Paper proposes a new deflation varimax method for vintage factor analysis.
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Paper optimizes tensor deflation for non-orthogonal signals.
Study analyzes Hotelling-type tensor deflation for spiked tensors, providing insights into signal and noise.
Study analyzes accuracy of tensor deflation in noisy conditions.
Paper investigates existence of deflators in financial markets.
In this paper, we implement a stochastic deflator with five economic and financial risk factors: interest rates, market price of risk, stock prices, default intensities, and convenience yields. We examine the deflator with different financial assets, such as stocks, zero-coupon bonds, vanilla options, and corporate cou…
We solve optimal consumption in a market with bounded risk.
The paper analyzes deflation for estimating a low-rank spike in large tensors with noise.
We analyse the structure of local martingale deflators projected on smaller filtrations. In a general continuous-path setting, we show that the local martingale part in the multiplicative Doob-Meyer decomposition of projected local martingale deflators are themselves local martingale deflators in the smaller informatio…
New method finds linear relationships across multiple data blocks using proximal gradient descent with constraint.
Study resolves duality gap in optimal consumption with random income termination.
This paper analyzes how errors accumulate in PCA's deflation method.
Let be two filtrations and be a semimartingale possessing a local martingale deflator. Consider a stopping time. We study the problem whether or can have local martingale deflators. A suitable theoretical framework…
The paper shows how gradient flow on over-parametrized tensor decomposition behaves like deflation.
Develops a method to estimate the shadow riskless rate from empirical data.
There is an extensive historical dataset on real GDP per capita prepared by Angus Maddison. This dataset covers the period since 1870 with continuous annual estimates in developed countries. All time series for individual economies have a clear structural break between 1940 and 1950. The behavior before 1940 and after …
We consider the problem of estimating multiple principal components using the recently-proposed Sparse and Functional Principal Components Analysis (SFPCA) estimator. We first propose an extension of SFPCA which estimates several principal components simultaneously using manifold optimization techniques to enforce orth…
The paper studies optimal maps between hyperbolic surfaces, focusing on their rigidity and obstructions.
DFSOS improves sparse discriminant analysis for high-dimensional data.
We consider the following multi-component sparse PCA problem: given a set of data points, we seek to extract a small number of sparse components with disjoint supports that jointly capture the maximum possible variance. These components can be computed one by one, repeatedly solving the single-component problem and def…
New analysis improves black-box -PCA algorithms, reducing parameter loss.
We undertake a study of markets from the perspective of a financial agent with limited access to information. The set of wealth processes available to the agent is structured with reasonable economic properties, instead of the usual practice of taking it to consist of stochastic integrals against a semimartingale integ…
No arbitrage in financial markets with special semimartingales.
We re-estimate statistical properties and predictive power of a set of Phillips curves, which are expressed as linear and lagged relationships between the rates of inflation, unemployment, and change in labour force. For France, several relationships were estimated eight years ago. The change rate of labour force was u…
In this paper we study arbitrage theory of financial markets in the absence of a numéraire both in discrete and continuous time. In our main results, we provide a generalization of the classical equivalence between no unbounded profits with bounded risk (NUPBR) and the existence of a supermartingale deflator. To obtain…
New method deflates manifolds to visualize high-dimensional data.
The implementation of conventional sparse principal component analysis (SPCA) on high-dimensional data sets has become a time consuming work. In this paper, a series of subspace projections are constructed efficiently by using Household QR factorization. With the aid of these subspace projections, a fast deflation meth…
Unified framework models multiple financial and insurance term structures.
Bayesian method improves dictionary learning for complex problems.
The paper provides a new uniform tail bound for empirical processes.
A new method inflates and deflates data manifolds to estimate densities without losing universality.
This paper presents a stochastic model for discrete-time trading in financial markets where trading costs are given by convex cost functions and portfolios are constrained by convex sets. The model does not assume the existence of a cash account/numeraire. In addition to classical frictionless markets and markets with …
Extends utility maximization theory for infinite horizons without strong no-arbitrage assumptions.
I sketch a program for a microeconomic theory of the main component of the business cycle as a recurring disequilibrium, driven by incompleteness of the financial market and by information asymmetries between borrowers and lenders. This proposal seeks to incorporate five distinct but connected processes that have been …
A constrained informationally efficient market is defined to be one whose price process arises as the outcome of some equilibrium where agents face restrictions on trade. This paper investigates the case of short sale constraints, a setting which despite its simplicity, generates new insights. In particular, it is show…
KLD token adjusts supply based on macroeconomic debt index, creating deflationary effect.
We present an elementary treatment of the Optional Decomposition Theorem for continuous semimartingales and general filtrations. This treatment does not assume the existence of equivalent local martingale measure(s), only that of strictly positive local martingale deflator(s).
This paper considers an initial market model, specified by its underlying assets and its flow of information , and an arbitrary random time which might not be an -stopping time. As the death time and the default time (that might represent) can be seen when they occur only, the progress…
Singapore's cooling measures did not increase housing wealth overall.
In a semimartingale financial market model, it is shown that there is equivalence between absence of arbitrage of the first kind (a weak viability condition) and the existence of a strictly positive process that acts as a local martingale deflator on nonnegative wealth processes.
We solve the problem of pricing and optimal exercise of American call-type options in markets which do not necessarily admit an equivalent local martingale measure. This resolves an open question proposed by Fernholz and Karatzas [Stochastic Portfolio Theory: A Survey, Handbook of Numerical Analysis, 15:89-168, 2009].
Partial Least Squares (PLS) methods have been heavily exploited to analyse the association between two blocs of data. These powerful approaches can be applied to data sets where the number of variables is greater than the number of observations and in presence of high collinearity between variables. Different sparse ve…
Sharp rates found for learning with dependent data, avoiding sample size deflation.
The paper describes how martingales can be represented after a random time in financial models.
The aim of this paper is to compare statistical properties of a bubble period with those of the anti-bubble period in stock markets. We investigate the statistical properties of daily data for the Nikkei 225 index in the 28-year period from January 1975 to April 2003, corresponded to the periods of bubbles and anti-bub…
In this paper, we introduce a numeraire-free and original probability based framework for financial markets. We reformulate or characterize fair markets, the optional decomposition theorem, superhedging, attainable claims and complete markets in terms of martingale deflators, present a recent result of Kramkov and Scha…
Model explains stock price bubbles through debt crises and financial crashes.
New algorithm improves heteroskedastic PCA performance.