Evaluation of pairs trading strategy at the Brazilian financial market

Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. The idea is simple: find two stocks that move together and take long/short positions when they diverge abnormally, hoping that the prices will converge in the future. From the academic point of view of weak market efficiency theory, pairs trading strategy shouldn’t present positive performance since, according to it, the actual price of a stock reflects its past trading data, including historical prices. This leaves us with a question, does pairs trading strategy presents positive performance for the Brazilian market? The main objective of this research is to verify the performance and risk of pairs trading in the Brazilian financial market for different frequencies of the database, daily, weekly and monthly prices for the same time period. The main conclusion of this simulation is that pairs trading strategy was a profitable and market neutral strategy at the Brazilian Market. Such profitability was consistent over a region of the strategy’s parameters. The best results were found for the highest frequency (daily), which is an intuitive result

Bollinger Bands Thirty Years Later

The goal of this study is to explain and examine the statistical underpinnings of the Bollinger Band methodology. We start off by elucidating the rolling regression time series model and deriving its explicit relationship to Bollinger Bands. Next we illustrate the use of Bollinger Bands in pairs trading and prove the existence of a specific return duration relationship in Bollinger Band pairs trading.Then by viewing the Bollinger Band moving average as an approximation to the random walk plus noise (RWPN) time series model, we develop a pairs trading variant that we call "Fixed Forecast Maximum Duration' Bands" (FFMDPT). Lastly, we conduct pairs trading simulations using SAP and Nikkei index data in order to compare the performance of the variant with Bollinger Bands

Evaluation of pairs trading strategy at the Brazilian financial market

Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. The idea is simple: find two stocks that move together and take long/short positions when they diverge abnormally, hoping that the prices will converge in the future. From the academic point of view of weak market efficiency theory, pairs trading strategy shouldn’t present positive performance since, according to it, the actual price of a stock reflects its past trading data, including historical prices. This leaves us with a question, does pairs trading strategy presents positive performance for the Brazilian market? The main objective of this research is to verify the performance and risk of pairs trading in the Brazilian financial market for different frequencies of the database, daily, weekly and monthly prices for the same time period. The main conclusion of this simulation is that pairs trading strategy was a profitable and market neutral strategy at the Brazilian Market. Such profitability was consistent over a region of the strategy’s parameters. The best results were found for the highest frequency (daily), which is an intuitive result.pairs trading, quantitative strategy, asset allocation

Improving pairs trading

This paper tests the Pairs Trading strategy as proposed by Gatev, Goetzmann and Rouwenhorts (2006). It investigates if the profitability of pairs opening after an above average volume day in one of the assets are distinct in returns characteristics and if the introduction of a limit on the days the pair is open can improve the strategy returns. Results suggest that indeed pairs opening after a single sided shock are less profitable and that a limitation on the numbers of days a pair is open can significantly improve the profitability by as much as 30 basis points per month

Pairs Trading under Drift Uncertainty and Risk Penalization

In this work, we study a dynamic portfolio optimization problem related to pairs trading, which is an investment strategy that matches a long position in one security with a short position in another security with similar characteristics. The relationship between pairs, called a spread, is modeled by a Gaussian mean-reverting process whose drift rate is modulated by an unobservable continuous-time, finite-state Markov chain. Using the classical stochastic filtering theory, we reduce this problem with partial information to the one with full information and solve it for the logarithmic utility function, where the terminal wealth is penalized by the riskiness of the portfolio according to the realized volatility of the wealth process. We characterize optimal dollar-neutral strategies as well as optimal value functions under full and partial information and show that the certainty equivalence principle holds for the optimal portfolio strategy. Finally, we provide a numerical analysis for a toy example with a two-state Markov chain.Comment: 24 pages, 4 figure

Simulated Trading-An Analysis of Pairs Trading

In this report, we explain and analyze a trading strategy, popularly known as Pairs trading. We begin by explaining what a pair trading strategy entails. Since there are various ways of implementing the strategy, we describe the methodology selected by us in section 3. Thereafter, we look at the returns from the strategy and benchmark it to the S&P 500 index in Section 4. In section 5, we examine the risks involved in pairs trading. Section 6 looks at some of the limitations we faced while trading and Section 7 points out some mistakes we made. Finally, we discuss some risk control measures in Section 8 and conclude in Section 9 with comments on whether we would implement the strategy in real life and if so, with what changes.

Optimal Pairs Trading Rules

This thesis derives an optimal trading rule for a pair of historically correlated stocks. When one stock\u27s price increases and the other one\u27s decreases, a trade of the pair is triggered. The idea is to short the winner and to long the loser with the hope that the prices of the two assets will converge again. In this thesis the spread of the two stocks is governed by a mean-reverting model. The objective is to trade the pair in such a way as to maximize an overall return. The same slippage cost is imposed on every trade. Furthermore, a local-time process to the spread is introduced in order to avoid infinitely large gains. We use the associated Hamilton-Jacobi-Bellman equations to characterize the value functions which are solved by using the smooth-fit method. It is shown that the solution of the optimal pairs trading problem can be obtained by solving a set of nonlinear equations. Additionally, a set of sufficient conditions is provided in form of a verification theorem. The thesis concludes with a numerical example

Pairs trading : strategy refinements

In this paper, we apply the pairs trading strategy, original presented by Nunzio Tartaglia in mid-80´s, for the period between 2004 and 2014, to stocks listed in the London Stock Exchange. Our trading strategy seems to be highly profitable, with an average 6-month excess return of 15.39%. The strategy also proved to have better results when faced trouble economic environments like the subprime crisis. We have implemented several add-ons to the strategy, aiming to reduce its risk. A new liquidity restriction was implemented in selecting pairs so that the strategy is not constrained by any concerns about liquidity problems. Another implementation was the creation of stop loss strategies based on number of days with losses and by loss percentage, which, however, proved to be unrewarding on the attempt to maximize the returns. On the other hand, by proving the unfeasibility of the stop loss strategies, we also proved the robustness of our strategy because we perceive that even if the return of the pair is going down for consecutive days or for a certain percentage, it ends up converging

Dynamic Pairs Trading Strategy For The Companies Listed In The Istanbul Stock Exchange

In this research we performed pairs trading strategy based on a comparative mean reversion of asset prices with daily data over the period 2002 through 2008 in Istanbul Stock Exchange. We did not categorize stock pairs by sectors and therefore it is possible to observe mean reversion characteristics of different stocks that are selected from ISE-30 index. The initial formation period is 125 days (approx. 6 months) while we measure the performance results daily. Then both formation process and trading strategies have been structured as dynamic (rolling windows) market trading model through 2008. The results indicate that pairs produced average returns of % 3.36 daily comparing with the naïve buy and hold strategy. However ISE30 daily average return performance % 0.038 between 2002-2008 period. Our trading constraints and trading commissions take away the excess return on pairs mostly. Furthermore, the performance analysis reveals that the pairs trading strategy yields excess returns with less volatility than the market portfolio.mean reversion, pairs trading, distance method, market neutral portfolio, Istanbul Stock Exchange, trading strategies