Wall Street's growing influence on plastic surgery

The advent of managed care has unleashed market forces on the health care system. One result of these new pressures is a shift from nonprofit to Wall Street-based financing. This report quantifies these trends by comparing health organizations' financial structures in the 1980s and now. The reasons behind this shift and the function of the stock market are examined. A review of Wall Street's key financial measures confirms that health care has shifted to the stock market as its principal means of financing. The stock market works by assigning a current price to a company's stock based on estimates for future earnings. Thus, companies desire predictability in their costs, revenues, and profits. Plastic surgeons can master this system by meeting the challenges imposed by Wall Street financing. Important steps include continuously measuring costs and outcomes of procedures, demanding cost data from hospitals and payers, using these data to improve costs and outcomes, and taking advantage of the system's openness to innovation and easier access to capital. As they seek to protect their role as medical decision makers under the new free-market system, plastic surgeons can benefit from understanding the mechanisms of the stock market.     

Being on the Field When the Game Is Still Under Way. The Financial Press and Stock Markets in Times of Crisis

This paper looks at the relationship between negative news and stock markets in times of global crisis, such as the 2008/2009 period. We analysed one year of front page banner headlines of three financial newspapers, the Wall Street Journal, Financial Times, and Il Sole24ore to examine the influence of bad news both on stock market volatility and dynamic correlation. Our results show that the press and markets influenced each other in generating market volatility and in particular, that the Wall Street Journal had a crucial effect both on the volatility and correlation between the US and foreign markets. We also found significant differences between newspapers in their interpretation of the crisis, with the Financial Times being significantly pessimistic even in phases of low market volatility. Our results confirm the reflexive nature of stock markets. When the situation is uncertain and unpredictable, market behaviour may even reflect qualitative, big picture, and subjective information such as streamers in a newspaper, whose economic and informative value is questionable.     

Network Environment and Financial Risk Using Machine Learning and Sentiment Analysis

Under the network environment, the trading volume and asset price of a financial commodity or instrument are affected by various complicated factors. Machine learning and sentiment analysis provide powerful tools to collect a great deal of data from the website and retrieve useful information for effectively forecasting financial risk of associated companies. This article studies trading volume and asset price risk when sentimental financial information data are available using both sentiment analysis and popular machine learning approaches: artificial neural network (ANN) and support vector machine (SVM). Nonlinear GARCH-based mining models are developed by integrating GARCH (generalized autoregressive conditional heteroskedasticity) theory and ANN and SVM. Empirical studies in the U.S. stock market show that the proposed approach achieves favorable forecast performances. GARCH-based SVM outperforms GARCH-based ANN for volatility forecast, whereas GARCH-based ANN achieves a better forecast result for the volatility trend. Results also indicate a strong correlation between information sentiment and both trading volume and asset price volatility.     

Disciplining Investment Bankers, Disciplining the Economy: Wall Street's Institutional Culture of Crisis and the Downsizing of "Corporate America"

ABSTRACT   Countering the "mystique" of finance as abstract and disembedding, in this article I approach the financial market from the site of investment banking corporate culture to concretize large-scale processes and access its effects in the world. By investigating Wall Street investment banks' role in two pivotal socioeconomic phenomena—rampant downsizings throughout "corporate America" and the financial bubble and bust of 2001—I explore whether financial crises and corporate downsizing can be better understood via Wall Street's quotidian practices. I draw theoretical inspiration from the figure of the downsized investment banker, who embodies and connects Wall Street's rationales for downsizing as well as "the effects." Although shareholder value and externalized market justifications are Wall Street's models for understanding downsizing, I move beyond these dominant assumptions, demonstrating that bankers' own work experiences, market temporalities, and organizational culture serve as an incisive model to explain Wall Street's role in downsizing and financial crisis. [Keywords: Wall Street, corporate downsizing, financial markets, shareholder value, organizational culture]     

Study on Market Stability and Price Limit of Chinese Stock Index Futures Market: An Agent-Based Modeling Perspective

This paper explores a method of managing the risk of the stock index futures market and the cross-market through analyzing the effectiveness of price limits on the Chinese Stock Index 300 futures market. We adopt a cross-market artificial financial market (include the stock market and the stock index futures market) as a platform on which to simulate the operation of the CSI 300 futures market by changing the settings of price limits. After comparing the market stability under different price limits by appropriate liquidity and volatility indicators, we find that enhancing price limits or removing price limits both play a negative impact on market stability. In contrast, a positive impact exists on market stability if the existing price limit is maintained (increase of limit by10%, down by 10%) or it is broadened to a proper extent. Our study provides reasonable advice for a price limit setting and risk management for CSI 300 futures.     

Managed care's attempts to capture aesthetic surgery

Managed care organizations recently have attempted to add aesthetic surgery to their line of available services. To better understand the challenges posed by these actions, all members of the American Society for Aesthetic Plastic Surgery were surveyed about managed care overtures to aesthetic plastic surgeons, their responses, and the likely responses of their patients. The goal was to examine both the supplier and consumer ends of the aesthetic surgery market to determine the likely effects of managed care's attempts to capture aesthetic surgery. A total of 632 plastic surgeons returned the surveys (response rate, 54.5 percent). Twenty-two percent reported being approached by managed care organizations about joining a panel of aesthetic surgeons. Approximately one-quarter of the plastic surgeons said they would participate in aesthetic surgery panels developed by managed care organizations. Characteristics significantly associated with willingness to participate were solo practice structure, a low percentage of practice revenues from aesthetic surgery, and a very competitive practice environment. Plastic surgeons believed that their colleagues would be even more willing to acquiesce to managed care aesthetic surgery; more than one-third said that 25 to 50 percent of their colleagues would join, and nearly one-third thought that more than half would participate. Plastic surgeons believed that many of their patients would also participate in managed care aesthetic surgery. Twenty-four percent thought that more than half of their patients would choose an aesthetic surgeon through their managed care organization if that organization developed a network for aesthetic surgery. This figure increased to almost 40 percent if the organization would deny coverage for complications resulting from nonpanel surgeons, and to 41 percent if the organization would offer price discounts. This survey shows that most plastic surgeons are against managed care aesthetic surgery. But it also shows that some plastic surgeons will participate, and that most plastic surgeons think many of their colleagues and patients will do likewise. This means that managed care organizations have the potential to make inroads in aesthetic surgery on both the supplier and consumer ends of the market. To prevent managed care from capturing aesthetic surgery, plastic surgeons must anticipate the likely business strategy of managed care. To this end, they must understand the steps involved in the creation of a new service business and offer organized countermeasures against each of them.     

The financial environment of aesthetic surgery: results of a survey of plastic surgeons

To gather information about aesthetic surgery's current practice structures, competitive environment, patient price sensitivity, and marketing and practice development requirements, a two-page survey was developed and mailed to all 1180 members of the American Society for Aesthetic Plastic Surgery. A total of 632 surveys were returned (response rate of 54.5 percent). Most aesthetic plastic surgeons said they were in solo practice (63.3 percent). More than two-thirds described the marketplace as "very competitive," with 59 percent reporting 25 or more surgeons offering aesthetic surgery in their area. They estimated their patients' average income at $62,800. Nearly all plastic surgeons labeled their patients as "moderately price sensitive" (62.3 percent) or "very price sensitive" (30.6 percent). Similarly, 23.2 percent estimated that they had lost 20 or more patients within the last year for reasons of price. Practice development and marketing efforts represented an average of 7.3 percent of plastic surgeons' working time. Parameters associated with a high percentage of time devoted to these activities were solo practice, percentage of revenue from aesthetic surgery greater than 50 percent, a practice environment designation of moderately or very competitive, and ten or more area surgeons offering aesthetic surgery (p < 0.05). High patient income led to only slight decreases in price sensitivity and did not significantly reduce the amount of time spent on marketing and practice development. Although the rest of the healthcare industry has undergone a period of consolidation, aesthetic surgeons have been able to resist these changes. The results of this survey suggest that the fragmented nature of the aesthetic surgery industry is associated with additional burdens on plastic surgeons. As the aesthetic surgery market becomes more competitive, plastic surgeons may benefit from consolidation to reduce costs and maximize efficiency.     

Confidence and the Stock Market: An Agent-Based Approach

Using a behavioral finance approach we study the impact of behavioral bias. We construct an artificial market consisting of fundamentalists and chartists to model the decision-making process of various agents. The agents differ in their strategies for evaluating stock prices, and exhibit differing memory lengths and confidence levels. When we increase the heterogeneity of the strategies used by the agents, in particular the memory lengths, we observe excess volatility and kurtosis, in agreement with real market fluctuations—indicating that agents in real-world financial markets exhibit widely differing memory lengths. We incorporate the behavioral traits of adaptive confidence and observe a positive correlation between average confidence and return rate, indicating that market sentiment is an important driver in price fluctuations. The introduction of market confidence increases price volatility, reflecting the negative effect of irrationality in market behavior.     

Discount cosmetic surgery: industry trends and strategies for success

Discount cosmetic surgery is a topic of interest to plastic surgeons. To understand this trend and its effects on plastic surgeons, it is necessary to review the economics of cosmetic surgery, plastic surgery's practice environment, and the broader business principles of service industries.Recent work looked at the economics of the plastic surgery market. This analysis demonstrated that increased local density of plastic surgeons was associated with lower adjusted fees for cosmetic procedures. A survey of plastic surgeons about their practice environment revealed that 93 percent categorized the majority of their patients as very or moderately price-sensitive. Fully 98 percent described their business climate as very or moderately competitive and most plastic surgeons thought they lost a sizable number of cosmetic patients within the last year for reasons of price.A standard industry analysis, when applied to cosmetic surgery, reveals the following: an increased number of surgeons leads to lower fees (reducing their bargaining power as suppliers), patients are price-sensitive (increasing their bargaining power as buyers), and there are few barriers to entry among providers (allowing potential new entrants into the market). Such a situation is conducive to discounting taking hold-and even becoming the industry norm.In this environment, business strategy dictates there are three protocols for success: discounting, differentiation, and focus. Discounting joins the trend toward cutting fees. Success comes from increasing volume and efficiency and thus preserving profits. Differentiation creates an industrywide perception of uniqueness; this requires broadly positioning plastic surgeons as holders of a distinct brand identity separate from other "cosmetic surgeons." The final strategy is to focus on a particular buyer group to develop a market niche, such as establishing a "Park Avenue" practice catering to patients who demand a prestigious surgeon, although this is likely a small segment of the overall patient population. Plastic surgeons that buck the trend toward discount cosmetic surgery must take concrete and potentially costly steps to implement a plausible strategy for distinguishing their practices within the crowded cosmetic surgery market.     

Impact of Stock Market Structure on Intertrade Time and Price Dynamics

We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies'' market capitalization–a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets.     

Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk

We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor''s 500 index for 1994–2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.     

A Financial Market Model Incorporating Herd Behaviour

Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents’ accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents’ accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.     

Analysis of a group purchasing organization under demand and price uncertainty

Based on an industrial case study, we present a stochastic model of a supply chain consisting of a set of buyers and suppliers and a group purchasing organization (GPO). The GPO combines orders from buyers in a two-period model. Demand and price in the second period are random. An advance selling opportunity is available to all suppliers and buyers in the first-period market. Buyers decide how much to buy through the GPO in the first period and how much to procure from the market at a lower or higher price in the second period. Suppliers determine the amount of capacity to sell through the GPO in the first period and to hold in reserve in order to meet demand in the second period. The GPO conducts a uniform-price reverse auction to select suppliers and decides on the price that will be offered to buyers to maximize its profit. By determining the optimal decisions of buyers, suppliers, and the GPO, we answer the following questions: Do suppliers and buyers benefit from working with a GPO? How do the uncertainty in demand, the share of GPO orders in the advance sales market, and the uncertainty in price influence the players’ decisions and profits? What are the characteristics of an environment that would encourage suppliers and buyers to work with a GPO? We show that a GPO helps buyers and suppliers to mitigate demand and price risks effectively while collecting a premium by serving as an intermediary between them.     

Universal Behavior of Extreme Price Movements in Stock Markets

Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using a large collection of data from three different stock markets, we present evidence that a modification to the random model—adding a slow, but significant, fluctuation to the standard deviation of the process—accurately explains the probability of different-sized price changes, including the relative high frequency of extreme movements. Furthermore, we show that this process is similar across stocks so that their price fluctuations can be characterized by a single curve. Because the behavior of price fluctuations is rooted in the characteristics of volatility, we expect our results to bring increased interest to stochastic volatility models, and especially to those that can produce the properties of volatility reported here.     

The Ability of Analysts' Recommendations to Predict Optimistic and Pessimistic Forecasts

Previous researches show that buy (growth) companies conduct income increasing earnings management in order to meet forecasts and generate positive forecast Errors (FEs). This behavior however, is not inherent in sell (non-growth) companies. Using the aforementioned background, this research hypothesizes that since sell companies are pressured to avoid income increasing earnings management, they are capable, and in fact more inclined, to pursue income decreasing Forecast Management (FM) with the purpose of generating positive FEs. Using a sample of 6553 firm-years of companies that are listed in the NYSE between the years 2005–2010, the study determines that sell companies conduct income decreasing FM to generate positive FEs. However, the frequency of positive FEs of sell companies does not exceed that of buy companies. Using the efficiency perspective, the study suggests that even though buy and sell companies have immense motivation in avoiding negative FEs, they exploit different but efficient strategies, respectively, in order to meet forecasts. Furthermore, the findings illuminated the complexities behind informative and opportunistic forecasts that falls under the efficiency versus opportunistic theories in literature.     

Aesthetic surgery economics: lessons from corporate boardrooms to plastic surgery practices

Healthcare traditionally has been described as not conforming to the laws of economics. Consumers pay for aesthetic surgery directly, thus freeing it from the usual confounding factors and making it more likely to comply with the market forces explained by economics. Recent studies have demonstrated the ability of classic economics to analyze, predict, and optimize the financial environment of aesthetic surgery. This article describes economic principles and how they can be applied to aesthetic surgery. Some of the basic instruments of economics include the study of supply and demand, prices, and price elasticity; capital investments; communication and cooperation; and consumer cognitive limitations. Each of these tools offers plastic surgeons the opportunity to gain improved control of their financial environment.     

Statistical Properties and Pre-Hit Dynamics of Price Limit Hits in the Chinese Stock Markets

Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders’ short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of price limit hits are not well studied partially due to the fact that main stock markets such as the US markets and most European markets do not set price limits. Here, we perform detailed analyses of the high-frequency data of all A-share common stocks traded on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2000 to 2011 to investigate the statistical properties of price limit hits and the dynamical evolution of several important financial variables before stock price hits its limits. We compare the properties of up-limit hits and down-limit hits. We also divide the whole period into three bullish periods and three bearish periods to unveil possible differences during bullish and bearish market states. To uncover the impacts of stock capitalization on price limit hits, we partition all stocks into six portfolios according to their capitalizations on different trading days. We find that the price limit trading rule has a cooling-off effect (object to the magnet effect), indicating that the rule takes effect in the Chinese stock markets. We find that price continuation is much more likely to occur than price reversal on the next trading day after a limit-hitting day, especially for down-limit hits, which has potential practical values for market practitioners.     

The Application of Cash-Flow-at-Risk to Risk Management in a Deregulated Electricity Market

The current level of deregulation in electricity markets is continuing to expand. Although each of these markets has individual operational and financial structures, one common characteristic is volatility. This volatility is significant and time-varying, and the persistence of this volatility makes the management of financial risk a priority among market participants.

This article considers two applications of an innovative spot price model to risk management in such a market. The first application is the empirical estimation of risk premia in the market considered here. The results support other approaches, which find the risk premia to be both significant and time-variant. In addition, this work considers the application of a Cash-Flow-at-Risk (CFaR) approach to measuring and comparing financial risk among various portfolio alternatives. These portfolios are considered from the perspective of the electricity producer, and the electricity purchaser. This approach is flexible and practical, allowing the comparison among portfolios and across seasons. The results of this analysis show that derivative instruments are significantly over-priced in this market, and that producers have the opportunity to earn significant profits, above those justified by the inherent risk in the market.     

Playing the Stockmarket in Tana Toraja

This paper describes the players and the play in a weekly stockmarket in Tana Toraja. South Sulawesi, where up to 600 buffalo bulls are bought and sold for exorbitant prices by any standards. These prices are partly determined by external, global economic forces. The buffaloes are all intended for sacrifice in elaborate funerals. Although contributed by individuals or families they are conceived as part of mana. the common wealth of tongkonan. the origin houses of the Toraja. Live bulls cannot be given away but are able to be lent in ceremonial exchanges at funerals. After sacrifice, their raw meat is distributed to participants in the funeral in a version of potlatch. Bulls mediate all exchange. apart from mundane commodity exchange, and are liquid assets. A mature black bull is an object of general equivalence able to be exchanged as payment for certain symbolic objects. In the past the production, distribution and circulation of buffaloes, both on the hoof and as meat, were controlled by the nobility. Buffaloes were said to be in finite supply. They derived from the Upperworld and accompanied the ancestors of the Toraja nobility to this world and were replenished through the ritual of the ways of the ancestors. Now the advent of the market has democratised buffaloes. There has been a dispersion of wealth and the power that the bulls embody. Any man—noble, commoner or former slave‐who has sufficient cash is able to buy and sell buffaloes: to have a share in the stockmarket. The marketplace has become a new field of power play, one where innovative methods are being found for increasing the supply of buffaloes by importing hundreds of inferior quality buffaloes and by a program of artificial insemination which has been instigated by the local government. In the parlance of Wall Street this is a bull market.     

Forecasting Financial Extremes: A Network Degree Measure of Super-Exponential Growth

Investors in stock market are usually greedy during bull markets and scared during bear markets. The greed or fear spreads across investors quickly. This is known as the herding effect, and often leads to a fast movement of stock prices. During such market regimes, stock prices change at a super-exponential rate and are normally followed by a trend reversal that corrects the previous overreaction. In this paper, we construct an indicator to measure the magnitude of the super-exponential growth of stock prices, by measuring the degree of the price network, generated from the price time series. Twelve major international stock indices have been investigated. Error diagram tests show that this new indicator has strong predictive power for financial extremes, both peaks and troughs. By varying the parameters used to construct the error diagram, we show the predictive power is very robust. The new indicator has a better performance than the LPPL pattern recognition indicator.