Price-limit effectiveness: evidence from the Borsa Istanbul (BIST)

Purpose This paper aims to analyze the impact of price-limit hits by hit type and when such hits start and stop using intraday trades and quotes at a one-second frequency for firms included in the BIST-50 index during the 13-months starting with March 2008. Like the recent COVID-19 period, this period includes the heightened stress in global financial markets in September 2008. Design/methodology/approach Using intra-day trades and quotes at a one-second frequency, the authors examine the market effects of price limits for firms included in the BIST-50 index during the global financial crisis. The authors compare the values of various metrics for 60 min centered on price-limit hit periods. The authors conduct robustness tests using auto regressive integrated moving average (ARIMA) models with trade-by-trade and with 3-min returns. Findings The findings are supportive of the following hypotheses: magnet price effects, greater informational asymmetric effects of market quality and each version of price discovery. Results are robust using samples differentiated by cross-listed status, same-day quotes instead of transaction prices and equidistant and trade-by-trade returns. Originality/value The authors use intraday data to reduce measurement error that is particularly pronounced when daily data are used to assess price limits that start and/or stop during a trading session. The authors contribute to the micro-structure literature by using ARIMA models with trade-by-trade and 3-min returns to alleviate some bias due to the autocorrelations in returns around price-limit hits in the presence of a magnet effect. The authors include some recent regulation changes in various countries to illustrate the importance of circuit breakers using price limits during COVID-19.

An empirical behavioral order-driven model with price limit rules

We propose an empirical behavioral order-driven (EBOD) model with price limit rules, which consists of an order placement process and an order cancellation process. All the ingredients of the model are determined based on the empirical microscopic regularities in the order flows of stocks traded on the Shenzhen Stock Exchange. The model can reproduce the main stylized facts in real markets. Computational experiments unveil that asymmetric setting of price limits will cause the stock price to diverge exponentially when the up price limit is higher than the down price limit and to vanish vice versa. We also find that asymmetric price limits have little influence on the correlation structure of the return series and the volatility series, but cause remarkable changes in the average returns and the tail exponents of returns. Our EBOD model provides a suitable computational experiment platform for academics, market participants, and policy makers.

AN ECONOMIC ANALYSIS OF THE FACTORS AFFECTING EGGS IMPORTING IN IRAQ FOR THE PERIOD (2003 – 2018 (AND PREDECTION THE EGGS IMPORTING FOR THE PERIOD (2019 – 2025)

This study aimed to determine the most important factors affecting importing of table eggs in Iraq for the period 2003 - 2018. To achieve the objectives the analysis phase was divided into two parts, the first was to measure factors affecting the importing of table eggs in order to obtain a mathematical relationship between the dependent variable (imports) and the independent variables represented by the local price of table eggs and the price limits for table eggs, the exchange rate, the national income, the population, the local production of table eggs, and the number of table egg projects. The second stage was to predict for the period (2019-2025) using the simple regression method. The results showed that the continuous increase in the population will lead to an increase in the imported quantities of table eggs due to the increase in consumer demand for this product eggs, Most estimated parameters of importing function were significant at 5%. The highest expected amount of imported table eggs (10056 million eggs) on 2025, while the lowest amount (7631.36 million eggs) on 2019. It can be concluded that there is no government policies in subsidizing production inputs and supporting the final product. The study recommended for a policy to protect domestic products from foreign competition.

Idiosyncratic volatility and interruption mechanisms in South Korean stock markets

PurposeThe purpose of this study is to examine how the volatility interruption (VI) mechanisms affect idiosyncratic volatilities in Korean stock markets.Design/methodology/approachCollecting the South Korea Stock Market (KOSPI) data from June 15, 2015 to March 31, 2019, we collect each residual, εi,t, from three different estimated models: capital asset pricing model (CAPM), FF3 and FF5. To estimate the conditional idiosyncratic volatility, the authors employ two conditional time-varying measurements: GARCH and TGARCH.FindingsThe results show that the conditional idiosyncratic volatility increases when stock prices reach the upper and lower static limits, indicating the implementation of adopting static VI mechanism neither stabilize market conditions nor reduce excess volatility along with the existence of price limits.Originality/valueAlthough market regulators and policymakers improve market conditions with the advanced VI mechanism, the empirical results show the adverse effect of the mechanism. Not allowing investors to earn above average returns without accepting above average risks makes Korean stock markets inefficient along with advanced VI mechanisms.

Estimating Short-Term Returns with Volatilities for High Frequency Stock Trades in Emerging Economies Using Gaussian Processes (GPs)

Fundamental theorem behind financial markets is that stock prices are intrinsically complex and stochastic in nature. One of the complexities is the volatilities associated with stock prices. Price volatility is often detrimental to the return economics and thus investors should factor it in when making investment decisions, choices, and temporal or permanent moves. It is therefore crucial to make necessary and regular stock price volatility forecasts for the safety and economics of investors’ returns. These forecasts should be accurate and not misleading. Different traditional models and methods such as ARCH, GARCH have been intuitively implemented to make such forecasts, however they fail to effectively capture the short-term volatility forecasts. In this paper we investigate and implement a combination of numeric and probabilistic models towards short-term volatility and return forecasting for high frequency trades. The essence is that: one-day-ahead volatility forecasts were made with Gaussian Processes (GPs) applied to the outputs of a numerical market prediction (NMP) model. Firstly, the stock price data from NMP was corrected by a GP. Since it not easy to set price limits in a market due to its free nature, and randomness of the prices, a censored GP was used to model the relationship between the corrected stock prices and returns. To validate the proposed approach, forecasting errors were evaluated using the implied and estimated data.

CUSTOMER PREFERENCES ON SUSTAINABLE FASHION PURCHASES: A CONCEPTUAL MODEL

This research purpose is to investigate customer motivation when purchasing sustainable fashion. These research objectives are to investigate customers' perception toward sustainable fashion, to determine the preferences of customers in buying sustainable fashion, and the range of price limits of customers in purchasing sustainable fashion. Therefore, for this research, there are several papers that are being reviewed and preliminary research being conducted. The literature analysis and preliminary studies have shown that customer preferences such as Price, Quality, Design, Brand Image, and Promotion influencing sustainable fashion purchases. Based on the literature review and preliminary study, this research was able to produce a simple conceptual framework. This research’ findings will be useful for fashion brand owners in developing their business. These findings can be useful to create pricing strategies, marketing strategies, and product strategies.