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We extend Kyle's (1985) model of insider trading to the case where liquidity provided by noise traders follows a general stochastic process. Even though the level of noise trading volatility is observable, in equilibrium, measured price impact is stochastic. If noise trading volatility is mean-reverting, then the equilibrium price follows a multivariate 'stochastic bridge' process, which displays stochastic volatility. This is because insiders choose to optimally wait to trade more aggressively when noise trading activity is higher. In equilibrium, market makers anticipate this, and adjust prices accordingly. More private information is revealed when volatility is higher. In time series, insiders trade more aggressively, when measured price impact is lower. Therefore, execution costs to uninformed traders can be higher when price impact is lower.

Distributed ledger technologies rely on consensus protocols confronting traders with random waiting times until the transfer of ownership is accomplished. This time consuming settlement process exposes arbitrageurs to price risk and imposes limits to arbitrage. We derive theoretical arbitrage boundaries under general assumptions and show that they increase with expected latency, latency uncertainty, spot volatility, and risk aversion. Using high-frequency data from the Bitcoin network, we estimate arbitrage boundaries due to settlement latency of on average 124 basis points, covering 88% of the observed cross-exchange price differences. Settlement through decentralized systems thus induces non-trivial frictions affecting market efficiency and price formation.

The relationship between uncertainty and managerial flexibility is particularly crucial in addressing capital projects. We consider a firm that can invest in a project in either a single (lumpy investment) or multiple stages (stepwise investment) under price uncertainty and has discretion over not only the time of investment but also the size of the project. We confirm that if the capacity of a project is fixed and the investment premium associated with stepwise investment is positive, then lumpy investment becomes more valuable than a stepwise investment strategy under high price uncertainty. By contrast, if a firm has discretion over capacity, then we show that the stepwise investment strategy always dominates that of lumpy investment. In addition, we show that the total amount of installed capacity under a stepwise investment strategy is always greater than that under lumpy investment. © Springer Verlag 2016. The final publication is available at https://link.springer.com/article/10.1007%2Fs00291-016-0460-0. This is the authors' accepted and refereed manuscript to the article.

We analyze a model where irrational and rational informed traders exchange a risky asset with irrational market makers. Irrational traders misperceive the mean of prior information (optimistic/pessimistic bias) and the variance of the noise in their private signal (overconfidence/ underconfidence bias). Irrational market makers misperceive both the mean and the variance of the prior information. We show that moderately underconfident traders can outperform rational ones and that irrational market makers can fare better than rational ones. Lastly, we find that extreme level of confidence implies high trading volume.

Analysing the relationships between elements of an enterprise's financial statements, especially between elements from the balance sheet and those from the profit and loss account, the rates of return adds greater utility to the consumers of financial information, offering the possibility to make comparisons over time and space as well as to make reference to internal and external rates. Considering the companies listed on Bucharest Stock Exchange among the best performing, due to the high requirements imposed by a stock market, in this paper has been analyzed the way the financial crisis affected the financial performance in Mining and Quarrying Domain.

How many and which firms issue equity and bonds in domestic and international markets, how do these firms grow relative to non-issuing firms, and how does firm performance vary along the firm size distribution (FSD)? To evaluate these questions, we construct a new dataset by matching data on firm-level capital raising activity with balance sheet data for 45,527 listed firms in 51 countries. Three main patterns emerge from the analysis. (1) Only a few large firms issue equity or bonds, and among them a small subset has raised a large proportion of the funds raised during the 1990s and 2000s. (2) Issuers grow faster than non-issuers in terms of assets, sales, and employment, that is, firms do not simply use securities markets to adjust their financial accounts. (3) The FSD of issuers evolves differently from that of non-issuers, tightening among issuers and widening among non-issuers.

Investors’ motivation on derivatives market is a profit gain under the law of “buy cheap and sell expensive” no matter the order in which the two operations succeed. Contracts for difference are a good option for short-term investment. The possibility to trade very cheap, relatively simple mechanism of trading and permanent marking to market make the CFD perfect tools for short-term speculators. The investments in CFD aren’t suitable for any investor. Depending on the risks that the investor wants to assume and the knowledge he acquired so far, the decision to invest in CFD can be taken. The permanent increase of the derivatives number has the role to enable a large number of participants to find the right product for everybody.

The project aims to create an econometric model which allows the forecasting of the evolution of Romania’s real economy, as well as the evolution of the system of Romanian financial markets. The study basis is represented by the assimilation of real economies with physics systems which are appropriate to the modeling with the aid of statistical physics and thermodynamics of open systems. Where certain data come under record, some economic and market processes can be assimilated with afferent processes to some Brownian systems.

The paper deals with the issue of stock market informational inefficiency differentiating between the main signals which indicate inefficiency manifestation within these markets. We discuss two main sources of inefficiency, price momentum and the mean reverting process, insisting on the causes of these departures. Also, we discuss the main stock market seasonal anomalies (the January effect, week end effect and the holiday effect) in the same time with those related tot the issuers’ characteristics (the size effect, value and growth stocks) keeping in touch with the main empirical results found in the case of the Bucharest Stock Exchange (BSE). In the end, the prediction capacity of different indicators to foresee future price evolution is carefully analyzed.

Taking into account the actual economic situation of the world with numerous financial crisis, the insurance companies should control their financial stability in order to avoid the insolvency or even bankruptcy state. Thus, the insurers should find the adequate methods of substantiating the premium installments, the adequate ways of attracting insurances in order to achieve the right structure of the portfolio and the desired level of financial stability within the company. The present paper proposes mathematical calculation, through which different solution may be given in order to optimize insurance portfolio, determining thus its adequate structure to a certain level of stability planned by the company. The result of elaborated studies and analysis represents an useful instrument for the insured persons, being able to choose the right type of insurance, resting on its comparisons, analysis and conclusions, and for the insurance companies, being meant to improve their subscription and investment activity, as well as the financial stability. The mathematical calculation shown within this paper may be applied in practice and improved.

The arrival of news plays an extremely important role in the stock market because it mainly drives the movement of the stock market. In this paper, therefore, we would like to investigate how the Vietnamese stock market responses to the arrival of news via applying the AR – EGARCH in Mean model. Our research result indicates that the arrival of bad news has a greater impact on the conditional volatility than the arrival of good news does. We also found that there exists a positive tradeoff between the stock market returns and conditional volatility in the Vietnamese stock market.

Review of the book titled 'Rethinking Housing Bubbles The Role of Household and Bank Balance Sheets in Modeling Economic Cycles' by Steven D. Gjerstad and Vernon L. Smith. Published by Cambridge University Press in May 2014.

We propose a new method of testing asset pricing models that relies on using quantities rather than prices or returns. We use the capital flows into and out of mutual funds to infer which risk model investors use. We derive a simple test statistic that allows us to infer, from a set of candidate models, the model that is closest to the model that investors use in making their capital allocation decisions. Using this methodology, we find that of the models most commonly used in the literature, the Capital Asset Pricing Model is the closest. The finding that investors’ revealed preferences are most aligned with the Capital Asset Pricing Model despite the fact that the model has been shown to perform poorly relative to other models in explaining cross sectional variation in expected returns, is an important puzzle for future research. We also document that a large fraction of mutual fund flows remain unexplained.

Parameter learning strongly amplifies the impact of macroeconomic shocks on marginal utility when the representative agent has a preference for early resolution of uncertainty. This occurs as rational belief updating generates subjective long-run consumption risks. We consider general equilibrium models with unknown parameters governing either long-run economic growth, rare events, or model selection. Overall, parameter learning generates long-lasting, quantitatively significant additional macroeconomic risks that help explain standard asset pricing puzzles. (JEL C52, D83, E13, E32, G12)

This paper reveals the underlying market’s preferences over the on going Euro area sovereign debt crisis. It builds on a loss function with reference to the ‘basis’, the difference between the spread over swap and Credit Default Swap (CDS) for sovereign bonds. This loss function is general and flexible as it nests both a lin-lin and quad-quad functional form. The sample covers those Euro area member states most at risk of default namely: Greece, Portugal, Ireland, Spain and Italy. Results show that market’s preferences for some Euro area countries, in particular Greece, have shifted towards pessimism post the Emergency Financing Mechanism (EFM) and troika. If anything, market’s reading of Euro area debt crisis points to the direction of serious misalignments post EFM and troika fuelled by growing pessimism and thus uncertainty. Having derived market’s preferences, we explore the impact of some specific market characteristics and fiscal rules and fiscal institutions on those preferences. Fiscal rules and institutions appear to improve market’s perception over fiscal sustainability, whilst the 3M Euribor, 3M Eurepo, outstanding debt to GDP, and iTraxx main investment grade index also shape market’s preferences.

This paper describes our construction of the Global Financial Development Database and uses the data to compare financial systems around the world. The database provides information on financial systems in 205 economies over the period from 1960 to 2010 and includes measures of (1) size of financial institutions and markets (financial depth), (2) degree to which individuals and firms can and do use financial services (access), (3) efficiency of financial intermediaries and markets in intermediating resources and facilitating financial transactions (efficiency), and (4) stability of financial institutions and markets (stability).

Using a comprehensive sample of trades by Schedule 13D filers, who possess valuable private information when they accumulate stocks of targeted companies, this paper studies whether several liquidity measures reveal the presence of informed trading. The evidence suggests that when Schedule 13D filers trade aggressively, both high-frequency and low-frequency measures of stock liquidity indicate a higher stock liquidity. Importantly, measures that have been used as direct proxies for adverse selection, such the Kyle (1985) lambda, the Easley et al. (1996) pin measure, and the Amihud (2002) illiquidity measure, suggest that the adverse selection is lower when informed trading takes place. The evidence is consistent with informed traders being more aggressive when measured stock liquidity is high.

This paper is the introduction to the forthcoming book, Recent Developments in Alternative Finance: Empirical Assessments and Economic Implications, Proceedings of Second International Symposium in Computational Economics and Finance. The conference was held in Tunis, Tunisia, March 15-17, 2012. The volume will appear as volume 22 of the Emerald Press monograph series, International Symposia in Economic Theory and Econometrics. The topic of the conference was alternative approaches to finance.

This thesis consists of four self-contained papers related to banking, credit markets and financial stability. Paper [I] presents a credit market model and finds, using an agent based modeling approach, that credit crunches have a tendency to occur; even when credit markets are almost entirely transparent in the absence of external shocks. We find evidence supporting the asset deterioration hypothesis and results that emphasize the importance of accurate firm quality estimates. In addition, we find that an increase in the debt’s time to maturity, homogenous expected default rates and a conservative lending approach, reduces the probability of a credit crunch. Thus, our results suggest some up till now partially overlooked components contributing to the financial stability of an economy. Paper [II] derives an econometric disequilibrium model for time series data. This is done by error correcting the supply of some good. The model separates between a continuously clearing market and a clearing market in the long-run such that we are able to obtain a novel test of clearing markets. We apply the model to the Swedish market for short-term business loans, and find that this market is characterized by a long-run nonmarket clearing equilibrium. Paper [III] studies the risk-return profile of centralized and decentralized banks. We address the conditions that favor a particular lending regime while acknowledging the effects on lending and returns caused by the course of the business cycle. To analyze these issues, we develop a model which incorporates two stylized facts; (i) banks in which lending decisions are decentralized tend to have a lower cost associated with screening potential borrowers and (ii) decentralized decision-making may generate inefficient outcomes because of lack of coordination. Simulations are used to compare the two banking regimes. Among the results, it is found that even though a bank group where decisions are decentralized may end up with a portfolio of loans which is (relatively) poorly diversified between regions, the ability to effectively screen potential borrowers may nevertheless give a decentralized bank a lower overall risk in the lending portfolio than when decisions are centralized. In Paper [IV], we argue that the practice used in the valuation of a portfolio of assets is important for the calculation of the Value at Risk. In particular, a seller seeking to liquidate a large portfolio may not face horizontal demand curves. We propose a partially new approach for incorporating this fact in the Value at Risk and Expected Shortfall measures and in an empirical illustration, we compare it to a competing approach. We find substantial differences.

Many leading asset pricing models predict that the term structures of expected returns and volatilities on dividend strips are strongly upward sloping. Yet the empirical evidence suggests otherwise. This discrepancy can be reconciled if these models replace their exogenously specified dividend dynamics with processes that are derived endogenously from capital structure policies that generate stationary leverage ratios. Under this policy, shareholders are being forced to divest (invest) when leverage is low (high), which shifts risk from long-horizon to short-horizon dividend strips. This framework also generates stock volatility that is higher than long-horizon dividend volatility, even with constant market prices of risk.

I present evidence that higher frequency measures of inflation expectations outperform lower frequency measures of inflation expectations in tests of accuracy, predictive power, and rationality. For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Surveys of Consumers. While these measures have been useful in developing models of forecasting inflation, the data are low frequency measures that are anachronistic in the modern era of high frequency and real-time data. I present a collection of 37 different measures of inflation expectations, including many previously unexploited monthly and real-time measures of inflation expectations. These higher frequency measures tend to outperform the standard three low frequency survey measures in tests of accuracy, predictive power, and rationality, indicating that there are benefits to using higher frequency measures of inflation expectations. Out of sample forecasts confirm the findings.

This paper explores the presence of the turn – of – the – month effect on Bucharest Stock Exchange. We employ daily values from 2002 to 2011 of the two important indices of the Romanian capital market: BET – C and RAQ – C, composed on the stock prices of some of the biggest Romanian companies and RAQ – C, which includes the stock prices of smaller firms. We find evidences of the turn – of – the – month effect only for the BET – C evolution.

In this paper we study a new factor that matters for fertility and consumption decisions: the risks associated with having and raising a child. We analyze a real options model with incomplete markets to explicitly model both children as a risky investment and the parental option to time fertility. We focus on CRRA preferences and uninsurable shocks to future parental income and to the costs of raising a child. We obtain several results that are new relative to the standard Beckerian fertility framework where children are deterministic goods: i) Independently of wealth, higher child cost volatility diminishes fertility. ii) Consumption is decreasing in higher cost volatility but the slope flattens as wealth increases. iii) Wealth alters the way in which the agent's risk tolerance impacts the fertility and consumption decisions. For low wealth levels, risk aversion speeds up fertility and lowers consumption with children serving as an utility insurance mechanism. iv) Fertility is increasing in the correlation between income and child cost shocks. v) The sign of this correlation determines if higher income volatility speeds up or delays fertility. vi) Fertility is U-shaped in the income over wealth ratio. Finally, we use regression analysis to provide empirical support for the theoretical results.

This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk (VaR) and Expected Shortfall (ES). The spectral risk measures are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of spectral risk measures and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. Running head: financial risk measures for futures positions.

There are a wide range of local Social and Solidarity Economy (SSE) initiatives in Hungary. Initiatives are aimed at rural development (LEADER), community development, ecology, employment and settlement rejuvenation. Participants are not always aware whether they are more attached to the concept of SSE than that of Local Economic Development (LED), or vice versa. No national platform encouraging the identification of shared interests and goals has been established yet. Perhaps, this is the very reason why there has been no breakthrough in government policies with a neoliberal bias. After the completion of a few non-profit employment programmes, interest in the development of local community may, going forward, bring about significant changes that can create a social and economic environment that goes well beyond tenders and facilitates self-reliance. However, only if we are familiar with the basic principles and systems of the SSE and LED can we utilise the benefits arising from local community economic development. Furthermore, in order to be able to use external help efficiently and conduct domestic and international discussions, we have to identify our position along the global spectrum.

"La mirada convencional de los no especialistas es que la alta concentración en un mercado implica necesariamente falta de competencia, por ello se demanda medidas para evitar la alta concentración. La teoría económica sugiere muchas razones para que este vínculo no exista. En este documento analizamos 7 productos bancarios en el Perú y mostramos, a través de la estimación econométrica de un modelo de demanda residual corregido por la calidad del producto que ofrece cada institución financiera, que en efecto la alta concentración no implica falta de competencia. Por el contrario, los datos sugieren que en la mayoría de los mercados la competencia aumentó."

The two decades of post reform period in India witnessed transformation of the economy in to a higher growth plane signaling the arrival of the country in the global stage. But this robust growth failed to translate the economic well being of the large number of marginalized and excluded sections due to structural rigidities. For economic growth of a nation to be sustainable, it requires all sections of the society included and participates in the growth process. One of the many alternative strategies available for Inclusive Growth is through developing an Inclusive Financial System. Financial inclusion is useful to facilitate economic transaction, manage day today resources, improve quality of life, protect against vulnerability, make productivity enhancing investments and leverage assets. But the indicators of financial use in the country are very poor and there is wide inequality among different sections of the society, between rural and urban areas and between geographical areas. In this context, the paper builds the case for developing inclusive financial system for achieving inclusive economic growth in India. The rationale for inclusive financial system, taking banking services to the vulnerable sections, role of micro finance institutions in spreading financial literacy and the role of technology in taking financial services available & affordable to the poor are discussed in the paper.

For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Survey. While these measures have been useful in developing models of forecasting inflation, the data are low frequency measures which appear anachronistic in the modern era of high frequency and real-time data. I present a collection of 37 different measures of inflation expectations, including many previously unexploited monthly and real-time measures of inflation expectations. These higher frequency measures tend to outperform the standard three low frequency survey measures in tests of accuracy, predictive power, and rationality, indicating that there are benefits to using higher frequency measures of inflation expectations. Out of sample forecasts confirm the findings.

Managing current account balances – defining the value of the necessary closing level – is perhaps the most exciting daily routine activity of corporate financial managers. The relevant discussion of this subject in Corporate Finance by Brealey and Myers, one of the most popular manuals of today’s higher education in finances, refers to research conducted over 60 years ago. This manual applies the Baumol model to current account balance management, starting from the costs of simple inventory management. An enhancement of the above is the Miller-Orr model, which restricts the volatility of the cash balances between an upper and the lower limit, and defines the value at one-third as the return point. Our globalised world is characterized by electronic banking, which has fundamentally changed the entire system of finances. Research done on figures of the 2000s led to results that were different than before. According to new findings, in modern accelerated cash management the level of current account balances is not determined by the assumed “inventory management costs” (through the development of electronic methods, they have decreased drastically, anyhow), rather the habits of cash transaction management.

We add to the concerns raised in Ljungqvist, Malloy and Marston, 2009, Rewriting History, Journal of Finance, 64, 1935-1960, about the reliability of the I/B/E/S data provided by Thomson Reuters (TR). Many of the dates reported as earnings announcement dates are not earnings announcement dates; there are inconsistencies between these dates and those reported in Worldscope, another TR database; and summaries of financial analysts’ forecasts can be misleading. Following discussions with the authors, TR has reviewed approximately 2 million records and is in the process of correcting some 50,000 of them. Further reviews are under way.

We argue that the practise of valuing the portfolio is important for the calculation of the V aR. In particular, the seller (buyer) of an asset does not face horizontal demand (supply) curves. We propose a partially new approach for incorporating this fact in the V aR and in an empirical illustration we compare it to a competing approach. We find substantial differences.

In an industry characterized by oligopolistic market structures there are generally firms that have enough market power as to influence the pricing and output decisions of all participants, forcing others to follow the strategies followed by the dominant firm(s) with very little opportunity to do otherwise. When a dominant firm is part of a larger corporation, which gives it the financial capacity to support an above‐average, long‐term investment, as a logical reaction to protect (or minimize the loss of market share), the rest of the participants in the industry are expected to also make an attempt to increase their investments, fundamentally affecting the long‐term capital structure strategy. This work’s contribution consists on presenting an empirical analysis of the capital structure decisions of the non‐dominant firms in the Self‐Service Discount Stores Industry (SSDSI) that result from the rapid expansion of Wal‐Mart in the Mexican market.

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16 sentiment surveys of distinct respondent universes and employ the technique of principal components analysis to extract the common signals from the surveys. I show that the ability of different population groups to anticipate correctly economic growth and excess stock returns is not identical, implying that not all sentiment is the same, although there exist some common components. I demonstrate that sentiment surveys have significant predictive power for both GDP growth and excess stock returns, and that the results are robust to the inclusion of information pertaining to the macroeconomic environment and momentum. Furthermore, the findings reject the conventional wisdom that the effect of sentiment is apparent exclusively in small-capitalization stocks.

This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16 sentiment surveys of distinct respondent universes and employ the technique of principal components analysis to extract the common signals from the surveys. I show that the ability of different population groups to anticipate correctly economic growth and excess stock returns is not identical, implying that not all sentiment is the same, although there exist some common components. I demonstrate that sentiment surveys have significant predictive power for both GDP growth and excess stock returns, and that the results are robust to the inclusion of information pertaining to the macroeconomic environment and momentum. Furthermore, the findings reject the conventional wisdom that the effect of sentiment is apparent exclusively in small-capitalization stocks.

The current financial crisis has made it abundantly clear that business cycle modeling can no longer abstract from financial factors. It is also clear that the current standard approach of modeling labor markets without explicit unemployment has its limitations. We extend what is becoming the standard new Keynesian model in three dimensions. First, we incorporate financial frictions in the accumulation and management of capital. Second, we model the labor market using a search and matching framework. Third, we extend the model into a small open economy setting. Finally, we estimate the model using Bayesian techniques with Swedish data. Our main results are as follows: (1) The financial shock to entrepreneurial wealth is pivotal for explaining business cycle fluctuations. It accounts for two-thirds of the variance in investment and a quarter of the variance in GDP. (2) The marginal efficiency of investment shock has very limited importance. The reason for this is that we match financial market data. (3) In contrast to the existing literature on estimated DSGE models, our model does not need any wage markup shocks or similar shocks with low autocorrelation to match the data. Furthermore, the low-frequency labor preference shock that we do allow is not important in explaining GDP. (4) The tightness of the labor market is unimportant for the cost of adjusting the workforce. In other words, there are costs of hiring but no significant costs of vacancy postings per se.

(VF)Cet article examine les implications sur les recherches en finance d’entreprise du renouvellement récent des conceptions théoriques sur le fonctionnement des marchés financiers. En distinguant les approches issues de la finance comportementale de celles portées par les conventionnalistes ou par les tenants de l’utilisation des études sociales de la finance ou de la sociologie économique, le travail présenté ici permet d’identifier un certain nombre de perspectives pour les recherches futures en finance d’entreprise.(VA)This paper analyzes the consequences on corporate finance of changes in the standard paradigm approaching financial markets in terms of the rationality of their actors. Describing the characteristics of different trends in the recent literature (behavioural finance, conventions theory and the social studies in finance), we identify some paths for future research.

The paper estimates and examines the empirical plausibility of asset pricing models that attempt to explain features of financial markets such as the size of the equity premium and the volatility of the stock market. In one model, the long-run risks (LRR) model of Bansal and Yaron, low-frequency movements, and time-varying uncertainty in aggregate consumption growth are the key channels for understanding asset prices. In another, as typified by Campbell and Cochrane, habit formation, which generates time-varying risk aversion and consequently time variation in risk premia, is the key channel. These models are fitted to data using simulation estimators. Both models are found to fit the data equally well at conventional significance levels, and they can track quite closely a new measure of realized annual volatility. Further, scrutiny using a rich array of diagnostics suggests that the LRR model is preferred. Copyright 2007, Wiley-Blackwell.

In this survey paper I summarize the literature's findings on the short-run and long-run effects of stock split announcements as well as what happens in the preceding and subsequent years around a stock split event. I also summarize how firm characteristics influence these results. Furthermore, I discuss the various theories regarding why splits occur and why stock return distributions change subsequent to split events. I specifically focus on the changes in the first and second moments of stock returns and analyze related theories such as optimal trading, optimal tick size, liquidity, and signaling. More importantly I present the pros and cons of each of these theories and discuss which of them are more plausible. I suggest that a combination of the several theories suggested in the literature can rationally explain the return distribution changes around stock splits. I conclude with suggestions for future research.

This paper proposes a new method for measuring investor 'risk appetite'. Like other indicators in the literature, it is based on a comparison of risk-neutral probabilities of future returns with the corresponding subjective probabilities. The precise nature of the comparison is novel, however, and involves comparing probabilities across the full range of potential returns. Unlike other indicators, our measure of market sentiment distinguishes risk appetite from risk aversion, and is reported in levels rather than changes. Implementation of the approach yields results that respond to crises and other major economic events in a plausible manner.

This Paper solves explicitly a simple equilibrium asset pricing model with liquidity risk – the risk arising from unpredictable changes in liquidity over time. In our liquidity-adjusted capital asset pricing model, a security’s required return depends on its expected liquidity as well as on the covariances of its own return and liquidity with market return and market liquidity. In addition, the model shows how a negative shock to a security’s liquidity, if it is persistent, results in low contemporaneous returns and high predicted future returns. The model provides a simple, unified framework for understanding the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels.

Conventional time series analysis, focusing exclusively on a time series at a given scale, lacks the ability to explain the nature of the data generating process. A process equation that successfully explains daily price changes, for example, is unable to characterize the nature of hourly price changes. On the other hand, statistical properties of monthly price changes are often not fully covered by a model based on daily price changes. In this paper, we simultaneously model regimes of volatilities at multiple time scales through wavelet-domain hidden Markov models. We establish an important stylized property of volatility across different time scales. We call this property asymmetric vertical dependence. It is asymmetric in the sense that a low volatility state (regime) at a long time horizon is most likely followed by low volatility states at shorter time horizons. On the other hand, a high volatility state at long time horizons does not necessarily imply a high volatility state at shorter time horizons. Our analysis provides evidence that volatility is a mixture of high and low volatility regimes, resulting in a distribution that is non-Gaussian. This result has important implications regarding the scaling behavior of volatility, and consequently, the calculation of risk at different time scales.

A widely held belief in financial economics suggests that stock prices always adequately reflect all available information. Price movements away from fundamentals are assumed to occur only infrequently, if at all. "False" prices are supposed to be corrected by the counter-actions of "rational" investors reestablishing equilibrium. However, empirical evidence of widespread irrationality among investors as well as theoretical insights into the properties of complex systems suggest that this view is too static. In fact, it can be shown that under certain conditions dynamic disequilibria have a considerable probability of being "locked in". The mass media play no mean role in this: By conditioning trend-following behavior and fostering coordination among large numbers of investors, the media can help bring about such destabilizing moves. Media attention can induce positive feedback by increasing the level of excess noise in the market while decreasing the number of perceived behavioral options. Meta-communication thus generated is a prime source of instability in financial markets.

Numerous empirical studies have demonstrated that asset prices react rapidly, if at all, to news published in the mass media. In many cases, the information has been discounted and prices have already moved upon primary publication through news wires, press releases or firm announcements. Any remaining information is usually quickly priced in after dissemination through the mass media. But not always: Often enough delayed price adjustments, underreactions as well as overreactions, can be observed after particular news reports have been published. This points to inadequacies in the efficient markets hypothesis as well as in Behavioral Finance theories: Delayed reactions appear too often to be explained away as "anomalies" within models of rational pricing. But they appear too eratically to be explained as "normalities" such as in newer models of systematically irrational pricing. In other words: Asset prices frequently do not react to news published in the media. Sometimes they do. The evidence leads to the following conclusion: That markets can be efficient and inefficient at the same time.

We consider the optimal asset allocation choice of an investor who can invest in cash (a money market bank account), nominal bonds, and stocks (the stock index). The investor faces an incomplete market setting and is not able to perfectly hedge long run real interest rate risk using the available securities. The optimal invest- ment strategy is consistent with the following features of popular investment advice which have been pointed out as puzzles: (i) a decreasing fraction of stocks in the portfolio as time passes towards the investment horizon, and (ii) a higher bond to stock ratio for more conservative (less risk tolerant) investors (Canner, Mankiw and Weil, 1997). The model for asset price dynamics is calibrated to US market data and, furthermore, risk aversion parameters and time horizons are calibrated so as to obtain a match between the optimal asset allocations and observed investment recommendations for \aggressive," \moderate," and \conservative" investor groups with di®erent investment horizons.

A seller wishes to sell an object to one of multiple bidders. The valuations of the bidders are privately known. We consider the joint design problem in which the seller can decide the accuracy by which bidders learn their valuation and to whom to sell at what price. We establish that optimal information structures in an optimal auction exhibit a number of properties: (i) information structures can be represented by monotone partitions, (ii) the cardinality of each partition is finite, (iii) the partitions are asymmetric across agents. These properties imply that the optimal selling strategy of a seller can be implemented by a sequence of exclusive take-it or leave-it offers.

We construct a new method of decomposing the variance of national incomes into components in such a way as to indicate the most important 'residual' risk-sharing opportunities among peoples of the world. The risk-sharing opportunities we study are nonsystematic risk-sharing opportunities. These are the risk-sharing opportunities that remain if systematic risk were already shared, see Athanasoulis and Shiller (2000). The new method developed here uses a simpler approach to deriving the components based on pure variance reduction. With the new method, the income component securities are derived in terms of eigenvectors of a transformed variance matrix of world incomes, but with this method the transformation is to use the residuals when incomes are regressed on world income instead of deviations of incomes from average world income as in Athanasoulis and Shiller (2001). The method is applied using Summers-Heston (1991)data on national incomes for large countries 1950-1990, using two different methods of estimating variances.

The market portfolio is in one sense the least important portfolio to provide to investors. In an J-agent one-period stochastic endowment economy, where preferences are quadratic, a social-welfare-minded contract designer would never create a contract that would allow trading the market portfolio. Even the complete set of contracts, all J 1 of them, which achieve a first best solution, never span the market portfolio. These conclusions rely on the assumption that the contract designer has perfect information about agents' utilities. We also show that as the contract designer's information about agents' utilities becomes more imperfect, the optimal contracts approach contracts that weight individual endowments in proportion to elements of eigenvectors of the variance matrix of endowments. Then, if there is a strong enough market component to endowments, a portfolio approximating the market portfolio may be the most important portfolio.