Stage One - The Monitoring System
We began by establishing a foundation of past performance for each advisor related to the initial six 51% parameters detailed in article # 16 Refining Performance Evaluation an earlier article. A brief update is that over any 12 month time frame the following six parameters or acceptable variables from the parameters have to be established.
- 51% of all markets traded have to be profitable.
- 51% of all trades within each market have to be profitable.
- Profits have to exceed losses by at least 51% for each market traded.
- 51% of the initial margin required for each market is the maximum capital at risk on each trade.
- 51% of all markets traded at any time need to be profitable.
- Profits have to exceed losses of the composite portfolio by at least 51% at any one time.
This also becomes an internal benchmark for each strategy. Continuing analysis also requires tracking realized trades for each market and integrating them into an entire return. Realized trades are then translated into a rate of return based only on capital at risk, cost of money and time.
Some traders do not monitor individual trades. If the advisor trades only one or two markets, ask for maximum margin relative to realized returns for each period. Although inaccurate it’s better than beginning equity, which has no relationship to returns and capital at risk. Also request the 13 column track record used to assemble the capsule performance table in disclosure documents. Be sure that the trader who produced results you have is still trading the money.
Stage Two - The Foundation - How Information is Applied
Over time a weekly, bi-weekly or monthly table of percentage values representing the ratio of realized trading returns relative to capital at risk becomes a valuable tool for making decisions. The tables represent an example of a realized trading return relative to capital at risk used to produce the return (Realized Ratio as defined by SafeMoneyMetrics).
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The example is simplified. One value represents realized returns and $2200 represents margin requirements. The profit/loss values were listed in one excel column and margin in another. The third column is a result of dividing profit or loss by margin. We then took the average minimum and maximum for the data. An increased percentage indicates that the ratio is more profitable. As the percentage declines, the strategy is less profitable. Apply the example to every market traded in a strategy to see which market contributes to increased or decreased performance. We garner early insight into the potential of heavier losses before they become catastrophic. Decision rules and trend analysis can then be integrated.
The graph on the next page is the same data relative to a ZERO baseline. If we add data for each market traded in a strategy, we would learn how each market correlates with the others. Also how each market contributes to or detracts from the composite return.
We believe this to be an accurate indicator of Modern Portfolio Theory functioning at its best.
Composite Data
Individual Markets Relative to the Composite
Stage Three - Transposing Fundamental Truth for Increased Clarity
When used in hedging, basis is the difference between local cash market conditions and the nearest futures price. Basis remains constant no matter what market conditions are because basis includes analysis of the cash market. "Basis Analysis" is what people study and use when planning a hedge strategy. Basically we look at only two aspects of derivatives to formulate decisions. Basis and nearest futures price, life is that simple folks!
We adapted the direct strategy to use for asset management. Rather than track the difference between nearest futures and the local cash market, we simply applied a formula that includes capital at risk and realized trading returns. Those two factors are always in a relationship that either adds to or detracts from account profitability. It is a direct consistent relationship that can be adapted to individual trade analysis, any time interval bulking trades, each market within the composite or multi-advisor strategies and composite results. It tracks error efficiently and will accurately perceive strategy imbalances before a serious draw-down and within the market or sector causing the weakness.
Account Volatility
The analysis can also incorporate a ratio or percentage expression of capital at risk relative to unrealized returns for the same time frame. We call it a volatility ratio when used with SafeMoneyMetrics. The difference is an indicator of account volatility, without being distorted by account size. A correlation of realized to unrealized ratios can also prove useful. Although imperfect, a realized ratio applied to any aspect of analysis works for directly evaluating what any derivative investment really is: A human being taking disciplined action in a current market for the purpose of achieving a positive result.
Multiple Applications Become Possible
- The reliability of a Sharpe Ratio, Professor Dowd's decision rules described in "Beyond Value at Risk" DB Starks Trend Analysis or any traditional analysis is increased because traditional analysis can also be applied to SafeMoneyMetrics data.
- As the profitability percentage declines or narrows against a 0 baseline (profitability becomes less, we are in a draw-down) maybe a good time to add capital if the major decision to keep the strategy remains accurate. See Client Risk Management
- As differentials increase or widen we can distribute profits (profitability increases).
- During a period of lower percentages, look at each component of the composite to efficiently locate the weakness.
- We have immediate access to useful information and heightened awareness as to which part of the strategy relative to current market conditions needs to be adjusted.
- Superfluous information is eliminated, so the quality of decisions is increased.
- Compounded $1000 Unit values can be calculated for presentation purposes without severe distortion of truth.
- Data is easily applied to or integrated with traditional applications of risk analysis.
- An abundance of data over a short period of time increases the quality of risk management.
- If data is gathered weekly, time is contracted and risk control is increased. We can also benefit by using advisors having shorter formal track records. WHY? Many good advisors are missed early on because 36 data points (three years) minimum is needed for prudent analysis.
- Data can easily be reformatted for research purposes.
- Early warning reveals itself in trade evaluation and correlation analysis for each market and to the internal benchmark; rather than monthly rate of return calculations, draw-down analysis and relationships to benchmarks external to the strategy, which are all misleading.
- Correlation analysis using realized returns relative to capital at risk offers an impeccable foundation to compare and integrate multi-advisor investments