ETF Global Investor
- hypothetical · Annual Return (Compounded)
- 8.5%
- Max Drawdown
- 55.0%
- Trades
- 90
- Win Trades
- 37.8%
- Profit Factor
- 5.40
- Win Months
- 65.1%
About this strategy
Automated ETF Investing -- Remove the Emotion and Guesswork from Trading
The ETF Global Investor is a dynamic and complete investment system because it :
1. Always invests in sync with the prevailing trends
2. Selects the strongest sectors and regions of the world
3. Diversifies over different ETF positions and multiple asset classes
4. Does not risk more than 2% of account equity on any position
5. Is based on objective mathematical logic and not subjective factors
6. AutoTrading removes the bane of all investors.. the emotions of fear & greed
7. Uses strict risk management by employing trailing stops to reduce losses or lock-in profits
But quite frankly, the ETF Global Investor may not be for everyone. If you are satisfied with buy-and-hold "index fund investing" and merely keeping up with market averages, then this system may be too ambitious for you.
The ETF Global Investor is meant for the serious wealth builder who is not afraid to invest in any sector or region of the world and follow our strict discipline of cutting losses quickly while letting winners ride.
The 10-year period from 2000-2009 has been referred to as the Lost Decade. During these years, the 10-year average annualized return of the U.S. equity market (as measured by the S&P 500) was -1% (-0.95% to be exact). A $10,000 investment on Jan. 1, 2000, was worth $9,089 on Dec. 31, 2009.
Most investors have learned this lesson: perfectly timing markets in any form, be it stocks or exchange traded funds (ETFs), is next to impossible. So why are people still following the herd? There has to be a better way.
According to TrimTabs Investment Research, regular investors have lost around $39 billions more than was necessary in the stock markets as a result of buying during booms and selling during market panics, writes Brett Arends for Yahoo! Finance.
TrimTabs' data reveals that over the past decade, investors who bought when everyone else was selling and sold when everyone else was buying were the ones who came out on top. It sounds simple enough, but it isn't easy. Human instincts are hard-wired to follow the herd, since there is safety in numbers. But this evolutionary quirk doesn't serve us so well in the markets.
Putting feelings and emotion before cool logic does more harm than good. It's best to have a plan and a strategy in place. We use an advanced trend following strategy, which uses relative strength momentum (RSM) as a buying and selling guide. It helps minimize the emotional impact you can have on your investments and also provides a sell strategy to help protect you on the downside.
Why You Need a Proven Entry & Exit Strategy?
When it comes to investing in exchange traded funds (ETFs), having a strategy can be the difference between having a winning year and a losing one. Successful investing is hard work and takes a lot of time and discipline.
Emotional actions are failures, most of the time. What you need to do, especially in investing, is to remain totally objective. Easier said than done!
For this reason, we suggest using the EGI Investors trend following method, which will enable one to get in on any potential long-term uptrend without having to worry about staying in a certain profit/loss range. When the trend is over, you employ stop losses in order to protect yourself on the downside.
Another key component of having a strategy and checking out emotionally is to resist the urge to look back with regret. Not every trade is going to be a winner. Instead, learn from your mistakes while keeping your eyes fixed on the horizon.
When it comes to exchange traded fund (ETF) investing, do you have a strategy that you follow no matter what the market throws your way?
When you hold a position and it's in a long-term uptrend, you don't have to think about selling it. But what about on the downside? Is there a point at which you'd let go? Having a stop loss (and sticking to it) is one of the most important things an investor can do.
While investors want to be part of uptrends, especially long ones, at some point when the trend reverses itself (all trends come to an end sooner or later), those investors will want to protect their gains and limit their losses. Stop losses can assist with this.
Entry and exit strategies remove the emotional aspect of investing, which often shows itself in the form of rationalization. Thoughts such as "If I sell now, it could come back" are the bane of many investors.
But having strategies dictates that if a stock or fund is not "working," then you get rid of it and don't give it another thought. Knowing that there's a cap on how much you can lose can be reassuring to investors.
When you purchase an exchange traded fund (ETF), you're eventually going to have to sell it someday. By having an exit strategy, your decisions will have reason and definition behind them and there will be no confusion for you.
Trailing stops help investors by reducing losses or locking-in profits. They also remove the emotional part of investing and put a cap on the amount that one can lose.
Who's Going To Look Out For You If You Won't?
ETFs are the hottest thing going right now for investors, and we're living in volatile times. If you let them work for you, ETFs are a simple and cost-effective way to build and protect your future.
The increasing popularity of Exchange Traded Funds (ETF's) creates almost limitless opportunities for individual investors. But with a universe of more than 900 ETF's available to investors these days, the decision of what to own can quickly become overwhelming. To help with this dilemma, we have developed the ETF Global Investor system.
The portfolio utilizes a flexible approach of asset allocation. There are no predetermined guidelines whatsoever as to the level of stocks, bonds, cash, regions, countries, sectors, or even asset classes in the portfolio! In short, this is a completely flexible portfolio designed to follow the performance trail wherever it leads us. We can always find a bull market somewhere, if we know where to look.
The portfolio consists entirely of low-cost, tax efficient ETF's with an overall objective to "own the best and ignore the rest." More specifically, from a universe of over 900 ETFs, the ETF Global Investor will own only the top performers.
We scan a database consisting of more than 900 ETFs every day to find the best and the brightest ETFs for you. These include all domestic, international, commodity (including gold, silver, oil and agriculture), currency and inverse ETFs.
The ETF Global Investor can include both leveraged and inverse ETF's in the portfolio. It uses a self-adaptive, sector rotation strategy so during bear markets the inverse and the leveraged inverse ETFs are likely to rule the portfolio. Because of its self-adaptive nature, the selection algorithm can always find ETFs that are outperforming the market.
Diversification over 10 different ETFs plus the trailing stop ensures that we risk no more than 2% of account equity on any single trade. All buy & sell orders are placed and trailing stops adjusted before market open so there is no need to monitor anything during the day.
The system is a scientifically proven method for maximizing your investment while minimizing your downside risk. The ETF Global Investor is completely driven by mathematics - it analyzes ETF performance and determines which ETFs in the entire world are outperforming all others.
For a Limited Time, You Also Get a 15-day FREE Trial.
Don't decide now whether the ETF Global Investor is right for you. Take a full 15 days to put us to the test! If it doesn't show you exactly how to find the best ETFs in any market, just cancel and you will not be billed. There is absolutely no risk for you.
You will be NOT be charged during the free trial period. That will let you check out the system for a full 15 days at no cost to you.
After the 15-day trial, your credit card will be automatically billed $99.97 (only $3.33 per day) on the same date every month till you cancel. Membership is month-to-month and you may cancel at any time. You are in complete control.
Auto-trading is recommended so that all buy & sell trades are placed and trailing stops are adjusted automatically. That way you will not miss any crucial entries or exits.
But the system may be also used without auto-trading turned on, which means you'll have to place all trades manually with your preferred broker.
Your satisfaction is completely assured through our no risk, you-can't-lose, no-questions-asked, iron-clad guarantee.
If for any reason, you are not completely delighted with the ETF Global Investor, just cancel within 15 days and owe absolutely nothing. No hard feelings, no hassles and absolutely no questions asked.
Sincerely,
Roger Williams
Portfolio Manager, ETF Global Investor
P.S. This really is a no-brainer. Just try the ETF Global Investor for the next 15 days. It does not cost you anything - zero, zilch, nada. You will receive a reminder e-mail (with an unsubscription link) a couple of days before the trial ends so that there are no surprises. Just cancel at that time if you feel that the ETF Global Investor is not suitable for you.
The ETF Global Investor is a dynamic and complete investment system because it :
1. Always invests in sync with the prevailing trends
2. Selects the strongest sectors and regions of the world
3. Diversifies over different ETF positions and multiple asset classes
4. Does not risk more than 2% of account equity on any position
5. Is based on objective mathematical logic and not subjective factors
6. AutoTrading removes the bane of all investors.. the emotions of fear & greed
7. Uses strict risk management by employing trailing stops to reduce losses or lock-in profits
But quite frankly, the ETF Global Investor may not be for everyone. If you are satisfied with buy-and-hold "index fund investing" and merely keeping up with market averages, then this system may be too ambitious for you.
The ETF Global Investor is meant for the serious wealth builder who is not afraid to invest in any sector or region of the world and follow our strict discipline of cutting losses quickly while letting winners ride.
The 10-year period from 2000-2009 has been referred to as the Lost Decade. During these years, the 10-year average annualized return of the U.S. equity market (as measured by the S&P 500) was -1% (-0.95% to be exact). A $10,000 investment on Jan. 1, 2000, was worth $9,089 on Dec. 31, 2009.
Most investors have learned this lesson: perfectly timing markets in any form, be it stocks or exchange traded funds (ETFs), is next to impossible. So why are people still following the herd? There has to be a better way.
According to TrimTabs Investment Research, regular investors have lost around $39 billions more than was necessary in the stock markets as a result of buying during booms and selling during market panics, writes Brett Arends for Yahoo! Finance.
TrimTabs' data reveals that over the past decade, investors who bought when everyone else was selling and sold when everyone else was buying were the ones who came out on top. It sounds simple enough, but it isn't easy. Human instincts are hard-wired to follow the herd, since there is safety in numbers. But this evolutionary quirk doesn't serve us so well in the markets.
Putting feelings and emotion before cool logic does more harm than good. It's best to have a plan and a strategy in place. We use an advanced trend following strategy, which uses relative strength momentum (RSM) as a buying and selling guide. It helps minimize the emotional impact you can have on your investments and also provides a sell strategy to help protect you on the downside.
Why You Need a Proven Entry & Exit Strategy?
When it comes to investing in exchange traded funds (ETFs), having a strategy can be the difference between having a winning year and a losing one. Successful investing is hard work and takes a lot of time and discipline.
Emotional actions are failures, most of the time. What you need to do, especially in investing, is to remain totally objective. Easier said than done!
For this reason, we suggest using the EGI Investors trend following method, which will enable one to get in on any potential long-term uptrend without having to worry about staying in a certain profit/loss range. When the trend is over, you employ stop losses in order to protect yourself on the downside.
Another key component of having a strategy and checking out emotionally is to resist the urge to look back with regret. Not every trade is going to be a winner. Instead, learn from your mistakes while keeping your eyes fixed on the horizon.
When it comes to exchange traded fund (ETF) investing, do you have a strategy that you follow no matter what the market throws your way?
When you hold a position and it's in a long-term uptrend, you don't have to think about selling it. But what about on the downside? Is there a point at which you'd let go? Having a stop loss (and sticking to it) is one of the most important things an investor can do.
While investors want to be part of uptrends, especially long ones, at some point when the trend reverses itself (all trends come to an end sooner or later), those investors will want to protect their gains and limit their losses. Stop losses can assist with this.
Entry and exit strategies remove the emotional aspect of investing, which often shows itself in the form of rationalization. Thoughts such as "If I sell now, it could come back" are the bane of many investors.
But having strategies dictates that if a stock or fund is not "working," then you get rid of it and don't give it another thought. Knowing that there's a cap on how much you can lose can be reassuring to investors.
When you purchase an exchange traded fund (ETF), you're eventually going to have to sell it someday. By having an exit strategy, your decisions will have reason and definition behind them and there will be no confusion for you.
Trailing stops help investors by reducing losses or locking-in profits. They also remove the emotional part of investing and put a cap on the amount that one can lose.
Who's Going To Look Out For You If You Won't?
ETFs are the hottest thing going right now for investors, and we're living in volatile times. If you let them work for you, ETFs are a simple and cost-effective way to build and protect your future.
The increasing popularity of Exchange Traded Funds (ETF's) creates almost limitless opportunities for individual investors. But with a universe of more than 900 ETF's available to investors these days, the decision of what to own can quickly become overwhelming. To help with this dilemma, we have developed the ETF Global Investor system.
The portfolio utilizes a flexible approach of asset allocation. There are no predetermined guidelines whatsoever as to the level of stocks, bonds, cash, regions, countries, sectors, or even asset classes in the portfolio! In short, this is a completely flexible portfolio designed to follow the performance trail wherever it leads us. We can always find a bull market somewhere, if we know where to look.
The portfolio consists entirely of low-cost, tax efficient ETF's with an overall objective to "own the best and ignore the rest." More specifically, from a universe of over 900 ETFs, the ETF Global Investor will own only the top performers.
We scan a database consisting of more than 900 ETFs every day to find the best and the brightest ETFs for you. These include all domestic, international, commodity (including gold, silver, oil and agriculture), currency and inverse ETFs.
The ETF Global Investor can include both leveraged and inverse ETF's in the portfolio. It uses a self-adaptive, sector rotation strategy so during bear markets the inverse and the leveraged inverse ETFs are likely to rule the portfolio. Because of its self-adaptive nature, the selection algorithm can always find ETFs that are outperforming the market.
Diversification over 10 different ETFs plus the trailing stop ensures that we risk no more than 2% of account equity on any single trade. All buy & sell orders are placed and trailing stops adjusted before market open so there is no need to monitor anything during the day.
The system is a scientifically proven method for maximizing your investment while minimizing your downside risk. The ETF Global Investor is completely driven by mathematics - it analyzes ETF performance and determines which ETFs in the entire world are outperforming all others.
For a Limited Time, You Also Get a 15-day FREE Trial.
Don't decide now whether the ETF Global Investor is right for you. Take a full 15 days to put us to the test! If it doesn't show you exactly how to find the best ETFs in any market, just cancel and you will not be billed. There is absolutely no risk for you.
You will be NOT be charged during the free trial period. That will let you check out the system for a full 15 days at no cost to you.
After the 15-day trial, your credit card will be automatically billed $99.97 (only $3.33 per day) on the same date every month till you cancel. Membership is month-to-month and you may cancel at any time. You are in complete control.
Auto-trading is recommended so that all buy & sell trades are placed and trailing stops are adjusted automatically. That way you will not miss any crucial entries or exits.
But the system may be also used without auto-trading turned on, which means you'll have to place all trades manually with your preferred broker.
Your satisfaction is completely assured through our no risk, you-can't-lose, no-questions-asked, iron-clad guarantee.
If for any reason, you are not completely delighted with the ETF Global Investor, just cancel within 15 days and owe absolutely nothing. No hard feelings, no hassles and absolutely no questions asked.
Sincerely,
Roger Williams
Portfolio Manager, ETF Global Investor
P.S. This really is a no-brainer. Just try the ETF Global Investor for the next 15 days. It does not cost you anything - zero, zilch, nada. You will receive a reminder e-mail (with an unsubscription link) a couple of days before the trial ends so that there are no surprises. Just cancel at that time if you feel that the ETF Global Investor is not suitable for you.
Hypothetical Monthly Returns (includes fees/commissions)
| Year | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | YTD |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2010 | 9.2 | 4.5 | -3.1 | 12.1 | 23.9 | ||||||||
| 2011 | 4.0 | 5.1 | -10.2 | 7.0 | -12.2 | -8.1 | -4.0 | -5.7 | -6.1 | 3.5 | -17.7 | 1.5 | -37.8 |
| 2012 | -17.6 | 27.4 | 3.4 | 0.5 | -7.0 | 4.7 | 0.8 | 2.9 | 1.6 | -2.1 | 0.2 | -0.5 | 9.3 |
| 2013 | 5.5 | 0.9 | 3.2 | 1.5 | 3.6 | -1.2 | 5.0 | -3.6 | 3.7 | 5.1 | 1.9 | 2.4 | 31.4 |
| 2014 | -3.1 | 4.8 | -2.0 | 1.3 | 1.8 | 1.8 | -1.4 | 4.5 | -1.3 | 2.4 | 4.7 | 0.4 | 14.4 |
| 2015 | -1.1 | 5.4 | -1.2 | 0.1 | 1.2 | -1.9 | 3.4 | -4.3 | 1.2 | 6.4 | 0.9 | -1.8 | 8.2 |
| 2016 | -3.5 | 0.8 | 5.4 | -1.3 | 1.0 | 0.7 | 4.0 | -0.5 | -0.7 | -1.1 | 2.9 | 0.4 | 8.0 |
| 2017 | 2.4 | 3.5 | 0.3 | 1.9 | 1.5 | -0.9 | 1.0 | -0.6 | 0.9 | 2.9 | 4.1 | 2.0 | 20.6 |
| 2018 | 5.9 | -0.9 | -3.4 | 2.0 | 2.0 | 2.0 | 1.8 | 4.9 | -0.6 | -8.4 | 0.2 | -5.7 | -1.2 |
| 2019 | 8.6 | 2.3 | 3.6 | 0.0 | 0.0 | -0.5 | 3.4 | 1.8 | 1.7 | 2.8 | 29.1 | ||
| 2020 | 1.9 | -7.4 | -13.5 | 13.8 | 8.3 | 2.1 | 4.7 | 9.8 | -3.6 | 0.2 | 7.6 | 0.0 | 0.0 |
| 2021 | -15.7 | 3.7 | -1.0 | 1.5 | 2.2 | 0.4 | -1.8 | 5.7 | 1.3 | 3.3 | -2.0 | ||
| 2022 | -7.6 | -0.4 | 5.1 | -7.2 | -4.5 | -8.4 | 11.2 | -2.2 | -6.0 | 2.8 | 1.9 | -6.4 | -21.2 |
| 2023 | 7.6 | -1.7 | -1.4 | 3.0 | 1.3 | 4.0 | 4.2 | -1.3 | -4.5 | -3.0 | 8.4 | 5.8 | 23.8 |
| 2024 | -0.5 | 4.2 | 2.4 | -3.5 | 1.2 | 2.6 | 1.8 | 0.3 | 2.7 | 1.7 | 4.7 | 1.3 | 20.3 |
| 2025 | 2.7 | -3.0 | -3.8 | -3.9 | 7.8 | 1.1 | 2.8 | 2.8 | 1.5 | 1.7 | 0.0 | 0.5 | 10.2 |
| 2026 | 2.2 | -0.9 | -4.3 | 7.0 | 2.6 | -2.8 | 0.4 | 3.9 | -3.7 | 4.1 |
Statistics
Overview
| Strategy began | 9/1/2010 |
|---|---|
| Suggested Minimum Capital | $10,000 |
| Age | 195 months |
| What it trades | Stocks |
| # Trades | 90 |
| # Profitable | 34 |
| % Profitable | 37.8% |
| Avg trade duration | 279.5 days |
| Max peak-to-valley drawdown | 55.0% |
| drawdown period | Feb 18, 2011 - Jan 29, 2012 |
| Annual Return (Compounded) | 8.5% |
| Avg win | $962 |
| Avg loss | $120 |
Ratios
| W:L ratio | 5.42 |
|---|---|
| Sharpe Ratio | 0.38 |
| Sortino Ratio | 0.53 |
| Calmar Ratio | 0.99 |
CORRELATION STATISTICS
| Correlation to SP500 | 0.58 |
|---|---|
| Return Percent SP500 (cumu) during strategy life | 599.1% |
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | -330.8% |
Return Statistics
| Ann Return (w trading costs) | 8.5% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | 0.1% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | 9.0% |
Slump
| Current Slump as Pcnt Equity | 3.8% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.0% |
Instruments
| Percent Trades Forex | 0.0% |
|---|---|
| Percent Trades Futures | 0.0% |
| Percent Trades Options | 0.0% |
| Percent Trades Stocks | 1.0% |
Risk of Ruin (Monte-Carlo)
| Chance of 10% account loss | 100.0% |
|---|---|
| Chance of 20% account loss | 100.0% |
| Chance of 30% account loss | 100.0% |
| Chance of 40% account loss | 100.0% |
| Chance of 50% account loss | 100.0% |
| Chance of 60% account loss (Monte Carlo) | 0.0% |
| Chance of 70% account loss (Monte Carlo) | 0.0% |
| Chance of 80% account loss (Monte Carlo) | 0.0% |
| Chance of 90% account loss (Monte Carlo) | 0.0% |
| Chance of 100% account loss (Monte Carlo) | 0.0% |
Automation
| Percentage Signals Automated | 0.0% |
|---|
Popularity
| Popularity (Today) | 0 |
|---|---|
| Popularity (Last 6 weeks) | 0 |
| Popularity (7 days, Percentile 1000 scale) | 0 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 0 |
|---|---|
| TOS percent | 0.0% |
Win / Loss
| Avg Loss | $120 |
|---|---|
| Avg Win | $962 |
| # Winners | 34 |
| Sum Trade PL (losers) | $6,737 |
| Sum Trade PL (winners) | $32,708 |
| Num Months Winners | 124 |
| # Losers | 56 |
| % Winners | 37.8% |
Dividends
| Dividends Received in Model Acct | 3806 |
|---|
Age
| Num Months filled monthly returns table | 193 |
|---|
Frequency
| Avg Position Time (mins) | 402445.12 |
|---|---|
| Avg Position Time (hrs) | 6707.42 |
| Avg Trade Length | 279.50 |
| Last Trade Ago | 5406 |
Regression
| Alpha | 0 |
|---|---|
| Beta | 0.60 |
| Treynor Index | 0.04 |
Maximum Adverse Excursion (MAE)
| MAE:Equity, average, all trades | 0.01 |
|---|---|
| MAE:Equity, 95th Percentile Value for this strat | 0.02 |
| MAE:Equity, average, losing trades | 0.01 |
| MAE:Equity, losing trades only, 95th Percentile Value for this strat | — |
| MAE:Equity, average, winning trades | 0 |
| MAE:Equity, win trades only, 95th Percentile Value for this strat | — |
| Avg(MAE) / Avg(PL) - All trades | 0.32 |
| MAE:PL (avg, all trades) | -0.29 |
| MAE:PL (avg, losing trades) | — |
| MAE:PL - Losing Trades - this strat Percentile of All Strats | 7.57 |
| MAE:PL - Winning Trades - this strat Percentile of All Strats | 29.90 |
| MAE:PL (avg, winning trades) | — |
| MAE:PL - worst single value for strategy | — |
| Avg(MAE) / Avg(PL) - Winning trades | 0.04 |
| Avg(MAE) / Avg(PL) - Losing trades | -1.05 |
| Hold-and-Hope Ratio | 2.83 |
RATIO STATISTICS
| Mean | 0.32 |
|---|---|
| SD | 0.23 |
| Sharpe ratio (Glass type estimate) | 1.37 |
| Sharpe ratio (Hedges UMVUE) | 1.35 |
| df | 53 |
| t | 2.91 |
| p | 0.00 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.40 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 2.32 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.39 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 2.31 |
| Sortino ratio | 2.90 |
| Upside Potential Ratio | 4.41 |
| Upside part of mean | 0.49 |
| Downside part of mean | -0.17 |
| Upside SD | 0.22 |
| Downside SD | 0.11 |
| N nonnegative terms | 36 |
| N negative terms | 18 |
| N of observations | 54 |
| Mean of predictor | 0.44 |
| Mean of criterion | 0.32 |
| SD of predictor | 0.25 |
| SD of criterion | 0.23 |
| Covariance | 0.04 |
| r | 0.64 |
| b (slope, estimate of beta) | 0.60 |
| a (intercept, estimate of alpha) | 0.06 |
| Mean Square Error | 0.03 |
| DF error | 52 |
| t(b) | 6.01 |
| p(b) | 0 |
| t(a) | 0.60 |
| p(a) | 0.28 |
| Lowerbound of 95% confidence interval for beta | 0.40 |
| Upperbound of 95% confidence interval for beta | 0.80 |
| Lowerbound of 95% confidence interval for alpha | -0.14 |
| Upperbound of 95% confidence interval for alpha | 0.25 |
| Treynor index (mean / b) | 0.53 |
| Jensen alpha (a) | 0.06 |
| Mean | 0.29 |
| SD | 0.23 |
| Sharpe ratio (Glass type estimate) | 1.28 |
| Sharpe ratio (Hedges UMVUE) | 1.26 |
| df | 53 |
| t | 2.71 |
| p | 0.00 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.32 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 2.23 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.31 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 2.22 |
| Sortino ratio | 2.50 |
| Upside Potential Ratio | 3.99 |
| Upside part of mean | 0.47 |
| Downside part of mean | -0.17 |
| Upside SD | 0.21 |
| Downside SD | 0.12 |
| N nonnegative terms | 36 |
| N negative terms | 18 |
| N of observations | 54 |
| Mean of predictor | 0.40 |
| Mean of criterion | 0.29 |
| SD of predictor | 0.24 |
| SD of criterion | 0.23 |
| Covariance | 0.04 |
| r | 0.66 |
| b (slope, estimate of beta) | 0.63 |
| a (intercept, estimate of alpha) | 0.04 |
| Mean Square Error | 0.03 |
| DF error | 52 |
| t(b) | 6.31 |
| p(b) | 0 |
| t(a) | 0.44 |
| p(a) | 0.33 |
| Lowerbound of 95% confidence interval for beta | 0.43 |
| Upperbound of 95% confidence interval for beta | 0.83 |
| Lowerbound of 95% confidence interval for alpha | -0.14 |
| Upperbound of 95% confidence interval for alpha | 0.22 |
| Treynor index (mean / b) | 0.47 |
| Jensen alpha (a) | 0.04 |
| VaR(95%) | 0.08 |
| Expected Shortfall on VaR | 0.11 |
| VaR(95%) | 0.02 |
| Expected Shortfall on VaR | 0.05 |
| Mean | 0.36 |
| SD | 0.34 |
| Sharpe ratio (Glass type estimate) | 1.07 |
| Sharpe ratio (Hedges UMVUE) | 1.07 |
| df | 1195 |
| t | 2.29 |
| p | 0.46 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.15 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.99 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.15 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.99 |
| Sortino ratio | 1.48 |
| Upside Potential Ratio | 7.38 |
| Upside part of mean | 1.80 |
| Downside part of mean | -1.44 |
| Upside SD | 0.23 |
| Downside SD | 0.24 |
| N nonnegative terms | 726 |
| N negative terms | 470 |
| N of observations | 1196 |
| Mean of predictor | 0.48 |
| Mean of criterion | 0.36 |
| SD of predictor | 0.33 |
| SD of criterion | 0.34 |
| Covariance | 0.07 |
| r | 0.64 |
| b (slope, estimate of beta) | 0.65 |
| a (intercept, estimate of alpha) | 0.05 |
| Mean Square Error | 0.07 |
| DF error | 1194 |
| t(b) | 28.70 |
| p(b) | 0.18 |
| t(a) | 0.38 |
| p(a) | 0.49 |
| Lowerbound of 95% confidence interval for beta | 0.60 |
| Upperbound of 95% confidence interval for beta | 0.69 |
| Lowerbound of 95% confidence interval for alpha | -0.19 |
| Upperbound of 95% confidence interval for alpha | 0.28 |
| Treynor index (mean / b) | 0.56 |
| Jensen alpha (a) | 0.05 |
| Mean | 0.30 |
| SD | 0.34 |
| Sharpe ratio (Glass type estimate) | 0.89 |
| Sharpe ratio (Hedges UMVUE) | 0.89 |
| df | 1195 |
| t | 1.90 |
| p | 0.47 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.03 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 1.81 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.03 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 1.81 |
| Sortino ratio | 1.19 |
| Upside Potential Ratio | 6.95 |
| Upside part of mean | 1.77 |
| Downside part of mean | -1.47 |
| Upside SD | 0.22 |
| Downside SD | 0.25 |
| N nonnegative terms | 726 |
| N negative terms | 470 |
| N of observations | 1196 |
| Mean of predictor | 0.43 |
| Mean of criterion | 0.30 |
| SD of predictor | 0.34 |
| SD of criterion | 0.34 |
| Covariance | 0.08 |
| r | 0.65 |
| b (slope, estimate of beta) | 0.64 |
| a (intercept, estimate of alpha) | 0.03 |
| Mean Square Error | 0.07 |
| DF error | 1194 |
| t(b) | 29.33 |
| p(b) | 0.18 |
| t(a) | 0.23 |
| p(a) | 0.50 |
| Lowerbound of 95% confidence interval for beta | 0.60 |
| Upperbound of 95% confidence interval for beta | 0.68 |
| Lowerbound of 95% confidence interval for alpha | -0.21 |
| Upperbound of 95% confidence interval for alpha | 0.27 |
| Treynor index (mean / b) | 0.47 |
| Jensen alpha (a) | 0.03 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.04 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.02 |
| Mean | 1.01 |
| SD | 0.35 |
| Sharpe ratio (Glass type estimate) | 2.89 |
| Sharpe ratio (Hedges UMVUE) | 2.87 |
| df | 130 |
| t | 2.04 |
| p | 0.41 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | 0.09 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 5.68 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | 0.08 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 5.67 |
| Sortino ratio | 4.49 |
| Upside Potential Ratio | 11.53 |
| Upside part of mean | 2.60 |
| Downside part of mean | -1.58 |
| Upside SD | 0.27 |
| Downside SD | 0.23 |
| N nonnegative terms | 80 |
| N negative terms | 51 |
| N of observations | 131 |
| Mean of predictor | 1.44 |
| Mean of criterion | 1.01 |
| SD of predictor | 0.40 |
| SD of criterion | 0.35 |
| Covariance | 0.13 |
| r | 0.92 |
| b (slope, estimate of beta) | 0.81 |
| a (intercept, estimate of alpha) | -0.16 |
| Mean Square Error | 0.02 |
| DF error | 129 |
| t(b) | 26.44 |
| p(b) | 0.01 |
| t(a) | -0.78 |
| p(a) | 0.54 |
| Lowerbound of 95% confidence interval for beta | 0.75 |
| Upperbound of 95% confidence interval for beta | 0.87 |
| Lowerbound of 95% confidence interval for alpha | -0.55 |
| Upperbound of 95% confidence interval for alpha | 0.24 |
| Treynor index (mean / b) | 1.24 |
| Jensen alpha (a) | -0.16 |
| Mean | 0.95 |
| SD | 0.35 |
| Sharpe ratio (Glass type estimate) | 2.71 |
| Sharpe ratio (Hedges UMVUE) | 2.69 |
| df | 130 |
| t | 1.92 |
| p | 0.42 |
| Lowerbound of 95% confidence interval for Sharpe Ratio | -0.09 |
| Upperbound of 95% confidence interval for Sharpe Ratio | 5.50 |
| Lowerbound of 95% CI (Gibbons, Hedeker & Davis approximation | -0.10 |
| Upperbound of 95% CI (Gibbons, Hedeker & Davis approximation | 5.49 |
| Sortino ratio | 4.12 |
| Upside Potential Ratio | 11.11 |
| Upside part of mean | 2.56 |
| Downside part of mean | -1.61 |
| Upside SD | 0.27 |
| Downside SD | 0.23 |
| N nonnegative terms | 80 |
| N negative terms | 51 |
| N of observations | 131 |
| Mean of predictor | 1.35 |
| Mean of criterion | 0.95 |
| SD of predictor | 0.40 |
| SD of criterion | 0.35 |
| Covariance | 0.13 |
| r | 0.92 |
| b (slope, estimate of beta) | 0.81 |
| a (intercept, estimate of alpha) | -0.15 |
| Mean Square Error | 0.02 |
| DF error | 129 |
| t(b) | 26.41 |
| p(b) | 0.01 |
| t(a) | -0.75 |
| p(a) | 0.54 |
| Lowerbound of 95% confidence interval for beta | 0.75 |
| VAR (95 Confidence Intrvl) | 0.03 |
| Upperbound of 95% confidence interval for beta | 0.87 |
| Lowerbound of 95% confidence interval for alpha | -0.55 |
| Upperbound of 95% confidence interval for alpha | 0.25 |
| Treynor index (mean / b) | 1.17 |
| Jensen alpha (a) | -0.15 |
| VaR(95%) | 0.03 |
| Expected Shortfall on VaR | 0.04 |
| VaR(95%) | 0.01 |
| Expected Shortfall on VaR | 0.02 |
ORDER STATISTICS
| Number of observations | 54 |
|---|---|
| Minimum | 0.86 |
| Quartile 1 | 0.99 |
| Median | 1.02 |
| Quartile 3 | 1.06 |
| Maximum | 1.20 |
| Mean of quarter 1 | 0.95 |
| Mean of quarter 2 | 1.01 |
| Mean of quarter 3 | 1.04 |
| Mean of quarter 4 | 1.11 |
| Inter Quartile Range | 0.07 |
| Number outliers low | 1 |
| Percentage of outliers low | 0.02 |
| Mean of outliers low | 0.86 |
| Number of outliers high | 2 |
| Percentage of outliers high | 0.04 |
| Mean of outliers high | 1.18 |
| Extreme Value Index (moments method) | -0.59 |
| VaR(95%) (moments method) | 0.04 |
| Expected Shortfall (moments method) | 0.04 |
| Extreme Value Index (regression method) | -0.23 |
| VaR(95%) (regression method) | 0.06 |
| Expected Shortfall (regression method) | 0.08 |
| Number of observations | 1196 |
| Minimum | 0.80 |
| Quartile 1 | 0.99 |
| Median | 1.00 |
| Quartile 3 | 1.01 |
| Maximum | 1.14 |
| Mean of quarter 1 | 0.98 |
| Mean of quarter 2 | 1.00 |
| Mean of quarter 3 | 1.00 |
| Mean of quarter 4 | 1.02 |
| Inter Quartile Range | 0.01 |
| Number outliers low | 69 |
| Percentage of outliers low | 0.06 |
| Mean of outliers low | 0.95 |
| Number of outliers high | 51 |
| Percentage of outliers high | 0.04 |
| Mean of outliers high | 1.05 |
| Extreme Value Index (moments method) | 0.60 |
| VaR(95%) (moments method) | 0.02 |
| Expected Shortfall (moments method) | 0.06 |
| Extreme Value Index (regression method) | 0.39 |
| VaR(95%) (regression method) | 0.02 |
| Expected Shortfall (regression method) | 0.03 |
| Number of observations | 131 |
| Minimum | 0.92 |
| Quartile 1 | 0.99 |
| Median | 1.00 |
| Quartile 3 | 1.02 |
| Maximum | 1.07 |
| Mean of quarter 1 | 0.98 |
| Mean of quarter 2 | 1.00 |
| Mean of quarter 3 | 1.01 |
| Mean of quarter 4 | 1.03 |
| Inter Quartile Range | 0.02 |
| Number outliers low | 4 |
| Percentage of outliers low | 0.03 |
| Mean of outliers low | 0.94 |
| Number of outliers high | 3 |
| Percentage of outliers high | 0.02 |
| Mean of outliers high | 1.06 |
| Extreme Value Index (moments method) | 0.45 |
| VaR(95%) (moments method) | 0.02 |
| Expected Shortfall (moments method) | 0.05 |
| Extreme Value Index (regression method) | 0.14 |
| VaR(95%) (regression method) | 0.02 |
| Expected Shortfall (regression method) | 0.03 |
DRAW DOWN STATISTICS
| Number of observations | 7 |
|---|---|
| Minimum | 0.00 |
| Quartile 1 | 0.02 |
| Median | 0.04 |
| Quartile 3 | 0.12 |
| Maximum | 0.32 |
| Mean of quarter 1 | 0.01 |
| Mean of quarter 2 | 0.03 |
| Mean of quarter 3 | 0.05 |
| Mean of quarter 4 | 0.25 |
| Inter Quartile Range | 0.09 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.14 |
| Mean of outliers high | 0.32 |
| Extreme Value Index (moments method) | 0 |
| VaR(95%) (moments method) | 0 |
| Expected Shortfall (moments method) | 0 |
| Extreme Value Index (regression method) | 0 |
| VaR(95%) (regression method) | 0 |
| Expected Shortfall (regression method) | 0 |
| Number of observations | 67 |
| Minimum | 0.00 |
| Quartile 1 | 0.01 |
| Median | 0.02 |
| Quartile 3 | 0.05 |
| Maximum | 0.36 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.01 |
| Mean of quarter 3 | 0.03 |
| Mean of quarter 4 | 0.11 |
| Inter Quartile Range | 0.04 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 7 |
| Percentage of outliers high | 0.10 |
| Mean of outliers high | 0.20 |
| Extreme Value Index (moments method) | 0.64 |
| VaR(95%) (moments method) | 0.13 |
| Expected Shortfall (moments method) | 0.38 |
| Extreme Value Index (regression method) | 0.98 |
| VaR(95%) (regression method) | 0.11 |
| Expected Shortfall (regression method) | 4.26 |
| Number of observations | 21 |
| Minimum | 0.00 |
| Quartile 1 | 0.01 |
| Median | 0.01 |
| Quartile 3 | 0.05 |
| Maximum | 0.14 |
| Mean of quarter 1 | 0.00 |
| Mean of quarter 2 | 0.01 |
| Mean of quarter 3 | 0.03 |
| Mean of quarter 4 | 0.07 |
| Inter Quartile Range | 0.04 |
| Number outliers low | 0 |
| Percentage of outliers low | 0 |
| Mean of outliers low | 0 |
| Number of outliers high | 1 |
| Percentage of outliers high | 0.05 |
| Mean of outliers high | 0.14 |
| Extreme Value Index (moments method) | 0.43 |
| VaR(95%) (moments method) | 0.09 |
| Expected Shortfall (moments method) | 0.15 |
| Extreme Value Index (regression method) | 1.61 |
| VaR(95%) (regression method) | 0.09 |
| Expected Shortfall (regression method) | 0 |
| Strat Max DD how much worse than SP500 max DD during strat life? | -388561728 |
| Max Equity Drawdown (num days) | 345 |
| Last 4 Months - Pcnt Negative | 0.5% |
COMBINED STATISTICS
| Annualized return (arithmetic extrapolation) | 0.60 |
|---|---|
| Compounded annual return (geometric extrapolation) | 0.34 |
| Calmar ratio (compounded annual return / max draw down) | 1.07 |
| Compounded annual return / average of 25% largest draw downs | 1.37 |
| Compounded annual return / Expected Shortfall lognormal | 3.22 |
| j156mfCOMBRisPar | 0 |
| j157mfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 0.65 |
| Compounded annual return (geometric extrapolation) | 0.35 |
| Calmar ratio (compounded annual return / max draw down) | 0.99 |
| Compounded annual return / average of 25% largest draw downs | 3.08 |
| Compounded annual return / Expected Shortfall lognormal | 8.57 |
| j313dfCOMBRisPar | 0 |
| j314dfCOMBRisPar | 0 |
| Annualized return (arithmetic extrapolation) | 1.21 |
| Compounded annual return (geometric extrapolation) | 1.58 |
| Calmar ratio (compounded annual return / max draw down) | 11.63 |
| Compounded annual return / average of 25% largest draw downs | 21.37 |
| Compounded annual return / Expected Shortfall lognormal | 39.43 |
Trading record
Placed 145 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| XHB | long | 100 | Oct 24, 2011 | Nov 25, 2011 | ($115) |
| IEO | long | 24 | Nov 3, 2011 | Nov 23, 2011 | ($148) |
| XLU | long | 51 | Aug 25, 2011 | Nov 23, 2011 | ($4) |
| URE | long | 25 | Nov 3, 2011 | Nov 21, 2011 | ($179) |
| UWM | long | 38 | Oct 27, 2011 | Nov 21, 2011 | ($176) |
| USD | long | 45 | Oct 19, 2011 | Nov 2, 2011 | ($51) |
| DIG | long | 29 | Oct 27, 2011 | Nov 1, 2011 | ($176) |
| BNO | long | 42 | Oct 17, 2011 | Oct 27, 2011 | $8 |
| TLT | long | 14 | Oct 18, 2011 | Oct 27, 2011 | ($51) |
| BZQ | long | 15 | Oct 18, 2011 | Oct 24, 2011 | ($65) |
| HDGE | long | 49 | Aug 26, 2011 | Oct 11, 2011 | ($72) |
| DTO | long | 21 | Aug 26, 2011 | Oct 6, 2011 | $108 |
| ICF | long | 24 | Aug 30, 2011 | Sep 22, 2011 | ($172) |
| BCX | long | 100 | Aug 31, 2011 | Sep 19, 2011 | ($213) |
| DAG | long | 87 | Aug 24, 2011 | Sep 16, 2011 | ($160) |
| NUGT | long | 0 | Aug 29, 2011 | Sep 15, 2011 | $0 |
| EPP | long | 38 | Aug 30, 2011 | Sep 14, 2011 | ($131) |
| DGP | long | 28 | Jul 13, 2011 | Aug 25, 2011 | $244 |
| SMDD | long | 4 | Aug 3, 2011 | Aug 9, 2011 | $451 |
| PSLV | long | 71 | Aug 4, 2011 | Aug 9, 2011 | ($215) |
| NUGT | long | 0 | Jul 18, 2011 | Aug 4, 2011 | $0 |
| QLD | long | 64 | Jul 6, 2011 | Aug 4, 2011 | ($160) |
| FXD | long | 81 | Jul 5, 2011 | Aug 3, 2011 | ($167) |
| XRT | long | 66 | Jul 8, 2011 | Aug 3, 2011 | ($158) |
| URE | long | 23 | Jul 21, 2011 | Aug 2, 2011 | ($154) |
| IHF | long | 27 | Jun 22, 2011 | Jul 26, 2011 | ($9) |
| PPH | long | 50 | May 17, 2011 | Jul 26, 2011 | ($24) |
| DRN | long | 32 | Jun 22, 2011 | Jul 14, 2011 | $48 |
| DTO | long | 30 | Jun 8, 2011 | Jul 5, 2011 | $103 |
| TQQQ | long | 56 | May 13, 2011 | Jun 6, 2011 | ($179) |
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.