Counterparty Credit Risk - Hedge Funds - Essay Example

Business Summary By Summary Counterparty Credit Risk- Hedge Funds Counter party credit risks arethe exposures of the non-payment on the responsibility of that counterparty. Traders and accountants value this risk and consider it as an option to default. It is often identified as the counterparty valuation adjustment. The various classes of counterparty entail hedge funds, sovereigns, and corporate and financial institutions. Hedge funds are a combined term for joint investment medium that utilizes a huge range of changing strategies (Zimmermann, 2009). Hedge funds aims to reduce volatility and the risk preserve capital and deliver positive returns under all market conditions. Hedge fund is often depend on the manager’s expertise, is largely offered as private investment, is structured as limited partnership and often presents a narrow range of investors. Compared to the traditional funds, Hedge funds; have an industry size of $2.6 trillion, it has an absolute return, it has short or long investment, has high strategic complexity, has lower correlation to the market, has leverage, higher turnover, high based on performance, has large minimum investment and a low transparency. Investors are high net worth people, institutional investors and funds of funds managers. For hedge funds, the minimum size of investment is often high and at least 1 million dollars. Investors often seek stable, attractive and non market correlated returns. Pension funds make up 15%, followed by individual funds 30%, endowment 12% percent and corporation 11% (Zimmermann, 2009). Hedge fund strategies cover aids in representing the hedge fund universe that includes event driven, long/short equity, global macro, multi-strategy, emerging markets, fixed income arbitrage, managed future. Event driven strategy helps to exploit pricing that results from corporate events that are often anticipated. Managed futures strategy is also known as commodity trading advisors and is an approach aimed at investing in futures contracts in equity, bond, current market and commodity (Zimmermann, 2009). It utilizes pattern and trend recognition models as well as means reversion. Fund of hedge funds entails investing in another hedge fund. The main aim is the fund, manager and strategy. Some of the key risks to the hedge fund strategy entail poor liquidity, high leverage, lack of regulation, operational risks and lack of transparency (Zimmermann, 2009). CPP is the proportion portfolio insurance which aids in ensuring a hundred percent of the capitals of the investors is protected. CPPI determines the composition of investment between non risk assets such as fixed term deposits and cash as well as the risk assets that comprise of the hedge funds. Summary two Advanced topics in alternative asset management; techniques, structure and strategies. Some of the topic that are covered under investment management and trading includes trading strategies; arbitrate, techniques; short selling, market innovation; high frequency trading and trading business structures that entails the hedge funds. Hedge fund is often considered a trading/investment vehicle since it can sell short, can use leverage, typically not open to retail investors and can invest in unrated issues/low quality. Typical United States hedge funds for example involve general partners and investors being directed towards hedge funds limited partnership (Amenc, Martellini and Vaissié, 2013). . Some of arbitrate trading examples includes statistical arbitrate, special convergence; merger arbitrate, arbitrate risk profile and arbitrate return sources; convertible arbitrate. The mechanics of short selling entails association of various factors such as funds, security, prime broker and security market. Short selling in distressed situations are often associated with short cover, asymmetrical risk profile, high cost of borrow and limited supply of stock borrow. The last topic is algorithmic trading that is defined as the utilization of the electric platforms for entering orders of trading with the algorithm deciding order aspects such as price, quantity and price of an order or in numerous cases initiating order without the interventions of people (Amenc, Martellini and Vaissié, 2013). High frequency trading is a special class of algorithm trading in which computers make elaborate decisions to kick off orders basing on the information that is obtained electronically, before traders are capable of dispensing the information that they are able to see. The approach has resulted to change in the microstructure of the market in a way that liquidity is given. Sell side traders some hedge funds and market makers provide liquidity to the market, executing and generating orders automatically. Algorithm trading is widely utilized by mutual funds, pension funds, and by side intuitional traders, to divide large traders into smaller trades in order to manage market risks and impacts (Amenc, Martellini and Vaissié, 2013). . Scaling laws and trading models The global financial assets government bonds, equities, corporate bonds, loans, secutized and non-securitized loan. The global asset was estimated at 225 trillion. Assets are often managed for either self interests or when the economy is non-zero sum total where the information can increase and accumulate wealth. People tend to manage assets in various ways. The reality of finance and economy has remained to be complex and has to be handled in an effective manner. Managers can either crack the problems that have been encountered or give up in despair (Ernst & van Dongen, 2010). The trading strategies for quant funds entail intraday models, directional volatility, and volatility arbitrates. Technical analysis presents a lot of weaknesses such as too late, no consistent theory, trader’s remorse, open to interpretation and analyst bias. Fundamental analysis entails issues such as company analysis, industry analysis and economic analysis and targets value investors, contrarian investors and buys and hold investors. Some of the weaknesses of the fundamental analysis involves being too late, model quality may be unstable, it is open to interpretation and being designed for one week, quarterly and for a longer time period. Companies such as computers, pharmaceutical and other industries have invested heavily in R& D. Investment strategies can be focus on various factors such as the market with the aim of consistently generating profits. Market determines the asset prices and is part of the real economy. Markets provide liquidity and are the real source of equity. High price increment is considered a cost to the economy. The difference between a limit order and the market order is that limit orders knows the price but is unaware of when the order will be processed. Market order on the other end is where a trader is unaware of the price but they are aware of when to execute. The scaling laws are vital is assessing the market as a result of ensuring consistent mapping of events (Ernst & van Dongen, 2010). Summary 4 The Market risk framework and the Fundamental Review of the Trading Book There are various market risks that often affect investment. Credit/insurer is the risk of loss due to borrower default on any debt type. It applies to loans, bonds and off balance sheet exposures. Counterparty risk is a risk where a default takes place before the final settlement. Credit assessment of risks involves bank’s own models, ratings systems and assessing creditworthiness. Other types of risks include operational risk, operational risk assessment and liquidity risk. The five standard marketing risks factors include equity risk, currency risk. Credit spread risks, interest rate risks (Arewa, 2010). The risk in the market can be measured by utilizing the measurements such as sensitivity, value at risk, stress and scenario testing, marketing value and nominal position. Value at risk (VaR) is a risk measure that is often utilized to estimate the risk of trading portfolio. VaR present the various types of risks and predict the worst case that is expected after a period that has been set out within the confidence interval. The primary methods that are often utilized to calculate the value at risk includes historical simulations, variance covariance and Monte Carlo method. The senior management and the board should always be involved in the management of the various risks. Risks can be managed by utilizing the IT systems, internal audit, prudent valuation of position and value at risk model validation (Arewa, 2010). Basel 2.5 is the capital component for market risks. It entails increased risk charge, comprehensive risk measures and stressed value at risk. The financial crisis exposed market weaknesses. In 2009 the Basel committee invoked a lot of revisions to the market risk framework that was in place. The trading book’s fundamental review was of essence in ensuring that the identified issues were corrected in the right manner (Xiao, 2013). The current boundary is largely associated with trading intent. New boundary aims at being less susceptible to arbitrate by offering more information and guidance for the supervisors as well as maintaining a link with the trading intent. The new standardised approach aims at getting a balance of simplicity and risk sensitivity. No diversification across risk classes such as commodity risk, equity risk, general interest rate risk, foreign exchange, default risk and credit spread risks (Arewa, 2010). References Amenc, N., Martellini, L. and Vaissié, M. 2013. Benefits and risks of alternative investment strategies. Journal of Asset Management, 4(2), pp.96-118. Arewa, O. 2010. Trading Places: Securities Regulation, Market Crisis, and Network Risk. SSRN Journal. Bondarenko, O. 2011. Variance Trading and Market Price of Variance Risk. SSRN Journal. Ernst, M. and van Dongen, P. 2010. Scaling laws in aggregation: Fragmentation models with detailed balance. Physical Review A, 36(1), pp.435-437. Xiao, T. 2013. A simple and precise method for pricing convertible bond with credit risk. Journal of Derivatives & Hedge Funds, 19(4), pp.259-277. Zimmermann, H. 2009. Credit Risk Transfer, Hedge Funds, and the Supply of Liquidity. SSRN Journal. Read More