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He is a former director of corporate risk management and a derivatives trader at Merrill Lynch, as well as head of options trading at UBS and Chase. Hedge funds are lightly regulated investment funds open only to institutional or qualified satisfying minimum wealth requirements investors, with limited liquidity quarterly or annual redemptionsthat charge performance fees. The fee structure is typically 2 percent of assets under management plus 20 percent of profits.
Both numbers can be higher or lower. The 20 percent incentive fee may be subject to high-water marking —that is, requiring the fund to make up losses first. The largest operators of hedge funds include J. Although global macro, fixed-income, and event-driven funds often attract press coverage, more than 50 percent of all hedge funds employ strategies focused on equities.
Figure 1 shows a breakdown compiled from various sources as of the end of the first quarter of As early as the late s, academic researchers started doubting hedge fund claims to superior performance and superior manager skill alpha.
They asked three broad questions: If so, is the performance trading strategies using options as a hedge funds over time luck or alpha? If so, why, and can it be replicated with simpler alternatives beta at lower fees with daily redemption? Many studies point out two main problems with hedge fund databases: The latter causes the overstatement of overall returns, as failed funds are deleted from aggregate return calculations.
Fung and Hsieh pointed out that when hedge funds migrate from one database to another, or databases are merged, performance has to be supplied for early years backfill or the fund has to be deleted survivorship. Bollen and Pool found evidence that funds use discretion in valuing illiquid securities trading strategies using options as a hedge funds temporarily overstate their returns.
Bollen and Whaley showed the errors produced in trying to estimate alpha, or overperforming a benchmark, when the benchmark itself constantly moves shift in asset classes, strategies, and leverage. Despite these problems, Griffin and Xu showed that hedge funds beat mutual funds in stock-picking by close to 1. However, they found little evidence of differential ability between hedge funds herding the same ideas? Arnott and West explored the erosion of gross returns of funds of funds by fees asset-based plus carry.
Early studies on performance persistence reached divergent conclusions. Agarwal and Naik found persistence in the — period, attributing it to superior mutual fund managers opening new hedge funds. Several studies documented that, similar to mutual funds, large size and fund inflows negatively affect subsequent performance.
Boyson found strongest persistence in younger and smaller funds, which as a group also outperform older, larger ones by more than 10 percent. Eling provided a good synthesis trading strategies using options as a hedge funds the various studies of performance persistence over the years.
He attributes more of it to data biases than to option-like strategies. Takahashi and Yamamoto classified replication strategies into factor-based, rule-based, and distribution replication and reviewed each one. Hasanhodzic and Lo were the first to test the linear factor-based replication models.
Their main findings were that non-linear and conditional models do not necessarily improve replication—choosing better economic factors does. However, the replication strategies systematically underperform the actual hedge funds. Research based on net returns tends trading strategies using options as a hedge funds understate returns because of beta exposure by 60 basis points per year. Replication should be based on gross returns.
Fung and Hsieh reviewed the trading strategies using options as a hedge funds replication. Fung and Hsieh identified five strategies as accounting for 45 percent of the variation of hedge fund returns. Others added them for merger arbitrage, convertible arbitrage, and general equity and emerging markets funds. Jaeger estimated that with factor-based, rule-based, and distributional replication, beta can account for up to 90 percent of hedge fund returns.
His book reviewed the entire spectrum of techniques. Roncalli and Weisang developed statistical filtering methods to address the issues of slow reactivity of replication to tactical reallocation and the inability to capture non-linear positions; they also proposed the core-satellite approach to overcoming the lack of access to the alpha of hedge funds.
The core-satellite model stresses traditional long asset class allocation for the bulk of investment dollars, supplemented with satellite alpha-focused investments. Hedge funds pursue a variety of investment strategies. Table 1 shows my classification of hedge funds, based not on the asset classes covered, but on the subjective criterion of how the relative value that the fund tries to unlock is pursued.
Broadly, I group the funds into four blocks, from general bets on asset class groups, all the way down to technical mispricing. Let us delve into the classification of hedge funds presented in Table 1 with concrete examples. Directional Asset Class Arbitrage. The horizon is a few weeks to a year. We bet on some asset classes outperforming others, or some securities within an asset class outperforming others. We design a long-short, an overweight, or an open-ended carry trade.
There are two distinct strategies in this space: The first is a play on the prospects of a merger or a company breakup, with profit coming from the correct assessment of trading strategies using options as a hedge funds probability of the corporate event. With assumptions about the volatility of the assets, we can trading strategies using options as a hedge funds the equity given the market value of the debt, and vice versa.
We use the put-call parity to break down the total enterprise value of the firm into equity plus debt:. If the value of the enterprise falls below the face value of the debt, they will not get the full principal back downgrade, default. Implicitly, they have written a put option on the value of the firm.
We do know, however, that at higher volatility numbers, we get a greater undervaluation of equity given debt and overvaluation of debt given equity. We short the debt perhaps hedged with long Treasuries and buy the equity, or the other way around. This option-theoretic approach can be pushed further to value the different tranches of debt relative to each other. The yields-to-maturity on senior and subordinated imply certain probabilities of default and trade at spreads to Treasuries.
Viewing the junior tranches as claims on the total value of the assets minus the senior debt, we can use the option theory to imply the strike prices and thus derive the relative value of the junior debt. In this space, the logic is a decomposition of the value of a security into the sum of its pieces. In fixed income, coupon bonds are composed of principal and coupon strips. In hybrid asset classes, convertibles are packages of bullet bonds and long options to convert into equity.
In managed futures, the cash-and-carry is used to put together a basis or convergence trade. One side is rich; the other is cheap. The glue is an option model or the cost of financing. The principle is synthetic replication.
Statistical arbitrage is driven by large computerized models that factorize the universe of securities into systematic portfolio and residual security-specific risk. Statistical arbitrage cannot be implemented by a small, unsophisticated player. Suppose we want to construct a short-term momentum strategy for U.
We believe in first-order autocorrelation. The index model we choose may be an academic one like Fama and French or Carhart We find the factor loadings trading strategies using options as a hedge funds for all the stocks we are going to trade and construct the residuals of the realized stock returns minus index model returns.
The sums of the loadings on each factor identify the market neutral hedges with respect to the factors. We dig into the residual data to discover momentum or reversal signals. Suppose that in applying an autoregressive-moving average ARMA 2,1 model we find statistical significance in the AR trading strategies using options as a hedge funds.
We buy stocks with long momentum signals; we short stocks with sell momentum signals. On any given day, some stocks get included in the long portfolio, and some get included trading strategies using options as a hedge funds the short portfolio.
From the individual exposures to the index factors, we compute the net hedge to eliminate the directional risk zero beta. The expected net excess return we hope to generate from all the longs and shorts over time is our model alpha. The statistical approach can be applied to yield curve points, currencies, and commodities in which we can exploit inherent correlation of related assets. It is, however, distinct from the theoretical arbitrage. There we relied on theoretical no-arbitrage bounds of frictionless markets applied to real markets relative value mispricing.
It is a good idea for a pension fund manager, endowment manager, or financial adviser to separate passive parts of the portfolio from the active ones. This is the core-satellite model. The core asset class allocation decisions are made first at the top level. Then the residual investment dollars are allocated to individual managers. The passive management and active management certainly require different sets of skills. This separation is not always easy to achieve.
Actively managed portfolios mix market beta exposure with security selection alpha. This is where the idea of alpha transfer comes in. In an alpha transfer, a hedge fund trading strategies using options as a hedge funds makes a pure portable alpha play by hedging out the beta exposure s. Let us consider the following example.
The pension fund does not want the manager to simply buy the underpriced stocks as that would also expose it to the market risk of U. The underpriced stocks waiting to correct up could sink if the market overall corrects down.
The fund offers a portable alpha solution. It hedges its overall exposure to U. This way, the returns of the fund reflect the pure security selection alpha over the designated bogey, and the pension fund can manage its asset allocation independently of the security selection.
The process of separating the asset class exposure from specific risk plays is the alpha transfer. The biggest attraction and risk of a hedge fund is an almost unlimited discretion afforded the fund manager.
This engenders two negative aspects of hedge fund investing—style drift and clustering.