MoneyScience News |
- Blog Post: WealthandCapitalMarketsBlog: Webinar Replay: The #NextGen Investor: Preferences, Behaviors, and Technology Adoption
- Published / Preprint: Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio. (arXiv:1506.06180v1 [q-fin.CP])
- Published / Preprint: Nonparametric estimates of pricing functionals. (arXiv:1506.06568v1 [q-fin.PR])
- Published / Preprint: Model-free Superhedging Duality. (arXiv:1506.06608v1 [q-fin.MF])
- Published / Preprint: Systemic risk in multiplex networks with asymmetric coupling and threshold feedback. (arXiv:1506.06664v1 [physics.soc-ph])
- Published / Preprint: Understanding the Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of 7 Randomised Experiments. (arXiv:1506.06669v1 [q-fin.EC])
- Blog Post: iMFdirect: Inequality's Toll on Growth
- How Silicon Valley and Wall Street arrived at a new gold rush called Bitcoin
| Posted: 23 Jun 2015 01:07 AM PDT How can wealth managers capture the next wave of clients in light of a shift in the core client base, dynamic client expectations, stringent regulations, and emerging technology? Celent clients can catch the replay to the latest Celent WM webinar here: http://celent.com/node/33745read more... Visit MoneyScience for the Complete Article.      |
| Posted: 22 Jun 2015 05:37 PM PDT We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series approximation for this quantity. The zeroth-order approximation of the value... Visit MoneyScience for the Complete Article.    |
| Posted: 22 Jun 2015 05:37 PM PDT We analyze the empirical performance of several non-parametric estimators of the pricing functional for European options, using historical put and call prices on the S&P500 during the year 2012. Two main families of estimators are considered, obtained by estimating the pricing functional directly, and by estimating the (Black-Scholes) implied volatility surface, respectively. In each case... Visit MoneyScience for the Complete Article.    |
| Published / Preprint: Model-free Superhedging Duality. (arXiv:1506.06608v1 [q-fin.MF]) Posted: 22 Jun 2015 05:37 PM PDT In a model free discrete time financial market, we prove the superhedging duality theorem, where trading is allowed with dynamic and semi-static strategies. We also show that the initial cost of the cheapest portfolio that dominates a contingent claim on every possible path $\omega \in \Omega$, might be strictly greater than the upper bound of the no-arbitrage prices. We therefore... Visit MoneyScience for the Complete Article.    |
| Posted: 22 Jun 2015 05:37 PM PDT We study cascades on a two-layer multiplex network, with asymmetric feedback that depends on the coupling strength between the layers. Based on an analytical branching process approximation, we calculate the systemic risk measured by the final fraction of failed nodes on a reference layer. The results are compared with the case of a single layer network that is an aggregated representation of the... Visit MoneyScience for the Complete Article.    |
| Posted: 22 Jun 2015 05:37 PM PDT Bayesian hierarchical models serve as a standard methodology for aggregation and synthesis, used widely in statistics and other disciplines. I use this framework to aggregate the data from seven randomised experiments of expanding access to microcredit, assessing both the general impact of the intervention and the heterogeneity across contexts. The general impact on household profits is small,... Visit MoneyScience for the Complete Article.    |
| Blog Post: iMFdirect: Inequality's Toll on Growth Posted: 22 Jun 2015 10:46 AM PDT by iMFdirectread more... Visit MoneyScience for the Complete Article.    |
| How Silicon Valley and Wall Street arrived at a new gold rush called Bitcoin Posted: 22 Jun 2015 03:59 AM PDT How Silicon Valley and Wall Street arrived at a new gold rush called#bitcoin http://t.co/wYdJpbw6Cz — moneyscience (@moneyscience) June 22, 2015 Visit MoneyScience for the Complete Article.    |
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