Summary Of Results for Intermediate Model Oct 2011

The above presents the summary results for the Intermediate trading model through Oct 2011. The second table shows monthly returns since inception of strategy and the graph compares the monthly returns of the strategy vs the monthly return of the SP500 for comparison. Note that the strategy is much less volatile than SP500 and less subject to tail risk and black swan events. The strategy is highly scalable and can take over 1billion in capital so is ideally suited for a money management firm or hedge fund that has the capacity to scale.

September Results 2011

I have been working on some adjustments of the model where we improve returns considerably with a bit more volatility. The adjustments are due to changing the weighting schemes applied to each ETF strategy to be less dynamic ie the weights are not adjusted daily the idea here is to avoid sharp migrations in the weights on a daily basis. This well also reduce transaction costs. Enclosed find the summary results note that the annual Sharpe Ratio on average is 2.87 which is favorable for a strategy using daily prices.

Summary Of Results for Intermediate Model Aug 2011

Enclosed find the summary performance through the end of Aug 2011. Overall the strategy has performed well since inception in 2005 with a max drawdown of approx 1.7% from high to low. The reason for this is because the strategy carefully weights each particular ETF (proprietary weighting scheme) and may be half in cash at any given time. The average rolling 12 mth sharpe ratio exceeds 3.5. I can provide mthly results but in this table I am producing annual to date.

New Long Positions Established

On August 18th my models went long at the close on the following assets
ETFs EWZ, QQQ, OIH, SPY, EWJ, XLF. As of Aug 22 the system is down just over 6% which compares favorable with both the SP500 and the QQQs which are down 12.84% and 13.4% respectively. The massive EEM ETF faired even worse down over 15.8%. The last time this particular model saw such a down-turn was in 2008 where the downturn was even more pronounced. Remember that the idea was to create a model that has robust returns but avoids some of the major downturns. Now the volatility can be controlled by adjusting the amount of money an investor allocates in the model and the amount allocated to cash. Now that everything is more automated I will be updateing my positions more frequently.

Legal Disclaimer: Note that I am not a registered investment advisor so anyone using my trading signals does so at their own risk. This is not an offer to buy or sell securities

Summary Of Results through Aug 12 for intermediate model

The average annual return since inception in July 2005 is 18% with an average sharpe ratio of 1.87; The average winning month is 3% and the average losing month is 1.5%; Winning months outperform losers 2:1. For 2010 we were up through the end of July but are now flat due to an almost 5% drop in August. This also reduced our rolling sharpe ratio due to the sharpe increase in volatility in early august. However over all this model has been fairly robust since inception and held up well in 2008 relative to market indexes. It has performed well in August on relative terms given the extremely high level of volatility and the problems spreading through the euro-zone as well as the political stale-mate in washington. The table below indicates the summary results

.

Current Trading Signals

Below is a list of my current signals for each ETF that I currently follow and the date on which they were received.  Note that I get my signals on the close of a particular day and I follow highly liquid ETFs this makes for a scalable strategy.   The next phase of development is to come up with a tactical asset allocation model based on the ETFs I am tracking, Im not there yet but im giving a lot of thought as to the best way to implement it.  

XLF   Long on 06/01/2011   @ 15.31
EWJ   Long on 06/15/2011   @ 10
EWZ  Long on 06/06/2011   @ 73.01
FXI    Long on 06/01/2011   @ 44.48
SLV   Long on 06/01/2011   @ 35.75
SPY   Long on  06/15/2011  @ 126.39

QQQ, OIH, EEM, GLD are giving no signal at the moment.   I realize that there are a wide range of ETFs that are also fairly liquid but I have focussed my attention on some of the largest ones.   Also I cover a fairly broad spectrum of the markets for example Brazil, the emerging markets block, China, SP500, Nasdaq, Silver, Gold and Japan.   I hope to add a few bond and currency ETFs just to see how my models performs there.    Note these are signals determined based on my Intermediate Mean Reversion Methods. 

Note I should qualify that I am not a registered investment advisor and I am not making any recommendations to buy or sell securities.

Updated Intermediate Model Results Table

I added two new ETFs to my Intermediate Mean Reversion Model.  If anyone wants any more details on results for any of the individual ETFs feel free to ask me.

Results For Intermediate Models

Above find the results for my "Intermediate Mean Reversion Models".  This is a summary using data back to Feb 2 2002.  The reason I chose that date was for consistency.  All of the ETFs considered had data going back to at minimum this date and they were among the most liquid actively traded ETFs.  The reason I of course select the most liquid ETFs is for ease of scalability.  In each instance the Strategy Volatility for the Model is considerably less than for the underlying ETF.   I also include the returns of a long only position in the SPY ETF for comparisons sake.  I have more data available for each individual model upon request.

My New Model

I realize it has been a while since I have posted but I have been focussing my attention on developing a short/medium model.  I started with the oil market and I am using an extreme mean reversion model with stops.   Overall in a highly trending market the longer dated models work very well.  If the model is too short dated it takes the trader out of trends are they are being established.  However on the way up it is never a smooth path so I sought to develop a model with about half the volatility of the ETF but that trades more frequently than my long dated model.   This model has a 70% winning ratio (ie the number of winning trades exceeds the number of losers).  The overall volatility of this model is half that of the underlying ETF.  The model traded three times in the month of may exiting on 05/20/2011.    

Results For Shorter Dated Oil Model Through March 2011

Below find the results for my shorter dated model applied to the OIH ETF.  The goal in this endeavor was to find a much shorter dated model that would trade more frequently than the long dated models that I use.   The other goal was to develop a model that is much less volatile than the underlying ETF.  In this case the volatility of the model is 12% vs over 50% for the underlying ETF.   Additionally the number of uptrades to down trades is 12:2 which is extremely high and the dollar value of an up trade is over two times the dollar value of a down trade.  This indicates that the model is fairly robust.  It should be noted that the model has not made as much money as the underlying ETF but has eliminated some of the huge draw-downs associated with the ETF.   In 2008 for example the model was up over 9% while the underlying OIH ETF was down 60%.
 

	Trading Statistics
	Model
UpTrade	12
AvgUpTradepnl	$100,472.21
DnTrade	2
AvgDnTradepnl	-$38,366.28
AvgTotTradepnl	$80,638.14
Total Trades	14
WinRatio	%85.71
StratVol	%12.24
MktVol	%50.94

An Article on FundFlows From IndexUniverse

http://www.indexuniverse.com/sections/features/8626-2010-etf-fund-flows-vanguard-leads-all-firms.html

An Interesting Article on Factor Models

Below find an interesting article on the use of Factor Models applied to ETF's from seeking alpha
http://seekingalpha.com/article/261570-a-simple-macro-factor-relative-strength-model?source=email_etf_daily.

An interesting article on the global Economy

I am posting the following link to seeking alpha
http://seekingalpha.com/article/261001-2-resources-related-etfs-signal-caution-for-the-global-economy

A New Study on Hedge Fund Performance

Sometimes in this blog I will provide links to articles from other blogs that I thought looked fairly compelling.  This piece was written by Gary Kaminsky who is a frequent guest on CNBC and was previewed on the oxtones blog.  http://oxstones.com/kaminskys-call-hedge-funds-do-worse-than-market/

The iShares MSCI New Zealand Market Investable Index Fund

                     The iShares MSCI New Zealand Market Investable Index Fund

In this note I want to review a relatively new ETF the iShares MSCI New Zealand Market Investable Index Fund (ENZL).   This is a small ETF with just over $80 million dollars in investable assets.  The largest holdings are Fletcher Building Ltd (21.86%) which is a conglomerate that has five divisions namely building products, distribution, infrastructure, laminates and panels and steel that does business not only domestically but across throughout Asia, the Middle East and Europe.  Telecom Corp of New Zealand (16.29%) which is New Zealands largest telecommunications company. 

In terms of sector distribution the largest are Materials (24.77%), Telecommunications (16.29%), Consumer Discretionary (12.91%),  Financials (12.30%), Utilities (11.52%), and Industrials (11.03%).   Its nearest neighbor the iShares MSCI Australia Index Fund (EWA) has the following sector breakdown Financials (42.20%), Materials (29.09%), Consumer Staples (9.21%), Energy (6.59%), Industrials (4.22%).  Note that the financial sector is a much smaller component of (ENZL) while Materials and Industrials are well represented in (ENZL).  Since March 1996 (EWA) has increased 329%.  So far since its inception six months ago (ENZL) has increased 16.4%.  It remains to be seen whether (ENZL) will be popular with institutions who may want to use this as an indirect way to get exposure to the Pacific region but does not have a large exposure to the financial sector.    

 Disclaimer:  This is not a recommendation to buy or sell securities. Etftrendanalyzer is not a registered investment advisor and hence we do not recommend any securities or other investments.   Our readers should not rely on the accuracy or completeness of the information contained herein and should not be rely upon it in  making any investment decisions

Examining VIX ETF Performance During A Sell-Off | ETF Database

I would like to share the article below which examines the performance of the volatility ETF's vs the actual spot VIX. This is a very good article
which illustrates why great care must be taken when using these products

Examining VIX ETF Performance During A Sell-Off ETF Database

A High Octane ETF

One ETF that exploded today is a relatively new product introduced last year namely the TVIX VelocityShares Daily 2x VIX Short Term ETN.  The ETNs are issued by Credit Suisse AG via its Nassau Branch and is an  unsecured obligation of Credit Suisse.  It does not pay interest and there is no guarantee of return of principal.   The return performance is linked to (2x) the daily performance of the S&P 500 VIX Short-Term Futures Index (less the investor fee which is subtracted daily (1.65%/365) ) .    This product allows the end user to express a view on the direction of volatility.  Today TVIX has increased by 8.64% to 50.45  so this is an extremely high octane product and is up substantially from its most recent low of 33.56 but still way off the highs at 112.35 in mid december 2010.  No doubt the explosion in volatility is due to the recent tsunami and nuclear crisis in Japan which could be classified as a black swan event.   Once again today the Nuclear and Uranium ETF (NLR) is down almost 4.5% and the iShares MSCI Japan Index (EWJ) is down over 0.45%.  Recall from yesterdays note that during the last earthquake in Kobe in January 1995 that the Nikkei fell almost 30% through the first half of 2005.

Disclaimer:  This is not a recommendation to buy or sell securities. Etftrendanalyzer is not a registered investment advisor and hence we do not recommend any securities or other investments.   Our readers should not rely on the accuracy or completeness of the information contained herein and should not be rely upon it in  making any investment decisions

The immediate impact of the Japanese Earthquake

The immediate impact of the tsunami and prospect of nuclear meltdown being felt in the Japan ETFs iShares MSCI Japan Index (EWJ) is that it has traded down over 10% as of this writing.  EWJ is the largest Japan based ETF (6.18Billion Net Assets) whose largest components include industrials, consumer cyclicals, materials and technology.  The last time that EWJ has traded below this level was in the first quarter of 2009 at the height of the financial crisis, where it was almost 30% lower than it was now. 

Note that while this is a sudden sharp shock to Japans industrial base it is not clear as to what impact this will have to Japans GDP as it is unclear what direction the ongoing nuclear crisis is going.  

Note that the EWJ 10 strike puts maturing in Jan 20 2011 puts have almost doubled in value in two days.  There have also been large buyers of the 9 strike puts maturing in Jan 20 2011 both have seen a sharp spikes in volume.   For an investor looking to go long Japan at a lower price selling puts is a way of minimizing downside risk since the investor only loses when the ETF value goes below (9-premium collected by put seller).  Note that during the 1995 Kobe earthquake the Nikkei dropped 25% over a five and a half month period and then recovered by the end of 1995.

 

 Unsurprisingly the much less liquid Van Eck Market Vectors Nuclear and Uraniam ETF (NLR) down over 13.5%,  has taken the biggest hit as governments around the world re-evaluate their nuclear programs going forward.  No doubt some governments will look to upgrade their existing facilities noting the size of the earthquake in Japan, however as always occurs in a crisis of this nature this will put the building of new nuclear plants on hold for several years in many countries. 

Disclaimer:  This is not a recommendation to buy or sell securities. Etftrendanalyzer is not a registered investment advisor and hence we do not recommend any securities or other investments.   Our readers should not rely on the accuracy or completeness of the information contained herein and should not be rely upon it in  making any investment decisions

Update On the Oil Model

I thought given events in the middle east that this would be a prudent time to review our long term OIL model.   Note that the models I have developed here look for extreme moves and attempt to identify the inception of long term trends.  Therefor they are long term models ie you can be long for a long time or out of the market for a long time.   They in a sense ride the wave of the trend.   Note that the model exited the market near the prior peak in April 2008 and stayed out until April 2009 and is currently still long.   The result of this is that the model itself missed the downturn that occurred from the prior peak and re-entered the market once more as a new uptrend was being established that uptrend continues.  The idea of these models is to outperform the underlying ETF

How does the prior years return impact future performance (Part 2)

In this post I decided to continue the prior study.  In the prior post I present a study that looks at how future performance is impacted by the prior year for some of the most liquid ETFs.  I now extend these results by reviewing  the best and worst performers of 2010 and eliminated those that were less than 500million USD in size and have very low volume.  The results below indicate that when you have extreme movements either up or down there is a period of reversal.  Note that the exception is UNG which seems to have gone down since inception however both EWP and EWI have gone up 13% since 12/31/2010 and all the best performers in ETF have had a reversal.  Note that while TUR did not have an extreme movement upwards in 2010 (anything over 50% is extreme) it was still among the top performers.  It will be interesting to monitor these positions throught the first half of 2011 to see where they end up.   Note as a disclaimer these are merely observations that I am making about the ETF market and not live positions.

How does the prior years return impact future performance

In the following study I decided to analyze the walk forward performance of some highly liquid ETFs.  For this study the ETFs are divided into four buckets of performance over the prior year.   The buckets are as follows,  bucket1 (-50% to -25%),  bucket2 (-25% to 0%), bucket3 (0% to 25%),  bucket4 (25% to 50%).  The walk forward periods are 90, 120 and 252 days.   What is interesting is that the best walk-forward performance occurs when the prior year performance is in bucket1 (-50% to -25%). 

The 252 days walk-forward period performance is on average between 45% and 70% if the prior year was in bucket1.   Similarly in all cases if the average over the prior year was in bucket 4 (25% to 50%) in the next 90, 120, 252 walk forward periods the performance is negative.    The trading strategy would be load up  when the prior year is in bucket 1and short when the prior year is in bucket 4 .  Note also the the 252 day walk forward period is significantly better than both the 90 and 120 day periods.

Results For the Brazil EWZ Model

The last long EWZ trade was entered on  08/27/2010 and exited  10/05/2010 right now the system is neutral.  The system had a return of 16% for 2010 vs a gain of 7.07% for the underlyer.  So far the underlyer EWZ has had a net loss since year end 2010 while the system has remained neutral.

Emerging Markets Model Performance Through Jan 2011

The table below summarizes the results of our strategy as applied to the EEMs (Emerging Markets ETF).  We exited a long position in late November 2011 and are currently neutral.

Cumulative Performance Of QQQQ Model

In this post I want to summarize the performance of our QQQQ model from inception.  We recently exited a long position on January 14 2011 and are currently neutral.   The QQQQ model is an example of our slow trading systems which identify longer dated trends and stick with them.   The key to the model is to avoid major pitfalls and downturns.   The model can be either in or out of the market for long periods of time.  Most notably when the NASDAQ bubble burst in 2000 the model stayed out of the market while the NASDAQ lost half its value.   The model goes long in 2002 and avoids the meltdown in 2008 going long again in 2009.   The purpose of this model is identify long term trends.   It is worthwhile noting that if you invested $1000,000 in the QQQQ at the end of April 2000 you would still be down over 40% by today.  Whereas if you traded the QQQQ ETF using the model you end up 340% over the same period with much less volatility.

A Correlation Study between ETFs

The other day I was reading an article in Seeking Alpha by Erik Gholtoghian in which he established a multi-factor capm model between DRYS, SEA and USO which can be summarized as follows:

 DRYS weekly % change = 1.38*weekly% change in SEA+.56*weekly %change in USO.

SEA is the Guggenheim/Delta Global Shipping ETF which was introduced in the middle of last year, OIH is the Merrill Lynch Oil Service Holders ETF.  I decided to conduct a  study that examined the correlation of SEA with respect to commodities that are shipped by DRYS container ships.  In the first chart the correlation matrix includes data from the SEA ETF which started trading in June last year.   The strongest relationship exists between XLE and IYM for  06/14/2010 till present and from jan 3 2007-present.  There is also a strong correlation between SEA and IYM and XLE over the much shorter period.  These represent potential trading opportunities assuming that pairs trade within certain ranges and they mean revert.

The first chart below summarizes the relationship between IYM and XLE from January 2007 till the present.  Clearly there are buying opportunites when IYM trades below XLE and selling opportunties when IYM crosses above XLE.  There are a few ways to play this one could go long IYM at some point after crossing XLE from above and waiting till it once more crosses XLE from below.  A second trade is to buy XLE and Sell IYM when the spread between the two has widened and close out the position when it converges.

In the second chart below I incorporate the SEA data from 06/14/2010

till present. 

Some Interesting Charts

I decided to perform a study which examined the relationship between DRYS which is the largest carrier of dry bulk goods by market cap vs some key ETFs.   DryShips, Inc., engages in the ownership and operation of drybulk carriers and drilling rigs that operate worldwide. Its drybulk fleet principally carries drybulk commodities, including coal, iron ore, and grains; and minor bulk items, such as bauxite, phosphate, fertilizers, and steel products.  DryShips also engages in the shipment of oil based products throughout the world.   The ETF's I selected for the study were as follows  IYM (Basic Materials),  SLX (Steel),  XME (Metals and Mining),  OIH (Oil).  All of these ETF's have exposure to stock holdings in the various sectors.

In the first chart below I divide the ETF Close Price by the DRYS Close Price for that day.  These ratios achieved their low points in October29 2007 this coincided with a peak in DRYS.  Note that IYM, SLX, XME and OIH peaked in August 2008 so that the peak in DRYS preceded the subsequent collapse in IYM, SLX, XME and OIH by ten months.   The various ratios all achieved another peak in early March 09 which represented a major buying point in the markets.   These ratios are once more achieving new highs as we speak which bodes well for for IYM, SLX, XME and OIH.  I will analyze this line of thought further for my next posting when I will examine both the current and lagged returns of DRYS vs the ETF returns.

For Gold And Silver Bugs

Below I am enclosing the results of my gold and silver models.   The trend following models I employ are eant to capture long established trends in the underlying assets.   The GLD model entered the position in April 2005 and remained long through mid October 2010.   Note that in this particular instance the model more or less mimics the underlying GLD ETF. 

 The Silver Model modestly outperforms the SLV ETF but does so with approx 40% less volatility.  The rules for entry and exit are established in order to determine exit and entry points.   This methodology has worked well in both the QQQQs, EWZ, EWH in particular (refer to my first posting for results through Nov 2010).
The idea is to have a model that captures long term trends in multiple markets by applying a similar process for determining rules.   I have been playing around with some shorter dated models and will post the results of those when I am satisfied with the progress.   The ideal end user of these models would be fund managers adopting a long term horizon who may either use this model to trade these ETFs or to use it as an overlay to manage there own stock picking.  These models will not appy to the HFT community many of whose models success relies on picking off ones customers through the ability to co-locate their servers with the exchanges.

Musings on Markets: Herding behavior: Why, so what and what if?

Musings on Markets: Herding behavior: Why, so what and what if?

An Index and ETF with Exposure to Africa

Since this is MLK day I thought I would talk about an index that gives exposure to the African region.   One way such Index is the  "Dow Jones Africa Titans Index".  "The Dow Jones Africa Titans Index" is a pan-African index consisting of stocks trading on domestic exchanges as well as companies on international exchanges that obtain the bulk of there revenue from Africa.   As of now the local exchanges of South Africa, Egypt, Nigeria, Morocco, Kuwait and Kenya are considered.   To be considered a company must have a minimum market cap of $200 million dollars and a minimum one year trading volume of $million per day.  The most recognizable stocks to the international community may be Orascom Construction Industries the huge Egyptian construction conglomerate and Nigerian Breweries PLC.  According to Dow Jones web-site the country and sector allocations are as follows as of Dec 31 2010.

South Africa       25.70%                      Financials                  41.21%

Egypt                 20.51%                      Basic Materials          19.27%

Nigeria               16.46%                      Telecomm                 11.76%

Morocco            11.14%                      Oil and Gas               10.31%

UK                    10.01%                      Industrials                   6.52%

Canada                5.29%                      Consumer Goods       4.48%

Kuwait                4.33%                      Technology                 4.33%

US                      2.21%                      Consumer Services     2.14%

Australia              1.59%

Kenya                 1.46%

Norway               1.32%

One product that allows an investor to gain exposure to this index is the Market Vectors ETF distributed by Van Eck Securities Corporation and seeks to track as close as possible the Dow Jones Africa Titans index.   Note this particular ETF is not sponsored, endorsed or promoted by Dow Jones.   The ETF may be found under the symbol AFK.   Of course investors need to do their own due diligence as to whether this type of product is suitable for them and their own risk appetite.   More info on The Dow Jones Titans Indices may be found at the following link  http://www.djindexes.com/titans/ and info on the Africa ETF AFK can be found at www.vaneck.com.  I am sure given the explosion in ETFs that there will be other ETF's that will be created focussing on the Africa region and these may be less heavily weighted towards financials and more geared towards either Africas domestic resources lets watch and wait.

Important Disclosure

Note that ETFs are subject to a high degree of risk and in discussing this particular ETF it does not in any way mean an endorsement to buy or sell any such securities.   Investors need to do their own due diligence as to suitability of this or any other product.   ETFs may be affected by market conditions in both developed and nascent markets .  Particular risks associated with emerging market ETFs are social instability, expropriation of local companies and assets, political instability and armed conflict and insurgency.

A Correlation Study between ETFs

In setting up either long only or pairs trades it is useful to perform a correlation study to determine what happens when correlation breaks down.

Below I present three charts the first is the five year performance of five key ETFs SPY(US), EWZ(Brazil), EWH(Hong Kong), EEM(Emerging Markets), FXI(Shanghai Composite).   The second is a specific chart of the ratio of EWZ (prices) divided by EEM (prices).   The third chart is a correlation matrix between these assets one a longer dated correlation matrix the second over one year.   Note the extremely high correlations between EWZ and EEM.   The correlations are applied to 2 month cumulative returns as opposed to intra-day to highlight the relation-ship.  Also observe that that in the second chart that correlation can hit some fairly extreme values it is at those extremes that potential trading opportunities exist to either set up a long only position or a relative value pairs trade between the etfs EWZ vs EEM.   Note that when correlation falls apart and the ratio of EWZ to EEM prices falls below 1.2 this signifies good entry points to purchase EWZ.
It is also significant that while there is fairly high correlation between all these ETF's that EWZ has by far outperformed the other ETFs.   Brazil has the commodities that other emerging markets require to fuel there industrialization and this can help explain the outperformance.  Right now the ratio of EWZ to EEM is around 1.6 and correlation is hovering close to 1 extremely high.  At this juncture I would adopt a neutral position and await a better entry point when correlation once more breaks down.  

Relationship between the VIX and key ETFs

I thought it would be interesting to plot a chart of the VIX vs key ETFs namely SPY's, EWZ (Brazil), EWH (Hong Kong), EEM (Emerging Market).   What is interesting is what happens at huge extremes in the period from Oct 2008 to April 2009.  The VIX itself adjusted close breached the 80 level twice within the month between 10/26/2008 and 11/20/2008.   Note that Lehman Brothers filed for bankruptcy on 09/15/2008 and several other major institutions would have faced the same fate if the US govt had not acted.  However it took a further month for the VIX to spike this was preceded by the collapse in all markets.    From 11/20/2008 through to mid January the market started to rally again and the air came out of the VIX only to breach the 50 level on 03/02/2009.   Notably SPY, EWZ, EWH and EEM hit there lows in early March.   This is telling us that when you have the VIX hits extreme levels.   From the perspective of an investor the most liquid volatility ETF product is the iPath short term futures VIX ETN (VXX). Specifically, the S&P 500 VIX Short-Term Futures™ Index TR offers exposure to a daily rolling long position in the first and second month VIX futures contracts and reflects the implied volatility of the S&P 500^® Index at various points along the volatility forward curve. The index futures roll continuously throughout each month from the first month VIX futures contract into the second month VIX futures contract. More details can be found at http://www.ipathetn.com/ . 

LongTermTrendSystemResultsthroughNov2010

                 Enhanced Probability Technical Trading  Strategy Summary

Strategy Methodology- The idea was to combine technical analysis with statistical methods (distribution theory) in order to identify long term trends and turning points in the market considered.   The idea is to create a strategy that both outperforms the underlying market with less volatility than the underlier.    Several proprietary technical indicators are considered and there statistical distributions analyzed to determine buy and sell levels which are incorporated into a signal generator.  

Trades are only entered only after confirmation of several statistical and technical factors (this leads to a higher probability of a successful trade).   The trades are long term in nature as they go with the trend.   The period of analysis uses data from the 1999 or the inception of the ETF whichever is available.  It considers several bear markets including the most recent one which help stress test the strategy and set acceptable risk levels.   The strategy deploys a framework that increases the likelihood of a successful trade; stops are used to exit losing trades.  The strategy is deployed in various markets where there are high volume ETFs available.

Asset Selection- The strategy focuses on identifying appropriate entry and exit points in the most liquid exchange traded funds (ETF’s).   The reason for this is for both liquidity and scalability (numerous strategies focus on asset selection but ignore the need to scale for commercial viability).   The ETF’s selected are as follows SP500 Spider, NASDAQ (QQQQ’s), Emerging Market Index (EEM), Gold (GLD), Silver (SLV) and Oil (OIH). Note that in this initial phase of development the asset markets selected are diverse in that they comprise NASDAQ, SP500, emerging markets and commodities.   The same methodology can also be applied to individual stocks however the results I present here are for major market indices in the form of ETF’s.

Results

In this document I post the results for the NASDAQ, SPY, EWZ and EEM ETF (see below).  The other models are available in the spreadsheet attached along with Trade Statistics. (See attached)

The data considers several periods of dislocation in analyzing the system.  Namely NASDAQ Bubble Bursting, 2001-2002 bear market, 2008 credit crisis.  For example the NASDAQ Model did well in 2000 and stayed out of the market during this period and stays out during 2008.  The best year dollar wise is 2009 for the NASDAQ Model.   $1million dollars invested in the NASDAQ Model would result in total balance of over $3.28million by Nov 2010 compared with a loss of over 40% over the same period if invested in the underlyer.  The SPY Model increases by almost 100% for this period vs a slightly negative performance in the SPY ETF.

Strategy Deployment-- The strategy is ideally suited for a wealth management firm, mutual fund, or long only hedge fund that would deploy client capital in accordance with the signals to establish  a “technical long fund or fund of fund (via allocation to multiple asset classes)”.    These strategies are also ideally suited to institutions/family offices/insurance companies/endowment funds who are tired of paying extremely high fees to fund of funds and hedge funds.