Exploring Statistical Arbitrage Opportunities in the Term Structure of CDS Spreads

2015 ◽  
Author(s):  
Robert A. Jarrow ◽  
Haitao Li ◽  
Xiaoxia Ye
Keyword(s):  
Term Structure ◽  
Statistical Arbitrage ◽  
Arbitrage Opportunities

scholarly journals Informed traders

2008 ◽  
Vol 465 (2104) ◽  
pp. 1103-1122 ◽  
Author(s):  
Dorje C Brody ◽  
Mark H.A Davis ◽  
Robyn L Friedman ◽  
Lane P Hughston
Keyword(s):  
Mutual Information ◽  
Signal To Noise Ratio ◽  
Information Source ◽  
Asset Price ◽  
Market Participant ◽  
Asset Return ◽  
Additional Information ◽  
Statistical Arbitrage ◽  
Noisy Information ◽  
Arbitrage Opportunities

An asymmetric information model is introduced for the situation in which there is a small agent who is more susceptible to the flow of information in the market than the general market participant, and who tries to implement strategies based on the additional information. In this model market participants have access to a stream of noisy information concerning the future return of an asset, whereas the informed trader has access to a further information source which is obscured by an additional noise that may be correlated with the market noise. The informed trader uses the extraneous information source to seek statistical arbitrage opportunities, while at the same time accommodating the additional risk. The amount of information available to the general market participant concerning the asset return is measured by the mutual information of the asset price and the associated cash flow. The worth of the additional information source is then measured in terms of the difference of mutual information between the general market participant and the informed trader. This difference is shown to be non-negative when the signal-to-noise ratio of the information flow is known in advance. Explicit trading strategies leading to statistical arbitrage opportunities, taking advantage of the additional information, are constructed, illustrating how excess information can be translated into profit.

STATISTICAL ARBITRAGE IN THE MULTI-ASSET BLACK–SCHOLES ECONOMY

2017 ◽  
Vol 12 (01) ◽  
pp. 1750004
Author(s):  
AHMET GÖNCÜ ◽  
ERDINC AKYILDIRIM
Keyword(s):  
Model Parameters ◽  
Expected Return ◽  
Risky Assets ◽  
Quantitative Finance ◽  
No Arbitrage ◽  
Statistical Arbitrage ◽  
Arbitrage Opportunities ◽  
Complete Market ◽  
Black Scholes ◽  
Analytical Formulas

In this study, we consider the statistical arbitrage definition given in Hogan, S, R Jarrow, M Teo and M Warachka (2004). Testing market efficiency using statistical arbitrage with applications to momentum and value strategies, Journal of Financial Economics, 73, 525–565 and derive the statistical arbitrage condition in the multi-asset Black–Scholes economy building upon the single asset case studied in Göncü, A (2015). Statistical arbitrage in the Black Scholes framework. Quantitative Finance, 15(9), 1489–1499. Statistical arbitrage profits can be generated if there exists at least one asset in the economy that satisfies the statistical arbitrage condition. Therefore, adding a no-statistical arbitrage condition to no-arbitrage pricing models is not realistic if not feasible. However, with an example we show that what excludes statistical arbitrage opportunities in the Black–Scholes economy, and possibly in other complete market models, is the presence of uncertainty or stochasticity in the model parameters. Furthermore, we derive analytical formulas for the expected value and probability of loss of the statistical arbitrage portfolios and compute optimal boundaries to sell the risky assets in the portfolio by maximizing the expected return with a constraint on the probability of loss.

scholarly journals Arbitragem Estatística: Uma Abordagem por VECM

2018 ◽  
Vol 15 (4) ◽  
pp. 537
Author(s):  
Paula Andrea Soto ◽  
Juan Carlos Ruilova Teran
Keyword(s):  
Principal Component ◽  
Trading Strategies ◽  
Market Prices ◽  
Vector Error Correction ◽  
Statistical Arbitrage ◽  
Vector Error ◽  
Arbitrage Opportunities ◽  
Vector Error Correction Models ◽  
Financing Market

This work develops a statistical arbitrage model which was tested on the Brazilian stock market. Prices were modeled using VECM (Vector Error Correction Models) to create a self-financing, market-neutral, long/short trading strategy. In this strategy, deviations in the long-term equilibrium of prices are identified in order to create buy and sell signals. Portfolios with common trends were selected by means of Principal Component Analysis. The viability of this strategy was empirically addressed using simulations on these portfolios. Its performance was also compared to other long/short trading strategies and were all analyzed in terms of returns, volatility and statistical arbitrage opportunities. The methodology used in this paper shows good results for modeling prices, and though all trading strategies offer considerable gains for the investor, the proposed strategy stands out by presenting statistical arbitrage.

The Term Structure of Equity Risk: An Empirical Analysis

CFA Digest ◽  
1997 ◽  
Vol 27 (1) ◽  
pp. 56-57
Author(s):  
H. Kent Baker
Keyword(s):  
Empirical Analysis ◽  
Term Structure ◽  
Equity Risk
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