Narrow Results

We use order book data combined with tick data to analyze the supply curve models of liquidity issues in stock and option market trading. We show that supply curves really exist, and further that for highly liquid stocks they are linear. For slightly less liquid stocks the supply curve tends to be jump linear.

We construct a model for liquidity risk and price impacts in a limit order book setting with depth, resilience and tightness. We derive a wealth equation and a characterization of illiquidity costs. We show that we can separate liquidity costs due to depth and resilience from those related to tightness, and obtain a reduced model in which proportional costs due to the bid-ask spread is removed. From this, we obtain conditions under which the model is arbitrage free. By considering the standard utility maximization problem, this also allows us to obtain a stochastic discount factor and an asset pricing formula which is consistent with empirical findings (e.g., Brennan and Subrahmanyam (1996); Amihud and Mendelson (1986)). Furthermore, we show that in limiting cases for some parameters of the model, we derive many existing liquidity models present in the arbitrage pricing literature, including Çetin et al. (2004) and Rogers and Singh (2010). This offers a classification of different types of liquidity costs in terms of the depth and resilience of prices.

Traditionally derivatives have been valued in isolation. The balance sheet of which a derivative position is part, was not included in the valuation. Recently however, aspects of the valuation have been revised to incorporate certain elements of the balance sheet. Examples are the debt valuation adjustment which incorporates default risk of the bank holding the derivative, and the funding valuation adjustment that some authors have proposed to include the cost of funding into the valuation. This paper investigates the valuation of derivatives as part of a balance sheet. In particular, the paper considers funding costs, default risk and liquidity risk. A valuation framework is developed under the elastic funding assumption. This assumption states that funding costs reflect the quality of the assets, and any change in asset composition is immediately reflected in the funding costs. The result is that funding costs should not affect the value of derivatives. Furthermore, a new model for pricing liquidity risk is described. The paper highlights that the liquidity spread, used for discounting cashflows of illiquid assets, should be expressed in terms of the liquidation value (LV) of the asset, and the probability that the institution holding the asset needs to liquidate its assets.

We study the problem of optimally liquidating a large portfolio position in a limit-order market. We allow for both limit and market orders and the optimal solution is a combination of both types of orders. Market orders deplete the order book, making future trades more expensive, whereas limit orders can be entered at more favorable prices but are not guaranteed to be filled. We model the bid-ask spread with resilience by a jump process, and the market-order arrival process as a controlled Poisson process. The objective is to minimize the execution cost of the strategy. We formulate the problem as a mixed stochastic continuous control and impulse problem for which the value function is shown to be the unique viscosity solution of the associated variational inequalities. We conclude with a calibration of the model on recent market data and a numerical implementation.

Risk measures for multivariate financial positions are studied in a utility-based framework. Under a certain incomplete preference relation, shortfall and divergence risk measures are defined as the optimal values of specific set minimization problems. The dual relationship between these two classes of multivariate risk measures is constructed via a recent Lagrange duality for set optimization. In particular, it is shown that a shortfall risk measure can be written as an intersection over a family of divergence risk measures indexed by a scalarization parameter. Examples include set-valued versions of the entropic risk measure and the average value at risk. As a second step, the minimization of these risk measures subject to trading opportunities is studied in a general convex market in discrete time. The optimal value of the minimization problem, called the market risk measure, is also a set-valued risk measure. A dual representation for the market risk measure that decomposes the effects of the original risk measure and the frictions of the market is proved.

We consider a setup in which a large trader has sold a number of American-style derivatives and can have an impact on prices by trading the underlying asset for hedging purposes. The price impacts are assumed to be temporary and decay exponentially with time. Due to the impact of trading on prices, the large trader may also be tempted to minimize the payoff of the derivative by manipulating the underlying asset. Since the option holders have the right to exercise the option at any time before expiry, we consider a robust optimization problem for the large trader, in which the underlying uncertainty is the exercise time. It is shown that the solution of this optimization problem can be described as the solution of a double obstacle variational inequality. The optimal strategy for the large trader and the worst-case exercise time for the option holder are obtained explicitly in terms of the value function. We conclude with a sensitivity analysis in which we compare the timing and size of trades by the large trader as well as the exercise region for the options holders for different levels of liquidity, and identify situations that may lead to potential price manipulation.

We consider a financial market with zero-coupon bonds that are exposed to credit and liquidity risk. We revisit the famous Jarrow & Turnbull (1995) setting in order to account for these two intricately intertwined risk types. We utilize the foreign exchange analogy that interprets defaultable zero-coupon bonds as a conversion of nondefaultable foreign counterparts. The relevant exchange rate is only partially observable in the market filtration, which leads us naturally to an application of the concept of platonic financial markets as introduced by Cuchiero et al. (2020). We provide an example of tractable term structure models that are driven by a two-dimensional affine jump diffusion. Furthermore, we derive explicit valuation formulae for marketable products, e.g. for credit default swaps.

The transition from term-based reference rates to overnight reference rates has created a dislocation in the market-making processes between the interbank and non-interbank funding, and their respective derivatives markets. This dislocation can be attributed to differences in funding and corresponding interest rate swap transactions, a thesis we explain and characterize in detail. It is then shown how this dislocation may be resolved. Based on a systemic perspective of a stylized financial system, an aggregated banking system is constructed that is void of idiosyncratic credit risks but still vulnerable to liquidity risks. Within this setup, a mathematical modeling framework for term-cognizant interest rate systems is derived that enables the pricing and valuation of bank term funding and associated derivatives transactions with varying liquidity characteristics. Other outcomes include: (i) a detailed analysis of the incomplete market paradigm that encapsulates bank term funding rates and the risk management processes involved therein; and (ii) a recovery of consistency in the pricing and valuation between funding and related interest rate swap transactions, along with a mechanism to exchange term risk.

This study employs an alternative measure of liquidity risk to investigate its determinants by using an unbalanced panel dataset of commercial banks in 12 advanced economies over the period 1994–2006. Dependence on liquid assets for external funding, supervisory and regulatory factors, and macroeconomic factors are all determinants of liquidity risk. Because of higher funding costs for obtaining liquidity, liquidity risk is regarded as a discount for bank profitability, yet liquidity risk shows a premium on bank performance in terms of banks’ net interest margins. Liquidity risk has reverse impacts on bank performance in a market-based financial system.

This paper examines relative performance of alternative asset pricing models using individual security returns. The standard multivariate test used in studies comparing the performance of asset pricing models requires the number of stocks to be less than the number of time series observations, which requires grouping stocks into portfolios. This results in a loss of disaggregate stock information. We apply a different statistical test to overcome this problem and to investigate relative performance of alternative asset pricing models using individual security returns instead of portfolio returns. Our findings suggest that a parsimonious six-factor model that includes the momentum and orthogonal value factors outperforms all other models based on a number of measures as well as the average $F$-test. Unlike the standard multivariate test, we find that the average $F$-test has superior power to discriminate among competing models and does not reject all tested models.

This paper investigates the relationship among liquidity risk, cash-holdings, financial constraints, and capital-raising costs. Our results show that cash preservation has different impacts on the liquidity risk explained by different aspects. The liquidity risk is negatively related with cash holdings. More financial constraints increase the liquidity risk. The firms with low capital-raising costs hold more cash because of liquidity needs.

Financial market instability and losses driven by changes in stock prices, currencies, interest rates, and other factors are the primary causes of economic risk. One of the risk types with the highest priority for every business is financial risk. The consumer electronics manufacturing sector’s focus on rising technology is driving important growth and includes manufacturers of smartwatches, stylish home products, and smart speakers. Risks can arise from the inability to meet functional requirements and business expectations throughout the life cycle, from original formation to final disposal, while supplying competitive electronic products. All of this highlights the necessity and potential of thorough study in the field of financial risk in economic growth. With the help of owners and managers of top electronic manufacturing industries in India, this study’s goal is to examine and evaluate several aspects of financial risk in economic benefits. The main factors of the financial risk covered under the study include liquidity risk, market risk, credit risk, and operational risk. Financial risks also arise from a combination of macroeconomic factors, including changing interest rates on the market and the potential for default by sizable businesses or industries. Financial stability is of the utmost importance to a commercial enterprise to maintain its position and status in the commercial environment. All of this demonstrates the value and need for rigorous research in the area of financial risk affecting the performance of the organization. This study intends to analyze several components of financial risk in consumer electronic goods manufacturers in India. Various aspects discussed in the study revolving around financial risk management are an important factor and demand the maximum attention of the organization.

Ten years of data from an Ecuadorian microfinance entity together with data on macroeconomic variables was analyzed. Through a Vector Autoregressive Model, we established a one-way causal relationship between credit and liquidity risks. The model includes the feedback effects through successive deterioration of credit portfolio and illiquidity spreading and the effects of macroeconomics and financial variables on these risks. Our results corroborate the importance of incorporating new contagion channels in microfinance institutions’ risk management, which helps microfinance institutions become financially sustainable, generating a relatively stable level of profitability that can improve the entrepreneur’s economic situation.

Using data from the Lipper TASS hedge fund database over the period 1994–2012, we examine the role of liquidity risk in explaining the relation between asset size and hedge fund performance. While a significant negative size-performance relation exists for all hedge funds, once we stratify our sample by liquidity risk, we find that such a relationship only exists among funds with the highest liquidity risk. Liquidity risk is found to be another important source of diseconomies of scale in the hedge fund industry. Evidently, for high liquidity risk funds, large funds are less able to recover from the relatively more significant losses incurred during market-wide liquidity crises, resulting in lower performance for large funds relative to small funds.

In the U.S. Treasury market, the most recently issued, or so-called “on-the-run,” security typically trades at a price above those of more seasoned but otherwise comparable securities. This difference is known as the on-the-run premium. In this paper, yield spreads between pairs of Treasury Inflation-Protected Securities (TIPS) with both matching and nearly-matching maturities but of separate vintages are analyzed. Adjusting for differences in conventional liquidity premiums, values of embedded deflation options, and coupon rates, the results show a small, insignificant premium on recently issued TIPS, which leads us to conclude that there is no on-the-run premium in the TIPS market.

I test and find supporting evidence for the precautionary motive hypothesis of liquidity hoarding for U.S. commercial banks during the global financial crisis. I find that banks held more liquid assets in anticipation of future losses from securities write-downs. Exposure to securities losses in their investment portfolios and expected loan losses (measured by loan loss reserves) represent key measures of banks’ on-balance sheet risks, in addition to off-balance sheet liquidity risk stemming from unused loan commitments. Furthermore, unrealized securities losses and loan loss reserves seem to better capture the risks stemming from banks’ asset management and provide supporting evidence for the precautionary nature of liquidity hoarding. Moreover, I find that more than one-fourth of the reduction in bank lending during the crisis is due to the precautionary motive.

This paper aims to develop a methodology for the estimation of the idiosyncratic confidence level inherent within the process of determining the threshold of separation between volatile and stable deposit volumes. The idiosyncratic confidence level must be reflective of the institution’s specific risk preferences and liquidity risk management policies as anchored into the Principle 9 of the European Banking Authority and Basel Committee for Banking Supervision recommendations. We illustrate the proposed methodology by including liquidity constraints from the Basel III regulatory recommendations introduced in 2013. Furthermore, we point to other ancillary applications of such procedures in the financial risk management practice.

We examine the individual and joint effects of bank competition and revenue diversification on liquidity creation. We find that bank competition and revenue diversification have a positive impact on banks’ propensity to create liquidity. Competition appears to primarily impact on-balance-sheet liquidity creation while revenue diversification is a key driver of off-balance-sheet liquidity creation. When considered together, each has a moderating effect on the other in relation to liquidity creation suggesting a substitution effect between competition and revenue diversification. Such substitution effect, however, is found predominantly for small and medium banks and during crisis periods. Our findings suggest that policymakers and regulators should be cautious of a one-size-fits-all approach to bank competition and revenue diversification in promoting bank stability.

In this paper, we investigate the role of liquidity in banks lending activity and how liquidity provision is related to bank’s credit risk and others market-based risk measures, such as bank’s implied volatility skew from options traded on the market and realized volatility from futures contract on LIBOR, during periods of global financial distress. Credit risk is given by the ratio between loan loss reserves and total assets and we find that losses from lending activity force banks to build up new liquidity provisions only during the period of financial distress. Liquidity ratio is given by the sum of cash and short-term assets over total assets and we discovered that credit risk reduces liquidity ratio only in bad times, as this demand for liquid asset is suddenly switched on and the more reserves from loan losses the bank has, the more it cleans its balance sheet from long-term commitments in order to replenish its cash and short-term securities. When we control for market-based risk measures, we evidence that both implied volatility skew and LIBOR’s realized volatility are negatively related with the liquidity ratio and are useful in predicting a distress in bank’s liquidity holdings.

This study examines whether there is a strong relationship between stock liquidity, which proxies for the implicit cost of trading shares, and future stock returns in an asset-pricing context in the UK stock market. The time period, 1994–2016, includes the most recent global financial crisis that drained liquidity from financial markets worldwide. Four different measures of stock liquidity are employed; the empirical findings indicate that liquidity is a systematic pricing factor and explains a significant portion of the variation in stock returns, even after the inclusion of the other traditional risk factors. The results are robust to both forms of liquidity, either as a residual effect or in its original form as a separate risk factor. Finally, for the first time quantile regression is applied, showing that the liquidity risk factor (LIQ) absorbs a significant portion of the information content of the size and value factors, while remaining independent of the momentum factor.