Intentionality and free-will: the crucial effects of neuronal networks on human evolution

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Is (independent) subordination relevant in option pricing?

Monroe (1978) demonstrates that any local semimartingale can be represented as a time-changed Brownian Motion (BM). A natural question arises: does this representation theorem hold when the BM and the time-change are independent? We prove that a local semimartingale is not equivalent to a BM with a time-change that is independent from the BM. Our result is obtained utilizing a class of additive processes: the additive normal tempered stable (ATS). This class of processes exhibits an exceptional ability to accurately calibrate the equity volatility surface. We notice that the sub-class of additive processes that can be obtained with an independent additive subordination is incompatible with market data and shows significantly worse calibration performances than the ATS, especially on short time maturities. These results have been observed every business day in a semester on a dataset of S&P 500 and EURO STOXX 50 options

Factors Driving University Choice: A Principal Component Analysis on Italian Institutions

[EN] When investigating students’ motivations to enroll in university, a wide range of elements related to the overall student experience concerning both the institution and the surrounding context should be taken into account. The current study moves from this point to analyse students’ choice factors from a survey completed by 27,705 students across 23 Italian institutions by means of a logistic Principal Component Analysis. Results confirm the presence of multiple factors jointly influencing students’ choice, with geographical proximity, job opportunities in the region, university reputation and ease of access opposing one another. Aggregating results at institutional level, students’ distribution prove to be highly heterogeneous across universities. From this, a managerial tool is provided to position student population and derive strategic implications.  Finally, policy considerations are reported.http://ocs.editorial.upv.es/index.php/HEAD/HEAD18Azzone, G.; Soncin, M. (2018). Factors Driving University Choice: A Principal Component Analysis on Italian Institutions. Editorial Universitat Politècnica de València. 733-741. https://doi.org/10.4995/HEAD18.2018.8076OCS73374

Additive normal tempered stable processes for equity derivatives and power law scaling

We introduce a simple model for equity index derivatives. The model generalizes well known L\`evy Normal Tempered Stable processes (e.g. NIG and VG) with time dependent parameters. It accurately fits Equity index implied volatility surfaces in the whole time range of quoted instruments, including small time horizon (few days) and long time horizon options (years). We prove that the model is an Additive process that is constructed using an Additive subordinator. This allows us to use classical L\`evy-type pricing techniques. We discuss the calibration issues in detail and we show that, in terms of mean squared error, calibration is on average two orders of magnitude better than both L\`evy processes and Self-similar alternatives. We show that even if the model loses the classical stationarity property of L\`evy processes, it presents interesting scaling properties for the calibrated parameters

The effects of television on scholastic achievement

Thesis (M.A.)--Boston University, 1950

Neural Network Middle-Term Probabilistic Forecasting of Daily Power Consumption

Middle-term horizon (months to a year) power consumption prediction is a main challenge in the energy sector, in particular when probabilistic forecasting is considered. We propose a new modelling approach that incorporates trend, seasonality and weather conditions, as explicative variables in a shallow Neural Network with an autoregressive feature. We obtain excellent results for density forecast on the one-year test set applying it to the daily power consumption in New England U.S.A.. The quality of the achieved power consumption probabilistic forecasting has been verified, on the one hand, comparing the results to other standard models for density forecasting and, on the other hand, considering measures that are frequently used in the energy sector as pinball loss and CI backtesting

A fast Monte Carlo scheme for additive processes and option pricing

In this paper, we present a very fast Monte Carlo scheme for additive processes: the computational time is of the same order of magnitude of standard algorithms for Brownian motions. We analyze in detail numerical error sources and propose a technique that reduces the two major sources of error. We also compare our results with a benchmark method: the jump simulation with Gaussian approximation. We show an application to additive normal tempered stable processes, a class of additive processes that calibrates ``exactly" the implied volatility surface.Numerical results are relevant. This fast algorithm is also an accurate tool for pricing path-dependent discretely-monitoring options with errors of one bp or below

Differential Effects of Rotenone and Amytal on Mitochondrial Electron and Energy Transfer

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OXIDATION OF CHOLINE IN RAT LIVER MITOCHONDRIA.

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