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Volatility term structures in commodity markets
In this study, we comprehensively examine the volatility term structures in commodity markets. We model stateâdependent spillovers in principal components (PCs) of the volatility term structures of different commodities, as well as that of the equity market. We detect strong economic links and a substantial interconnectedness of the volatility term structures of commodities. Accounting for intraâcommodityâmarket spillovers significantly improves outâofâsample forecasts of the components of the volatility term structure. Spillovers following macroeconomic news announcements account for a large proportion of this forecast power. There thus seems to be substantial information transmission between different commodity markets
Volatility and dividend risk in perpetual American options
American options are financial instruments that can be exercised at any time
before expiration. In this paper we study the problem of pricing this kind of
derivatives within a framework in which some of the properties --volatility and
dividend policy-- of the underlaying stock can change at a random instant of
time, but in such a way that we can forecast their final values. Under this
assumption we can model actual market conditions because some of the most
relevant facts that may potentially affect a firm will entail sharp predictable
effects. We will analyse the consequences of this potential risk on perpetual
American derivatives, a topic connected with a wide class of recurrent problems
in physics: holders of American options must look for the fair price and the
optimal exercise strategy at once, a typical question of free absorbing
boundaries. We present explicit solutions to the most common contract
specifications and derive analytical expressions concerning the mean and higher
moments of the exercise time.Comment: 21 pages, 5 figures, iopart, submitted for publication; deep
revision, two new appendice
Enhanced Zeeman splitting in Ga0.25In0.75As quantum point contacts
The strength of the Zeeman splitting induced by an applied magnetic field is
an important factor for the realization of spin-resolved transport in
mesoscopic devices. We measure the Zeeman splitting for a quantum point contact
etched into a Ga0.25In0.75As quantum well, with the field oriented parallel to
the transport direction. We observe an enhancement of the Lande g-factor from
|g*|=3.8 +/- 0.2 for the third subband to |g*|=5.8 +/- 0.6 for the first
subband, six times larger than in GaAs. We report subband spacings in excess of
10 meV, which facilitates quantum transport at higher temperatures.Comment: [Version 2] Revtex4, 11 pages, 3 figures, accepted for publication in
Applied Physics Letter
Activity Dependent Branching Ratios in Stocks, Solar X-ray Flux, and the Bak-Tang-Wiesenfeld Sandpile Model
We define an activity dependent branching ratio that allows comparison of
different time series . The branching ratio is defined as . The random variable is the value of the next signal given
that the previous one is equal to , so . If
, the process is on average supercritical when the signal is equal to
, while if , it is subcritical. For stock prices we find
within statistical uncertainty, for all , consistent with an ``efficient
market hypothesis''. For stock volumes, solar X-ray flux intensities, and the
Bak-Tang-Wiesenfeld (BTW) sandpile model, is supercritical for small
values of activity and subcritical for the largest ones, indicating a tendency
to return to a typical value. For stock volumes this tendency has an
approximate power law behavior. For solar X-ray flux and the BTW model, there
is a broad regime of activity where , which we interpret as an
indicator of critical behavior. This is true despite different underlying
probability distributions for , and for . For the BTW model the
distribution of is Gaussian, for sufficiently larger than one, and
its variance grows linearly with . Hence, the activity in the BTW model
obeys a central limit theorem when sampling over past histories. The broad
region of activity where is close to one disappears once bulk dissipation
is introduced in the BTW model -- supporting our hypothesis that it is an
indicator of criticality.Comment: 7 pages, 11 figure
The Combinatorial World (of Auctions) According to GARP
Revealed preference techniques are used to test whether a data set is
compatible with rational behaviour. They are also incorporated as constraints
in mechanism design to encourage truthful behaviour in applications such as
combinatorial auctions. In the auction setting, we present an efficient
combinatorial algorithm to find a virtual valuation function with the optimal
(additive) rationality guarantee. Moreover, we show that there exists such a
valuation function that both is individually rational and is minimum (that is,
it is component-wise dominated by any other individually rational, virtual
valuation function that approximately fits the data). Similarly, given upper
bound constraints on the valuation function, we show how to fit the maximum
virtual valuation function with the optimal additive rationality guarantee. In
practice, revealed preference bidding constraints are very demanding. We
explain how approximate rationality can be used to create relaxed revealed
preference constraints in an auction. We then show how combinatorial methods
can be used to implement these relaxed constraints. Worst/best-case welfare
guarantees that result from the use of such mechanisms can be quantified via
the minimum/maximum virtual valuation function
Socially Optimal Mining Pools
Mining for Bitcoins is a high-risk high-reward activity. Miners, seeking to
reduce their variance and earn steadier rewards, collaborate in pooling
strategies where they jointly mine for Bitcoins. Whenever some pool participant
is successful, the earned rewards are appropriately split among all pool
participants. Currently a dozen of different pooling strategies (i.e., methods
for distributing the rewards) are in use for Bitcoin mining.
We here propose a formal model of utility and social welfare for Bitcoin
mining (and analogous mining systems) based on the theory of discounted
expected utility, and next study pooling strategies that maximize the social
welfare of miners. Our main result shows that one of the pooling strategies
actually employed in practice--the so-called geometric pay pool--achieves the
optimal steady-state utility for miners when its parameters are set
appropriately.
Our results apply not only to Bitcoin mining pools, but any other form of
pooled mining or crowdsourcing computations where the participants engage in
repeated random trials towards a common goal, and where "partial" solutions can
be efficiently verified
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