arXiv subjects

Vladimír Holý

Publications and source records attributed to Vladimír Holý.

26 records · Page 2Linked to original sources

arXiv2021

Bertram's Pairs Trading Strategy with Bounded Risk

Finding Bertram's optimal trading strategy for a pair of cointegrated assets following the Ornstein--Uhlenbeck price difference process can be formulated as an unconstrained convex optimization problem for maximization of expected profit per unit of time. This model is generalized to the form where the riskiness of profit, measured by its per-time-unit volatility, is controlled (e.g. in case of existence of limits on riskiness of trading strategies imposed by regulatory bodies). The resulting optimization problem need not be convex. In spite of this undesirable fact, it is demonstrated that the problem is still efficiently solvable. In addition, the problem that parameters of the price difference process are never known exactly and are imprecisely estimated from an observed finite sample is investigated (recalling that this problem is critical for practice). It is shown how the imprecision affects the optimal trading strategy by quantification of the loss caused by the imprecise estimate compared to a theoretical trader knowing the parameters exactly. The main results focus on the geometric and optimization-theoretic viewpoint of the risk-bounded trading strategy and the imprecision resulting from the statistical estimates.

q-fin.MF↗

arXiv2021

The Role of a Nation's Culture in the Country's Governance: Stochastic Frontier Analysis

What role does culture play in determining institutions in a country? This paper argues that the establishment of institutions is a process originating predominantly in a nation's culture and tries to discern the role of a cultural background in the governance of countries. We use the six Hofstede's Cultural Dimensions and the six Worldwide Governance Indicators to test the strength of the relationship on 94 countries between 1996 and 2019. We find that the strongest cultural characteristics are Power Distance with negative effect on governance and Long-Term Orientation with positive effect. We also determine how well countries transform their cultural characteristics into institutions using stochastic frontier analysis.

econ.GN↗

arXiv2021

Modeling Price Clustering in High-Frequency Prices

The price clustering phenomenon manifesting itself as an increased occurrence of specific prices is widely observed and well-documented for various financial instruments and markets. In the literature, however, it is rarely incorporated into price models. We consider that there are several types of agents trading only in specific multiples of the tick size resulting in an increased occurrence of these multiples in prices. For example, stocks on the NYSE and NASDAQ exchanges are traded with precision to one cent but multiples of five cents and ten cents occur much more often in prices. To capture this behavior, we propose a discrete price model based on a mixture of double Poisson distributions with dynamic volatility and dynamic proportions of agent types. The model is estimated by the maximum likelihood method. In an empirical study of DJIA stocks, we find that higher instantaneous volatility leads to weaker price clustering at the ultra-high frequency. This is in sharp contrast with results at low frequencies which show that daily realized volatility has a positive impact on price clustering.

q-fin.ST↗

arXiv2021

Clustering with Penalty for Joint Occurrence of Objects: Computational Aspects

The method of Holý, Sokol and Černý (Applied Soft Computing, 2017, Vol. 60, p. 752-762) clusters objects based on their incidence in a large number of given sets. The idea is to minimize the occurrence of multiple objects from the same cluster in the same set. In the current paper, we study computational aspects of the method. First, we prove that the problem of finding the optimal clustering is NP-hard. Second, to numerically find a suitable clustering, we propose to use the genetic algorithm augmented by a renumbering procedure, a fast task-specific local search heuristic and an initial solution based on a simplified model. Third, in a simulation study, we demonstrate that our improvements of the standard genetic algorithm significantly enhance its computational performance.

cs.AI↗

arXiv2020

Economic Conditions for Innovation: Private vs. Public Sector

The Hicks induced innovation hypothesis states that a price increase of a production factor is a spur to invention. We propose an alternative hypothesis restating that a spur to invention require not only an increase of one factor but also a decrease of at least one other factor to offset the companies' cost. We illustrate the need for our alternative hypothesis in a historical example of the industrial revolution in the United Kingdom. Furthermore, we econometrically evaluate both hypotheses in a case study of research and development (R&D) in 29 OECD countries from 2003 to 2017. Specifically, we investigate dependence of investments to R&D on economic environment represented by average wages and oil prices using panel regression. We find that our alternative hypothesis is supported for R&D funded and/or performed by business enterprises while the original Hicks hypothesis holds for R&D funded by the government and R&D performed by universities. Our results reflect that business sector is significantly influenced by market conditions, unlike the government and higher education sectors.

econ.GN↗

arXiv2020

Clustering of Arrivals in Queueing Systems: Autoregressive Conditional Duration Approach

Arrivals in queueing systems are typically assumed to be independent and exponentially distributed. Our analysis of an online bookshop, however, shows that there is an autocorrelation structure present. First, we adjust the inter-arrival times for diurnal and seasonal patterns. Second, we model adjusted inter-arrival times by the generalized autoregressive score (GAS) model based on the generalized gamma distribution in the spirit of the autoregressive conditional duration (ACD) models. Third, in a simulation study, we investigate the effects of the dynamic arrival model on the number of customers, the busy period, and the response time in queueing systems with single and multiple servers. We find that ignoring the autocorrelation structure leads to significantly underestimated performance measures and consequently suboptimal decisions. The proposed approach serves as a general methodology for the treatment of arrivals clustering in practice.

stat.AP↗

arXiv2020

How Many Customers Does a Retail Store Have?

The knowledge of the number of customers is the pillar of retail business analytics. In our setting, we assume that a portion of customers is monitored and easily counted due to the loyalty program while the rest is not monitored. The behavior of customers in both groups may significantly differ making the estimation of the number of unmonitored customers a non-trivial task. We identify shopping patterns of several customer segments which allows us to estimate the distribution of customers without the loyalty card using the maximum likelihood method. In a simulation study, we find that the proposed approach is quite precise even when the data sample is very small and its assumptions are violated to a certain degree. In an empirical study of a drugstore chain, we validate and illustrate the proposed approach in practice. The actual number of customers estimated by the proposed method is much higher than the number suggested by the naive estimate assuming the constant customer distribution. The proposed method can also be utilized to determine penetration of the loyalty program in the individual customer segments.

stat.AP↗

arXiv2020

The Role of Shopping Mission in Retail Customer Segmentation

In retailing, it is important to understand customer behavior and determine customer value. A useful tool to achieve such goals is the cluster analysis of transaction data. Typically, a customer segmentation is based on the recency, frequency and monetary value of shopping or the structure of purchased products. We take a different approach and base our segmentation on the shopping mission - a reason why a customer visits the shop. Shopping missions include focused purchases of specific product categories and general purchases of various sizes. In an application to a Czech drugstore chain, we show that the proposed segmentation brings unique information about customers and should be used alongside the traditional methods.

stat.AP↗