Risk Control of Mean-Reversion Time in Statistical Arbitrage

2016 ◽  
Author(s):  
George Papanicolaou ◽  
Joongyeub Yeo
Keyword(s):  
Risk Control ◽  
Mean Reversion ◽  
Statistical Arbitrage

Risk control of mean-reversion time in statistical arbitrage

2018 ◽  
Vol 6 (4) ◽  
pp. 263-290 ◽  
Author(s):  
Joongyeub Yeo ◽  
George Papanicolaou
Keyword(s):  
Risk Control ◽  
Mean Reversion ◽  
Statistical Arbitrage

scholarly journals Some Notes on the Formation of a Pair in Pairs Trading

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 348 ◽  
Author(s):  
José Pedro Ramos-Requena ◽  
Juan Evangelista Trinidad-Segovia ◽  
Miguel Ángel Sánchez-Granero
Keyword(s):  
Hurst Exponent ◽  
Optimal Allocation ◽  
Mean Reversion ◽  
Equal Weight ◽  
Allocation Strategy ◽  
Pairs Trading ◽  
Distance Correlation ◽  
Statistical Arbitrage ◽  
New Methodologies ◽  
Set Up

The main goal of the paper is to introduce different models to calculate the amount of money that must be allocated to each stock in a statistical arbitrage technique known as pairs trading. The traditional allocation strategy is based on an equal weight methodology. However, we will show how, with an optimal allocation, the performance of pairs trading increases significantly. Four methodologies are proposed to set up the optimal allocation. These methodologies are based on distance, correlation, cointegration and Hurst exponent (mean reversion). It is showed that the new methodologies provide an improvement in the obtained results with respect to an equal weighted strategy.

scholarly journals Statistical Arbitrage in Emerging Markets: A Global Test of Efficiency

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 179
Author(s):  
Karen Balladares ◽  
José Pedro Ramos-Requena ◽  
Juan Evangelista Trinidad-Segovia ◽  
Miguel Angel Sánchez-Granero
Keyword(s):  
Emerging Markets ◽  
Market Efficiency ◽  
Hurst Exponent ◽  
Mean Reversion ◽  
Trading Strategy ◽  
Emerging Countries ◽  
Pairs Trading ◽  
Global Test ◽  
Statistical Arbitrage

In this paper, we use a statistical arbitrage method in different developed and emerging countries to show that the profitability of the strategy is based on the degree of market efficiency. We will show that our strategy is more profitable in emerging ones and in periods with greater uncertainty. Our method consists of a Pairs Trading strategy based on the concept of mean reversion by selecting pair series that have the lower Hurst exponent. We also show that the pair selection with the lowest Hurst exponent has sense, and the lower the Hurst exponent of the pair series, the better the profitability that is obtained. The sample is composed by the 50 largest capitalized companies of 39 countries, and the performance of the strategy is analyzed during the period from 1 January 2000 to 10 April 2020. For a deeper analysis, this period is divided into three different subperiods and different portfolios are also considered.

Learning and Mean Reversion in Asset Returns

CFA Digest ◽  
2000 ◽  
Vol 30 (3) ◽  
pp. 56-57
Author(s):  
William H. Sackley
Keyword(s):  
Mean Reversion ◽  
Asset Returns

Nonlinear Mean Reversion in Stock Prices

CFA Digest ◽  
2008 ◽  
Vol 38 (4) ◽  
pp. 37-38
Author(s):  
Michael Kobal
Keyword(s):  
Stock Prices ◽  
Mean Reversion ◽  
Nonlinear Mean Reversion

The Statistics of Statistical Arbitrage

CFA Digest ◽  
2008 ◽  
Vol 38 (1) ◽  
pp. 83-84
Author(s):  
Robert Fernholz ◽  
Cary Maguire
Keyword(s):  
Statistical Arbitrage

Risk Control Techniques for Social Investing

CFA Digest ◽  
2002 ◽  
Vol 32 (2) ◽  
pp. 93-94
Author(s):  
William H. Sackley
Keyword(s):  
Risk Control ◽  
Control Techniques ◽  
Social Investing
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