In two previous papers the author developed a second-order price adjustment
(t\^atonnement) process. This paper extends the approach to include both
quantity and price adjustments. We demonstrate three results: a analogue to
physical energy, called "activity" arises naturally in the model, and is not
conserved in general; price and quantity trajectories must either end at a
local minimum of a scalar potential or circulate endlessly; and disturbances
into a subspace of substitutable commodities decay over time. From this we
argue,
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although we do not prove, that the model features global stability,
combined with local instability, a characteristic of many real markets.
Following these observations and a brief survey of empirical results for
price-setting and consumption behavior in markets for "real" goods (as opposed
to financial markets), we conjecture that Stigler and Becker's well-known
theory of consumer preference opens the possibility of substantial degeneracy
in commodity space, and therefore that price and quantity trajectories could
lie on a relatively low-dimensional subspace within the full commodity space.
A way to fight your traffic tickets. The paper was awarded a special prize of
$400 that the author did not have to pay to the state of California.
<br />In view of enormous, extremely surprising and completely unexpected public
interest to this work, we have added an appendix answering the two most common
questions.
A limit order book provides information on available limit order prices and
their volumes. Based on these quantities, we give an empirical result on the
relationship between the bid-ask liquidity balance and trade sign and we show
that liquidity balance on best bid/best ask is quite informative for predicting
the future market order's direction. Moreover, we define price jump as a
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sell
(buy) market order arrival which is executed at a price which is smaller
(larger) than the best bid (best ask) price at the moment just after the
precedent market order arrival. Features are then extracted related to limit
order volumes, limit order price gaps, market order information and limit order
event information. Logistic regression is applied to predict the price jump
from the limit order book's feature. LASSO logistic regression is introduced to
help us make variable selection from which we are capable to highlight the
importance of different features in predicting the future price jump. In order
to get rid of the intraday data seasonality, the analysis is based on two
separated datasets: morning dataset and afternoon dataset. Based on an analysis
on forty largest French stocks of CAC40, we find that trade sign and market
order size as well as the liquidity on the best bid (best ask) are consistently
informative for predicting the incoming price jump.
The practice of valuation by marking-to-market with current trading prices is
seriously flawed. Under leverage the problem is particularly dramatic: due to
the concave form of market impact, selling al
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ways initially causes the expected
leverage to increase. There is a critical leverage above which it is impossible
to exit a portfolio without leverage going to infinity and bankruptcy becoming
likely. Standard risk-management methods give no warning of this problem, which
easily occurs for aggressively leveraged positions in illiquid markets. We
propose an alternative accounting procedure based on the estimated market
impact of liquidation that removes the illusion of profit. This should curb the
leverage cycle and contribute to an enhanced stability of financial markets.
We consider the pricing of European-style structured credit payoff in a
static framework, where the underlying default times are independent given a
common factor. A practical application would consist of the pricing of
nth-to-default baskets under the Gaussian copula model (GCM). We provide
necessary and sufficient conditions so that the corresponding asset prices are
martingales and introduce the concept of "break-even" correlation matrix. When
no sudden jump-to-default events occur, we show that the perfect replication of
these payoffs under the GCM is obtained if and only if the underlying single
name credit spreads follow a particular family of dynamics. We calculate the
corresponding break-even correlations and we exhibit a class of Merton-style
models that are consistent with this result. We explain why the GCM does not
have a lot of competitors among the class of one-period static models, except
perhaps the Clayton copula.