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We consider an economy where individuals privately choose effort and trade competitively priced securities that pay off with effort-determined probability. We show that if insurance against a negative shock is sufficiently incomplete, then standard functional form restrictions ensure that individual objective functions are optimized by an effort and insurance combination that is unique and satisfies first- and second-order conditions. Modeling insurance incompleteness in terms of costly production of private insurance services, we characterize the constrained inefficiency arising in general equilibrium from competitive pricing of nonexclusive financial contracts.
We propose a new classification of consumption goods into nondurable goods, durable goods and a new class which we call “memorable” goods. A good is memorable if a consumer can draw current utility from its past consumption experience through memory. We construct a novel consumption-savings model in which a consumer has a well-defined preference ordering over both nondurable goods and memorable goods. Memorable goods consumption differs from nondurable goods consumption in that current memorable goods consumption may also impact future utility through the accumulation process of the stock of memory. In our model, households optimally choose a lumpy profile of memorable goods consumption even in a frictionless world. Using Consumer Expenditure Survey data, we then document levels and volatilities of different groups of consumption goods expenditures, as well as their expenditure patterns, and show that the expenditure patterns on memorable goods indeed differ significantly from those on nondurable and durable goods. Finally, we empirically evaluate our model’s predictions with respect to the welfare cost of consumption fluctuations and conduct an excess-sensitivity test of the consumption response to predictable income changes. We find that (i) the welfare cost of household-level consumption fluctuations may be overstated by 1.7 percentage points (11.9% points as opposed to 13.6% points of permanent consumption) if memorable goods are not appropriately accounted for; (ii) the finding of excess sensitivity of consumption documented in important papers of the literature might be entirely due to the presence of memorable goods.
There is mounting evidence that retail investors make predictable, costly investment mistakes, including underinvestment, naïve diversification, and payment of excessive fund fees. Over the past thirty-five years, however, participant-directed 401(k) plans have largely replaced professionally managed pension plans, requiring unsophisticated retail investors to navigate the financial markets themselves. Policy-makers have struggled with regulatory interventions designed to improve the quality of investment decisions without a clear understanding of the reasons for investor mistakes. Absent such an understanding, it is difficult to design effective regulatory responses. This article offers a first step in understanding the investor decision-making process. We use an internet-based experiment to disentangle possible explanations for inefficient investment decisions. The experiment employs a simplified construct of an employee’s allocation among the options in a retirement plan coupled with technology that enables us to collect data on the specific information that investors choose to view. In addition to collecting general information about the process by which investors choose among mutual fund options, we employ an experimental manipulation to test the effect of an instruction on the importance of mutual fund fees. Pairing this instruction with simplified fee disclosure allows us to distinguish between motivation-limits and cognition-limits as explanations for the widespread findings that investors ignore fees in their investment decisions. Our results offer partial but limited grounds for optimism. On the one hand, within our simplified experimental construct, our subjects allocated more money, on average, to higher-value funds. Furthermore, subjects who received the fees instruction paid closer attention to mutual fund fees and allocated their investments into funds with lower fees. On the other hand, the effects of even a blunt fees instruction were limited, and investors were unable to identify and avoid clearly inferior fund options. In addition, our results suggest that excessive, naïve diversification strategies are driving many investment decisions. Although our findings are preliminary, they suggest valuable avenues for future research and important implications for regulation of retail investing.
The substantial variation in the real price of oil since 2003 has renewed interest in the question of how to forecast monthly and quarterly oil prices. There also has been increased interest in the link between financial markets and oil markets, including the question of whether financial market information helps forecast the real price of oil in physical markets. An obvious advantage of financial data in forecasting oil prices is their availability in real time on a daily or weekly basis. We investigate whether mixed-frequency models may be used to take advantage of these rich data sets. We show that, among a range of alternative high-frequency predictors, especially changes in U.S. crude oil inventories produce substantial and statistically significant real-time improvements in forecast accuracy. The preferred MIDAS model reduces the MSPE by as much as 16 percent compared with the no-change forecast and has statistically significant directional accuracy as high as 82 percent. This MIDAS forecast also is more accurate than a mixed-frequency realtime VAR forecast, but not systematically more accurate than the corresponding forecast based on monthly inventories. We conclude that typically not much is lost by ignoring high-frequency financial data in forecasting the monthly real price of oil.
Model case procedures have some fundamentals in common with collective redress in civil law countries. This is particularly true in the field of investor protection which is highly regulated and marked by resulting enforcement failures, which led the German legislator to the enactment of the KapMuG and its recent amendment which highlight exemplary elements of model case procedure. A survey of the ongoing activities of the European Union in the area of collective redress and of its repercussions on the member state level therefore forms a suitable basis for the following analysis of the 2012 amendment of the KapMuG. It clearly brings into focus a shift from sector-specific regulation with an emphasis on the cross-border aspect of protecting consumers towards a “coherent approach” strengthening the enforcement of EU law. As a result, regulatory policy and collective redress are two sides of the same coin today. With respect to the KapMuG such a development brings about some tension between its aim to aggregate small individual claims as efficiently as possible and the dominant role of individual procedural rights in German civil procedure. This conflict can be illustrated by some specific rules of the KapMuG: its scope of application, the three-tier procedure of a model case procedure, the newly introduced notification of claims and the new opt-out settlement under the amended §§ 17-19.
We propose the realized systemic risk beta as a measure for financial companies’ contribution to systemic risk given network interdependence between firms’ tail risk exposures. Conditional on statistically pre-identified network spillover effects and market as well as balance sheet information, we define the realized systemic risk beta as the total time-varying marginal effect of a firm’s Value-at-risk (VaR) on the system’s VaR. Statistical inference reveals a multitude of relevant risk spillover channels and determines companies’ systemic importance in the U.S. financial system. Our approach can be used to monitor companies’ systemic importance allowing for a transparent macroprudential supervision.
We introduce a copula-based dynamic model for multivariate processes of (non-negative) high-frequency trading variables revealing time-varying conditional variances and correlations. Modeling the variables’ conditional mean processes using a multiplicative error model we map the resulting residuals into a Gaussian domain using a Gaussian copula. Based on high-frequency volatility, cumulative trading volumes, trade counts and market depth of various stocks traded at the NYSE, we show that the proposed copula-based transformation is supported by the data and allows capturing (multivariate) dynamics in higher order moments. The latter are modeled using a DCC-GARCH specification. We suggest estimating the model by composite maximum likelihood which is sufficiently flexible to be applicable in high dimensions. Strong empirical evidence for time-varying conditional (co-)variances in trading processes supports the usefulness of the approach. Taking these higher-order dynamics explicitly into account significantly improves the goodness-of-fit of the multiplicative error model and allows capturing time-varying liquidity risks.
Does it pay to invest in art? A selection-corrected returns perspective : [draft october 15, 2013]
(2013)
This paper shows the importance of correcting for sample selection when investing in illiquid assets with endogenous trading. Using a large sample of 20,538 paintings that were sold repeatedly at auction between 1972 and 2010, we find that paintings with higher price appreciation are more likely to trade. This strongly biases estimates of returns. The selection-corrected average annual index return is 6.5 percent, down from 10 percent for traditional uncorrected repeat sales regressions, and Sharpe Ratios drop from 0.24 to 0.04. From a pure financial perspective, passive index investing in paintings is not a viable investment strategy once selection bias is accounted for. Our results have important implications for other illiquid asset classes that trade endogenously.
The 2011 European short sale ban on financial stocks: a cure or a curse? : [version 31 july 2013]
(2013)
Did the August 2011 European short sale bans on financial stocks accomplish their goals? In order to answer this question, we use stock options’ implied volatility skews to proxy for investors’ risk aversion. We find that on ban announcement day, risk aversion levels rose for all stocks but more so for the banned financial stocks. The banned stocks’ volatility skews remained elevated during the ban but dropped for the other unbanned stocks. We show that it is the imposition of the ban itself that led to the increase in risk aversion rather than other causes such as information flow, options trading volumes, or stock specific factors. Substitution effects were minimal, as banned stocks’ put trading volumes and put-call ratios declined during the ban. We argue that although the ban succeeded in curbing further selling pressure on financial stocks by redirecting trading activity towards index options, this result came at the cost of increased risk aversion and some degree of market failure.
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.
We use responses to survey questions in the 2010 Italian Survey of Household Income and Wealth that ask consumers how much of an unexpected transitory income change they would consume. We find that the marginal propensity to consume (MPC) is 48 percent on average, and that there is substantial heterogeneity in the distribution. We find that households with low cash-on-hand exhibit a much higher MPC than affluent households, which is in agreement with models with precautionary savings where income risk plays an important role. The results have important implications for the evaluation of fiscal policy, and for predicting household responses to tax reforms and redistributive policies. In particular, we find that a debt-financed increase in transfers of 1 percent of national disposable income targeted to the bottom decile of the cash-on-hand distribution would increase aggregate consumption by 0.82 percent. Furthermore, we find that redistributing 1% of national disposable income from the top to the bottom decile of the income distribution would boost aggregate consumption by 0.33%.
La investigación sobre el desarrollo y la vida del derecho canónico en la América hispánica se ha visto enriquecida por la edición de los documentos de trabajo del Tercer Concilio Provincial Mexicano, celebrado en 1585. Esta monografía presenta las líneas de investigación que el autor está llevando a cabo en su tesis doctoral, confrontando los decretos promulgados con su iter redaccional de acuerdo a la información suministrada por los manuscritos editados. Los pedidos y memoriales presentados al concilio provincial pueden ser analizados, junto con la misma tarea legislativa, como un modo de resolución de conflictos por parte de la autoridad eclesiástica y su potestad de acuerdo con el derecho canónico entonces vigente.
Prior research suggests that those who rely on intuition rather than effortful reasoning when making decisions are less averse to risk and ambiguity. The evidence is largely correlational, however, leaving open the question of the direction of causality. In this paper, we present experimental evidence of causation running from reliance on intuition to risk and ambiguity preferences. We directly manipulate participants’ predilection to rely on intuition and find that enhancing reliance on intuition lowers the probability of being ambiguity averse by 30 percentage points and increases risk tolerance by about 30 percent in the experimental sub-population where we would a priori expect the manipulation to be successful(males).
Investment in financial literacy, social security and portfolio choice : [version may 21, 2013]
(2013)
We present an intertemporal portfolio choice model where individuals invest in financial literacy, save, allocate their wealth between a safe and a risky asset, and receive a pension when they retire. Financial literacy affects the excess return and the cost of stock market participation. Since literacy depreciates over time and has a cost related to current consumption, investors simultaneously choose how much to save, the portfolio allocation, and the optimal investment in literacy. This last depends on households' resources, its preference parameters and on how much financial literacy affects the returns on risky assets and the stock market participation cost, and the returns on social security wealth. The model implies one should observe a positive correlation between stock market participation (and risky asset share, conditional on participation) and financial literacy, and a negative correlation between the generosity of the social security system and financial literacy. The model also implies that the stock of financial literacy accumulated early in life is positively correlated with the individual's wealth and portfolio allocations later in life. Using microeconomic cross-country data, we find support for these predictions.
The U.S. Energy Information Administration (EIA) regularly publishes monthly and quarterly forecasts of the price of crude oil for horizons up to two years, which are widely used by practitioners. Traditionally, such out-of-sample forecasts have been largely judgmental, making them difficult to replicate and justify. An alternative is the use of real-time econometric oil price forecasting models. We investigate the merits of constructing combinations of six such models. Forecast combinations have received little attention in the oil price forecasting literature to date. We demonstrate that over the last 20 years suitably constructed real-time forecast combinations would have been systematically more accurate than the no-change forecast at horizons up to 6 quarters or 18 months. MSPE reduction may be as high as 12% and directional accuracy as high as 72%. The gains in accuracy are robust over time. In contrast, the EIA oil price forecasts not only tend to be less accurate than no-change forecasts, but are much less accurate than our preferred forecast combination. Moreover, including EIA forecasts in the forecast combination systematically lowers the accuracy of the combination forecast. We conclude that suitably constructed forecast combinations should replace traditional judgmental forecasts of the price of oil.
Are product spreads useful for forecasting? An empirical evaluation of the Verleger hypothesis
(2013)
Notwithstanding a resurgence in research on out-of-sample forecasts of the price of oil in recent years, there is one important approach to forecasting the real price of oil which has not been studied systematically to date. This approach is based on the premise that demand for crude oil derives from the demand for refined products such as gasoline or heating oil. Oil industry analysts such as Philip Verleger and financial analysts widely believe that there is predictive power in the product spread, defined as the difference between suitably weighted refined product market prices and the price of crude oil. Our objective is to evaluate this proposition. We derive from first principles a number of alternative forecasting model specifications involving product spreads and compare these models to the no-change forecast of the real price of oil. We show that not all product spread models are useful for out-of-sample forecasting, but some models are, even at horizons between one and two years. The most accurate model is a time-varying parameter model of gasoline and heating oil spot spreads that allows the marginal product market to change over time. We document MSPE reductions as high as 20% and directional accuracy as high as 63% at the two-year horizon, making product spread models a good complement to forecasting models based on economic fundamentals, which work best at short horizons.
U.S. retail food price increases in recent years may seem large in nominal terms, but after adjusting for inflation have been quite modest even after the change in U.S. biofuel policies in 2006. In contrast, increases in the real prices of corn, soybeans, wheat and rice received by U.S. farmers have been more substantial and can be linked in part to increases in the real price of oil. That link, however, appears largely driven by common macroeconomic determinants of the prices of oil and agricultural commodities rather than the pass-through from higher oil prices. We show that there is no evidence that corn ethanol mandates have created a tight link between oil and agricultural markets. Rather increases in food commodity prices not associated with changes in global real activity appear to reflect a wide range of idiosyncratic shocks ranging from changes in biofuel policies to poor harvests. Increases in agricultural commodity prices in turn contribute little to U.S. retail food price increases, because of the small cost share of agricultural products in food prices. There is no evidence that oil price shocks have caused more than a negligible increase in retail food prices in recent years. Nor is there evidence for the prevailing wisdom that oil-price driven increases in the cost of food processing, packaging, transportation and distribution are responsible for higher retail food prices. Finally, there is no evidence that oil-market specific events or for that matter U.S. biofuel policies help explain the evolution of the real price of rice, which is perhaps the single most important food commodity for many developing countries.
We investigate the theoretical impact of including two empirically-grounded insights in a dynamic life cycle portfolio choice model. The first is to recognize that, when managing their own financial wealth, investors incur opportunity costs in terms of current and future human capital accumulation, particularly if human capital is acquired via learning by doing. The second is that we incorporate age-varying efficiency patterns in financial decisionmaking. Both enhancements produce inactivity in portfolio adjustment patterns consistent with empirical evidence. We also analyze individuals’ optimal choice between self-managing their wealth versus delegating the task to a financial advisor. Delegation proves most valuable to the young and the old. Our calibrated model quantifies welfare gains from including investment time and money costs, as well as delegation, in a life cycle setting.
Household decisions are profoundly shaped by a complex set of financial options due to Social Security rules determining retirement, spousal, and survivor benefits, along with benefit adjustments that vary with the age at which these are claimed. These rules influence optimal household asset allocation, insurance, and work decisions, given life cycle demographic shocks such as marriage, divorce, and children. Our model generates a wealth profile and a low and stable equity fraction consistent with empirical evidence. We also confirm predictions that wives will claim retirement benefits earlier than husbands, while life insurance is mainly purchased by younger men. Our policy simulations imply that eliminating survivor benefits would sharply reduce claiming differences by sex while dramatically increasing men’s life insurance purchases.