scholarly journals Using Bibliometric Indicators from Patent Portfolio Valuation as Value Factor for Generating Smart Beta and Index Products

2020 ◽  
Author(s):  
Andreas Zagos ◽  
Stelian Brad
Keyword(s):  
Current Paper ◽  
Bibliometric Indicators ◽  
Market Data ◽  
Patent Value ◽  
Financial Products ◽  
A Value ◽  
Real Market ◽  
Portfolio Valuation ◽  
Patent Portfolio ◽  
Smart Beta

This paper goal is to present the results the use of patent valuation indicators as alternative data which can generate a value factor which is suitable to design financial products. Based on different patent value indicators which address the areas “assignee”, “technology” and “market” an “IP portfolio index” was designed and backtested with real market data. The outperformance of the IP portfolio index is shown in the current paper.

scholarly journals Integrating ESG Analysis into Smart Beta Strategies

2020 ◽  
Vol 12 (22) ◽  
pp. 9351
Author(s):  
Federica Ielasi ◽  
Paolo Ceccherini ◽  
Pietro Zito
Keyword(s):  
Investment Analysis ◽  
The Other ◽  
Portfolio Rebalancing ◽  
A Value ◽  
Ex Post ◽  
The Us ◽  
Ex Ante ◽  
The Impact ◽  
Smart Beta ◽  
Increase In Risk

Smart beta strategy is an increasingly frequent approach to investment analysis for portfolio selection and optimization and it can be combined with environmental, social, and governance (ESG) considerations. In order to verify the impact of the integration between ESG and smart beta analysis, first we apply a portfolio rebalancing based on ESG scores on securities selected according to different smart beta strategies (ex-post ESG rebalancing approach). Secondly, we apply different smart beta approaches to sustainable portfolios, screened according to the issuers’ ESG scores (ex-ante ESG screening approach). We find that ESG rebalancing and screening are able to impact both on return and risk statistics, but with a different level of efficiency for each smart beta strategy. ESG rebalancing proves to be particularly efficient when it is applied to a “Value” portfolio. On the other hand, when smart beta is applied to ESG-screened portfolios, “Growth” is the strategy which shows the highest increase in risk-adjusted performance, particularly in the US. Minimum volatility proves to be the most efficient smart beta strategy for sustainable portfolios. In general, the increase in the level of sustainability does not deteriorate the risk-adjusted performances of most smart beta strategies.

A value- and expectancy-based approach to understanding residents’ intended response to a wildfire threat

2016 ◽  
Vol 25 (4) ◽  
pp. 378 ◽  
Author(s):  
Ilona M. McNeill ◽  
Patrick D. Dunlop ◽  
Timothy C. Skinner ◽  
David L. Morrison
Keyword(s):  
Decision Making ◽  
Current Paper ◽  
Potential Outcomes ◽  
Positive Outcomes ◽  
A Value ◽  
Wait And See ◽  
Fire Threat ◽  
Scenario Study

To motivate residents to evacuate early in case of a wildfire threat, it is important to know what factors underlie their response-related decision-making. The current paper examines the role of the value and expectancy tied to potential outcomes of defending vs evacuating on awareness of a community fire threat. A scenario study among 339 Western Australians revealed that residents intending to leave immediately on awareness of a community fire threat differ from those not intending to leave immediately in both value and expectancy. For one, intended leavers were more likely than those intending to defend their property to have children. Also, the data showed a trend towards intended leavers being less likely to have livestock. Furthermore, intended leavers placed less importance on the survival of their property than those with other expressed intentions. They also reported lower expectancies regarding the likelihood of achieving positive outcomes by defending than those intending to defend or wait and see before deciding what to do. Finally, intended leavers perceived it more likely that they would avoid harm to their pets by evacuating than those intending to defend throughout or wait and see. These findings have important implications for strategies to influence residents’ response-related decision-making.

MODELING AND SIMULATION OF SEQUENTIAL AUCTIONS: PRICING AND CALIBRATION ALGORITHMS

2012 ◽  
Vol 03 (03) ◽  
pp. 1250009 ◽  
Author(s):  
EMMANUEL M. TADJOUDDINE
Keyword(s):  
Market Price ◽  
Payoff Function ◽  
Stochastic Volatility Model ◽  
Sequential Auctions ◽  
Future Market ◽  
Market Data ◽  
Algorithmic Differentiation ◽  
Financial Products ◽  
Volatility Model ◽  
The Right

We consider sequential auctions wherein seller and bidder agents need to price goods on sale at the 'right' market price. We propose algorithms based on a binomial model for both the seller and buyer. Then, we consider the problem of calibrating pricing models to market data. To this end, we studied a stochastic volatility model used for option pricing, derived, and analyzed Monte Carlo estimators for computing the gradient of a certain payoff function using Finite Differencing and Algorithmic Differentiation. We then assessed the accuracy and efficiency of both methods as well as their impacts into the optimization algorithm. Numerical results are presented and discussed. This work can benefit those engaged in electronic trading or investors in financial products with the need for fast and more precise predictions of future market data.

Quality preferences and pricing of fresh-cut salads in Italy: new evidence from market data

2017 ◽  
Vol 119 (7) ◽  
pp. 1473-1486 ◽  
Author(s):  
Vittoria Pilone ◽  
Antonio Stasi ◽  
Antonio Baselice
Keyword(s):  
Consumer Preferences ◽  
Hedonic Price ◽  
Product Price ◽  
Market Data ◽  
Content Type ◽  
Organic Certification ◽  
Fresh Cut ◽  
Real Market ◽  
Set Up ◽  
The Impact

Purpose In Europe fresh-cut fruit and vegetables, is one of the major growing segments in agro-food sector. Current literature reports a limited number of studies about consumers’ preferences towards these products. In particular, it lacks of studies focussed on fresh-cut salads and based on market data. In this paper, a study on consumer preferences towards the main attributes of Italian fresh-cut salads is proposed. More specifically the investigation is focussed on attributes assessable by consumers before purchase such as assortment, tenderness, product preparation and vegetable variety together with brand, size and type of packaging, presence of organic certification, promotion and product price. The purpose of this paper is to evaluate how much Italian consumers pay for those attributes with the aim to understand how much profitable could be different strategies in the sector. Design/methodology/approach The analysis is based on IRI-Infoscan scanner data, consisting of 881 fresh-cut products. The impact of each attributes on pricing is measured by means of a hedonic price model. Findings Main results show that, in Italy, fresh-cut salad price is greatly affected by tenderness, product preparation, assortment, brand, presence of organic certification, packaging attributes and vegetable variety. Practical implications Findings offer to producers the possibility to set up products by composing the mix of attributes that gives back the highest price. In addition, they provide some insights to define manufacturer’s strategies. Originality/value This paper represents a novelty in economic literature because it can be considered an example of consumer preferences analysis towards the different attributes of fresh-cut vegetables based on real market data.

scholarly journals A COMPARISON BETWEEN MRA AND ROUGH SET THEORY FOR MASS APPRAISAL. A CASE IN BARI

2004 ◽  
Vol 8 (4) ◽  
pp. 205-217 ◽  
Author(s):  
Maurizio D'amato
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Property Market ◽  
Specific Group ◽  
Market Data ◽  
Property Valuation ◽  
A Value ◽  
Valuation Methodology ◽  
The Relationship

Rough Set Theory is a property valuation methodology recently applied to property market data (d'Amato, 2002). This methodology may be applied in property market where few market data are available or where econometric analysis may be difficult or unreliable. This methodology was introduced by a polish mathematician (Pawlak, 1982). The model permit to estimate a property without defining an econometric model, although do not give any estimation of marginal or hedonic prices. I : ,he first version of RST was necessary to organize the data in classes before the valuation .The relationship between these classes defined if‐then rules. If a property belongs to a specific group then it will belong to a class of value. The relationship between the property and the class of value is dichotomous. In this paper will be offered a second version that improve the RST with a “value tolerance relation” in order to make more flexible the rule. In this case the results will come out from an explicit and specific relationship. The methodology has been tested on 69 transactions in the zone of Carrassi-Poggiofranco in the residential property market of Bari.

scholarly journals VOLATILITY EFFECTS ON THE ESCAPE TIME IN FINANCIAL MARKET MODELS

2008 ◽  
Vol 18 (09) ◽  
pp. 2775-2786 ◽  
Author(s):  
BERNARDO SPAGNOLO ◽  
DAVIDE VALENTI
Keyword(s):  
Stock Price ◽  
Probability Function ◽  
Initial Conditions ◽  
Market Model ◽  
Statistical Characteristics ◽  
Hitting Times ◽  
Escape Time ◽  
Cubic Nonlinearity ◽  
Market Data ◽  
Real Market

We briefly review the statistical properties of the escape times, or hitting times, for stock price returns by using different models which describe the stock market evolution. We compare the probability function (PF) of these escape times with that obtained from real market data. Afterwards we analyze in detail the effect both of noise and different initial conditions on the escape time in a market model with stochastic volatility and a cubic nonlinearity. For this model, we compare the PF of the stock price returns, the PF of the volatility and the return correlation with the same statistical characteristics obtained from real market data.

CONVEX REGULARIZATION OF LOCAL VOLATILITY ESTIMATION

2017 ◽  
Vol 20 (01) ◽  
pp. 1750006 ◽  
Author(s):  
VINICIUS ALBANI ◽  
ADRIANO DE CEZARO ◽  
JORGE P. ZUBELLI
Keyword(s):  
Implied Volatility ◽  
Convergence Rates ◽  
Surface Model ◽  
Option Prices ◽  
Local Volatility ◽  
Market Data ◽  
Regularization Techniques ◽  
Convex Regularization ◽  
Real Market ◽  
Volatility Surface

We apply convex regularization techniques to the problem of calibrating Dupire’s local volatility surface model taking into account the practical requirement of discrete grids and noisy data. Such requirements are the consequence of bid and ask spreads, quantization of the quoted prices and lack of liquidity of option prices for strikes far away from the at-the-money level. We obtain convergence rates and results comparable to those obtained in the idealized continuous setting. Our results allow us to take into account separately the uncertainties due to the price noise and those due to discretization errors, thus, allowing estimating better discretization levels both in the domain and in the image of the parameter to solution operator by a Morozov’s discrepancy principle. We illustrate the results with simulated as well as real market data. We also validate the results by comparing the implied volatility prices of market data with the computed prices of the calibrated model.

scholarly journals Calibration and simulation of Heston model

2017 ◽  
Vol 15 (1) ◽  
pp. 679-704 ◽  
Author(s):  
Milan Mrázek ◽  
Jan Pospíšil
Keyword(s):  
Variance Reduction ◽  
Calibration Procedure ◽  
Optimization Techniques ◽  
Stochastic Volatility Model ◽  
Heston Model ◽  
Approximation Formula ◽  
Market Data ◽  
Volatility Model ◽  
Calibration Methods ◽  
Real Market

Abstract We calibrate Heston stochastic volatility model to real market data using several optimization techniques. We compare both global and local optimizers for different weights showing remarkable differences even for data (DAX options) from two consecutive days. We provide a novel calibration procedure that incorporates the usage of approximation formula and outperforms significantly other existing calibration methods. We test and compare several simulation schemes using the parameters obtained by calibration to real market data. Next to the known schemes (log-Euler, Milstein, QE, Exact scheme, IJK) we introduce also a new method combining the Exact approach and Milstein (E+M) scheme. Test is carried out by pricing European call options by Monte Carlo method. Presented comparisons give an empirical evidence and recommendations what methods should and should not be used and why. We further improve the QE scheme by adapting the antithetic variates technique for variance reduction.

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