Market liquidity, closeout procedures and initial margin for CCPs

The obligatory clearing of certain contracts through CCPs, that is imposed by Regulation (EU) no. 648/2012 of 4 July 2012 on OTC derivatives, central counterparties and trade repositories (called “EMIR”, i.e. European Market Infrastructure Regulation), is justified by the need to increase the transparency of the derivatives market, to mitigate systemic risk and to promote stability of the financial system. Central counterparties (CCPs) are clearing houses that interpose themselves between the counterparties to the contracts traded on one or more financial markets, becoming the buyer to every seller and the seller to every buyer. In this way CCPs are responsible for the clearing of transactions concluded on derivatives market, which reduces the credit risk of individual counterparties. The EU legislator creates a legal framework for the functioning of CCPs that become new systemically important institutions. In addition, EMIR leads to the creation of a kind of monopoly as CCPs’ services become compulsory for entities involved in trading on financial instruments that will be subject to central clearing. For these reasons, EMIR represents new and difficult challenges for effective oversight and supervision of financial markets. The tendency to maintain a market structure where operate only a relatively limited number of CCPs is likely to be perpetuated due to the predominance of entities with established market position, as well as the presence of high sunk costs associated with the rigorous regulatory requirements that determine the possibility of entering the market. The regulation of financial market infrastructure has to take into consideration and to integrate two perspectives: micro (transaction costs) and macro (systemic risk).

Evaluation of different hedging strategies for commodity price risks of industrial cogeneration plants

Central Counterparties Help, But Do Not Assure Financial Stability

In financial derivatives investment, risk hedging and arbitrage strategies play a key role. Risk hedging aims to reduce the uncertainty caused by asset price fluctuations and provide investors with stable returns through derivatives such as futures, options, and credit default swaps (CDS). This strategy is widely used by enterprises and financial institutions to manage commodity prices, exchange rates, and credit risks. Arbitrage strategies use market price differences, especially pricing differences in different markets or at various time points, to seek risk-free or low-risk returns. This paper reviews existing literature on financial derivatives, sorting out the role of risk hedging in financial derivatives investment. It summarizes the basic principles, application cases, advantages, and limitations of risk hedging. Additionally, the research delves into the role of arbitrage strategies in financial derivatives investment, covering its basic principles, types, application cases, advantages, and limitations. This research finds that hedging strategies, through instruments such as futures, options, and credit default swaps, provide effective risk management by stabilizing returns and reducing the impact of market volatility. Arbitrage strategies, on the other hand, exploit market inefficiencies to generate low-risk or risk-free profits, thereby enhancing market efficiency and liquidity. Despite these advantages, this paper also highlights certain limitations, such as the complexity and cost of hedging instruments, and the diminishing arbitrage opportunities as markets become more efficient.

Auf dem G20-Gipfel wurde 2009 beschlossen, dass insbesondere OTC-Derivate-Transaktionen künftig überwiegend über Zentrale Gegenparteien (Central Counterparties) abgewickelt werden sollten. Weltweit beträgt das pro Jahr abgewickelte Volumen von Zins-, Währungs- und Aktienderivaten mehr als 400 Billionen US-$. Nach dem Brexit stellt sich die Frage, ob das derzeit überwiegend in London abgewickelte Clearing von Euro-OTC-Derivaten auf eine Zentrale Gegenpartei in der EU verlagert werden sollte. Gegner einer solchen Relokation befürchten hohe Kosten für die Marktteilnehmer. Die bislang vorliegenden Kostenschätzungen sind jedoch viel zu hoch.

This dissertation empirically studies the implications of today's fast-paced markets for securities trading and clearing. Chapter 2 proposes an approach that not only tracks the risk exposure of a central counterparty (CCP), but also offers a decomposition. Implementing the approach on real-world data from a large equity CCP, we find that extreme CCP exposure changes are disproportionately due to crowded trades and extreme CCP exposures are highly concentrated in a few clearing members and risk factors. Chapter 3 utilizes a granular regulatory dataset to contrast the roles of dealer banks and high-frequency traders (HFTs) in liquidity provision and price discovery in the foreign exchange (FX) market. On liquidity provision, we find while order-book liquidity provided by HFTs is less sensitive to large market-wide volatility spikes, that by dealer banks is more resilient ahead of scheduled macroeconomic news announcements. On price discovery, HFTs contribute the dominant share through their high-frequency quote updates which incorporate public information. In contrast, dealer banks contribute to price discovery more through their trades, impounding private information. Chapter 4 examines the role of the public data feed in the US equities market. Using exogenous events affecting the speed and availability of the public data feed as an identification, we find that a faster public data feed has an adverse, albeit mild, impact on market liquidity, possibly as a result of more non-high-frequency algorithmic trading activities from informed institutional traders. However, when the public feed becomes corrupted or unavailable due to a technical glitch, market liquidity significantly worsens.

The Best Hedging Strategy in the Presence of Transaction Costs

We study the empirical performance of the classical minimum-variance hedging strategy, comparing several econometric models for estimating hedge ratios of crude oil, gasoline and heating oil crack spreads. Given the great variability and large jumps in both spot and futures prices, considerable care is required when processing the relevant data and accounting for the costs of maintaining and re-balancing the hedge position. We find that the variance reduction produced by all models is statistically and economically indistinguishable from the one-for-one “naïve” hedge. However, minimum-variance hedging models, especially those based on GARCH, generate much greater margin and transaction costs than the naïve hedge. Therefore we encourage hedgers to use a naïve hedging strategy on the crack spread bundles now offered by the exchange; this strategy is the cheapest and easiest to implement. Our conclusion contradicts the majority of the existing literature, which favours the implementation of GARCH-based hedging strategies.

Efficient Analytic Approximation of the Optimal Hedging Strategy for a European Call Option with Transaction Costs

Considerable theoretical work has been devoted to the problem of option pricing and hedging with transaction costs. A variety of methods have been suggested and are currently being used for dynamic hedging of options in the presence of transaction costs. However, very little was done on the subject of an empirical comparison of different methods for option hedging with transaction costs. In a few existing studies the different methods are compared by studying their empirical performances in hedging only a plain-vanilla short call option. The reader is tempted to assume that the ranking of the different methods for hedging any kind of option remains the same as that for a vanilla call. The main goal of this paper is to show that the ranking of the alternative hedging strategies depends crucially on the type of the option position being hedged and the risk preferences of the hedger. In addition, we present and implement a simple optimization method that, in some cases, improves considerably the performance of some hedging strategies.

Uncertainty effects on production mix and on hedging decisions: The case of Brazilian ethanol and sugar

The efficiency of financial trading is a fundamental concept in finance, essential to effective price discovery, minimising transaction costs, and maintaining market liquidity. Despite the theoretical robustness of concepts like the Efficient Market Hypothesis, empirical evidence reveals persistent inefficiencies, particularly in financial trading in emerging markets under globalisation and newer asset classes such as cryptocurrencies. The purpose of this article is to evaluate the efficiency of financial trading in the context of globalisation. To achieve this, ARIMA-GARCH time-series modelling was used. The empirical analysis incorporated data from developed financial markets (S&P 500, FTSE 100) and emerging financial markets (Shanghai Composite Index) from 2010 to 2023, focusing on transaction costs, liquidity, and volatility. The mathematical model incorporated components such as market price dynamics, transaction costs, liquidity, and flow rates information to construct a combined efficiency metric. The results demonstrate significant disparities in efficiency among markets. Financial trading in the developed markets exhibited lower volatility clustering and higher price predictability, indicative of greater efficiency. In contrast, financial trading in the emerging markets showed pronounced inefficiencies due to higher transaction costs and volatility. The proposed model enables us to quantify market efficiency and highlights the impact of liquidity and transaction costs on price alignment. It also provides a holistic view of market efficiency and serves as a tool for traders, policymakers, and regulators. Further research is recommended to empirically validate the model across different asset classes and assess its implications for regulatory frameworks.

Algorithmic trading for online portfolio selection under limited market liquidity

The objective of this research is to study the relationship between various aspects of corporate bonds liquidity , transaction costs and trading activity, and their perceived credit quality as measured by credit ratings. For debt securities, Credit quality and liquidity are perhaps the most important factors that affect the investors’ decisions whether to trade or hold these assets on their portfolio, as several theoretical and empirical studies identify these factors as key components of bonds yield spreads. However, the interaction and relationship between these two characteristics is not sufficiently addressed in the literature. From the investors’ perspective, it is beneficial to know whether they face a tradeoff between credit quality and liquidity or if both desirable features move in the same direction. We use more than twelve years of Enhanced TRACE data from 2002 to 2014 to analyze the liquidity of corporate bonds both cross-sectionally across credit ratings and intertemporally around credit rating changes. The first manuscript studies the relationship between corporate bonds’ credit risk and their market liquidity, and the dynamics of this relationship over the period from 2002 to 2014. Unlike the implication of theoretical models, our findings do not empirically support a monotonically positive relation between credit risk and transaction costs. Instead, we find an inverted U-shaped relationship where bonds with ratings near the Investment grade/ High yield boundary have the largest transaction costs (lowest liquidity) after controlling for other relevant factors. One explanation for this finding is that bond dealers behave more as brokers in speculative grade bonds and are reluctant to enter overnight positions in these risky securities, unless they find the other side of the trade. This kind of dealers behavior potentially reduces the transaction costs of lower rated bond, as captured by bid-ask spreads, to only reflect the cost of searching for counterparty rather than inventory or adverse selection risks, and may be even more pronounced during distressed market conditions due to more capital constrains and less funding liquidity. Consistent with this explanation, using a Markov Switching time series model, we find that while bid-ask spreads significantly increase for investment grade bonds during the crisis, they stay invariant for junk bonds. The second essay expands this investigation to examine the impact of rating changes on corporate bonds’ liquidity around the rating change announcements using an event study methodology. Many institutional investors such as insurance companies or pension funds are prohibited by regulations from

An international initiative to increase the use of central clearing for over-the counter (OTC) derivatives emerged as one of the reactions to the 2008 financial crisis. The move to central clearing is a fundamental change in the structure of the market. Central clearing will help control counterparty credit risk, but it also has potential implications for market liquidity. We analyze the relationship between liquidity and central clearing using information on credit default swap clearing at ICE Trust and ICE Clear Europe.We find that the central counterparty chooses the most liquid contracts for central clearing, consistent with liquidity characteristics being important in determining the safety and efficiency of clearing.We further find that the introduction of central clearing is associated with a slight increase in the liquidity of a contract. This is consistent with two countervailing effects. On the one hand, central clearing will likely increase collateral requirements relative to the prereform bilaterally cleared market, thereby increasing clearing costs and possibly reducing the liquidity of the market. On the other hand, improved management of counterparty credit risk, increased transparency and operational efficiencies at central counterparties could bring more competition into OTC derivative markets and serve to increase liquidity.