risk (the uncertainty in demand), the greater the profit share for the remanufacturer (supplier) in the supplier-led (remanufacturer-led) model.

Feature-reinforced dual-encoder aggregation network for flue-cured tobacco grading

Flue-cured tobacco grading plays a vital role in product acquisition and planting management. Due to the appearance similarity of inter-class tobacco leaves, the grading accuracy of existing algorithms could not conform to the requirements of accurate acquisition pricing and refined planting management. In this paper, we propose a feature-reinforced dual-encoder aggregation network (FDANet) on a machine vision-based platform for reliable tobacco grading. First, we propose a parallel dual-encoder structure consisting of the main encoder MobileNetV2 and the auxiliary encoder Swin Transformer, which is an indispensable component in the proposed FDANet. Furthermore, a well-designed multi-pooling channel aggregation (MCA) module extracts channel-related global information from the auxiliary encoder, which is leveraged to guide the main encoder. MCA transmits local effective information of the parallel dual-encoder to improve the classification accuracy. Additionally, the SMobileNetV2 blocks that embed the soft-attention module into the original MobileNetV2 blocks are proposed to enhance the representation of key channels. Finally, a feature reinforcement architecture is proposed to integrate the thickness of main vein into visual feature vector since it is a crucial feature perceived by the human visual system. The experimental results show that the proposed FDANet achieves mean test Accuracy of 79.30%, outperforming the novel Swin Transformer by 6.34%. In addition, our FDANet brings significant improvement compared to six state-of-the-art classification algorithms.

A Two-Side Approach to Acquisition Pricing and Completion

Prior literature on acquisition premiums has mainly focused on the potential participation and impact of the acquiring firm’s CEO while overlooking the prospective underlying role of the target firm’s CEO. We argue that buyers and sellers jointly explain and determine the price in the process of acquisitions: The Acquirer’s CEO offers a premium that the target’s CEO assesses to see whether it is acceptable. Consisting with this notion, we propose that the psychological characteristics of CEOs on both sides of the negotiation collectively influence the determination of the final price (premium) and the conclusion of the M&A transaction. We develop several predictions about CEO-specific optimism on both sides of acquisition transactions, and its effect on premiums offered, premiums paid, and acquisition completion. Based on a sample of 192 non-hostile acquisitions between 2012 and 2016, we find that the acquirer firm CEO specific optimism correlates with higher acquisition premiums offered, while the target firm CEO specific optimism predicts the final premium and transaction completion. This research adds to the acquisitions literature by taking a two-sided approach pricing these types of strategic transactions.

Analysis of Growth Strategies on Performance of Leather Industry, Kenya

The growth of the leather industry can help Kenya become industrialized. The leather industry contributes to economic growth through employment generation. However, data from the Kenya Association of Manufacturers demonstrate that more animals are slaughtered, but we still import more leather products. Little or no value addition is made on the hides and skins, and thus insignificant exports are done. This inspired the current study that sought to examine the influence of growth strategies on performance of the leather industry in Kenya. The study was literature-based. The study results showed that mergers & acquisition strategy, penetration strategy, diversification strategy, pricing strategy and differentiation strategy have a significant impact on performance. It was revealed that government regulation has a moderating effect on the relationship between business growth strategies and performance. The development of growth strategies such as mergers & acquisition strategy, penetration strategy, diversification strategy, pricing strategy and differentiation strategy can enhance the performance of the leather industry in Kenya. Growth strategies include methods that a firm uses to achieve its goals for expansion. The growth strategies play a central role in the expansion of a firm and enables to increase market shares and develop new markets and products. Based on the findings, the study recommended that firms in the leather industry need to consider embracing the growth strategies since it was found they have an impact on performance. The growth strategies such as mergers & acquisition strategy, penetration strategy, diversification strategy, pricing strategy and differentiation strategy can be embraced. The study also recommended that the companies should open new branches in new geographical areas to reach new customers. The companies need to assess how to retain the existing customers by developing new distribution channels. The firms in the leather industry should make the prices of the products more competitive in the market. The government should develop policies and frameworks that will support the firms in the leather industry. There is a need to have subsidies, incentives and a price ceiling that will support the growth of the firms in the leather industry. Keywords: Mergers & acquisition strategy, penetration strategy, diversification strategy, pricing strategy, differentiation strategy, performance, leather industry, Kenya

Time since targets’ initial public offerings, asymmetric information, uncertainty, and acquisition pricing

Abstract We document that acquirer announcement returns decrease and takeover premiums increase with the length of time since targets’ initial public offerings. Declining asymmetric information that leads to lower target valuation uncertainty for the acquirer can explain these effects. Newly public firms should have greater information asymmetry than established public firms that makes the target valuation more uncertain for a less-informed acquirer. Risk-averse acquirer managers pay less for riskier targets, resulting in relatively low takeover premiums and high acquirer announcement returns. Over time, as a target builds a public track record, the asymmetric information about its valuation declines, and takeover premiums increase to the benefit of target shareholders and the detriment of acquirer shareholders.

How do firms value debt capacity? Evidence from mergers and acquisitions

Abstract We examine how capital structure considerations affect acquisition pricing and valuation. We find that debt capacity improvement is value-enhancing for all acquirers when they gradually reveal their growth opportunities to the market. This is reflected in the long-run stock market returns, both 12- and 24-months after acquisition announcement. While both overlevered and underlevered acquirers benefit from an increase in debt capacity resulting from the merger, only overlevered acquirers pay higher premiums to increase debt capacity. Underlevered acquirers do not pay a premium for it; instead they consider market timing opportunities. Results are robust for alternative definitions of leverage and debt capacity improvement.

How Do Firms Value Debt Capacity? Evidence from Mergers and Acquisitions

We examine how capital structure considerations affect acquisition pricing and valuation. We find that debt capacity improvement is value-enhancing for all acquirers when they gradually reveal their growth opportunities to the market. This is reflected in the long-run stock market returns, both 12- and 24-months after acquisition announcement. While both overlevered and underlevered acquirers benefit from an increase in debt capacity resulting from the merger, only overlevered acquirers pay higher premiums to increase debt capacity. Underlevered acquirers do not pay a premium for it; instead they consider market timing opportunities. Results are robust for alternative definitions of leverage and debt capacity improvement.

Do Unlisted Targets Sell at Discounts?

Academic literature, practitioners, courts, and regulators routinely assert that both private and subsidiary targets sell at discounts relative to public targets. However, the empirical evidence to support this conclusion is thin. Our work alters the methodology from prior research to avoid biases due to both one-sided sample truncation and Jensen’s inequality. Following these changes, we find no evidence that unlisted targets sell at discounts. Our results hold under a number of different approaches and after controlling for known determinants of acquisition pricing.

Behavioral merger and acquisition pricing: Application to Verizon mergers with AOL and Yahoo

AbstractMergers and acquisitions (M&A) are important to companies as it allows them to acquire capabilities that they cannot create internally and to grow quickly. M&A transaction pricing relates to the pricing of these M&A deals and this article analyzes if behavioral finance factors like risk aversion, optimism, and loss aversion have an impact on this pricing. Prospect Theory and Cumulative Prospect Theory are applied to an agent‐based model to solve this problem. Results of this article show that M&A transaction price does respond to a change in risk aversion and optimism traits of the acquirer and target companies respectively, as well as, loss aversion and certainty (probability of gains and losses). When, the acquirer is risk taking and target company is optimistic, the M&A transaction price increases. However, with increasing certainty of gains and reducing loss aversion (increasing loss aversion co‐efficient; as gains are perceived to have the same weight as losses), the M&A transaction price seems to reduce. These results are compared with the recent mergers of Verizon and AOL as well as Verizon and Yahoo, to understand if these results would occur in practice. Analyzing these mergers, it seems that the outcomes from this model does provide insight on the pricing of these M&A transactions. This article also analyzes how these behaviors would impact the pricing when three different acquirers are trying to take over a target company. Results show that loss aversion has a significant effect on this pricing with risk aversion and optimism also having some minor impact. But, the existence of multiple acquirers does positively increase the M&A transaction price.

Returned Product Acquisition Pricing by Adaptive Neuro Fuzzy Inference System

In recent years, reverse logistics have become increasingly important for the firms as a both environmental and economical approach. By collecting the returned products, firms realize to recover after kind of activities. In return products collection, due to the fact that each returned products have different functionality, determining the acquisition price of the used products is an important problem. For this reason, a pricing approach that can be used for collecting returned products is proposed in this study. Since the different product models can be exist and the acquisition price can be affected by the new product price, the acquisition price is predicted by the ratio of the new product price to acquisition price. In this study, the acquisition price ratio to new product price is modeled by the adaptive neuro fuzzy inference system and a case study is conducted for the used cell phones collection. Four phone models that have different release dates take into consideration with general appearance and functionality parameters. When the results are examined, the proposed method prediction’s is pretty close to the expert view.

Short-sale constraints, information acquisition, and asset prices

During financial crises, financial market regulators often restrict short-selling to support prices and curb volatility. However, evidence suggests that short-selling bans during the turmoil in financial markets in 2007–2009 failed to achieve regulators' goals. We analyze a model of costly private information acquisition and asset pricing under short-sale constraints to examine a possible cause of this failure. We show that the constraints increase return volatility by adversely affecting the production of private information. When investors are highly risk averse or are holding highly correlated risky assets, the distortion in private information production arising from imposing short-sale constraints leads to undervaluation, implying that imposing short-selling bans during economic crises not only fails to curb volatility but also may fail to support prices.

Information, Imperfect Competition, and Volatility

An important consideration in informed trading is to explicitly take into account the effects of trades on asset prices. In this paper we develop a general equilibrium model of information acquisition and asset pricing under imperfect competition. We show that if investors are sufficiently risk averse, imperfect competition reduces their incentives to acquire information and the reduction may lead to significant illiquidity and price volatility in the market. The negative strategic value of information is the source of illiquidity and price volatility. Episodes of significant illiquidity occur in an environment in which the equilibrium information asymmetry is low. In contrast to the perfect competition model, we show that in the imperfect competition model there is generally strategic complementarity in investors' information acquisition decisions.

Acquisition Pricing and Inventory Decisions on Dual-Source Spare-Part System with Final Production and Remanufacturing

The life spans of durable goods are longer than their warranty periods. To satisfy the service demand of spare parts and keep the market competition advantage, enterprises have to maintain the longer inventory planning of spare parts. However, how to obtain a valid number of spare parts is difficult for those enterprises. In this paper, we consider a spare-part inventory problem, where the inventory can be replenished by two ways including the final production order and the remanufacturing way. Especially for the remanufacturing way, we consider the acquisition management problem of used products concerning an acquisition pricing decision. In a multiperiod setting, we formulate the problem into a dynamic optimization problem, where the system decisions include the final production order and acquisition price of used products at each period. By stochastic dynamic programming, we obtain the optimal policy of the acquisition pricing at each period and give the optimal policy structure of the optimization problem at the first period. Then, a recursion algorithm is designed to calculate the optimal decisions and the critical points in the policy. Finally, the numerical analyses show the effects of demand information and customer’s sensitive degree on the related decisions and the optimal cost.

Delegated Information Acquisition and Asset Pricing

This paper studies the joint determination of optimal contracts and equilibrium asset prices in an economy with multiple principal-agent pairs. Principals design optimal contracts that provide incentives for agents to acquire costly information. With agency problems, the agents’ compensation depends on the accuracy of their forecasts for asset prices and payos. Complementarities in information acquisition delegation arise as follows. As more principals hire agents to acquire information, asset prices become less noisy. Consequently, agents are more willing to acquire information because they can forecast asset prices more accurately, thus mitigating agency problems and encouraging other principals to hire agents. This mechanism can explain many interesting phenomena in markets, including multiple equilibria, herding, home bias and idiosyncratic volatility comovement.

Dynamic acquisition pricing policy under uncertain remanufactured-product demand

Purpose– The purpose of this paper is to investigate the dynamic acquisition pricing strategy for collecting used products (also known as cores or returns) in a finite planning horizon. In particular, this paper studies a cost-minimization model in which a firm offers acquisition price that impacts the quantity of the returns, and remanufactures the used product to satisfy the customer demand.Design/methodology/approach– This paper uses multi-period stochastic dynamic programming theory to model a remanufacturing system that faces the random demand for remanufactured products. The number of the returns at each period is uncertain and increases linearly with the acquisition price offered.Findings– The study shows that when the uncertainty of demand for remanufactured products increases, the remanufacturer should hold a higher core stock level to minimize the expected total cost and thus a higher acquisition price is needed to attract returns. However, given demand uncertainty, the optimal price decreases in the initial core stock level in each period. It also indicates that the optimal acquisition price increases in the variance of the returns, but decreases in the mean of the returns.Practical implications– The findings suggest that a remanufacturer could reduce the expected total cost by adjusting the acquisition price according to the number of returns periodically.Originality/value– Introducing the impact of supply uncertainty on the acquisition price of used products, this paper uses a multi-period dynamic model, instead of single period model in previous studies, to examine the remanufacturer’s dynamic acquisition pricing policy.

M&A Negotiations and Lawyer Expertise

We use proprietary data to look into the black box of M&A negotiations and to shed light on the effects of lawyer expertise on M&A contract design, the bargaining process, and acquisition pricing. Measuring the effects of buyer relative to seller lawyer expertise, we document that more expertise is associated with more beneficial negotiation outcomes across several dimensions. Lawyer fixed effects and geographic‐proximity instruments allow us to address concerns about the endogenous allocation of lawyers to deals or clients. Our results help explain the importance of league table rankings and the variation in legal fees within the legal M&A services industry.

Acquisition pricing and remanufacturing decisions in a closed-loop supply chain

This paper models a closed-loop supply chain (CLSC) with a manufacturer and its supply channels – recycle channel and reliable supply channel. We assume that the manufacturer may reuse the recycled main product component and remanufacture the product. The recycle channel shows stochastic recovery rate. Both the centralized (integrated) recycle channel CLSC and the decentralized recycle channel CLSC are studied. The optimal production decision and the optimal acquisition pricing decision are obtained for both the deterministic demand and the stochastic demand cases. Further, the paper discusses the supply chain inefficiency in this CLSC. It is shown that under decentralized recycle channel structure, the optimal acquisition price is always lower than the optimal acquisition price under centralized recycle channel structure, causing reduced recycle quantity and lower remanufactured quantity, which is similar to the effect of double marginalization in the normal forward supply chain. The cost difference between the two supply channels also increases such double marginalization impact. In order to reduce such supply chain inefficiency, two contracts (complete compensation and partial compensation) are proposed. It is shown that under certain conditions, both contracts are Pareto improving for the decentralized supply chain and can be used to coordinate the CLSC. Numerical examples are used to illustrate the results. The numerical examples show the different preferences of supply chain parties on different risk reductions in the decentralized system. In general, the interests on demand risk reduction is aligned between the recycle channel supplier and the manufacturer with the manufacturer showing higher motivation; on the other hand, recycle channel supplier and the manufacturer may have conflict of interests in supply risk reduction when the supply risk is low, and their interests are aligned when the supply risk is high.

Learning About Target Firms and Pricing of Acquisitions

We analyze the effects of learning about target firms on acquisition pricing. Newly public firms should be more opaque than established firms with long track records. An acquirer with superior information about a newly public firm can negotiate a favorable takeover price because lessinformed potential acquirers have a bidding handicap. Consistent with the effects of learning, acquirer announcement returns decrease and takeover premiums increase with the length of time since the targets’ initial public offerings. Our results provide new insights into the determinants of acquirer announcement returns and the effects of learning on acquisition pricing. Moreover, the target’s listing status alone does not seem to fully explain why acquirer announcement returns in acquisitions of public targets are significantly lower than in acquisitions of private targets.

The Effect of Options on Information Acquisition and Asset Pricing

We study the eect of introducing an options market on investors’ incentive to collect private information in a rational expectation equilibrium model. We show that an options market has two eects on information acquisition: a negative eect, as options act as substitutes for information, and a positive eect, as informed investors have less need for options and can earn prots from selling them. When the population of informed investors is high because of the low information acquisition cost, the supply for options is larger than the demand, leading to low option prices. Low option prices in turn induce investors to use options instead of information to reduce risk, while informed investors have little opportunity to earn prots from selling options to cover their information acquisition cost. Introducing an options market thus decreases investors’ incentive to acquire information, and the prices of the underlying assets become less informative, leading to lower prices and higher volatilities. A dynamic extension of this analysis shows that introducing an options market increases the price reactions to earnings announcements. However, when the information acquisition cost is high, the opposite eects arise. Further analysis shows that our results are robust for more general derivatives. These results provide a potentially unied theory to reconcile the conicting empirical ndings on the options listing of individual stocks in both the U.S. market and international markets.