Bid Ask Research Articles

Investigating Statistical Features of the FX Bid Ask Series in a Small Economy with a Sizeable Informal Economy

The assessment of the effect of the informal use of a foreign currency on the corresponding FX rates toward the national currency is a very difficult task, requiring direct calculation and modeling. It comes mostly because of the unknown quantity of foreign money used in the informal sector, but also because of the lack of quantitative calculation models. To overcome this gap and to realize a qualitative description of this effect in a concrete economic environment, we propose herein a comparative analysis between the behavior of two typical FX rate series recorded in the Albanian currency market, the Euro-ALL and USD-ALL, providing that the Euro is used commonly as a national currency substitute in the informal economy and the USD is not. So, we have evidenced that the un-stationarity degree of the Bid and Ask spread distribution for the Euro-ALL FX series is higher than for the corresponding USD-ALL case, but with a lower variance. Those features occurring simultaneously can be explained by assuming that informal use of the Euro acts as an additional perturbation on the FX system, imposing high nonstationary, but at the same time it provides reservoir or source features for the money disbalances, reducing the average fluctuations. Next, the depth of the market measured by the average Bid-Ask Spread has resulted in a smaller price for the Euro currency, indicating a lower cost of the transactions and reinforcing the assumption regarding the distribution’s in-stationarity features. Based on those indicatory findings, we propose to realize indirect evidence for our assumptions by comparing the reproduction of the corresponding distribution using autoregressive models. In this case, we have evidenced that the distribution of the FX Euro-ALL spread can be reproduced better if we include in standard ARCHX (m, n, p) models a term that mimics the informality measure. When applying the same procedure for the USD-ALL spread, the resulting distribution has not matched equally well with the original ones. Those findings have been discussed in the framework of an alternative description of the effect of the informal use of foreign currency in a small economy with a sizeable informal sector, which convene our current system under analysis, but we believe that they can be applicable for similar economic environments. Doi: 10.28991/HEF-2024-05-01-02 Full Text: PDF

Adopsi Extensible Business Reporting Language dan Asimetri Informasi

The research objective is to verify the effect of the adoption of Extensible Business Reporting Language (XBRL) on information asymmetry in companies listed on the IDX. The sample was selected using a purposive sampling technique which was then analyzed using multiple linear regression. The research sample consisted of 329 companies with a total sample of 1,974 companies being observed. The results of this study show that the adoption of XBRL has a positive effect on information asymmetry. Firm size and turnover ratio control variables were found to have a negative effect on information asymmetry. The research results have implications for the gap in information distribution and technology acceptance between large and small investors. XBRL can help reduce data aggregation costs, but investors must then understand how to derive the informational benefits of new data. Therefore, investors must weigh the costs of data aggregation against the benefits when deciding whether to use new technologies that are voluntary or mandatory.Keywords: Extensible Business Reporting Language; Information Asymmetry; Bid Ask Spread.

Market Maker Inventory, Bid–Ask Spreads, and the Computation of Option Implied Risk Measures

Abstract We present empirical evidence showing that option-implied risk measures (OIRMs) are substantially impacted by bid–ask spreads in underlying options. Asking prices are more sensitive to shocks than bids, leading to highly skewed distributions of spreads. We derive and estimate a model of market making that empirically matches these asymmetric responses as well as the time-series properties of bid–ask spreads. Using these estimates to obtain bias-corrected option quotes, we compute several popular OIRMs. We find that fear and risk premia associated with market events that affect the center of the return distribution or unpredictable return jumps are on average overstated when relying on option mid-quotes, whereas risk associated with return-tail events is larger once the bias has been corrected.

The Dynamics of Three Currencies’ Bid–Ask Spread From the Perspective of Import–Export Success: Novel Findings for Digital Trade and Sustainable Production

Import and export have been acknowledged for their beneficial effects on sustainable economic development. In the context of economic globalization, the dynamics of exchange rates are more critical and necessary to export success and sustainable development. Therefore, understanding the dynamics of exchange rates contributes to the achievement of export success so as to promote sustainable production. The aim of this research was to find out the dynamics of spreads in foreign exchange rates over 15 years and the systematic relationship between dynamics of spreads in foreign exchange rates and information arrival and dynamics of spreads and cost of carry. The multiple regression, dummy variable test, and vector autoregressive model show that most variations in the spreads result from relative spread rather than information arrival and cost of carry for the long term. The information arrival and cost of carry have almost no influence upon relative spread, even during the global financial crisis in 2008. This article suggests that exporters should pay more attention to the effects of relative spread rather than information arrival and cost of carry in the foreign exchange market when they carry out foreign trade.

BEHAVIOR HOLDING PERIOD DETERMINATION WITH MODERATING YIELD TO MATURITY IN INDONESIA AND MALAYSIA MANUFACTURING OPEN COMPANIES

Study this aim for test Influence Bid Ask Spread, Market value, and Variance Return, Dividend payout ratio to Holding Period with Yield to Maturity as moderating variable. Type of data used that is secondary data in the form of report finance companies listed on the Indonesia Stock Exchange and the Malaysia Stock Exchange. Data analysis techniques used is Moderating Regression Analysis (MRA). Population in research this is whole company manufacturers listed on the Indonesia Stock Exchange and the Malaysia Stock Exchange with population used _ totaling 488 companies with technique purposive sampling method. Variable independent study this is Bid Ask Spread, Market Value, Variance Return, and Dividend Payout Ratio. Variable dependent Mark company be measured with Holding Period. Whereas Yield to Maturity is variable moderation. Research results show Bid Ask Spread, Market Value, Return Variance, Dividend Payout Ratio by simultaneous take effect positive significant to Holding Period. Whereas by Partial Bid Ask Spread, Variance Return and Dividend Payout Ratio take effect positive and significant to Holding Period. Market Value take effect positive However no significant to Holding Period. Then addition Yield to Maturity as moderating variable between variable independent to variable dependent results obtained _ is Bid Ask Spread is positive and significant to Holding Period through Yield to Maturity. Variance Return take effect positive no significant to Holding Period through Yield to Maturity. Whereas Market Value and Dividend Payout Ratio take effect negative no significant to Holding Period through Yield to Maturity.

Linkage Stock Price, Trading Volume Activity, Stock Returns and Trading Frequency on Bid Ask Spread

The purpose of this study was to to examine the effect of stock prices, trading volume activities, stockreturns and trading frequency of the bid ask spread of LQ45 company. Determination of the studysample consist of 42 companies conducted using purposive sampling method. As for hypothesistesting and research instruments using multiple linear regression analysis SPSS 20.0. Result of thisstudy prove that all of the independent variable does not affect the bid ask spread

Effect of Bid Ask Spread, Profitability, and Free Cash Flow on Earning Management

The purpose of this study was to determine the effect of bid ask spread, profitability, and free cash flow on earnings management. The population in this study are manufacturing companies listed on the Indonesia Stock Exchange in 2016-2018. The sampling method used was purposive sampling with predetermined criteria. Earning management is determined by the accruals method. The results of this study stated that the bid ask spread did not have a significant effect on earnings management, while profitability and free cash flow had a significant effect on earnings management.

Determinant of Bid - Ask Spread Share on LQ45 Index Emitents in Indonesia

The rapid development of capital market activities has brought profound changes to the demands of information quality. The issue surrounding stock prices is one indicator that investors consider to invest. So the difference between the selling price and the purchase price of a stock (spread) affects the level of liquidity of the stock. Factors also influence the Bid-Ask Spread, one of which is the stock price. When the stock price is high, it means that the shares are actively traded. Not only stock prices, stock price volatility is also considered to affect investment risk and uncertainty, as seen from fluctuations in stock price volatility. Another variable is the trading volume which describes the activity of the number of shares traded on the capital market, so that indirectly the trading volume of a security gives an influence on the Bid-Ask Spread. The study was conducted on Issuers listed in the LQ45 index for the period January 2016 - July 2019 on the Indonesia Stock Exchange. A sample of 31 companies with secondary data from the LQ45 report published by the Indonesia Stock Exchange. The study uses analysis techniques used to test the hypotheses in this study is the Panel Data Regression Method with the help of Eviews Application. The model chosen is the fixed effect model with the results of negative and significant stock price variables and other variables namely stock volatility, trading volume and positive and significant company size on the bid ask spread. All research variables together have a significant effect on Bid Ask Spread.

Reinvestigate the Bid–Ask Bounce Effect and Pricing of Idiosyncratic Volatility: The Case of the Australian Market

We investigate the bid–ask bounce effect on estimation of idiosyncratic volatility (IVOL) from asset pricing perspective using a comprehensive country-specific sample. We find that the idiosyncratic volatility–return relationship remains significant while controlling for stock size. However, the explanatory power of IVOL disappears completely when stock liquidity is controlled for. These findings support our argument that the bid–ask bounce effect on pricing of IVOL is strongly influenced by stock liquidity. Our results indicate that mid-price is the “true” price to measure IVOL of the least liquid stocks in the Australian stock market.

Roll’s Model of Bid Ask Spread: Implicit Evidence from BSE

This paper empirically studies the bid ask spread model as proposed by Richard Roll using the data from Bombay Stock Exchange (henceforth, BSE). The objective is to understand and determine whether the impact of various events like the abolition of Badla, introduction of Electronic Trading and Futures Trading in BSE, are sufficiently captured by Roll’s model or not. The order processing cost model was taken into consideration for the three period event study, namely: i. Pre and post impact when the Badla was banned, ii. Introduction of Electronic trading in BSE, and iii. Commencement of futures trading in BSE Although the empirical findings presented here are those of the stocks which comprises the Sensex, but it gives a good picture of the market response as a whole as the volume of trading in the BSE is highly skewed in favor of the Sensex scripts.The results indicate that Roll’s model does not fit the data very well. There is a large number of covariance of price change which is positive, which is contrary to the proposed model. The variation of the calculated spread is also significant on a month to month basis. Further research is needed to propose a theoretical framework for Indian stock market.

PENGARUH UKURAN PERUSAHAAN, BID ASK SPREAD, DAN VOLUME PERDAGANGAN TERHADAP PRICE REVERSAL

“Pengaruh Ukuran Perusahaan, Bid Ask Spread, dan Volume Perdagangan Terhadap Price Reversal”is a research that purpose to analyze the factors that affect Price Reversal on companies listed in the Index LQ45 period November 8 - November 16, 2016. This research is an associative study to determine the relationship or influence between two or more variables.
 The population that used in this study are all companies listed in the Indonesia Stock Exchange during the study period. The method of collecting data using purposive sampling. Data that obtained from purposive sampling method is 44 companies. Analyze method which used in this research are multiple linear regression. Testing the hypothesis by using the adjusted coefficient of determination, t-statistic test and f-statistic test.
 The result of this research shows that firm size has positive and significant effect to Price Reversal, Bid Ask Spread has positive and significant effect to Price Reversal, and Trading Volume has positive and significant impact to Price Reversal.
 The implications of the above conclusions are that investors can pay attention to the firm's size factor, bid ask spread and trading volume as a basic for consideration to trade on the exchange to get the best return in accordance with the compensation of the risk that they received.

Components of the Bid–Ask Spread and Variance: A Unified Approach

We develop a structural model for the price formation and liquidity supply of an asset. Our model facilitates decompositions of both the bid–ask spread and the return variance into components related to adverse selection, inventory, and order processing costs. Furthermore, the model shows how the fragmentation of trading volume across trading venues influences inventory pressure and price discovery. We use the model to analyze intraday price formation for gold futures traded at the Shanghai Futures Exchange. We find that order processing costs explain about 50% of the futures bid–ask spread, whereas the remaining 50% is equally due to asymmetric information and to inventory costs. About a third of the variance in futures returns is attributable to microstructure noise. Trading at the spot market has a significant influence on futures price discovery, but only a limited impact on the futures bid–ask spread. © 2016 Wiley Periodicals, Inc. Jrl Fut Mark 36:545–563, 2016

Option Bid–Ask Spread and Liquidity

This article focuses on the search for a economically meaningful and easy to implement summary quantitative measure for option liquidity. The author shows that the relative spread measure (quoted dollar bid–ask spread relative to the midquote price) not only leads to liquidity ranking of options that is contrary to the popular view, but it is also biased against lower-priced options and hence can lead to erroneous conclusion about the liquidity risk premium of options. To gain economic insight in this regard, he uses a simple inventory hedging model of bid–ask spreads. He proposes two alternative summary measures of option liquidity: one using the implied dollar volatility of the asset to scale the dollar spread and the other expressing the bid, ask, and midquote option prices in terms of respective implied volatilities. Using a sample of more than two million end-of-day option quotes for 30 Dow Jones stocks and Goldman Sachs, the author finds that these very simple and intuitive measures seem to produce a liquidity ranking of options that is generally consistent with common knowledge about options liquidity.

Option Bid–Ask Spread and Liquidity

Option Bid–Ask Spread and Liquidity

Intraday Trading and Bid–Ask Spread Characteristics for SPX and SPY Options

With intraday financial data increasingly available, we are now able to explore the microstructure of trading in detail. One feature that is typically seen in intraday stock returns is a clear U-shaped pattern of trading activity: a lot of action after the opening and at the close, with a lower amount around the midday lunch hour. Such patterns are found for various trading measures, including volume, bid–ask spreads, and volatility. Options markets may or may not exhibit a similar pattern as their underlying stocks; evidence is sparse and shows differing results for different markets. Mishra and Daigler find the intraday trading patterns for two closely related index options are quite different. SPX options are written on the S&P 500 index and are traded at the CBOE both electronically and by open outcry. SPY options are written on the SPDR exchange traded fund, which is designed to replicate the daily returns on the S&P 500. The SPDR ETF is traded electronically on many trading platforms. SPX options are traded in large size by financial firms and individuals, whereas SPY options seem to appeal more to the retail trader. As with stocks, SPY options show the U-shaped pattern, whereas it is not found with the SPX. An interesting comparison between the calm environment of 2007 and the market turmoil in 2008 reveals that while trading volume for SPY contracts shot up in the crisis, volume for SPX contracts did not.

Bid–Ask Spreads and Implied Volatilities of Key Players in a FX Options Market

AbstractThis study proposes a simultaneous estimation of the bid–ask spreads (BAS) and implied volatility (IV), based on trading options of various key players in the Israeli OTC FX options market. It explores the surface shape of both variables based on a “clientele effect.” We employ detailed data on OTC foreign exchange options trading that enable us to examine the behavior of the key players (financial companies, non‐financial firms, households, and foreign investors) during relatively turbulent and tranquil periods. Using simultaneous unbiased estimates of BAS and IV, we find substantial differences in BASs among key players while insignificant differences in IV. This evidence reflects differences in key players' profile such as trading size, sophistication and contestability on one hand and a “no arbitrage opportunities” of IV on the other hand. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark

Response of double-auction markets to instantaneous Selling–Buying signals with stochastic Bid–Ask spread

Statistical properties of order-driven double-auction markets with Bid–Ask spread are investigated through the dynamical quantities such as response function. We first attempt to utilize the so-called Madhavan–Richardson–Roomans model (MRR for short) to simulate the stochastic process of the price-change in empirical data sets (say, EUR/JPY or USD/JPY exchange rates) in which the Bid–Ask spread fluctuates in time. We find that the MRR theory apparently fails to simulate so much as the qualitative behaviour (‘non-monotonic’ behaviour) of the response function R(l) (l denotes the difference of times at which the response function is evaluated) calculated from the data. Especially, we confirm that the stochastic nature of the Bid–Ask spread causes apparent deviations from a linear relationship between the R(l) and the auto-correlation function C(l), namely, \({R(l) \propto -C(l)}\). To make the microscopic model of double-auction markets having stochastic Bid–Ask spread, we use the minority game with a finite market history length and find numerically that appropriate extension of the game shows quite similar behaviour of the response function to the empirical evidence. We also reveal that the minority game modeling with the adaptive (‘annealed’) look-up table reproduces the non-linear relationship \({R(l) \propto -f(C(l))}\) (f(x) stands for a non-linear function leading to ‘λ-shapes’) more effectively than the fixed (‘quenched’) look-up table does.

Back from Beyond the Bid–Ask Spread: Estimating Liquidity in International Markets

Research on the topic of liquidity has greatly benefited from the improved availability of data. Researchers have addressed questions regarding the factors that influence bid–ask spreads and the relationship between spreads and risk, return and liquidity. Intraday data have been used to measure the effective spread, and researchers have been able to refine the concepts of liquidity to include the price impact of transactions on a trade‐by‐trade analysis. The growth in the creation of tax‐transparent securities has greatly enhanced the visibility of securitized real estate, and has naturally led to the question of whether the increased visibility of real estate has caused market liquidity to change. Although the growth in the public market for securitized real estate has occurred in international markets, it has not been accompanied by universal publication of transaction data. Therefore, this article develops an aggregate daily data‐based test for liquidity and applies the test to U.S. data in order to check for consistency with the results of prior intraday analysis. If the two approaches produce similar results, we can apply the same technique to markets in which less detailed data are available and offer conclusions on the liquidity of a wider set of markets.

Model‐based quantification of the volatility of options at transaction level with extended count regression models

AbstractIn this paper, we elaborate how Poisson regression models of different complexity can be used in order to model absolute transaction price changes of an exchange‐traded security. When combined with an adequate autoregressive conditional duration model, our modelling approach can be used to construct a complete modelling framework for a security's absolute returns at transaction level, and thus for a model‐based quantification of intraday volatility and risk. We apply our approach to absolute price changes of an option on the XETRA DAX index based on quote‐by‐quote data from the EUREX exchange and find that within our Bayesian framework a Poisson generalized linear model (GLM) with a latent AR(1) process in the mean is the best model for our data according to the deviance information criterion (DIC). While, according to our modelling results, the price development of the underlying, the intrinsic value of the option at the time of the trade, the number of new quotations between two price changes, the time between two price changes and the Bid–Ask spread have significant effects on the size of the price changes, this is not the case for the remaining time to maturity of the option. Copyright © 2006 John Wiley & Sons, Ltd.

The Post-Reform Bid–Ask Spread Disparity between NASDAQ and the NYSE

The Post-Reform Bid–Ask Spread Disparity between NASDAQ and the NYSE