The Tale of Two Financial Crises: An Entropic Perspective

Abstract:We collected data pertaining to Chinese listed commercial banks from 2008 to 2016 and found that the competition between banks is becoming increasingly fierce. Commercial banks have actively carried out diversification strategies for greater returns, and the financial reports show that profits are increasingly coming from the non-interest income benefits of diversification strategies. However, diversification comes with risk. We built a panel threshold model and investigated the effect of income diversification on a bank's profitability and risk. Diversification was first measured by the Herfindahl-Hirschman index (HHI), and the results show that there is a nonlinear relationship between diversification and profitability or risk does exist. We introduced an interesting index based on the entropy to test the robustness of our model and found that a threshold effect exists in both our models, which is statistically significant. We believe the combination of the entropy index (ENTI) and the HHI enables more efficient study of the relationship between diversification and profitability or risk more efficiently. Bankers and their customers have increasingly been interested in income diversification, and they value risk as well. We suggest that banks of different sizes should adopt the corresponding diversification strategy to achieve sustainable development.

Section: The Diversified Use Of Entropymentioning

confidence: 99%

Does Income Diversification Benefit the Sustainable Development of Chinese Listed Banks? Analysis Based on Entropy and the Herfindahl–Hirschman Index

Jiang

Han

2018

“…In our research, we adopt an enhanced time-dependent pattern entropy method introduced in [9] (see also [10,11]) that reduces variations to binary symbolic dynamics and considers the pattern of symbols in a sliding temporal window.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Bentes and Menezes [31] used the concept of Tsallis entropy, which constitutes a possible generalization of the Boltzmann-Gibbs or Shannon entropy to investigate the volatility of seven indexes. It was also used in a comparative analysis of stock markets before the financial crisis in 1987 and 2008 [10]. A review of the application of entropy in finance can be found in [32][33][34].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Permutation Entropy as a Measure of Information Gain/Loss in the Different Symbolic Descriptions of Financial Data

Kozák

Kania

Juszczuk

2020

Financial markets give a large number of trading opportunities. However, over-complicated systems make it very difficult to be effectively used by decision-makers. Volatility and noise present in the markets evoke a need to simplify the market picture derived for the decision-makers. Symbolic representation fits in this concept and greatly reduces data complexity. However, at the same time, some information from the market is lost. Our motivation is to answer the question: What is the impact of introducing different data representation on the overall amount of information derived for the decision-maker? We concentrate on the possibility of using entropy as a measure of the information gain/loss for the financial data, and as a basic form, we assume permutation entropy with later modifications. We investigate different symbolic representations and compare them with classical data representation in terms of entropy. The real-world data covering the time span of 10 years are used in the experiments. The results and the statistical verification show that extending the symbolic description of the time series does not affect the permutation entropy values.

“…Zhou et al [32] investigated the properties of six kinds of entropy based on risk measures and discovered that none of the risk measures satisfied the system's properties. Based on the 1987 and 2008 financial crises, Gençay and Gradojevic [33] provided a comparative analysis of stock market dynamics and successfuly predicted that aggregate market expectations use risk management measures based on entropy. Considering that large consumers needed to decide their energy procurement strategy, Gao et al [34] developed an electric energy procurement decision-making model and analyzed the entropy characteristic of the model.…”

Section: Introductionmentioning

confidence: 99%

The Entropy Complexity of an Asymmetric Dual-Channel Supply Chain with Probabilistic Selling

Huang

2018

Considering consumers’ attitudes to risks for probabilistic products and probabilistic selling, this paper develops a dynamic Stackelberg game model of the supply chain considering the asymmetric dual-channel structure. Based on entropy theory and dynamic theory, we analyze and simulate the influences of decision variables and parameters on the stability and entropy of asymmetric dual-channel supply chain systems using bifurcation, entropy diagram, the parameter plot basin, attractor, etc. The results show that decision variables and parameters have great impacts on the stability of asymmetric dual-channel supply chains; the supply chain system will enter chaos through flip bifurcation or Neimark–Sacker bifurcation with the increase of the system entropy, and thus the system is more complex and falls into a chaotic state, with its entropy increased. The stability of the system can become robust with the increase of the probability that product a becomes a probabilistic product, and it weakens with the increase of the risk preference of customers for probabilistic products and the relative bargaining power of the retailer. A manufacturer using the direct selling channel may obtain greater profit than one using traditional selling channels. Using the method of parameter adjustment and feedback control, the entropy of the supply chain system will decline, and the supply chain system will fall into a stable state. Therefore, in the actual market of probabilistic selling, the manufacturers and retailers should pay attention to the parameters and adjustment speed of prices and ensure the stability of the game process and the orderliness of the dual-channel supply chain.