Market Scenario Analysis

Risk Management Indexing index construction methodology has showcased its workability across markets, assets, risk preferences. In this white paper, we illustrate the working of RMI across different market scenarios, a bull market, a bear market and a sideways market. We had such market scenarios over the last decade across regions. For this paper, we have taken the US 30 and Europe 50 RMI models.
Scenarios: Different market scenarios translate to different starting points. There has always been a question regarding what if the RMI would have started in a different point of time. The idea was to assume different periods of growth and decay all not necessarily ending in the ongoing Nov 2013. Different periods of testing would test the methodology over different volatility conditions and remove any starting point bias.
Rebalancing strawman: Another discussion regarding rebalancing periods also becomes pertinent at this stage. The debate about whether to rebalance or not to rebalance takes another direction; as Arnott points out in, “Rebalancing still works”, writing a counter argument against Paul Merriman’s, “Why rebalancing could be a huge mistake”. Arnott said “Merriman has merely put forth, and knocked down, a flimsy and meaningless straw man. His argument requires that an investor, who values a particular asset mix at the outset, has no cares about how far that mix may drift away from that starting mix over time. If rebalancing is useful for asset allocation, it’s useful within segments of the stock market”. Merriman had suggested that rebalancing could work between stocks and bonds but not among stocks itself. Even Jason Hsu (Arnott’s team) points out in,“why we don’t rebalance”.“Despite all of the intellect and adaptive learning that we bring to bear, sadly human beings with our changing risk aversion are poorly suited as stewards for managing long-term returns.
But is rebalancing the only contributor to alpha? Just because investors suffer from behavioral errors and are ill equipped to understanding and time value, should rebalancing as an idea be overemphasized? Though rebalancing could be understood as a point of divergence warranting a need for allocation, but a superior allocation methodology could work across rebalancing periods and rebalancing period can just become another optimizable quant variable. The RMI methodology works across rebalancing periods.

Sharpe Ratio: Where Ra is the asset return, Rb is the return on a benchmark asset (taken as 1%), such as the risk free rate of return or an index such as the S&P 500. E[Ra-Rb] is the expected value of the excess of the asset return over the benchmark return, and {sigma} is the standard deviation of this excess return.
Summary: Periods of study; both the Indices have been studied for a minimum of 4 years and max of 10 years with starting data from 2000. RMI had more outperformance periods, risk-weighted excess returns. In case of the RMI US 30, there was only one period of underperformance over 17 test cases and two periods of marginal higher volatility (less than 0.1%). Europe 50 is one of the best cases for RMI just like TSX Toronto. The Europe 50 beat its benchmark in all the 17 cases (across volatility and returns). Looking for an underperforming case would be no more chance, but a cooked up case.