25,709 research outputs found

    Dealers' hedging of interest rate options in the U.S. dollar fixed-income market

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    Despite investors' willingness to hold a variety of financial assets and risks, a significant share of interest rate options exposures remains in the hands of dealers. This concentration of risk makes the interest rate options market an ideal place to explore the effects of dealers' dynamic hedging on underlying markets. Using data from a global survey of derivatives dealers and other sources, this article estimates the potential impact of dynamic hedging by interest rate options dealers on the fixed-income market. The author finds that for short-term maturities, turnover volume in the most liquid hedging instruments is more than large enough to absorb dealers' dynamic hedges. For medium-term maturities, however, an unusually large interest rate shock could lead to hedging difficulties.Hedging (Finance) ; Options (Finance)

    The Nature of Alpha

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    We suggest an empirical model of investment strategy returns which elucidates the importance of non-Gaussian features, such as time-varying volatility, asymmetry and fat tails, in explaining the level of expected returns. Estimating the model on the (former) Lehman Brothers Hedge Fund Index data, we demonstrate that the volatility compensation is a significant component of the expected returns for most strategy styles, suggesting that many of these strategies should be thought of as being `short vol'. We present some fundamental and technical reasons why this should indeed be the case, and suggest explanation for exception cases exhibiting `long vol' characteristics. We conclude by drawing some lessons for hedge fund portfolio construction.Comment: 22 pages, 5 figures, 3 table

    Market Risk Dynamics and Competitiveness After the Euro: Evidence from EMU Members

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    In this paper we propose an empirical model that considers theoretical facts on the relationship between real exchange rates and the net exports of the economy to supplement the interaction of a number of financial and economic factors with the stock market. We discuss the impact of exchange rate fluctuations on market risk in terms of Value at Risk (VaR). Our empirical findings show that common currency introduction produced increments in VaR whereas European stock returns are more sensitive to changes in competitiveness regarding the EMU rather than national exports. Finally, we show that the synchronisation of variation in competitiveness through the introduction of a single currency has made these changes more decisive in explaining financial market fluctuations.http://deepblue.lib.umich.edu/bitstream/2027.42/64351/1/wp916.pd

    Does Intellectual Capital Affect the Volatility of Returns? An Empirical Investigation on Italian Listed Companies

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    In modern information economies, economic success increasingly depends on the ability to apply knowledge and to transform it into firm value. While intellectual capital plays a critical role in firm success, it is an intangible asset that is difficult to measure and that is unrecorded by the firm. Difficulties in measuring intellectual capital, as well as the dynamic nature of the firms that rely on it, may lead to greater stock market volatility/risk. Consistent with this expectation, in statistical tests we find that intellectual capital, measured by VAIC, positively relates to the volatility of stock returns section among Italian listed companies. We find this positive relation for two components of a firm’s risk: systematic risk and specific risk. The finding is relevant to both investors concerned with understanding the risk/reward balance of particular investments and regulators concerned with market stability

    Asset Market Liquidity Risk Management: A Generalized Theoretical Modeling Approach for Trading and Fund Management Portfolios

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    Asset market liquidity risk is a significant and perplexing subject and though the term market liquidity risk is used quite chronically in academic literature it lacks an unambiguous definition, let alone understanding of the proposed risk measures. To this end, this paper presents a review of contemporary thoughts and attempts vis-Ă -vis asset market/liquidity risk management. Furthermore, this research focuses on the theoretical aspects of asset liquidity risk and presents critically two reciprocal approaches to measuring market liquidity risk for individual trading securities, and discusses the problems that arise in attempting to quantify asset market liquidity risk at a portfolio level. This paper extends research literature related to the assessment of asset market/liquidity risk by providing a generalized theoretical modeling underpinning that handle, from the same perspective, market and liquidity risks jointly and integrate both risks into a portfolio setting without a commensurate increase of statistical postulations. As such, we argue that market and liquidity risk components are correlated in most cases and can be integrated into one single market/liquidity framework that consists of two interrelated sub-components. The first component is attributed to the impact of adverse price movements, while the second component focuses on the risk of variation in transactions costs due to bid-ask spreads and it attempts to measure the likelihood that it will cost more than expected to liquidate the asset position. We thereafter propose a concrete theoretical foundation and a new modeling framework that attempts to tackle the issue of market/liquidity risk at a portfolio level by combining two asset market/liquidity risk models. The first model is a re-engineered and robust liquidity horizon multiplier that can aid in producing realistic asset market liquidity losses during the unwinding period. The essence of the model is based on the concept of Liquidity-Adjusted Value-at-Risk (L-VaR) framework, and particularly from the perspective of trading portfolios that have both long and short trading positions. Conversely, the second model is related to the transactions cost of liquidation due to bid-ask spreads and includes an improved technique that tackles the issue of bid-ask spread volatility. As such, the model comprises a new approach to contemplating the impact of time-varying volatility of the bid-ask spread and its upshot on the overall asset market/liquidity risk.Economic Capital; Emerging Markets; Financial Engineering; Financial Risk Management; Financial Markets; Liquidity Risk; Portfolio Management; Liquidity Adjusted Value at Risk

    On The Exchange Rate Risk Contribution To The Performance Of International Investments: The Case Of Romania

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    The paper examines the impact of changes in the Romanian currency exchange rates against the US dollar and the euro on an investment in the Romanian stock market from the perspective of a US dollar and euro based investor. Our analysis is directed towards identifying the significance of exchange rate volatility for the total risk of a Romanian investment from the perspective of investors with the US dollar and euro as reference currencies. Our results indicate that during more turbulent times investors were better off if invested in their home markets. We also find that the exchange rate risk decreased the risk that a US dollar or a euro-based investor was exposed to in Romania. The contribution of exchange rate risk to the risk of an international investor diversified in his home market and the Romanian market is small, even negative, with no significant differences turbulent versus normal times.Exchange rate, Romania, international investments, volatility

    The Rise and Fall of S&P500 Variance Futures

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    Volatility is an indispensible component of sensible portfolio risk management. The volatility of an asset of composite index can be traded by using volatility derivatives, such as volatility and variance swaps, options and futures. The most popular volatility index is VIX, which is a key measure of market expectations of volatility, and hence is a key barometer of investor sentiment and market volatility. Investors interpret the VIX cash index as a “fear” index, and of VIX options and VIX futures as derivatives of the “fear” index. VIX is based on S&P500 call and put options over a wide range of strike prices, and hence is not model based. Speculators can trade on volatility risk with VIX derivatives, with views on whether volatility will increase or decrease in the future, while hedgers can use volatility derivatives to avoid exposure to volatility risk. VIX and its options and futures derivatives has been widely analysed in recent years. An alternative volatility derivative to VIX is the S&P500 variance futures, which is an expectation of the variance of the S&P500 cash index. Variance futures are futures contracts written on realized variance, or standardized variance swaps. The S&P500 variance futures are not model based, so the assumptions underlying the index do not seem to have been clearly understood. As these two variance futures are thinly traded, their returns are not easy to model accurately using a variety of risk models. This paper analyses the S&P500 3-month variance futures before, during and after the GFC, as well as for the full data period, for each of three alternative conditional volatility models and three densities, in order to determine whether exposure to risk can be incorporated into a financial portfolio without taking positions on the S&P500 index itself.Risk management, financial derivatives, futures, options, swaps, 3-month variance futures, 12-month variance futures, risk exposure, volatility.
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