HFTViz: Visualization for the exploration of high frequency trading data

High Frequency Trading (HFT), mainly based on high speed infrastructure, is a significant element of the trading industry. However, trading machines generate enormous quantities of trading messages that are difficult to explore for financial researchers and traders. Visualization tools of financial data usually focus on portfolio management and the analysis of the relationships between risk and return. Beside risk-return relationship, there are other aspects that attract financial researchers like liquidity and moments of flash crashes in the market. HFT researchers can extract these aspects from HFT data since it shows every detail of the market movement. In this paper, we present HFTViz, a visualization tool designed to help financial researchers explore the HFT dataset provided by NASDAQ exchange. HFTViz provides a comprehensive dashboard aimed at facilitate HFT data exploration. HFTViz contains two sections. It first proposes an overview of the market on a specific date. After selecting desired stocks from overview visualization to investigate in detail, HFTViz also provides a detailed view of the trading messages, the trading volumes and the liquidity measures. In a case study gathering five domain experts, we illustrate the usefulness of HFTViz.

RELATIVE STANDING OF ROE AND ROCE IN EFFECTIVE LIQUIDITY MANAGEMENT: EVIDENCE FROM BANGLADESHI COMMERCIAL BANKS

This study has been designed for examining the effectiveness of liquidity management through the relative standing of ROE and ROCE of Nationalized Commercial Banks in Bangladesh for the duration of 2008–2018. Six NCBs are selected purposively as sample. The study relies on a balanced panel data set of 66 observations which are gathered from the annual reports of banks and analyzed by random effects regression model. However, the research only examined a few variables. The empirical results reveal that the selected NCBs have been portraying better standing in case of ROE than ROCE in effective liquidity management. The value of R2 of ROE is 75.25%; it signifies that the explanatory measures could clarify 75.25% of the variations in ROE. Among the liquidity measures, Assets/Shareholders Equity has highly significant negative effect; Tier 1 Capital/Risk Weighted Assets has highly significant positive effect; Deposits/Assets have some significant positive and Bank Size in terms of Deposits has some significant negative effect on ROE of the selected NCBs.

RELATIVE STANDING OF ROE AND ROCE IN EFFECTIVE LIQUIDITY MANAGEMENT: EVIDENCE FROM BANGLADESHI COMMERCIAL BANKS

This study has been designed for examining the effectiveness of liquidity management through the relative standing of ROE and ROCE of Nationalized Commercial Banks in Bangladesh for the duration of 2008–2018. Six NCBs are selected purposively as sample. The study relies on a balanced panel data set of 66 observations which are gathered from the annual reports of banks and analyzed by random effects regression model. However, the research only examined a few variables. The empirical results reveal that the selected NCBs have been portraying better standing in case of ROE than ROCE in effective liquidity management. The value of R2 of ROE is 75.25%; it signifies that the explanatory measures could clarify 75.25% of the variations in ROE. Among the liquidity measures, Assets/Shareholders Equity has highly significant negative effect; Tier 1 Capital/Risk Weighted Assets has highly significant positive effect; Deposits/Assets have some significant positive and Bank Size in terms of Deposits has some significant negative effect on ROE of the selected NCBs.

Bank capital, liquidity and risk in Ghana

Purpose Capital, risk and liquidity are the vitality of the banking industry, which can improve the efficiency of banking and promote the efficiency of resource allocation. The purpose of this study is to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Design/methodology/approach The authors adopted the system generalized method of moments (GMM) to examine how Basel III new liquidity ratios affect bank capital and risk adjustments and how banks respond to the new liquidity rules. Based on the call reports data from banks, GMM was used to test the hypotheses that new liquidity ratios affect bank capital and risk adjustments, as well as how banks respond to the regulation. Findings The results indicate banks targeted capital, risk and liquidity and simultaneously coordinate short-term adjustments in capital and risk. New liquidity measures enable banks to coordinate risk and liquidity decisions. Short-term adjustments in new liquidity rules inversely impact bank capital. Short-term adjustments in new liquidity rules inversely impact bank capital and capital adjustments adversely affect changes in the liquidity coverage ratio (LCR). Research limitations/implications The primary results revealed that Ghanaian banks simultaneously coordinate and target capital, risk exposure and liquidity level. Also, capital adjustments positively influence risk adjustments and vice versa while bidirectional negative coordination exists between bank capital and risk on one hand and liquidity on the other hand. Short-term adjustments in new liquidity rule inversely impact bank capital and capital adjustments adversely affect changes in the LCR. The findings partially confirm the theoretical predictions of Repullo (2005) regarding the negative links between capital, risk and liquidity but the authors have higher capital induces higher risk. Practical implications Banks should balance off their targeted risk and liquidity in order not to sacrifice capital accumulation for liquidity. Originality/value This research offers new contributions in the research of bank management of capital and liquidity toward banks during a financial crisis from a theoretical perspective and trust management from an applicative perspective.

Liquidity Mismatch Index and Bank Performance

The relationship between liquidity and bank performance in finance literature remains an unresolved empirical issue. The main objective of this article was to investigate the relationship between liquidity mismatch index (LMI) initially developed by Brunnermeier, Gorton and Krishnamurthy (2012) and further developed by Bai, Krishnamurthy, and Weymuller (2018) and South African bank performance empirically. Different from other prior studies, the study undertook to determine the relationship employing the liquidity measure that integrates both market liquidity and funding liquidity within a context of asset liability mismatches. The unit of analysis was a panel of 12 South African banks over the period 2008–2018. Specifically, two liquidity measures – the bank liquidity mismatch index (BLMI) and the aggregate liquidity mismatch index (ALMI) were regressed against bank performance matrices. The newly developed liquidity measures are based on portfolio management theory and they account for the significance of liquidity spirals. Results revealed that, bank performance is negatively and significantly related with BLMI. While the bank performance is positively related to ALMI, the relationship is not significant. Also, the nature of relationship is dependent on the measure of profitability employed.

A DYNAMIC AND STATIC VIEW OF THE FINANCIAL SECURITY OF DAIRY COOPERATIVES

The aim of the research was to identify and assess the dynamic and static dimension of the financial security of dairy cooperatives in the area of liquidity. Cooperatives with a higher equity value than average and with a cash flow statement were purposively selected. The final research sample included 20 dairy cooperatives. The research period covered the period from 2017 to 2019. Statistically speaking, dairy cooperatives are generally financially secure as a result of the specific nature of their business, which is geared towards benefiting their members – milk suppliers – through timely payments for raw material delivered. Most of the entities studied were characterised by over-liquidity in static terms, which should be assessed favourably from the perspective of the cooperative form of management. In dynamic terms, however, not all entities were characterised by favourable values of cash productivity ratios. Static liquidity measures do not provide a complete and transparent picture of the financial security of dairy cooperatives and should be considered both static and dynamic. Only an interpretation of the two dimensions of liquidity indicators will allow an effective interpretation of this issue in relation to dairy cooperatives. Moreover, when assessing liquidity, account should be taken of the specificities of cooperative management activities, where static measures in this area are above literature standards, while dynamic liquidity measures do not always reach satisfactory volumes.

Earnings Management and Stock Liquidity

This chapter tests whether the earnings management practices in Turkey are considered informative or opportunistic by outside investors by examining its effect on stock liquidity. Earnings management is measured by discretionary accruals calculated by two different competing methods. Stock liquidity is also proxied by two different measures: the illiquidity measure of Amihud and the turnover ratio. Amihud's illiquidity measure indicates firms' daily price responses associated with the trading volume and the turnover ratio indicates how many times a stock changes its owner in a year. Relevant control variables are also included in the models. A positive association between earnings management and stock liquidity implies informative earnings management and vice versa. Earnings management is found to be positively associated with stock market liquidity. Results favor the informative earnings management view for Turkish firms and are robust to alternative specifications of earnings management and stock liquidity measures.

Assessing Commonality in Liquidity: Evidence from an Emerging Market’s Index Stocks

This study investigates the degree to which movements in stock liquidity is determined by common underlying factors in a large emerging market, India. This degree is called commonality. Commonality has been measured for NIFTY50 stocks using high frequency data across a variety of liquidity measures. This study empirically verifies the relative strength of market- and industry-wide liquidity in explaining commonality. Furthermore, the study analyses the impact of industry-wide liquidity on the liquidity of individual stocks belonging to the key industries of Indian economy, viz. consumer goods and pharma, energy, financial services, infrastructure, information technology (IT) and telecom, manufacturing and natural resources. Among all the sectors studied infrastructure, IT and telecom, manufacturing and natural resources sectors possess higher degree of Industry-wide commonality. This means fund managers find it difficult in altering a portfolio having greater exposure to these sectors. Studying the behaviour of commonality will also assist regulators in monitoring abnormal market fluctuations. The study contributes to the understanding of commonality on an emerging order driven market like India.