A Review of the Fractal Market Hypothesis for Trading and Market Price Prediction

This paper provides a review of the Fractal Market Hypothesis (FMH) focusing on financial times series analysis. In order to put the FMH into a broader perspective, the Random Walk and Efficient Market Hypotheses are considered together with the basic principles of fractal geometry. After exploring the historical developments associated with different financial hypotheses, an overview of the basic mathematical modelling is provided. The principal goal of this paper is to consider the intrinsic scaling properties that are characteristic for each hypothesis. In regard to the FMH, it is explained why a financial time series can be taken to be characterised by a 1/t1−1/γ scaling law, where γ>0 is the Lévy index, which is able to quantify the likelihood of extreme changes in price differences occurring (or otherwise). In this context, the paper explores how the Lévy index, coupled with other metrics, such as the Lyapunov Exponent and the Volatility, can be combined to provide long-term forecasts. Using these forecasts as a quantification for risk assessment, short-term price predictions are considered using a machine learning approach to evolve a nonlinear formula that simulates price values. A short case study is presented which reports on the use of this approach to forecast Bitcoin exchange rate values.

Information Efficiency of the European CO2 Trading Market in the Period 2008-2021

This work examined the information efficiency of the European CO2 trading market for the period 2008-2021. The analysis is based on the singular value decomposition (SVD) approach and the task is to test whether the dynamics of logarithmic price differences are consistent with a random process. The results showed that the information efficiency changes over time and scales, which is in line with adaptive market hypothesis notions. High market efficiency was exhibited in Phase II (2008-2012), but large deviations from efficiency, especially for quarterly scale, were exhibited in Phase III. However, Phase IV has shown a behavior that is consistent with the information efficiency. The findings in the present study suggest that the European carbon market is gradually attaining a state of financial maturity.

Can SMEs in the food industry expect competitive advantages from proactive CSR when CSR trade-offs exist?

PurposeThe study aims to examine the effects of proactive vs passive environmental corporate social responsibility (CSR) in the context of small and medium size enterprises (SMEs), factoring in the moderating effects of price and the mediating effects of company–consumer identification(C-C identification) on consumer responses.Design/methodology/approachAn experiment with general consumer samples was conducted. A randomized 2 (CSR levels: proactive CSR vs passive CSR) × 2 (price as a CSR trade-off: higher price vs lower price) full factorial design was used.FindingsThe study findings revealed that proactive environmental CSR not only engendered more positive C-C identification but also resulted in more favorable consumer attitudes, stronger supportive communication intent and purchase intent. In addition, when a company demonstrates proactive CSR, consumers' C-C identification is generally positive irrespective of price differences, and in turn, more positive reactions follow. When a company takes a passive approach and offers lower prices, respondents showed significantly less positive C-C identification, and less favorable responses. This indicates that passive environmental CSR programs can potentially backfire, especially when combined with lower prices. This study also shows the important mediating impact of C-C identification on consumer responses.Originality/valueThis study is one of the few to explore consumer perceptions of and reactions toward the food industry's environmental CSR programs by degree of CSR involvement and price differences in the context of SMEs. This study's findings provide useful information to SME managers and public relations practitioners who work closely with SMEs, allowing them to make informed strategic decisions, especially when they evaluate the extent of their company's commitment to environmentally proactive CSR practices and its communication to consumers.

A survey on recent advances in transmission congestion management

For the last few decades, the power sector has been restructuring throughout the world, and because of this, congestion is bound to take place in the network. Congestion can lead to market failure, violate transmission capability limits and high electricity prices, and end up threatening the power systems’ reliability and security. Increased congestion may also lead to unexpected price differences in power markets leading to market power. In a deregulated power market (DPM), the independent system operator (ISO)’s fundamental challenge is to preserve the power market’s reliability and safety by improving market efficiency when the network is congested. Therefore, congestion management (CM) is essential in DPM and is the key to the power system. This paper carries out a congestion management methods survey to bring together all recent publications in the DPM. It aims to help readers summarize progressive CM methods, along with traditional CM methods that have been discussed so far. In this paper, we have carried out a comparative survey of the various well-known CM methods.

Out of Sync Subnational Housing Markets and Macroprudential Policies in the UK

We examine whether regionally differentiated macroprudential policies can address financial stability concerns and moderate house price differences in the UK. We disaggregate both the household sector and the housing stock in a two-region DSGE model with out of sync subnational housing markets and compare four policy types: standard monetary policy, leaning against the wind monetary policy, national macroprudential policy or one that targets region-specific LTV ratios. In terms of reducing variances of house prices, regionally differentiated macroprudential policy performs best, provided the policy authorities are concerned with stabilising output and house prices rather than simply minimising the variance of inflation.

Time-Invariance Coefficients Tests with the Adaptive Multi-Factor Model

This paper tests a multi-factor asset pricing model that does not assume that the return’s beta coefficients are constants. This is done by estimating the generalized arbitrage pricing theory (GAPT) using price differences. An implication of the GAPT is that when using price differences instead of returns, the beta coefficients are constant. We employ the adaptive multi-factor (AMF) model to test the GAPT utilizing a Groupwise Interpretable Basis Selection (GIBS) algorithm to identify the relevant factors from among all traded exchange-traded funds. We compare the performance of the AMF model with the Fama–French 5-factor (FF5) model. For nearly all time periods less than six years, the beta coefficients are time-invariant for the AMF model, but not for the FF5 model. This implies that the AMF model with a rolling window (such as five years) is more consistent with realized asset returns than is the FF5 model.

The changing retail landscape for tobacco: dollar stores and the availability of cheap cigarettes among tobacco-related priority populations

IntroductionDollar stores are rapidly altering the retail landscape for tobacco. Two of the three largest chains sell tobacco products in more than 24 000 stores across the USA. We sought to examine whether dollar stores are more likely to be located in disadvantaged neighbourhoods and whether dollar stores charge less for cigarettes than other tobacco retailers.MethodsData were collected from a statewide random sample of licensed tobacco retailers in California (n=7678) in 2019. Logistic regression modelled odds of a census tract containing at least one dollar store as a function of tract demographics. Linear mixed models compared price of the cheapest cigarette pack by store type, controlling for tract demographics.ResultsCensus tracts with lower median household income, rural status and higher proportions of school-age youth were more likely to contain at least one dollar store. The cheapest cigarette pack cost less in dollar stores compared with all store types examined except tobacco shops. Estimated price differences ranged from $0.32 (95% CI: 0.14 to 0.51) more in liquor stores and $0.39 (95% CI: 0.22 to 0.57) more in convenience stores, to $0.82 (95% CI: 0.64 to 1.01) more in small markets and $1.86 (95% CI: 1.61 to 2.11) more in stores classified as ‘other’.ConclusionsDollar stores may exacerbate smoking-related inequities by contributing to the availability of cheaper cigarettes in neighbourhoods that are lower income, rural and have greater proportions of youth. Pro-equity retail policies, such as minimum price laws and density reduction policies, could mitigate the health consequences of dollar stores’ rapid expansion.

The price behavior of the MGO bunker market: An integrated causality and interpretive structural modeling approach

Marine fuel price differences of supply centers have a significant effect on operators’ budgets, and so are closely monitored by traders, charterers and shipowners. The aim of this study is to determine the volatility spillovers between the prices of the major fuel centers in the world and to form a hierarchical structure based on the influence and dependence powers of these centers. For this purpose, an integrated structure of causality in variance and Interpretive Structural Modeling (ISM) methods are used. The data set used in this study includes marine gas oil (MGO) prices for 8 fuel centers used extensively in the world, namely: Fujairah, Hong Kong, Houston, Istanbul, New York, Piraeus, Rotterdam, and Singapore. This data consists of 782 daily observations covering a 3-year-period between 14.04.2017 and 13.04.2020. The ISM results reveal that these fuel centers lie at 6 different levels based on their driving and dependence powers, sources of price volatility in the market are Fujairah and Singapore, and the center that is most affected by volatility is Piraeus. In addition to drawing a macro frame for the fuel market, the results obtained are thought to be useful in reducing risk in the market due to uncertainty for stakeholders.

A Fast, Straightforward and Inexpensive Method for the Authentication of Baijiu Spirit Samples by Fluorescence Spectroscopy

The Chinese spirit baijiu is currently the world’s bestselling spirit, with more than ten billion liters sold in 2018. This is a figure that puts its sales higher than whiskey, vodka, gin, and tequila combined. The multitude of baijiu varieties available in the market differ in several ways ranging from aging to the traditional artisanship involved in producing the final spirit to several other features, including the rarity of the bottle. A result of these differences is a wide distribution of prices for the various baijiu products. Consequently, a single bottle of baijiu can cost anywhere from a few dollars, up to thousands of US dollars. The price differences among the various baijiu spirits necessitate the existence of reliable scientific methods that can efficiently differentiate and authenticate the qualities of baijiu spirits. In addition, the existence of such methods facilitates the prevention of counterfeit sales of the final product. Considering this, we introduce an analytical chemistry method that distinguishes amongst different baijiu spirits based on fluorescence spectroscopy. Its attributes include the low cost and convenience that allows analysis either before or while the spirit is in the market. Our work herein focuses on the analysis of thirty different varieties of baijiu spirits from six different distilleries from East Asia and North America by fluorescence emission spectroscopy, which is associated to the price of the product. For the analysis, we employed a HORIBA FLUOROLOG 3 (HORIBA—Jobin Yvon) spectrometer. Major advantages of this method include the low cost, as no consumables except a quartz reusable cuvette are required, the minimal waste, and finally the quick processing of data.