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An empirical data analysis of "price runs" in daily financial indices: Dynamically assessing market geometric distributional behavior.

ABSTRACT: In financial time series there are time periods in which market indices values or assets prices increase or decrease monotonically. We call those events "price runs", "elementary uninterrupted trends" or just "uninterrupted trends". In this paper we study the distribution of the duration of uninterrupted trends for the daily indices DJIA, NASDAQ, IPC and Nikkei 225 during the period of time from 10/30/1978 to 08/07/2020 and we compare the simple geometric statistical model with [Formula: see text] consistent with the EMH to the empirical data. By a fitting procedure, it is found that the geometric distribution with parameter [Formula: see text] provides a good model for uninterrupted trends of short and medium duration for the more mature markets; however, longest duration events still need to be statistically characterized. Estimated values of the parameter p were also obtained and confirmed by calculating the mean value of p fluctuations from empirical data. Additionally, the observed trend duration distributions for the different studied markets are compared over time by means of the Anderson-Darling (AD) test, to the expected geometric distribution with parameter [Formula: see text] and to a geometric distribution with a free parameter p, making possible to assess and compare different market geometric behavior for different dates as well as to measure the fraction of time runs duration from studied markets are consistent with the geometric distribution with [Formula: see text] and in parametric free way.

SUBMITTER: Olivares-Sanchez HR

PROVIDER: S-EPMC9262240 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Herd behaviour in financial markets is a recurring phenomenon that exacerbates asset price volatility, and is considered a possible contributor to market fragility. While numerous studies investigate herd behaviour in financial markets, it is often considered without reference to the pricing of financial instruments or other market dynamics. Here, a trader interaction model based upon informational cascades in the presence of information thresholds is used to construct a new model of asset price returns that allows for both quiescent and herd-like regimes. Agent interaction is modelled using a stochastic pulse-coupled network, parametrised by information thresholds and a network coupling probability. Agents may possess either one or two information thresholds that, in each case, determine the number of distinct states an agent may occupy before trading takes place. In the case where agents possess two thresholds (labelled as the finite state-space model, corresponding to agents' accumulating information over a bounded state-space), and where coupling strength is maximal, an asymptotic expression for the cascade-size probability is derived and shown to follow a power law when a critical value of network coupling probability is attained. For a range of model parameters, a mixture of negative binomial distributions is used to approximate the cascade-size distribution. This approximation is subsequently used to express the volatility of model price returns in terms of the model parameter which controls the network coupling probability. In the case where agents possess a single pulse-coupling threshold (labelled as the semi-infinite state-space model corresponding to agents' accumulating information over an unbounded state-space), numerical evidence is presented that demonstrates volatility clustering and long-memory patterns in the volatility of asset returns. Finally, output from the model is compared to both the distribution of historical stock returns and the market price of an equity index option.

Project description:BackgroundTen U.S. states, Canada, and Uruguay have passed laws to legalize the production and sale of cannabis for non-medical purposes. Available research has documented rapidly falling prices and changing product mixes, but many details are not well understood: particularly, the popularity, prices, and product characteristics of different cannabis edibles and extract-based products - each offering different ways to consume cannabis, with unclear health consequences.MethodsThis paper analyzes data from Washington's recreational cannabis market, which has recorded over 110 million retail item-transactions from July 2014 to October 2017. Previous research on price and product trends has focused mostly on herbal cannabis, which accounts for the majority, but a decreasing share, of sales. This paper applies advanced text-analytic methods to provide new insights, including (A) estimating potency data for edibles and (B) identifying extract sub-types. Patterns and trends are described, across product types, regarding THC and CBD profiles and price per THC.ResultsExtracts accounted for 28.5% of sales in October 2017. Of extracts categorized to subtype, nearly half were identified as "dabs", and another half "cartridges". In October 2017, price per 10 mg THC was roughly $3 among edibles, 70 cents among extract cartridges, and 30-40 cents for other flower and other extracts; solid concentrates offered the lowest priced THC among extract products. Price declines continue but have slowed. High-CBD chemovars are becoming more common, but still are almost non-existent in flower marijuana and rare (1% of sales) among extract products.ConclusionAs Washington's recreational cannabis market has developed over three and a half years, trends identified in that market may serve as an early indication of potential issues in other states. Legislators and regulators in other jurisdictions with commercial non-medical cannabis markets may wish to establish policies responsive to these trends in product popularity, price, and potency.

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An empirical data analysis of "price runs" in daily financial indices: Dynamically assessing market geometric distributional behavior.

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