Bid-ask Spread Research Articles

A machine learning algorithm for stock picking built on information based outliers

Stock picking based on regularities in time series is one of the most studied topics in the financial industry. Various machine learning techniques have been employed for this task. We build a trading strategy algorithm that receives as input indicators defined through outliers in the time series of stocks (return, volume, volatility, bid-ask spread). The procedure identifies the most relevant subset of indicators for the prediction of stock returns by combining an heuristic search strategy, guided from the Information Gain Criterium, with the Naive-Bayes classification algorithm. We apply the methodology to two sets of stocks belonging respectively to the EUROSTOXX50 and the DOW JONES index. Performance is smoother than in the Buy&Hold strategy and yields a higher risk-adjusted return, in particular in a turbulent period. However, outperformance vanishes when transaction costs (5–15 basis points) are inserted. Asset return and return/volume serial correlation turn out to be the most relevant indicators to build the trading algorithm.

Dynamics of return and liquidity (co) jumps in emerging foreign exchange markets

We investigate the dynamics of return and liquidity (co) jumps for three of the most traded emerging market currencies vis-à-vis US dollar. Accordingly, an increase in the average bid-ask spread (realized volatility) significantly reduces the duration between consecutive return (liquidity) jumps, while liquidity and volatility only play a partial role on the duration between consecutive return-liquidity cojumps. There is also evidence of vicious return-liquidity spirals in views of the positive contemporaneous impact of liquidity jumps on volatility and return jumps on the bid-ask spread. Finally, scheduled macroeconomic news and central bank announcements increase the likelihood of both return and liquidity (co) jumps.

Failing to forecast rare events

Do more talented traders prefer to bet on and against rare events or common events? Bets on rare events include out of the money options. Bets against rare events include the carry trade and investment grade bonds. In a model where traders specialize, equilibrium pricing reflects trading ability: A market with more skilled traders has a larger bid ask spread. We show that lower skill traders bet on and against rare events, while higher skill traders bet on and against frequent events, leading to higher bid-ask spreads in common event assets, and reducing financial markets’ ability to predict rare events.

ANALISIS PERBANDINGAN TRADING VOLUME ACTIVITY, ABNORMAL RETURN SAHAM DAN BID ASK SPREAD SEBELUM DAN SESUDAH STOCK SPLIT

A stock split is when a company divides the existing shares of its stock into multiple new shares. The split is done by dividing each existing shares into more than one shares. A lower share price can make the stock more attractive to a broad range of investors so that the sale of shares can be further increased. This study aims to determine the differences in trading volume activity, abnormal returns and bid-ask spreads before and after the stock split. The event window used in this study is 20 days consisting of 10 days before the stock split and 10 days after the stock split. This study was conducted on 28 companies that announcess Stock Splits during the 2015-2019 period. The method used in this study was to use the Wilcoxon signed rank test which was processed with the help of SPSS version 25. The results of this study indicate that there are significant differences in Trading Volume Activity and Abnormal Return before and after the announcement of Stock Split

Funding Liquidity and Market Liquidity: The Broker-Dealer Perspective

We provide direct evidence of how dealers’ funding liquidity affects their liquidity provision in securities markets. Worse funding liquidity (higher repo haircuts and rates) leads to larger bid-ask spreads and transaction costs in corporate bonds. We also find that dealers’ relationships with money funds are important determinants of their repo haircuts and rates. Using dealers’ exposure to the 2016 Securities and Exchange Commission (SEC) money fund reform as an instrument, we show that funding liquidity indeed has a causal effect on market liquidity. Finally, dealers with lower funding liquidity tend to have smaller market shares and execute more trades on an agency basis. This paper was accepted by Haoxiang Zhu, finance.

Forecasting the intra-day effective bid ask spread by combining density forecasts

ABSTRACT The bid-ask spread refers to the tightness dimension of liquidity and can be used as a proxy for transaction costs. Despite the importance of the bid-ask spread in the financial literature, few studies have investigated its forecastability. We propose a new methodology to predict the bid ask spread by combining density forecasts of two types of models: Multiplicative Errors Models and ARMA-GARCH models. Our method is employed to predict the effective intra-day bid-ask spread series of all shares pertaining to the CAC40 index. Using a one-step-ahead out-of-sample framework, we resort on the Model Confidence Set procedure to classify models and we found that the proposed model appears to beat all the benchmark specifications.

THE EFFECT OF COMPANY CHARACTERISTICS TOWARDS CARBON EMISSION DISCLOSURE AND ITS IMPACT ON ECONOMIC CONSEQUENCES IN NON-FINANCIAL REGISTERED COMPANIES IN INDONESIA, MALAYSIA, THAILAND AND THE PHILIPPINES PERIOD FOR 2008-2017

This research was conducted to know the company's characteristics, the determining factors for the disclosure of carbon emissions, and the impact of the disclosure of carbon emissions on economic consequences. The financial result in this study is the decision-making behavior of businesses, governments, and creditors as a result of accounting reporting, in this case, environmental disclosures contained in annual reports and sustainable reports. This study's sample amounted to 45 companies registered in Indonesia, Malaysia, Thailand, and the Philippines, with an observation period of 2008 to 2017. To measure the disclosure of carbon emissions by creating a checklist based on information from the CDP. Company characteristics are proxied by profitability, leverage, size, and sales growth, while economic consequences are proxied by the bid-ask spread, trading volume, and stock price volatility. The analytical method used in this study is the Partial Least Square (PLS) method using the WARP PLS version 5.0 application. From the test results, it was found that Profitability and Size had a positive effect on disclosure of carbon emissions, growth sales had a negative effect, and leverage had no effect. Meanwhile, the impact of disclosing carbon emissions on the bid-ask spread, trading volume, and stock price volatility has a positive effect.

How to Regulate Corporate Social Responsibility Reporting - International Evidence on the Impact of Different Regulatory Approaches

This paper examines how differences in CSR reporting regulations influence their impact on information asymmetry for both the firms affected and their non-affected peers. Using an international sample of firms based in 24 countries, of which 12 countries have adopted CSR regulations, we find that the decrease in bid-ask spreads after CSR mandates is stronger for mandates issued by governments than for those issued by stock exchanges and stronger for mandates requiring standalone CSR reports than for those requiring other formats. We document that CSR mandates also mitigate the information asymmetry of non-affected firms due to comparability externalities. In cross-sectional analyses, we find that the effect on information asymmetry associated with mandates is greater for firms that use well-established reporting guidelines, such as the Global Reporting Initiative (GRI). We control for firms’ CSR performance in sensitivity analyses and find that the decrease in information asymmetry is attributable to increased disclosure rather than to a change in CSR activity.

The impact of arbitrage on market liquidity

I study how arbitrage affects liquidity by analyzing several billion trades in the American Depositary Receipt (ADR) market from 2001 to 2016. Price deviations persist, on average, for 12 min, and mainly arise because of price pressure. Impulse response functions estimated at 1 min intervals indicate that a positive shock to arbitrage—simultaneous trades of the ADR and the home-market share in the opposite direction—decreases deviations and bid-ask spreads. I confirm these findings by exploiting institutional details that create exogenous variation in the impediments to arbitrage across days. Overall, these results suggest that arbitrage decreases price pressure and provides liquidity.

Who provides liquidity, and when?

We model competition for liquidity provision between high-frequency traders (HFTs) and slower execution algorithms (EAs) designed to minimize investors’ transaction costs. Under continuous pricing, EAs dominate liquidity provision by using aggressive limit orders to stimulate HFTs’ market orders. Under discrete pricing, HFTs dominate liquidity provision if the bid-ask spread is binding at one tick. If the tick size (minimum price variation) is not binding, EAs choose between stimulating HFTs and providing liquidity to non-HFTs. Transaction costs increase with the tick size but can be negatively correlated with the bid-ask spread when all traders can provide liquidity.

Regulation and stock market quality: The impact of MiFID II provision on research unbundling

This paper investigates the effects produced by the unbundling of analyst research costs required by MiFID II on market quality, as measured by stock liquidity and price efficiency. We find that the payment of an explicit price for research is associated with a reduction in analyst coverage in the EU. Unexpectedly, the reduction is stronger for large-cap stocks. For mid- and large-cap stocks analyst coverage in the EU is still greater than in the US. The reduction in analyst coverage observed in the EU is part of a downward trend that initiated prior to MiFID II and contributes to close the gap between the two regions. We also find no change in the bid-ask spread for small-, mid- and large-cap stocks, and a slight increase for micro-cap stocks. We observe no significant change in price efficiency. Taken together our findings seem to suggest that there was an overproduction of research in Europe with the previous regulatory regime. However, the growth of passive management and index funds may also explain the observed decrease in coverage.

The Effect of Information Asymmetry and Business Diversification on Cost of Equity Capital

This study aims to examine the effect of information asymmetry and business diversification on the cost of equity capital in mining companies listed in the Indonesia Stock Exchange with a sample of 14 companies for the 2017-2019 period. Data analysis used descriptive research with quantitative research methods in the form of secondary data. Information asymmetry is measured using the bid-ask spread and diversification is measured using the Herfindahl Index proxy while the cost of equity capital is measured using the Ohlson model. Hypothesis testing is carried out using multiple linear regression analysis to see how much influence information asymmetry and diversification have on the cost of equity capital. The result indicated that information asymmetry had a positive impact on the cost of equity capital and business diversification had a positive impact on the cost of equity capital.

Bias in the effective bid-ask spread

The effective bid-ask spread measured relative to the spread midpoint overstates the true effective bid-ask spread in markets with discrete prices and elastic liquidity demand. The average bias is 13%–18% for S&P 500 stocks in general, depending on the estimator used as benchmark, and up to 97% for low-priced stocks. Cross-sectional bias variation across stocks, trading venues, and investor groups can influence research inference. The use of the midpoint also undermines liquidity timing and trading performance evaluations, and can lead non-sophisticated investors to overpay for liquidity. To overcome these problems, the paper proposes new estimators of the effective bid-ask spread.

Product market competition and the cost of equity capital

This paper provides empirical evidence that firms in more competitive industries have lower cost of equity capital than those in concentrated industries. The association between product market competition and the cost of equity capital is more pronounced with lower analyst coverage, lower forecast accuracy, higher forecast dispersion, and higher bid-ask spread. Using import tariff rate reductions as a quasi-natural experiment, we find that tariff reductions intensify domestic product market competition, which in turn reduces firms’ cost of equity capital. When the tariff rate reduction is larger, the more intensified competition reduces the cost of equity capital to a greater extent. Tariff rate reductions also influence firms’ financing policy, cash flow from operations, and growth rate.

The Microstructure of Cointegrated Assets

We define the micro price of multiple cointegrated assets. This yields a notion of fair prices, as a function of the observable state of multiple order books. We compute the microprices of two highly cointegrated assets, using Level-1 data collected on Interactive Brokers. We design an execution algorithm based on this two dimentional microprice and show that it can save half of the bid-ask spread cost. The code for this paper is available here: https://github.com/xhshenxin/Micro_Price

An examination of the liquidity of equity carve-out parents

Although there have been other equity carve-out (ECO) studies, this is the first study to examine the liquidity of ECO parents. We investigate the traded parents of 234 equity carve-outs (ECO) during the period from 1993 to 2018. We examine several variables and their impact on three liquidity measures: bid-ask spread, turnover, and volatility. We confirm the Vijh (1994) liquidity measures: bid-ask spread, turnover, and volatility liquidity measures over seven periods: carve-out announcement, carve-out ex-date, five-day post carve-out period, lock-up date, second event announcement, second event ex-date, and the five-day post second event period. Also, we observe that consistent with Bali, Peng, Shen, and Tang (2014), liquidity can vary over time; liquidity measures peak at the lock-up date and the second event announcement date. In addition, we extend Cao, Field, and Hanka (2004), who excluded equity carve-outs and we observe that carve-out parent liquidity increases at the lock-up period. Moreover, we observe that the type of subsidiary second event can influence carve-out parent liquidity. The implications are that investors can economically benefit from ECO liquidity.

Accuracy of deep learning in calibrating HJM forward curves

We price European-style options written on forward contracts in a commodity market, which we model with an infinite-dimensional Heath–Jarrow–Morton (HJM) approach. For this purpose, we introduce a new class of state-dependent volatility operators that map the square integrable noise into the Filipović space of forward curves. For calibration, we specify a fully parametrized version of our model and train a neural network to approximate the true option price as a function of the model parameters. This neural network can then be used to calibrate the HJM parameters based on observed option prices. We conduct a numerical case study based on artificially generated option prices in a deterministic volatility setting. In this setting, we derive closed pricing formulas, allowing us to benchmark the neural network based calibration approach. We also study calibration in illiquid markets with a large bid-ask spread. The experiments reveal a high degree of accuracy in recovering the prices after calibration, even if the original meaning of the model parameters is partly lost in the approximation step.

ECONOMIC POLICY UNCERTAINTY AND THE BITCOIN MARKET: AN INVESTIGATION IN THE COVID-19 PANDEMIC WITH TRANSFER ENTROPY

This paper investigates the prediction power of economic policy uncertainty on Bitcoin trading (return, volume, and volatility) over the period from May 2013 to June 2019. We employ the Transfer Entropy model with the following two different regimes (i) stationary and (ii) nonstationary assumption. We construct different algorithm calculations for returns, volume and volatility to test how this proxy impacts. We find that the global Economic Policy Uncertainty negatively causes Bitcoin volumes and volatilities. Therefore, under uncertain regimes, investors are risk-averse to trade, which makes the market less volatile. Our findings confirm the existence of pessimistic risk premium, the theory of deteriorating liquidity and the widen bid-ask spread, which lead to a decline in trading volume under uncertainties in the Bitcoin market. By using different reliable data sources as well as expanding timeframe until May 2020 with COVID-19 pandemic, our results remain robust. Hence, the practical implications will be the useful tools for different parties in the Bitcoin market in the financial turbulence context.

Banka Opaklığının Hisse Senedi Fiyat Gecikmesine Etkisi: BİST te İşlem Gören Bankalar Üzerine Bir Araştırma (The Effect of Bank Opacity on Stock Price Delay: A Research on Banks Traded on BIST)

Purpose – The purpose of this study is to determine the effects of opacity on the stock price delay in banks traded on BIST in the 2007-2019 period. Design/methodology/approach – This research uses the data of stock price, bid-ask spread, share turnover, market capitalization, book-to-market ratio, beta, idiosyncratic volatility, and also for opacity analysis it uses the data of investment securities, deposits, total assets, loans, long-term debt, shareholder equity, debt-to-equity ratio. The parameters of the panel regression model were estimated using the generalized least squares (GLS) estimator. Findings – According to the results, it was observed that the banks which have lower stock price, liquidity, beta; higher idiosyncratic volatility, firm value, non-mortgage loans, other opaque assets (derivative financial assets, fixed assets, intangible assets etc.), deposits, long-term debts, equity and total debt to equity ratio are more opaque, and opacity disrupts the price efficiency of stocks and increases the price delay. Discussion – While the price delay is expected to decrease as the stock turnover rate increases, it is seen in the analysis results that the price delay has increased. It is thought that in inefficient and shallow markets speculative transactions may occur, high volume values may not reflect real buyers-sellers, and the limited number of data in the study causes results contrary to expectations.

An Evaluation of the Tracking Performance of Exchange Traded Funds (ETFs): The Case of Indian Index ETFs

The present study investigates how efficiently India-domiciled exchange traded funds (ETFs) replicate the returns of their underlying indices and analyses the factors that determine the tracking performance. We use a three-pronged approach involving Capital Asset Pricing Model (CAPM) regression, cointegration-Vector Error Correction Model methodology and tracking errors (TEs) to assess tracking efficiency. Random-effects panel regression is employed to evaluate how fund-specific factors influence tracking ability. We find that ETFs carry significantly lower exposure towards their indices than what their objective would suggest. Long-run linkages with benchmarks exist for most ETFs, but the price deviations from the indices are fairly persistent. The TEs for the majority of the funds are large and non-trivial. Bid-ask spreads, price-net asset value deviations, fund’s age and, to some extent, its size are the primary factors that influence tracking performance. ETFs in developed markets such as the USA and Europe have been found to exhibit superior benchmarking abilities. The study is expected to assist investors in developing a more efficient ETF portfolio and to help fund providers improve the quality of their offerings.