1,387 research outputs found
The Futility of Utility: how market dynamics marginalize Adam Smith
Econometrics is based on the nonempiric notion of utility. Prices, dynamics,
and market equilibria are supposed to be derived from utility. Utility is
usually treated by economists as a price potential, other times utility rates
are treated as Lagrangians. Assumptions of integrability of Lagrangians and
dynamics are implicitly and uncritically made. In particular, economists assume
that price is the gradient of utility in equilibrium, but I show that price as
the gradient of utility is an integrability condition for the Hamiltonian
dynamics of an optimization problem in econometric control theory. One
consequence is that, in a nonintegrable dynamical system, price cannot be
expressed as a function of demand or supply variables. Another consequence is
that utility maximization does not describe equiulibrium. I point out that the
maximization of Gibbs entropy would describe equilibrium, if equilibrium could
be achieved, but equilibrium does not describe real markets. To emphasize the
inconsistency of the economists' notion of 'equilibrium', I discuss both
deterministic and stochastic dynamics of excess demand and observe that Adam
Smith's stabilizing hand is not to be found either in deterministic or
stochastic dynamical models of markets, nor in the observed motions of asset
prices. Evidence for stability of prices of assets in free markets simply has
not been found.Comment: 46 pages. accepte
The Futility of Utility: how market dynamics marginalize Adam Smith
General Equilibrium Theory in econometrics is based on the vague notion of utility. Prices, dynamics, and market equilibria are supposed to be derived from utility. Utility is sometimes treated like a potential, other times like a Lagrangian. Illegal assumptions of integrability of actions and dynamics are usually made. Economists usually assume that price is the gradient of utility in equilibrium, but I observe instead that price as the gradient of utility is an integrability condition for the Hamiltonian dynamics of an optimization problem. I discuss both deterministic and statistical descriptions of the dynamics of excess demand and observe that Adam Smith's stabilizing hand is not to be found either in deterministic or stochastic dynamical models of markets nor in the observed motions of asset prices. Evidence for stability of prices of assets in free markets has not been found.Utility; general equilibrium; nonintegrability; control dynamics; conservation laws; chaos; instability; supply-demand curves; nonequilibrium dynamics
Optimal leverage from non-ergodicity
In modern portfolio theory, the balancing of expected returns on investments
against uncertainties in those returns is aided by the use of utility
functions. The Kelly criterion offers another approach, rooted in information
theory, that always implies logarithmic utility. The two approaches seem
incompatible, too loosely or too tightly constraining investors' risk
preferences, from their respective perspectives. The conflict can be understood
on the basis that the multiplicative models used in both approaches are
non-ergodic which leads to ensemble-average returns differing from time-average
returns in single realizations. The classic treatments, from the very beginning
of probability theory, use ensemble-averages, whereas the Kelly-result is
obtained by considering time-averages. Maximizing the time-average growth rates
for an investment defines an optimal leverage, whereas growth rates derived
from ensemble-average returns depend linearly on leverage. The latter measure
can thus incentivize investors to maximize leverage, which is detrimental to
time-average growth and overall market stability. The Sharpe ratio is
insensitive to leverage. Its relation to optimal leverage is discussed. A
better understanding of the significance of time-irreversibility and
non-ergodicity and the resulting bounds on leverage may help policy makers in
reshaping financial risk controls.Comment: 17 pages, 3 figures. Updated figures and extended discussion of
ergodicit
Measuring time preferences
We review research that measures time preferences—i.e., preferences over intertemporal tradeoffs. We distinguish between studies using financial flows, which we call “money earlier or later” (MEL) decisions and studies that use time-dated consumption/effort. Under different structural models, we show how to translate what MEL experiments directly measure (required rates of return for financial flows) into a discount function over utils. We summarize empirical regularities found in MEL studies and the predictive power of those studies. We explain why MEL choices are driven in part by some factors that are distinct from underlying time preferences.National Institutes of Health (NIA R01AG021650 and P01AG005842) and the Pershing Square Fund for Research in the Foundations of Human Behavior
Classes of fast and specific search mechanisms for proteins on DNA
Problems of search and recognition appear over different scales in biological
systems. In this review we focus on the challenges posed by interactions
between proteins, in particular transcription factors, and DNA and possible
mechanisms which allow for a fast and selective target location. Initially we
argue that DNA-binding proteins can be classified, broadly, into three distinct
classes which we illustrate using experimental data. Each class calls for a
different search process and we discuss the possible application of different
search mechanisms proposed over the years to each class. The main thrust of
this review is a new mechanism which is based on barrier discrimination. We
introduce the model and analyze in detail its consequences. It is shown that
this mechanism applies to all classes of transcription factors and can lead to
a fast and specific search. Moreover, it is shown that the mechanism has
interesting transient features which allow for stability at the target despite
rapid binding and unbinding of the transcription factor from the target.Comment: 65 pages, 23 figure
Fundamental Framework for Technical Analysis
Starting from the characterization of the past time evolution of market
prices in terms of two fundamental indicators, price velocity and price
acceleration, we construct a general classification of the possible patterns
characterizing the deviation or defects from the random walk market state and
its time-translational invariant properties. The classification relies on two
dimensionless parameters, the Froude number characterizing the relative
strength of the acceleration with respect to the velocity and the time horizon
forecast dimensionalized to the training period. Trend-following and contrarian
patterns are found to coexist and depend on the dimensionless time horizon. The
classification is based on the symmetry requirements of invariance with respect
to change of price units and of functional scale-invariance in the space of
scenarii. This ``renormalized scenario'' approach is fundamentally
probabilistic in nature and exemplifies the view that multiple competing
scenarii have to be taken into account for the same past history. Empirical
tests are performed on on about nine to thirty years of daily returns of twelve
data sets comprising some major indices (Dow Jones, SP500, Nasdaq, DAX, FTSE,
Nikkei), some major bonds (JGB, TYX) and some major currencies against the US
dollar (GBP, CHF, DEM, JPY). Our ``renormalized scenario'' exhibits
statistically significant predictive power in essentially all market phases. In
constrast, a trend following strategy and trend + acceleration following
strategy perform well only on different and specific market phases. The value
of the ``renormalized scenario'' approach lies in the fact that it always finds
the best of the two, based on a calculation of the stability of their predicted
market trajectories.Comment: Latex, 27 page
Evolutionary games on graphs
Game theory is one of the key paradigms behind many scientific disciplines
from biology to behavioral sciences to economics. In its evolutionary form and
especially when the interacting agents are linked in a specific social network
the underlying solution concepts and methods are very similar to those applied
in non-equilibrium statistical physics. This review gives a tutorial-type
overview of the field for physicists. The first three sections introduce the
necessary background in classical and evolutionary game theory from the basic
definitions to the most important results. The fourth section surveys the
topological complications implied by non-mean-field-type social network
structures in general. The last three sections discuss in detail the dynamic
behavior of three prominent classes of models: the Prisoner's Dilemma, the
Rock-Scissors-Paper game, and Competing Associations. The major theme of the
review is in what sense and how the graph structure of interactions can modify
and enrich the picture of long term behavioral patterns emerging in
evolutionary games.Comment: Review, final version, 133 pages, 65 figure
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