Large Price Changes Research Articles

Price Setting and Price Stickiness: A Behavioral Foundation of Inaction Bands

Abstract This paper puts forward a behavioral theory of price setting where managers maximize perceived profits following a process of mental accounting. The theory predicts a pricing rule that is similar to—but crucially different from—that of a standard menu cost theory: there is an inaction band, but there are two rather than just one target prices, depending on whether the firm updates its price upwards or downwards. The calibrated model replicates two patterns of price microdata that standard menu cost models have difficulty accounting for: (i) The distribution of price changes has both small and large price changes, and (ii) the hazard function of price changes is downward sloping initially, that is, firms that have just recently changed their price have a higher probability of changing it again, while this probability becomes constant thereafter.

High Price Impact Trade Identification and Its Implication for Volatility and Price Efficiency

We include limit order book (LOB) matchedness as a new trade attribute to identify high price impact trades (HPITs). HPITs are trades associated with large price changes relative to their volume proportion. We show that the inclusion of matchedness provides a finer analysis of the relationship between price contribution and trade categories. We further verify that a stronger presence of HPITs leads to a decline in volatility and improves price efficiency, which suggests a link between HPITs and informed trades.

The Health Costs of Cost Sharing.

What happens when patients suddenly stop their medications? We study the health consequences of drug interruptions caused by large, abrupt, and arbitrary changes in price. Medicare's prescription drug benefit as-if-randomly assigns 65-year-olds a drug budget as a function of their birth month, beyond which out-of-pocket costs suddenly increase. Those facing smaller budgets consume fewer drugs and die more: mortality increases 0.0164 percentage points per month (13.9%) for each $100 per month budget decrease (24.4%). This estimate is robust to a range of falsification checks and lies in the 97.8th percentile of 544 placebo estimates from similar populations that lack the same idiosyncratic budget policy. Several facts help make sense of this large effect. First, patients stop taking drugs that are both high value and suspected to cause life-threatening withdrawal syndromes when stopped. Second, using machine learning, we identify patients at the highest risk of drug-preventable adverse events. Contrary to the predictions of standard economic models, high-risk patients (e.g., those most likely to have a heart attack) cut back more than low-risk patients on exactly those drugs that would benefit them the most (e.g., statins). Finally, patients appear unaware of these risks. In a survey of 65-year-olds, only one-third believe that stopping their drugs for up to a month could have any serious consequences. We conclude that far from curbing waste, cost sharing is itself highly inefficient, resulting in missed opportunities to buy health at very low cost ($11,321 per life-year).

Seeking a shock haven: Hedging extreme upward oil price changes

Crude oil is prone to large upward price shocks, creating challenges for personal and corporate budgeting and the economy more broadly. In this paper, we systematically assess a range of possible assets which might function as shock havens against large oil price shocks. Empirical tests uncover a rich set of assets which act both as hedges and shock havens, including precious metals, soft commodities and, with less consistency, currencies. The range of possible hedges is extensive, marked by a positive correlation with oil returns on average. Gold, silver, platinum, corn, and wheat are shown to provide consistent shock haven properties across various specifications, including those surrounding the large oil price changes observed during the COVID-19 Pandemic and following the invasion of Ukraine.

Tensile Testing of Bolted Joints in Pultruded Glass Fibre Reinforced Plastic Profiles

Machine manufacturing and the automotive industry are often faced with supply chain problems for the raw materials used in the largest proportion (steel and aluminium) and the resulting large price changes. One solution to the lack of raw materials could be the introduction of new materials. Glass-fibre-reinforced plastic (GRP) profiles produced by pultrusion can be suitable for replacing metallic materials in many applications. However, one of the reasons for their limited distribution is the lack of well-established joining processes. The aim of the research is to test the tensile strength of the bolted connection of GRP sheet materials of different thickness according to an experimental design. Based on the experimental results, bolted joint recommendations can be provided for the examined GRP sections.

Oil Price Exposure and the Cross-Section of Stock Returns

Abstract We provide evidence that equity investors are slow to process information about how current oil price changes affect future earnings announcements. Stock prices respond to lagged quarterly oil price changes when firms start announcing earnings in the next quarter. A cross-sectional equity trading strategy that exploits this predictability yields an annualized Sharpe ratio of 0.50. Our oil-response forecast strategy earns especially high returns after large absolute oil price changes, in recessions or bear markets, and during peak earnings season. The predictability we document is consistent with limited attention, is not driven by risk factor exposure, and survives several robustness tests. (JEL G10, G11, G14, G40, Q41)

Modeling and simulation of financial returns under non-Gaussian distributions

It is well known that the probability distribution of high-frequency financial returns is characterized by a leptokurtic, heavy-tailed shape. This behavior undermines the typical assumption of Gaussian log-returns behind the standard approach to risk management and option pricing. Yet, there is no consensus on what class of probability distributions should be adopted to describe financial returns and different models used in the literature have demonstrated, to varying extent, an ability to reproduce empirically observed stylized facts. In order to provide some clarity, in this paper we perform a thorough study of the most popular models of return distributions as obtained in the empirical analyses of high-frequency financial data. We compare the statistical properties and simulate the dynamics of non-Gaussian financial fluctuations by means of Monte Carlo sampling from the different models in terms of realistic tail exponents. Our findings show a noticeable consistency between the considered return distributions in the modeling of the scaling properties of large price changes. We also discuss the convergence rate to the asymptotic distributions of the non-Gaussian stochastic processes and we study, as a first example of possible applications, the impact of our results on option pricing in comparison with the standard Black and Scholes approach.

Price setting on the two sides of the Atlantic - Evidence from supermarket scanner data

We compare supermarket price setting in the US and the euro area and assess its impact on food inflation. We introduce a novel scanner dataset of Germany, the Netherlands, France, and Italy (EA4) and contrast it with an equivalent dataset from the US. We find that both higher frequency and stronger state dependence of price changes contribute to higher flexibility of supermarket inflation in the US relative to the euro area. We argue that the driving force behind both factors is higher cross-sectional volatility in the US. Larger product-level fluctuations both force retailers to adjust prices more frequently and increase price misalignments, which increase the selection of large price changes. Both facts are well represented by a mildly state-dependent price-setting model, and they jointly explain over a third of the difference in food-inflation volatility between the US and the euro area as well as around a third of the difference between the inflation responses to the COVID-19 shock in Germany and Italy.

Persistent Monetary Non-neutrality in an Estimated Menu Cost Model with Partially Costly Information

We propose a model that reconciles microeconomic evidence of frequent and large price changes with sizable monetary non-neutrality. Firms incur separate lump-sum costs to change prices and to gather and process some information about marginal costs. Additional relevant information is continuously available and can be factored into pricing decisions at no cost. We estimate the model by Simulated Method of Moments, using price-setting statistics for the US economy. The model with free idiosyncratic and costly aggregate information fits well both targeted and untargeted microeconomic moments and generates almost three times as much monetary non-neutrality as the Calvo model. (JEL D21, D83, E23, E31, L11)

The Other Insiders: Personal Trading by Brokers, Analysts, and Fund Managers

Abstract When brokers, analysts, and fund managers buy or sell stocks for their own accounts, these “access employees” of financial institutions outperform retail investors over short windows up to a month. They earn particularly high abnormal returns when they trade before earnings announcements, revisions of analyst recommendations, and large stock price changes. We also find evidence consistent with profitable front-running and information leakage around the execution of corporate insider trades and block trades by mutual funds, as well as the release of revised recommendations by analysts who work at the same brokerage firm. (JEL G12, G14, G18) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Introduction

Introduction

Indirect Insider Trading

AbstractInsiders must disclose indirect trades made through accounts they control, including family, trust, retirement, and foundation accounts. Indirect trades through these accounts are more profitable than direct trades in the insider’s own account. They are also more likely to be made by “opportunistic” insiders who make nonroutine trades, or who trade profitably before earnings announcements, or who have a short investment horizon. These trades contain more predictive information about earnings surprises and large price changes, and they tend to be made by insiders at firms with high information asymmetry. Insiders also make fewer indirect trades following periods of intense regulatory scrutiny.

What drives most jumps in global crude oil prices? Fundamental shortage conditions, cartel, geopolitics or the behaviour of financial market participants

AbstractSeveral studies have emphasised the potential role of oil price volatility as a leading macroeconomic indicator, since it provides prominent information to energy traders, market participants and policymakers. In an effort to shed fresh insights into the underlying factors of wide oil price changes, the objective of this paper is twofold: First to capture large oil price changes caused by the arrival of surprising news (i.e., jumps); second to distinguish between short‐, medium‐ and long‐term determinants of jumps in oil prices due to changes in oil supply and demand fundamentals, factors associated with the market power of oil producers, speculation, geopolitical risks and OPEC's spare capacity. Using an empirical mode decomposition (EMD), we find that oil supply and demand forces are the most prevalent in determining oil price changes in the long run, which is quite predictable. OPEC gains increasing importance in the medium‐ and long‐terms. Our method also allows us to show that OPEC's use of spare capacity moderately reduces oil price volatility in the short‐term, thus suggesting a limited stabilising influence on the oil market. We consider broader policy implications for our results.

ON STOCK RETURN PATTERNS FOLLOWING LARGE MONTHLY PRICE MOVEMENTS: EMPIRICAL EVIDENCE FROM INDIA

The purpose of this study is to examine the short-horizon stock behaviour following large monthly price changes of the large, liquid stocks in the Indian stock market. The event study methodology is used with two different methodologies and three abnormal return computational methods to improve the robustness and reliability of the results. This study evidences significant reversals following both large price declines and increases up to six months. Further, stronger initial shocks were followed by stronger reversals. The results are consistent with the ‘overreaction hypothesis’ in the Indian stock market. The results are robust to microstructure effects, extreme events, industry, period, methodology and market effects. The abnormal returns following large price declines might be economically significant with potential economic profits for traders.

Extreme price co-movement of commodity futures and industrial production growth: An empirical evaluation

This paper studies how the extreme price co-movement of commodity futures indicates industrial production (IP) growth. In this regard, we model synchronized movements and large price changes into one measure by characterizing upside and downside price extremes. We find that the derived price extremes are positively associated with IP growth over the next quarter. We further conclude that such impact is not symmetric, as the impact led by downside extremes is robust whereas that of upside extremes is not. Our results reinforce the informational friction theory as well as those financial studies that emphasize downside risk.

Availability heuristic and reversals following large stock price changes: evidence from the FTSE 100

<abstract> <p>This paper examines if investors exhibited evidence of the availability heuristic in their investment decisions when significant price changes occurred in the British stock market during the 2010–2018 period. We raise the hypothesis that if a significant stock price move takes place on a day when the stock market index also undergoes a significant change (either positive or negative), then the magnitude of that shock may be increased by the availability of positive investment or negative outcomes. We applied three different proxies for large stock price changes which yielded a robust sample of events for this study. We found no significant evidence of the availability heuristic. In addition, we also found no significant evidence of price overreaction for both price decreases and increases. Inversely, we found robust results that suggest randomness in the behavior of stock prices in this period, thus supporting the efficiency of financial markets and opposing the results from similar studies carried out in the United States.</p> </abstract>

Cosine Willow Tree Structure under Lévy Processes with Application to Pricing Variance Derivatives

Lévy process models can capture the large price changes on sudden exogenous events and can better demonstrate the high peak and heavy tail characteristics of financial data. The Fourier transformation method is famous for pricing derivatives under the Lévy processes beause of its efficiency, how it separates models from payoff function, and how it handles models with characteristic functions, but it is criticized for its restriction on path dependency. In this article, we propose a unified cosine willow tree method, which inherits the merits of the transformation method but overcomes its shortcomings. Moreover, the hedging Greeks can be obtained as a by-product from the tree structure with minor extra cost. Some popular variance derivatives are also discussed to demonstrate the flexibility of the proposed method in handling path dependency. Finally, the theoretical convergence is analyzed for various Lévy process models.

Do volatility extensions improve the quality of closing call auctions?

AbstractTo improve the efficiency of the closing price, many equity exchanges apply volatility extensions to their closing call auctions (CCAs). If an imminent auction execution implies a large price change, the order submission period is extended to let traders reconsider their orders. This paper uses the introduction of closing auction volatility extensions at NASDAQ Nordic to provide the first analysis of the effects of such mechanisms. We find that the volatility extensions reduce transitory volatility and deter price manipulation at the close. Consistent with increased trust in the mechanism, the CCA attracts higher volumes after the change.

Deregulation and pricing of medical services: a policy experiment based in China

BackgroundPrice regulation is a common constraint in Chinese hospitals. Based on a policy experiment conducted in China on the price deregulation of private nonprofit hospitals, this study empirically examines the impact of medical service price regulation on the pricing of medical services by hospitals.MethodsUsing the claim data of insured inpatients residing in a major Chinese city for the period 2010–2015, this study constructs a DID (difference-in-differences) model to compare the impact of price deregulation on medical expenditure and expenditure structure between public and private nonprofit hospitals.ResultsThe empirical results based on micro data reveal that, price deregulated significantly increased the total expenditure per inpatient visit by 10.5%. In the itemized expenditure, the diagnostic test and drug expenditure per inpatient visit of private nonprofit hospitals decreased significantly, whereas the physician service expenditure per inpatient visit increased significantly. For expenditure structure, the proportions of drug expenditure and diagnostic test expenditure per inpatient visit significantly decreased by 5.7 and 3.1%, respectively. Furthermore, this paper also found that hospitals had larger price changes for dominant diseases than for non-dominant diseases.ConclusionsUnder price regulation, medical service prices generally become lower than their costs. Therefore, after price deregulation, private nonprofit hospitals increase medical service prices above their cost and achieve the service premium increasing physician medical services. Further, although price deregulation causes patient expenditure to increase to a certain level, it optimizes the expenditure structure, as well.

Stock Market Behavior after Large Price Changes and Winner-Loser Effect

This study examines the behavior of stock prices following large price changes. It also examines the presence of disposition prone investors and effect of size on stock returns. The study uses daily prices data from Pakistan Stock Exchange (Formerly, Karachi Stock Exchange (KSE)) for the period of January 2001 to July 2012. Our findings suggest that winners perform better than losers after experiencing large price shocks thus showing a momentum behavior. This also suggests that most of the investors in KSE behave rationally and we do not find any evidence of disposition effect in KSE. Further, pooled regression estimates show that size is positively related to post-event abnormal returns. The fixed effect model shows the presence of unobservable firm-specific and time specific effects that account for price continuation.