Research Papers
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Optuma and Research
A part of what we seek to do at Opuma is validate and benchmark different analysis to see how they compare in different types of markets. Our goal is to show the usefulness of indicators and demonstrate whether long-held beliefs about different Technical Analysis tools are based on fact or fiction.
We do this via our Signal Tester module. This module has been engineered to allow us to perform complex quantitative tests across hundreds of securities in seconds. Traditional Backtests show whether or not an idea can be traded, but they do not provide a full picture about what price is doing before and after the signal. The Signal Tester allows us to examine every instance of a technical signal across thousands of securities and measure the average performance and distribution of the average.
You will find a list of our Technical Analysis Research Projects from the Optuma team below. Make sure you follow us on Twitter or sign up for our Blog to be notified when new papers are added.
Volatility Based Support and Resistance
Author: Kirk Northington, CMT and Carson Dahlberg, CMT
Date: July 30th, 2016
Status: Working Paper
Favorable risk-adjusted returns can be, at times, as difficult to attain as a porcupine in a balloon factory. Forces are constantly at work to ensure that neither of these occurs. What follows will outline an emerging solution for forecasting technical price and volatility value levels. The solution is termed Volatility-Based Support Resistance (VBSR).
You will be able to understand how VBSR enables risk analysts, portfolio managers, and trading execution teams to forecast the best price levels for accumulation. Additionally, light will be shed on identifying points where market-implied volatility can be forecasted to alter its prevailing directional track.
Proper risk governance & oversight mandates that we execute careful processes for selecting opportunities. Steps to include macro market influences, investment mandates, and price/value forecasting involve multiple groups in the decision framework. Processes consume time and cause opportunities to be missed. Time, not unlike confirmation, consumes Alpha.
Buying Out Performers is Too Late
Author: Mathew Verdouw, CMT, CFTe
Date: August 5th, 2016
Status: Working Paper – Draft
In this paper we test the results of buying securities that have been outperforming the market. We are told two rules in finance: “Buy Low and Sell High” and also “Past Performance is not a guarantee of Future Returns”. Yet many advisers and investors will recommend the best-performing securities based on that very assumption. This paper shows that to maximise returns, there has to be a different way to examine when a security should be bought. We do this by using the Relative Rotation Graphs (RRG) to test if absolute returns can be improved by responding to the relative strength performance of each security using RRG charts. The paper also explains the basic concepts behind the RRG and gives the results from testing in all market conditions.
Dow's Theory of Confirmation Modernized
Author: Carson Dahlberg, CMT
Date: July 28th, 2016
Status: Complete
Charles Dow was concerned with managing returns in a context of risk. His process required identifying and confirming trends. He was aware the market trends were influenced by economics as well as behavioral biases. Therefore he required that up trends be confirmed in order to be more likely to persist. Dow’s Theory of Confirmation created a framework for making investment decisions. This paper takes Dow’s concept and models a modern version of Confirmation which demonstrates superior risk-adjusted returns.
Gann-Based Market Breadth
Author: Mathew Verdouw, CMT, CFTe
Date: August 1st, 2016
Status: Complete
RRG Weights
Author: Mathew Verdouw, CMT, CFTe
Date: February 24th, 2014
Status: Complete
Relative Rotation Graphs (RRG) are one of the most powerful ways that Relative Strength can be displayed and normalised on a single chart. In this paper, we explore if a set of securities on the RRG, which is benchmarked against an index that is made up of only those securities can be balanced on the X and Y axis. The results once we include Market Capitalisation are amazing.