1.
주식옵션과 dispersion trading에 이어지는 글입니다. 이번에는 금융투자회사들이 만든 내외부 보고서들입니다. 먼저 JPmorgan이 2005년에 내놓은 보고서입니다. 지수의 변동성과 지수를 구성하는 기초자산들의 변동성이 어떤 상관관계를 갖는지를 정리한 자료입니다. JPmorgan에서 근무했던 Sébastien Bossu의 홈페이지에 올라온 자료입니다.
또다른 자료는 파리 제1대학에 공부한 후 Lyxor Asset Management에서 인턴으로 근무한 Yujin Chloe Choi의 보고서입니다.자산운용사에서 아래와 같은 일을 했고 이를 논문으로 정리하였습니다.
My first task was to develop an analysis of the performances of the funds on _hidden assets` where the teamas main focus was on, such as Volatility Swap, Variance Swap, Correlation Swap, Covariance Swap, Absolute Dispersion, Call on Absolute Dispersion (Palladium). The purpose was to anticipate the profit and to know when and how to reallocate assets according to the market conditions. In particular, I have automated the analysis through VBA in Excel.
Analysis and Development Of Correlation Arbitrage Strategies on Equities중에서
2.
이번에는 독일에서 발표한 논문들입니다. 두 논문 모두 Dispersion Trading을 주제로 다루고 있습니다.
Studying the properties of the correlation trades
Dispersion Trading in German Option Market
첫번째 논문의 초록입니다.
This thesis tries to explore the profitability of the dispersion trading strategies. We begin examining the different methods proposed to price variance swaps. We have
developed a model that explains why the dispersion trading arises and what the main
drivers are. After a description of our model, we implement a dispersion trading in the EuroStoxx 50. We analyze the profile of a systematic short strategy of a variance swap on this index while being long the constituents. We show that there is sense in selling correlation on short-term. We also discuss the timing of the strategy and future developments and improvements.
Dispersion Trading 모형을 다룰 때 목차입니다.
7 Dispersion Trading
7.1 Setting the dispersion trading weights
7.1.1 Vanilla dispersion trading
7.1.2 Correlation-weighted dispersion trading
7.2 Profit and Loss
7.3 Empirical results
7.3.1 Sub samples
7.3.2 Timing
7.3.3 Optimal contract duration
7.3.4 Optimal weights
7.3.5 Optimal portfolio size
앞서 논문들이 2007년을 전후한 것이라고 2014년 10월에 나온 논문이 SSRN에 올라왔네요.
Dispersion in Options Traders’ Expectations and Stock Return Predictability
We propose a measure of dispersion in options traders expectations about future stock returns by using dispersion in trading volume across strike prices. We fi nd that an increased dispersion in expectations forecasts lower subsequent excess market returns at both short and long horizons. Trading strategies based on the dispersion measure reveal signi ficant utility gains for a mean-variance investor as compared to a buy-hold strategy. Further, the dispersion measure exhibits additional predictive power when combined with the variance risk premium, thus showing that the two variables capture different aspects of the variation in returns. We also find that the information embedded in the dispersion in expectations measure is neither subsumed by well-established predictors of market returns, nor by other option-implied measures that proxy for variance and jump risk, or reflect hedging demand. Our results can be interpreted in light of models explaining the effect of disagreement or ambiguity on asset returns.
3.
ARMA와 GARCH모형을 이용하여 변동성을 예측할 수 있는 지표를 개발한 분이 찾아오셨습니다. 과거데이타를 이용한 백테스팅을 하였고 현재 트레이더가 지표를 이용하여 실거래를 하면 검증하는 중이라고 합니다. 실시간 데이타를 이용한 라이브러리도 개발중입니다. 자세한 자료를 받지 못해 지금 소개를 해드릴 수 없지만 나중에 소개해볼까 합니다.
