Blockchain Intelligence: When Blockchain Meets Artificial Intelligence
Blockchain Intelligence: When Blockchain Meets Artificial Intelligence https://t.co/6sPXTvr32p â CryptAssets (@CryptAssets) February 25, 2020
View ArticleMean�field games with differing beliefs for algorithmic trading
Abstract Even when confronted with the same data, agents often disagree on a model of the real world. Here, we address the question of how interacting heterogeneous agents, who disagree on what model...
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The Carter Catastrophe
A Bayesian argument for why humans will soon be extinct.Continue reading on Cantorâs Paradise »
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When Feynman met Dirac
“I am Feynman. I am Dirac. (Silence)”Continue reading on Cantorâs Paradise »
View ArticleWall Street Tackles Sustainable Development Goals
In 2015 the United Nations defined 17 Sustainable Development Goals [no poverty, no hunger, health & well-being, etc.] along with 169 targets that were devised to allow for quantitative measurement...
View ArticleSEC to Hold National Compliance Outreach Seminar for Investment Companies and...
The Securities and Exchange Commission today announced the opening of registration for its compliance outreach programâs national seminar for investment companies and investment advisers. The event...
View ArticleDistributions of Historic Market Data -- Relaxation and Correlations....
We investigate relaxation and correlations in a class of mean-reverting models for stochastic variances. We derive closed-form expressions for the correlation functions and leverage for a general form...
View ArticleNumerical method for model-free pricing of exotic derivatives using rough...
We estimate prices of exotic options in a discrete-time model-free setting when the trader has access to market prices of a rich enough class of exotic and vanilla options. This is achieved by...
View ArticleA Practical Approach to Social Learning. (arXiv:2002.11017v1 [econ.TH])
Models of social learning feature either binary signals or abstract signal structures often deprived of micro-foundations. Both models are limited when analyzing interim results or performing empirical...
View ArticleG-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning....
We present a reinforcement learning approach to goal based wealth management problems such as optimization of retirement plans or target dated funds. In such problems, an investor seeks to achieve a...
View ArticleRandom horizon principal-agent problem. (arXiv:2002.10982v1 [math.OC])
We consider a general formulation of the random horizon Principal-Agent problem with a continuous payment and a lump-sum payment at termination. In the European version of the problem, the random...
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The growth of environmental, social and corporate governance in investing
The wealth management industry is continuously changing. As we have seen over the last few years, active management is falling out of fashion and has become less âfashionableâ with asset...
View ArticleScoring models for roboadvisory platforms: a network approach
In this paper, the authors show how to exploit the available data to build portfolios that better fit the risk profiles of investors. This is made possible, on the one hand, by constructing groups of...
View ArticleMapping bank securities across euro area sectors: comparing funding and...
In this paper, the authors present new evidence on the structure of euro area securities markets using a multilayer network approach.
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