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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%.
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.