Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS

Date

2020-08-01

Author

Kalayci, Betul
Ozmen, Ayse
Weber, Gerhard Wilhelm

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

373
views

0
downloads

Stochastic differential equations (SDEs) rapidly become one of the most well-known formats in which to express such diverse mathematical models under uncertainty such as financial models, neural systems, behavioral and neural responses, human reactions and behaviors. They belong to the main methods to describe randomness of a dynamical model today. In a financial system, different kinds of SDEs have been elaborated to model various financial assets. On the other hand, economists have conducted research on several empirical phenomena regarding the behaviour of individual investors, such as how their emotions and opinions influence their decisions. All those emotions and opinions are described by the word Sentiment. In finance, stochastic changes might occur according to investors' sentiment levels. In our study, we aim to represent the mutual effects between some financial process and investors' sentiment with constructing a coupled system of non-autonomous SDEs, evolving in time. These equations are hard to assess and solve. Therefore, we express them in a simplified manner by discretization and Multivariate Adaptive Regression Splines (MARS) model. MARS is a strong method for flexible regression and classification with interactive variables. Hereby, we treat time as another spatial variable. Eventually, we present a modern application with real-world data. This study finishes with a conclusion and an outlook towards future studies.

Subject Keywords

Management Science and Operations Research, General Decision Sciences

URI

https://hdl.handle.net/11511/52158

Journal

ANNALS OF OPERATIONS RESEARCH

DOI

https://doi.org/10.1007/s10479-020-03757-8

Collections

Graduate School of Applied Mathematics, Article

Suggestions

OpenMETU
Core

Stochastic differential games for optimal investment problems in a Markov regime-switching jump-diffusion market Savku, E.; Weber, Gerhard Wilhelm (Springer Science and Business Media LLC, 2020-08-01) We apply dynamic programming principle to discuss two optimal investment problems by using zero-sum and nonzero-sum stochastic game approaches in a continuous-time Markov regime-switching environment within the frame work of behavioral finance. We represent different states of an economy and, consequently, investors' floating levels of psychological reactions by aD-state Markov chain. The first application is a zero-sum game between an investor and the market, and the second one formulates a nonzero-sum sto...
Anti-periodic solutions for state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays Sayli, Mustafa; YILMAZ, ENES (Springer Science and Business Media LLC, 2017-11-01) In this paper, we address a new model of neural networks related to the impulsive phenomena which is called state-dependent impulsive recurrent neural networks with time-varying and continuously distributed delays. We investigate sufficient conditions on the existence and uniqueness of exponentially stable anti-periodic solution for these neural networks by employing method of coincide degree theory and an appropriate Lyapunov function. Moreover, we present an illustrative example to show the effectiveness ...
Neural network calibrated stochastic processes: forecasting financial assets Giebel, Stefan; Rainer, Martin (Springer Science and Business Media LLC, 2013-03-01) If a given dynamical process contains an inherently unpredictable component, it may be modeled as a stochastic process. Typical examples from financial markets are the dynamics of prices (e.g. prices of stocks or commodities) or fundamental rates (exchange rates etc.). The unknown future value of the corresponding stochastic process is usually estimated as the expected value under a suitable measure, which may be determined from distribution of past (historical) values. The predictive power of this estimati...
Optimal lot-sizing/vehicle-dispatching policies under stochastic lead times and stepwise fixed costs Alp, O; Erkip, NK; Gullu, R (Institute for Operations Research and the Management Sciences (INFORMS), 2003-01-01) We characterize optimal policies of a dynamic lot-sizing/vehicle-dispatching problem under dynamic deterministic demands and stochastic lead times. An essential feature of the problem is the structure of the ordering cost, where a fixed cost is incurred every time a batch is initiated (or a vehicle is hired) regardless of the portion of the batch (or vehicle) utilized. Moreover, for every unit of demand not satisfied on time, holding and backorder costs are incurred. Under mild assumptions we show that the ...
New approaches to regression by generalized additive models and continuous optimization for modern applications in finance, science and technology Taylan, P.; Weber, Gerhard Wilhelm; Beck, A. (Informa UK Limited, 2007-10-01) Generalized additive models belong to modern techniques frorn statistical learning, and are applicable in many areas of prediction, e.g. in financial mathamatics, computational biology, medicine, chemistry and environmental protection. In these models, the expectation of response is linked to the predictors via a link function. These models are fitted through local scoring algorithm using it scatterplot smoother as building blocks proposed by Hastie and Tibshirani (1987). In this article, we first give it s...

Citation Formats

B. Kalayci, A. Ozmen, and G. W. Weber, “Mutual relevance of investor sentiment and finance by modeling coupled stochastic systems with MARS,” ANNALS OF OPERATIONS RESEARCH, pp. 0–0, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52158.