2,927 research outputs found
Weak and strong no-arbitrage conditions for continuous financial markets
We propose a unified analysis of a whole spectrum of no-arbitrage conditions for finan- cial market models based on continuous semimartingales. In particular, we focus on no-arbitrage conditions weaker than the classical notions of No Arbitrage opportunity (NA) and No Free Lunch with Vanishing Risk (NFLVR). We provide a complete characterization of the considered no-arbitrage conditions, linking their validity to the characteristics of the discounted asset price process and to the existence and the properties of (weak) martingale deflators, and review classical as well as recent results
Review of I Am a Strange Loop by Douglas Hofstadter (2007) (review revised 2019)
Latest Sermon from the Church of Fundamentalist Naturalism by Pastor Hofstadter. Like his much more famous (or infamous for its relentless philosophical errors) work Godel, Escher, Bach, it has a superficial plausibility but if one understands that this is rampant scientism which mixes real scientific issues with philosophical ones (i.e., the only real issues are what language games we ought to play) then almost all its interest disappears. I provide a framework for analysis based in evolutionary psychology and the work of Wittgenstein (since updated in my more recent writings).
Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book âThe Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searleâ 2nd ed (2019). Those interested in more of my writings may see âTalking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 3rd ed (2019), The Logical Structure of Human Behavior (2019), and Suicidal Utopian Delusions in the 21st Century 4th ed (2019
Absolutely No Free Lunches!
This paper is concerned with learners who aim to learn patterns in infinite
binary sequences: shown longer and longer initial segments of a binary
sequence, they either attempt to predict whether the next bit will be a 0 or
will be a 1 or they issue forecast probabilities for these events. Several
variants of this problem are considered. In each case, a no-free-lunch result
of the following form is established: the problem of learning is a formidably
difficult one, in that no matter what method is pursued, failure is
incomparably more common that success; and difficult choices must be faced in
choosing a method of learning, since no approach dominates all others in its
range of success. In the simplest case, the comparison of the set of situations
in which a method fails and the set of situations in which it succeeds is a
matter of cardinality (countable vs. uncountable); in other cases, it is a
topological matter (meagre vs. co-meagre) or a hybrid computational-topological
matter (effectively meagre vs. effectively co-meagre)
Information, no-arbitrage and completeness for asset price models with a change point
We consider a general class of continuous asset price models where the drift
and the volatility functions, as well as the driving Brownian motions, change
at a random time . Under minimal assumptions on the random time and on
the driving Brownian motions, we study the behavior of the model in all the
filtrations which naturally arise in this setting, establishing martingale
representation results and characterizing the validity of the NA1 and NFLVR
no-arbitrage conditions.Comment: 21 page
Reinterpreting No Free Lunch
Since itâs inception, the âNo Free Lunch theoremâ has concerned the application of symmetry results rather than the symmetries themselves. In our view, the conflation of result and application obscures the simplicity, generality, and power of the symmetries involved. This paper separates result from application, focusing on and clarifying the nature of underlying symmetries. The result is a general set-theoretic version of NFL which speaks to symmetries when arbitrary domains and co-domains are involved. Although our framework is deterministic, we note situations where our deterministic set-theoretic results speak nevertheless to stochastic algorithms
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