The digital education revolution - the case of Boxlight corporation

The report in question provides an overall assessment of Boxlight Corporation's performance as of 12/31/2022 and is a section of the Annex to the Boxlight Corporation Company Report. To assess the company, we developed a historical analysis of the Corporation compared with a market overview analyzing its core value growth and competition drivers. Our results obtained from the Discounted Cash-Flow model estimate a target share price of $2.51, with a premium of$ 1.32. Therefore, our recommendation is to BUY Boxlight Corporation stoc

Box-constrained vector optimization: a steepest descent method without “a priori” scalarization

In this paper a notion of descent direction for a vector function defined on a box is introduced. This concept is based on an appropriate convex combination of the “projected” gradients of the components of the objective functions. The proposed approach does not involve an “apriori” scalarization since the coefficients of the convex combination of the projected gradients are the solutions of a suitable minimization problem depending on the feasible point considered. Subsequently, the descent directions are considered in the formulation of a first order optimality condition for Pareto optimality in a box-constrained multiobjective optimization problem. Moreover, a computational method is proposed to solve box-constrained multiobjective optimization problems. This method determines the critical points of the box constrained multiobjective optimization problem following the trajectories defined through the descent directions mentioned above. The convergence of the method to the critical points is proved. The numerical experience shows that the computational method efficiently determines the whole local Pareto front.Multi-objective optimization problems, path following methods, dynamical systems, minimal selection.

Why do financial markets asymmetrically smile? A simple formula in the multi-factor Heston model

A simple approach to determining the Gaussian kernel that constitutes the backbone of the multi-factor Heston model is proposed based on a suitable expansion in powers of volatilities of volatilities. This analysis provides Black-Scholes-like formulas for pricing European vanilla options, allowing for accurate approximations of the option prices under the multi-factor Heston model up to volatilities of volatilities on the order of 50%. The analysis also leads to a simple formula for the implied volatility showing that changes in the convexity of the volatility smile are due only to price skewness, and an easy formula to reproduce volatility indices via the realized volatility. Interestingly, the variance of the Gaussian kernel is equal to the variance of the continuously compounded return in the case of the Heston model. The empirical analyses presented assess the potential of our approach to capture market distortions while adequately forecasting the dynamics of the VIX index

A hybrid method to evaluate pure endowment policies: Crédit Agricole and ERGO Index linked policies

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From bond yield to macroeconomic instability: A parsimonious affine model

We present a hybrid Heston model with a common stochastic volatility to describe government bond yield dynamics. The model is analytically tractable and, therefore, can be efficiently estimated using the maximum likelihood approach and a specific expansion in order to cope with the curse of dimensionality. Twofold is the model contribution. First, it captures changes in the yield volatility and predict future yield values of Germany, French, Italy and Spain. The result is an early-warning indicator which anticipates phases of instability characterizing the time series investigated. Then, the model describes convergence/divergence phenomena among European government bond yields and explores the countries’ reactions to a common monetary policy described through the EONIA interbank rate. We also investigate the potential of this indicator on U.S. data (treasury bills).The research leading to these results has received funding from the European Union, Seventh Framework Programme FP7, under grant agreement FinMaP no. 612955

A calibration procedure for analyzing stock price dynamics in an agent-based framework

In this paper we introduce a calibration procedure for validating of agent based models. Starting from the well-known financial model of (Brock and Hommes, 1998), we show how an appropriate calibration enables the model to describe price time series. We formulate the calibration problem as a nonlinear constrained optimization that can be solved numerically via a gradient-based method. The calibration results show that the simplest version of the Brock and Hommes model, with two trader types, fundamentalists and trend-followers, replicates nicely the price series of four different markets indices: the S&P 500, the Euro Stoxx 50, the Nikkei 225 and the CSI 300. We show how the parameter values of the calibrated model are important in interpreting the trader behavior in the different markets investigated. These parameters are then used for price forecasting. To further improve the forecasting, we modify our calibration approach by increasing the trader information set. Finally, we show how this new approach improves the model׳s ability to predict market prices