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Optimal investment decisions by institutional investors require accurate predictions with respect to the development of stock markets. Motivated by previous research that revealed the unsatisfactory performance of existing stock market prediction models, this study proposes a novel prediction approach. Our proposed system combines Artificial Intelligence (AI) with data from Virtual Investment Communities (VICs) and leverages VICs’ ability to support the process of predicting stock markets. An empirical study with two different models using real data shows the potential of the AI-based system with VICs information as an instrument for stock market predictions. VICs can be a valuable addition but our results indicate that this type of data is only helpful in certain market phases.
We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of the United States, Donald J. Trump. We analyze around 1,400 of his tweets related to the US economy and classify them by topic and textual sentiment using machine learning algorithms. We investigate whether the tweets contain relevant information for financial markets, i.e. whether they affect market returns, volatility, and trading volumes. Using high-frequency data, we find that Trump’s tweets are most often a reaction to pre-existing market trends and therefore do not provide material new information that would influence prices or trading. We show that past market information can help predict Trump’s decision to tweet about the economy.
We develop a two-sector incomplete markets integrated assessment model to analyze the effectiveness of green quantitative easing (QE) in complementing fiscal policies for climate change mitigation. We model green QE through an outstanding stock of private assets held by a monetary authority and its portfolio allocation between a clean and a dirty sector of production. Green QE leads to a partial crowding out of private capital in the green sector and to a modest reduction of the global temperature by 0.04 degrees of Celsius until 2100. A moderate global carbon tax of 50 USD per tonne of carbon is 4 times more effective.
The ECB’s Outright Monetary Transactions (OMT) program, launched in summer 2012, indirectly recapitalized periphery country banks through its positive impact on the value of sovereign bonds. However, the regained stability of the European banking sector has not fully transferred into economic growth. We show that zombie lending behavior of banks that still remained undercapitalized after the OMT announcement is an important reason for this development. As a result, there was no positive impact on real economic activity like employment or investment. Instead, firms mainly used the newly acquired funds to build up cash reserves. Finally, we document that creditworthy firms in industries with a high prevalence of zombie firms suffered significantly from the credit misallocation, which slowed down the economic recovery.
We investigate the transmission of central bank liquidity to bank deposits and loan spreads in Europe over the January 2006 to June 2010 period. We find evidence consistent with an impaired transmission channel due to bank risk. Central bank liquidity does not translate into lower loan spreads for high-risk banks, even as it lowers deposit rates for both high-risk and low-risk banks. This adversely affects the balance sheets of high-risk bank borrowers, leading to lower payouts, lower capital expenditures, and lower employment. Overall, our results suggest that banks’ capital constraints at the time of an easing of monetary policy pose a challenge to the effectiveness of the bank lending channel and the effectiveness of the central bank as a lender of last resort.
The European Central Bank (ECB) has finalized its comprehensive assessment of the solvency of the largest banks in the euro area and on October 26 disclosed the results of this assessment. In the present paper, Acharya and Steffen compare the outcomes of the ECB's assessment to their own benchmark stress tests conducted for 39 publically listed financial institutions that are also included in the ECB's regulatory review. The authors identify a negative correlation between their benchmark estimates for capital shortfalls and the regulatory capital shortfall, but a positive correlation between their benchmark estimates for losses under stress both in the banking book and in the trading book. They conclude that the regulatory stress test outcomes are potentially heavily affected by discretion of national regulators in measuring what is capital, and especially the use of risk-weighted assets in calculating the prudential capital requirement.
We analytically show that a common across rich/poor individuals Stone-Geary utility function with subsistence consumption in the context of a simple two-asset portfolio-choice model is capable of qualitatively and quantitatively explaining: (i) the higher saving rates of the rich, (ii) the higher fraction of personal wealth held in risky assets by the rich, and (iii) the higher volatility of consumption of the wealthier. On the contrary, time-variant “keeping-up-with-the-Joneses” weighted average consumption which plays the role of moving benchmark subsistence consumption gives the same portfolio composition and saving rates across the rich and the poor, failing to reconcile the model with what micro data say. JEL Classification: G11, D91, E21, D81, D14, D11
We analytically show that a common across rich/poor individuals Stone-Geary utility function with subsistence consumption in the context of a simple two-asset portfolio-choice model is capable of qualitatively explaining: (i) the higher saving rates of the rich, (ii) the higher fraction of personal wealth held in stocks by the rich, and (iii) the higher volatility of consumption of the wealthier. On the contrary, time-variant "keeping-up with the Joneses" weighted average consumption playing the role of moving benchmark subsistence consumption gives the same portfolio composition and saving rates across the rich and the poor, failing to reconcile the model with what micro data say.
We develop a dynamic recursive model where political and economic decisions interact, to study how excessive debt-GDP ratios affect political sustainability of prudent fiscal policies. Rent seeking groups make political decisions – to cooperate (or not) – on the allocation of fiscal budgets (including rents) and issuance of sovereign debt. A classic commons problem triggers collective fiscal impatience and excessive debt issuing, leading to a vicious circle of high borrowing costs and sovereign default. We analytically characterize debt-GDP thresholds that foster cooperation among rent seeking groups and avoid default. Our analysis and application helps in understanding the politico-economic sustainability of sovereign rescues, emphasizing the need for fiscal targets and possible debt haircuts. We provide a calibrated example that quantifies the threshold debt-GDP ratio at 137%, remarkably close to the target set for private sector involvement in the case of Greece.
Learning and equilibrium selection in a monetary overlapping generations model with sticky prices
(2003)
We study adaptive learning in a monetary overlapping generations model with sticky prices and monopolistic competition for the case where learning agents observe current endogenous variables. Observability of current variables is essential for informational consistency of the learning setup with the model set up but generates multiple temporary equilibria when prices are flexible and prevents a straightforward construction of the learning dynamics. Sticky prices overcome this problem by avoiding simultaneity between prices and price expectations. Adaptive learning then robustly selects the determinate (monetary) steady state independent from the degree of imperfect competition. The indeterminate (non-monetary) steady state and non-stationary equilibria are never stable. Stability in a deterministic version of the model may differ because perfect foresight equilibria can be the limit of restricted perceptions equilibria of the stochastic economy with vanishing noise and thereby inherit different stability properties. This discontinuity at the zero variance of shocks suggests to analyze learning in stochastic models.
This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least squares learning to estimate two competing models of which one is consistent with rational expectations once learning is complete. When past performance governs the choice of forecast model, agents may prefer to use the inconsistent forecast model, which generates an equilibrium where forecasts are inefficient. While average output and inflation result the same as under rational expectations, higher moments differ substantially: output and inflation show persistence, inflation responds sluggishly to nominal disturbances, and the dynamic correlations of output and inflation match U.S. data surprisingly well.
This paper compares Bayesian decision theory with robust decision theory where the decision maker optimizes with respect to the worst state realization. For a class of robust decision problems there exists a sequence of Bayesian decision problems whose solution converges towards the robust solution. It is shown that the limiting Bayesian problem displays infinite risk aversion and that decisions are insensitive (robust) to the precise assignment of prior probabilities. This holds independent from whether the preference for robustness is global or restricted to local perturbations around some reference model.
We study optimal nominal demand policy in an economy with monopolistic competition and flexible prices when firms have imperfect common knowledge about the shocks hitting the economy. Parametrizing firms´ information imperfections by a (Shannon) capacity parameter that constrains the amount of information flowing to each firm, we study how policy that minimizes a quadratic objective in output and prices depends on this parameter. When price setting decisions of firms are strategic complements, for a large range of capacity values optimal policy nominally accommodates mark-up shocks in the short-run. This finding is robust to the policy maker observing shocks imperfectly or being uncertain about firms´ capacity parameter. With persistent mark-up shocks accommodation may increase in the medium term, but decreases in the long-run thereby generating a hump-shaped price response and a slow reduction in output. Instead, when prices are strategic substitutes, policy tends to react restrictively to mark-up shocks. However, rational expectations equilibria may then not exist with small amounts of imperfect common knowledge.
Ignoring the existence of the zero lower bound on nominal interest rates one considerably understates the value of monetary commitment in New Keynesian models. A stochastic forward-looking model with lower bound, calibrated to the U.S. economy, suggests that low values for the natural rate of interest lead to sizeable output losses and deflation under discretionary monetary policy. The fall in output and deflation are much larger than in the case with policy commitment and do not show up at all if the model abstracts from the existence of the lower bound. The welfare losses of discretionary policy increase even further when inflation is partly determined by lagged inflation in the Phillips curve. These results emerge because private sector expectations and the discretionary policy response to these expectations reinforce each other and cause the lower bound to be reached much earlier than under commitment. JEL Klassifikation: E31, E52
We determine optimal monetary policy under commitment in a forwardlooking New Keynesian model when nominal interest rates are bounded below by zero. The lower bound represents an occasionally binding constraint that causes the model and optimal policy to be nonlinear. A calibration to the U.S. economy suggests that policy should reduce nominal interest rates more aggressively than suggested by a model without lower bound. Rational agents anticipate the possibility of reaching the lower bound in the future and this amplifies the effects of adverse shocks well before the bound is reached. While the empirical magnitude of U.S. mark-up shocks seems too small to entail zero nominal interest rates, shocks affecting the natural real interest rate plausibly lead to a binding lower bound. Under optimal policy, however, this occurs quite infrequently and does not require targeting a positive average rate of inflation. Interestingly, the presence of binding real rate shocks alters the policy response to (non-binding) mark-up shocks. JEL Klassifikation: C63, E31, E52 .
We determine optimal monetary policy under commitment in a forwardlooking New Keynesian model when nominal interest rates are bounded below by zero. The lower bound represents an occasionally binding constraint that causes the model and optimal policy to be nonlinear. A calibration to the U.S. economy suggests that policy should reduce nominal interest rates more aggressively than suggested by a model without lower bound. Rational agents anticipate the possibility of reaching the lower bound in the future and this amplifies the effects of adverse shocks well before the bound is reached. While the empirical magnitude of U.S. mark-up shocks seems too small to entail zero nominal interest rates, shocks affecting the natural real interest rate plausibly lead to a binding lower bound. Under optimal policy, however, this occurs quite infrequently and does not imply positive average inflation rates in equilibrium. Interestingly, the presence of binding real rate shocks alters the policy response to (non-binding) mark-up shocks.
Zur Reform der Einlagensicherung: Elemente einer anreizkompatiblen Europäischen Rückversicherung
(2020)
Bankeinlagen bis 100.000 Euro sind de jure überall im Euroraum gleichermaßen vor Verlusten geschützt. De facto hängt der Wert dieser gesetzlichen Haftungszusage unter anderem von der Ausstattung des nationalen Sicherungsfonds und der relativen Größe des Bankensektors in einer Volkswirtschaft ab. Um die Homogenität des Einlagenschutzes zu gewährleisten und die Bankenunion zu vollenden, bedarf es einer einheitlichen europäischen Einlagensicherung. Die bestehende implizite Risikoteilung im Euroraum ist ordnungspolitisch nicht wünschenswert. Ferner kann eine explizite und glaubwürdige Zweitsicherung Fehlanreize zur Übernahme exzessiver Risiken verhindern, bevor es zum Schadensfall kommt. Daher plädiert dieser Beitrag für ein zweistufiges, streng subsidiär organisiertes Rückversicherungsmodell: Nationale Erstversicherungen würden einen festgeschriebenen Teil, die europäische Rückversicherung nachrangig den Rest der Deckungssumme besichern. Die Rückversicherung gewährt diese Liquiditätshilfen in Form von Kassenkrediten. Weil die Haftung auf nationaler Ebene verbleibt, werden Risiken geteilt aber nicht vergemeinschaftet. Marktgerechte Prämien müssen nicht nur das individuelle Risikogewicht einer Bank sondern auch länderspezifische Risikofaktoren berücksichtigen. Zuletzt braucht der Rückversicherer umfangreiche Aufsichtsrechte, um die Zahlungsfähigkeit der Erstversicherer mit Hinblick auf die nationalen Haftungspflichten jederzeit sicherzustellen.
Earlier studies of the seigniorage inflation model have found that the high-inflation steady state is not stable under adaptive learning. We reconsider this issue and analyze the full set of solutions for the linearized model. Our main focus is on stationary hyperinflationary paths near the high-inflation steady state. The hyperinflationary paths are stable under learning if agents can utilize contemporaneous data. However, in an economy populated by a mixture of agents, some of whom only have access to lagged data, stable inflationary paths emerge only if the proportion of agents with access to contemporaneous data is sufficiently high. JEL Klassifikation: C62, D83, D84, E31
Motivated by the observation that survey expectations of stock returns are inconsistent with rational return expectations under real-world probabilities, we investigate whether alternative expectations hypotheses entertained in the asset pricing literature are consistent with the survey evidence. We empirically test (1) the notion that survey forecasts constitute rational but risk-neutral forecasts of future returns, and (2) the notion that survey fore- casts are ambiguity averse/robust forecasts of future returns. We find that these alternative hypotheses are also strongly rejected by the data, albeit for different reasons. Hypothesis (1) is rejected because survey return forecasts are not in line with risk-free interest rates and because survey expected excess returns are predictable. Hypothesis (2) is rejected because agents are not al- ways pessimistic about future returns, instead often display overly optimistic return expectations. We speculate as to what kind of expectations theories might be consistent with the available survey evidence.
Optimal trend inflation
(2017)
We present a sticky-price model incorporating heterogeneous Firms and systematic firm-level productivity trends. Aggregating the model in closed form, we show that it delivers radically different predictions for the optimal inflation rate than canonical sticky price models featuring homogenous Firms:
(1) the optimal steady-state inflation rate generically differs from zero and,
(2) inflation optimally responds to productivity disturbances.
Using micro data from the US Census Bureau to estimate the inflation-relevant productivity trends at the firm level, we find that the optimal US inflation rate is positive. It was slightly above 2 percent in the year 1986, but continuously declined thereafter, reaching about 1 percent in the year 2013.
We analytically characterize optimal monetary policy for an augmented New Keynesian model with a housing sector. In a setting where the private sector has rational expectations about future housing prices and inflation, optimal monetary policy can be characterized without making reference to housing price developments: commitment to a 'target criterion' that refers to inflation and the output gap only is optimal, as in the standard model without a housing sector. When the policymaker is concerned with potential departures of private sector expectations from rational ones and seeks to choose a policy that is robust against such possible departures, then the optimal target criterion must also depend on housing prices. In the empirically realistic case where housing is subsidized and where monopoly power causes output to fall short of its optimal level, the robustly optimal target criterion requires the central bank to 'lean against' housing prices: following unexpected housing price increases, policy should adopt a stance that is projected to undershoot its normal targets for inflation and the output gap, and similarly aim to overshoot those targets in the case of unexpected declines in housing prices. The robustly optimal target criterion does not require that policy distinguish between 'fundamental' and 'non-fundamental' movements in housing prices.
Vorstandsvergütungen
(2002)
In the secondary art market, artists play no active role. This allows us to isolate cultural influences on the demand for female artists’ work from supply-side factors. Using 1.5 million auction transactions in 45 countries, we document a 47.6% gender discount in auction prices for paintings. The discount is higher in countries with greater gender inequality. In experiments, participants are unable to guess the gender of an artist simply by looking at a painting and they vary in their preferences for paintings associated with female artists. Women's art appears to sell for less because it is made by women.
In this paper, we develop a state-dependent sensitivity value-at-risk (SDSVaR) approach that enables us to quantify the direction, size, and duration of risk spillovers among financial institutions as a function of the state of financial markets (tranquil, normal, and volatile). Within a system of quantile regressions for four sets of major financial institutions (commercial banks, investment banks, hedge funds, and insurance companies) we show that while small during normal times, equivalent shocks lead to considerable spillover effects in volatile market periods. Commercial banks and, especially, hedge funds appear to play a major role in the transmission of shocks to other financial institutions. Using daily data, we can trace out the spillover effects over time in a set of impulse response functions and find that they reach their peak after 10 to 15 days.
Credit boom detection methodologies (such as threshold method) lack robustness as they are based on univariate detrending analysis and resort to ratios of credit to real activity. I propose a quantitative indicator to detect atypical behavior of credit from a multivariate system - a monetary VAR. This methodology explicitly accounts for endogenous interactions between credit, asset prices and real activity and detects atypical credit expansions and contractions in the Euro Area, Japan and the U.S. robustly and timely. The analysis also proves useful in real time.
This paper investigates the risk channel of monetary policy on the asset side of banks’ balance sheets. We use a factoraugmented vector autoregression (FAVAR) model to show that aggregate lending standards of U.S. banks, such as their collateral requirements for firms, are significantly loosened in response to an unexpected decrease in the Federal Funds rate. Based on this evidence, we reformulate the costly state verification (CSV) contract to allow for an active financial intermediary, embed it in a New Keynesian dynamic stochastic general equilibrium (DSGE) model, and show that – consistent with our empirical findings – an expansionary monetary policy shock implies a temporary increase in bank lending relative to borrower collateral. In the model, this is accompanied by a higher default rate of borrowers.
We find that on average consumers chose the contract that ex post minimized their net costs. A substantial fraction of consumers (about 40%) still chose the ex post sub-optimal contract, with some incurring hundreds of dollars of avoidable interest costs. Nonetheless, the probability of choosing the sub-optimal contract declines with the dollar magnitude of the potential error, and consumers with larger errors were more likely to subsequently switch to the optimal contract. Thus most of the errors appear not to have been very costly, with the exception that a small minority of consumers persists in holding substantially sub-optimal contracts without switching. Klassifikation: G11, G21, E21, E51
The reaction of consumer spending and debt to tax rebates – evidence from consumer credit data
(2008)
We use a new panel dataset of credit card accounts to analyze how consumer responded to the 2001 Federal income tax rebates. We estimate the monthly response of credit card payments, spending, and debt, exploiting the unique, randomized timing of the rebate disbursement. We find that, on average, consumers initially saved some of the rebate, by increasing their credit card payments and thereby paying down debt. But soon afterwards their spending increased, counter to the canonical Permanent-Income model. Spending rose most for consumers who were initially most likely to be liquidity constrained, whereas debt declined most (so saving rose most) for unconstrained consumers. More generally, the results suggest that there can be important dynamics in consumers’ response to “lumpy” increases in income like tax rebates, working in part through balance sheet (liquidity) mechanisms.
Even as online advertising continues to grow, a central question remains: Who to target? Yet, advertisers know little about how to select from the hundreds of audience segments for targeting (and combinations thereof) for a profitable online advertising campaign. Utilizing insights from a field experiment on Facebook (Study 1), we develop a model that helps advertisers solve the cold-start problem of selecting audience segments for targeting. Our model enables advertisers to calculate the break-even performance of an audience segment to make a targeted ad campaign at least as profitable as an untargeted one. Advertisers can use this novel model to decide whether to test specific audience segments in their campaigns (e.g., in randomized controlled trials). We apply our model to data from the Spotify ad platform to study the profitability of different audience segments (Study 2). Approximately half of those audience segments require the click-through rate to double compared to an untargeted campaign, which is unrealistically high for most ad campaigns. Our model also shows that narrow segments require a lift that is likely not attainable, specifically when the data quality of these segments is poor. We confirm this theoretical finding in an empirical study (Study 3): A decrease in data quality due to Apple’s introduction of the App Tracking Transparency (ATT) framework more negatively affects the click-through rate of narrow (versus broad) audience segments.
DESPITE AMPLE EVIDENCE THAT CUSTOMERS EXHIBIT HIGHER DISCOUNT RATES THAN FIRMS, IT IS NOT CLEAR HOW DIFFERENCES IN DISCOUNT RATES AFFECT OPTIMAL PRICES, PROFITS, AND WELFARE OF COMPLEMENTARY PRODUCTS (WHICH COULD BE GOODS OR SERVICES). WE SHOW FOR COMPLEMENTARY PROUCTS THAT HIGHER DISCOUNT RATES OF CUSTOMERS DO NOT INCREASE PROFIT OR CONSUMER SURPLUS. FIRMS, INCLUDING BANKS, WOULD BE ADVISED TO SEEK TO REDUCE EXCESSIVE DISCOUNT RATES AMONG CONSUMERS.
Modeling short-term interest rates as following regime-switching processes has become increasingly popular. Theoretically, regime-switching models are able to capture rational expectations of infrequently occurring discrete events. Technically, they allow for potential time-varying stationarity. After discussing both aspects with reference to the recent literature, this paper provides estimations of various univariate regime-switching specifications for the German three-month money market rate and bivariate specifications additionally including the term spread. However, the main contribution is a multi-step out-of-sample forecasting competition. It turns out that forecasts are improved substantially when allowing for state-dependence. Particularly, the informational content of the term spread for future short rate changes can be exploited optimally within a multivariate regime-switching framework.
This study uses Markov-switching models to evaluate the informational content of the term structure as a predictor of recessions in eight OECD countries. The empirical results suggest that for all countries the term spread is sensibly modelled as a two-state regime-switching process. Moreover, our simple univariate model turns out to be a filter that transforms accurately term spread changes into turning point predictions. The term structure is confirmed to be a reliable recession indicator. However, the results of probit estimations show that the markov-switching filter does not significantly improve the forecasting ability of the spread.
In this study a regime switching approach is applied to estimate the chartist and fundamentalist (c&f) exchange rate model originally proposed by Frankel and Froot (1986). The c&f model is tested against alternative regime switching specifications applying likelihood ratio tests. Nested atheoretical models like the popular segmented trends model suggested by Engel and Hamilton (1990) are rejected in favour of the multi agent model. Moreover, the c&f regime switching model seems to describe the data much better than a competing regime switching GARCH(1,1) model. Finally, our findings turned out to be relatively robust when estimating the model in subsamples. The empirical results suggest that the model is able to explain daily DM/Dollar forward exchange rate dynamics from 1982 to 1998.
A common prediction of macroeconomic models of credit market frictions is that the tightness of financial constraints is countercyclical. As a result, theory implies a negative collateralizability premium; that is, capital that can be used as collateral to relax financial constraints provides insurance against aggregate shocks and commands a lower risk compensation compared with non-collateralizable assets. We show that a longshort portfolio constructed using a novel measure of asset collateralizability generates an average excess return of around 8% per year. We develop a general equilibrium model with heterogeneous firms and financial constraints to quantitatively account for the collateralizability premium.
Most insurers in the European Union determine their regulatory capital requirements based on the standard formula of Solvency II. However, there is evidence that the standard formula inaccurately reflects insurers’ risk situation and may provide misleading steering incentives. In the second pillar, Solvency II requires insurers to perform a so-called “Own Risk and Solvency Assessment” (ORSA). In their ORSA, insurers must establish their own risk measurement approaches, including those based on scenarios, in order to derive suitable risk assessments and address shortcomings of the standard formula. The idea of this paper is to identify scenarios in such a way that the standard formula in connection with the ORSA provides a reliable basis for risk management decisions. Using an innovative method for scenario identification, our approach allows for a simple but relatively precise assessment of marginal and even non-marginal portfolio changes. We numerically evaluate the proposed approach in the context of market risk employing an internal model from the academic literature and the Solvency Capital Requirement (SCR) calculation under Solvency II.
Gradient capital allocation, also known as Euler allocation, is a technique used to redistribute diversified capital requirements among different segments of a portfolio. The method is commonly employed to identify dominant risks, assessing the risk-adjusted profitability of segments, and installing limit systems. However, capital allocation can be misleading in all these applications because it only accounts for the current portfolio composition and ignores how diversification effects may change with a portfolio restructuring. This paper proposes enhancing the gradient capital allocation by adding “orthogonal convexity scenarios” (OCS). OCS identify risk concentrations that potentially drive portfolio risk and become relevant after restructuring. OCS have strong ties with principal component analysis (PCA), but they are a more general concept and compatible with common empirical patterns of risk drivers being fat-tailed and increasingly dependent in market downturns. We illustrate possible applications of OCS in terms of risk communication and risk limits.
We show that the presence of high frequency trading (HFT) has significantly mitigated the frequency and severity of end-of-day price dislocation, counter to recent concerns expressed in the media. The effect of HFT is more pronounced on days when end of day price dislocation is more likely to be the result of market manipulation on days of option expiry dates and end of month. Moreover, the effect of HFT is more pronounced than the role of trading rules, surveillance, enforcement and legal conditions in curtailing the frequency and severity of end-of-day price dislocation. We show our findings are robust to different proxies of the start of HFT by trade size, cancellation of orders, and co-location.
We examine the impact of stock exchange trading rules and surveillance on the frequency and severity of suspected insider trading cases in 22 stock exchanges around the world over the period January 2003 through June 2011. Using new indices for market manipulation, insider trading, and broker-agency conflict based on the specific provisions of the trading rules of each stock exchange, along with surveillance to detect non-compliance with such rules, we show that more detailed exchange trading rules and surveillance over time and across markets significantly reduce the number of cases, but increase the profits per case.
In this paper we assess the implications of sunk costs and product differentiation on the pricing decisions of the multinational firms. For this purpose we use a modified version of Salop's spatial competition. The model yields clear-cut predictions regarding the effects of exchange rate shocks on the market structure and on pass-through. The main results are following: shocks within the band of inaction do not affect market structure. The upper bound of this range rises as the industry ratio of sunk- to fixed costs increases. As fixed costs and product heterogeneity jointly increase, the lower bound drops. Outside of the range, depreciations cause one or several of those foreign brands closest to the home brand to leave. This decreases the overall responsiveness of prices to exchange rate shocks. Large appreciations induce entry and increase the elasticity of prices. This asymmetry implies larger positive than negative PPP deviations. When accounting for price changes in foreign markets, strategic pricing behaviour is no longer sufficient to generate real exchange rate variability. Incomplete pass-through obtains if and only if the domestic firms have a smaller market share abroad. With large nominal exchange rate shocks a hysteresis result obtains if and only if sunk costs are non-zero. Klassifikation: C33, E31
Under a conventional policy rule, a central bank adjusts its policy rate linearly according to the gap between inflation and its target, and the gap between output and its potential. Under "the opportunistic approach to disinflation" a central bank controls inflation aggressively when inflation is far from its target, but concentrates more on output stabilization when inflation is close to its target, allowing supply shocks and unforeseen fluctuations in aggregate demand to move inflation within a certain band. We use stochastic simulations of a small-scale rational expectations model to contrast the behavior of output and inflation under opportunistic and linear rules. Klassifikation: E31, E52, E58, E61. July, 2005.
Recent empirical research found that the strong short-term relationship between monetary aggregates and US real output and inflation, as outlined in the classical study by M. Friedman and Schwartz, mostly disappeared since the early 1980s. In the light of the B. Friedman and Kuttner (1992) information value approach, we reevaluate the vanishing relationship between US monetary aggregates and these macroeconomic fundamentals by taking into account the international currency feature of the US dollar. In practice, by using official US data for foreign flows constructed by Porter and Judson (1996) we find that domestic money (currency component of M1 corrected for the foreign holdings of dollars) contains valuable information about future movements of US real output and inflation. Statistical evidence here provided thus suggests that the Friedman and Schwartz's stylized facts can be reestablished once the focus of analysis is back on the domestic monetary aggregates. This Version: August, 2001. Klassifikation: E3, E4, E5
Research on interbank networks and systemic importance is starting to recognise that the web of exposures linking banks balance sheets is more complex than the single-layer-of-exposure paradigm. We use data on exposures between large European banks broken down by both maturity and instrument type to characterise the main features of the multiplex structure of the network of large European banks. This multiplex network presents positive correlated multiplexity and a high similarity between layers, stemming both from standard similarity analyses as well as a core-periphery analyses of the different layers. We propose measures of systemic importance that fit the case in which banks are connected through an arbitrary number of layers (be it by instrument, maturity or a combination of both). Such measures allow for a decomposition of the global systemic importance index for any bank into the contributions of each of the sub-networks, providing a useful tool for banking regulators and supervisors. We use the dataset of exposures between large European banks to illustrate the proposed measures.
We uncover a new channel for spillovers of funding dry-ups. The 2016 US money market fund (MMF) reform exogenously reduced unsecured MMF funding for some banks. We use novel data to trace those banks to a platform for corporate deposit funding. We show that intensified competition for corporate deposits spilled the funding squeeze over to other banks with no MMF exposure. These banks paid more for deposits, and their pool of funding providers deteriorated. Moreover, their lending volumes and margins declined, and their stocks underperformed. Our results suggest that banks' competitiveness in funding markets affect their competitiveness in lending markets.
We present a network model of the interbank market in which optimizing risk averse banks lend to each other and invest in non-liquid assets. Market clearing takes place through a tâtonnement process which yields the equilibrium price, while traded quantities are determined by means of a matching algorithm. We compare three alternative matching algorithms: maximum entropy, closest matching and random matching. Contagion occurs through liquidity hoarding, interbank interlinkages and fire sale externalities. The resulting network configurations exhibits a core-periphery structure, dis-assortative behavior and low clustering coefficient. We measure systemic importance by means of network centrality and input-output metrics and the contribution of systemic risk by means of Shapley values. Within this framework we analyze the effects of prudential policies on the stability/efficiency trade-off. Liquidity requirements unequivocally decrease systemic risk but at the cost of lower efficiency (measured by aggregate investment in non-liquid assets); equity requirements tend to reduce risk (hence increase stability) without reducing significantly overall investment.
In many cases, the dire situation of public finances calls into question the very soundness of sovereigns and prompts corrective actions with far-reaching consequences. In this context, European authorities responded with several measures on different fronts, for instance by passing the "Fiscal Compact", which entered into force on January 1, 2013. Of critical importance in this framework is the assessment of a country’s situation by way of statistical measures, in order to take corrective actions when called for according to the letter of the law. If these statistics are not correct, there is a risk of imposing draconian measures on countries that do not really need it.
The implications of delegating fiscal decision making power to sub-national governments has become an area of significant interest over the past two decades, in the expectation that these reforms will lead to better and more efficient provision of public goods and services. The move towards decentralization has, however, not been homogeneously implemented on the revenue and expenditure side: decentralization has materialized more substantially on the latter than on the former, creating "vertical fiscal imbalances". These imbalances measure the extent to which sub-national governments’ expenditures are financed through their own revenues. This mismatch between own revenues and expenditures may have negative consequences for public finances performance, for example by softening the budget constraint of sub-national governments. Using a large sample of countries covering a long time period from the IMF’s Government Finance Statistics Yearbook, this paper is the first to examine the effects of vertical fiscal imbalances on fiscal performance through the accumulation of government debt. Our findings suggest that vertical fiscal imbalances are indeed relevant in explaining government debt accumulation, and call for a degree of caution when promoting fiscal decentralization.