994 research outputs found
Taxes and Mutual Fund Inflows Around Distribution Dates
Capital gain distributions by mutual funds generate tax liability for taxable shareholders, thereby reducing their after-tax returns. Taxable investors who are considering purchasing fund shares around distribution dates have an incentive to delay their purchase until after the distribution, since this will reduce the present value of their tax liability. Non-taxable shareholders, such as those who invest through IRAs and other tax-deferred accounts, face no such incentive for delaying purchase. This paper compares daily shareholder transactions by taxable and non-taxable investors in the mutual funds of a single no-load fund complex around distribution dates. Gross inflows to taxable accounts are significantly lower in the weeks preceding distribution dates than in the weeks following them, but gross inflows to tax-deferred accounts do not change around these dates. This finding suggests that some taxable shareholders time their purchase of mutual fund shares to avoid the tax acceleration associated with distributions. Taxable shareholders who purchase shares just before distribution dates also have shorter holding periods, on average, than those who buy after a distribution. The cost of the distribution-related tax acceleration for pre-distribution buyers is therefore somewhat less than that for those who buy after the distribution.
Impact of Investor's Varying Risk Aversion on the Dynamics of Asset Price Fluctuations
While the investors' responses to price changes and their price forecasts are
well accepted major factors contributing to large price fluctuations in
financial markets, our study shows that investors' heterogeneous and dynamic
risk aversion (DRA) preferences may play a more critical role in the dynamics
of asset price fluctuations. We propose and study a model of an artificial
stock market consisting of heterogeneous agents with DRA, and we find that DRA
is the main driving force for excess price fluctuations and the associated
volatility clustering. We employ a popular power utility function,
with agent specific and
time-dependent risk aversion index, , and we derive an approximate
formula for the demand function and aggregate price setting equation. The
dynamics of each agent's risk aversion index, (i=1,2,...,N), is
modeled by a bounded random walk with a constant variance . We show
numerically that our model reproduces most of the ``stylized'' facts observed
in the real data, suggesting that dynamic risk aversion is a key mechanism for
the emergence of these stylized facts.Comment: 17 pages, 7 figure
Random walks - a sequential approach
In this paper sequential monitoring schemes to detect nonparametric drifts
are studied for the random walk case. The procedure is based on a kernel
smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson
estimator and its as- sociated sequential partial sum process under
non-standard sampling. The asymptotic behavior differs substantially from the
stationary situation, if there is a unit root (random walk component). To
obtain meaningful asymptotic results we consider local nonpara- metric
alternatives for the drift component. It turns out that the rate of convergence
at which the drift vanishes determines whether the asymptotic properties of the
monitoring procedure are determined by a deterministic or random function.
Further, we provide a theoretical result about the optimal kernel for a given
alternative
Labor Force Status Dynamics in the German Labor Market - Individual Heterogeneity and Cyclical Sensitivity
Sovereign Bond Market Reactions to Fiscal Rules and No-Bailout Clauses – The Swiss Experience
Error Correction Models of Msa Housing 'Supply' Elasticities: Implications for Price Recovery
Risiken im Lebenszyklus: Theorie und Evidenz
Der einzelne Mensch ist im Lebensverlauf erheblichen biometrischen, ökonomischen, familiären und politischen Risiken ausgesetzt. Viele meinen, diese wären in den letzten Jahren größer geworden. Haben wir die richtigen Institutionen, um diese Risiken effizient abzudecken? Unter Institutionen verstehen wir individuelles Sparen, familiäre Hilfe, private Versicherungen und schließlich den Staat mit seinen Sozialversicherungen. Wo und wann funktionieren diese Institutionen? Wo und wann nicht? Was muss man tun, um sie zu verbessern? Wie sieht modernes "Social Risk Management" aus? Der erste Teil dieses Übersichtsbeitrags skizziert die wirtschaftstheoretischen Grundlagen des Sparverhaltens, der Portefeuillewahl und der Versicherungsnachfrage. Im Hauptteil werden die empirischen Befunde gesammelt, um im dritten Teil wirtschaftspolitische Schlussfolgerungen zu ziehen
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