Measuring Bond-Level Liquidity

Konstantinovsky, Vadim; Ng, Kwok Yuen; Phelps, Bruce D.

doi:10.3905/jpm.2016.42.4.116

Cited by 17 publications

(2 citation statements)

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“…This is consistent with the literature. [Konstantinovsky et al, 2016] argued that recent and large issues are cheaper to trade than seasoned and small ones, so bond age and issue size matter. High-risk securities (i.e., bonds with wide spreads to Treasuries) tend to be more expensive to trade than low-risk ones.…”

Section: Results From Two-step Lasso Regressionmentioning

confidence: 99%

Transaction Cost Analytics for Corporate Bonds

Guo¹,

Lehalle²,

Xu³

2019

Preprint

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With the rise of the electronic trading, corporate bond traders have access to data information of past trades. As a first step to automation, they have to start monitoring their own trades, and using past data to build a benchmark for the expected transaction costs with given bond characteristics and market conditions. Given the limited liquidity of corporate bonds which are traded few times daily, a statistical model is the only way to benchmark effective costs. It brings focused attention of the dealing desk of an institutional investor on the most costly trades, and enables identifying and improving business practices such as the market timing for selection counterparties.Unlike existing literature which focuses on general measurements using OLS, this paper takes the viewpoint of a given investor, and provides an analytical approach to establish a benchmark for transaction cost analysis in corporate bond tradings. Regularized methods are used to improve the selection of explanatory variables, as fewer variables provide easier analytics from a business perspective. This benchmark is constructed in two steps. The first step is the regression analysis with cross validation to identify abnormal trades. Three regression approaches, OLS, two-step Lasso and Elastic Net, are adopted to identify key features for the bid-ask spread of corporate bonds. The second step is to use the non-parametric approach to estimate the amplitude and decay pattern of price impact. A key discovery is the price impact asymmetry between customer-buy orders and consumer-sell orders. This benchmark can aid decision makings for retail investors when requesting quotes on the electronic platform.

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Section: Results From Two-step Lasso Regressionmentioning

confidence: 99%

Transaction Cost Analytics for Corporate Bonds

Guo¹,

Lehalle²,

Xu³

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Our third measure of liquidity, Liquidity Cost Score ( LCS ), is an estimate of transaction costs based on trader quotes. This measure (commercially offered by Barclays) uses the methodology introduced by Konstantinovsky, Ng, and Phelps (2016) and bid‐ask quotes data from Barclays trading desks 6 . LCS is an estimate of the cost of an institutional round‐lot transaction, measured as a percentage of the bond's price (hence a lower LCS signifies better liquidity).…”

Section: Sample and Methodologymentioning

confidence: 99%

Credit ETFs in Mutual Funds and Corporate Bond Liquidity

Meli

Todorova

2023

Financial Market

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We show that high yield (HY) mutual funds own and trade ETFs to manage liquidity needs driven by fund flows, whereas investment grade (IG) funds do not. The use of ETFs by HY mutual funds to manage liquidity shifts some trading away from bonds and into ETFs, which reduces the liquidity of the underlying bonds. This substitution effect outweighs the better-understood inclusion effect, whereby bond liquidity benefits from increased ETF ownership, such that the net effect of ETFs is to reduce HY liquidity. In IG, the substitution effect is not significant and ETFs result in increased bond liquidity.

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Transaction cost analytics for corporate bonds

Guo

Lehalle

2022

Quantitative Finance

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Measuring Bond-Level Liquidity

Cited by 17 publications

References 0 publications

Transaction Cost Analytics for Corporate Bonds

Transaction Cost Analytics for Corporate Bonds

Credit ETFs in Mutual Funds and Corporate Bond Liquidity

Transaction cost analytics for corporate bonds

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