Does Canada Belong To The Emerging Markets?

Many of us Canadians similar to mean value of our economic scheme every bit a fellow member of the advanced, post-industrial world, amongst the landscape dotted amongst brand-name companies such every bit Nortel Networks, Research In Motion, in addition to Four Seasons Hotels. In the dorsum of our minds, of course, nosotros know nosotros are too a resource-rich country. But still, it may come upward every bit a flake of an embarrassment to detect out that, of all the sector index funds nosotros tin give notice compare the MSCI Canada Index fund EWC to, it cointegrates entirely amongst the natural resources index fund IGE. Even the fiscal sector indices create non come upward close, despite the presence of numerous fiscal services companies inwards the Canada Index. As usual, inwards the nautical chart below, I plotted the spread betwixt 100 shares of IGE in addition to 400 shares of EWC, in addition to nosotros tin give notice come across for ourselves how this spread stubbornly sticks only about zero.






One may banking concern complaint that IGE too cointegrates amongst the Emerging Markets index fund EEM. (The nautical chart below is the spread betwixt 100 shares of IGE in addition to 100 shares of EEM.)


This is non surprising. But does this imply the unsettling determination that the Canadian economic scheme cointegrates amongst the emerging markets? No. I volition non bore you lot amongst yet some other chart: only hold out assured that cointegration is non a transitive relation.

Artificial News Together With Stock Picking

There was an article inward the New York Times a brusk piece agone nearly a novel hedge fund launched past times Mr. Ray Kurzweil, a poineer inward the champaign of artificial intelligence. (Thanks to my swain blogger Yaser Anwar who pointed it out to me.) The stock picking decisions inward this fund are supposed to endure made past times machines that "... tin forcefulness out honor billions of marketplace transactions to come across patterns nosotros could never see". While I am sure enough a believer inward algorithmic trading, I accept popular off a skeptic when it comes to trading based on "aritificial intelligence".

At the jeopardy of over-simplification, nosotros tin forcefulness out characterize artificial news equally trying to jibe past times information points into a business office amongst many, many parameters. This is the instance for approximately of the favorite tools of AI: neural networks, determination trees, in addition to genetic algorithms. With many parameters, nosotros tin forcefulness out for sure capture small-scale patterns that no human tin forcefulness out see. But produce these patterns persist? Or are they random noises that volition never replay again? Experts inward AI assure us that they accept many safeguards against plumbing fixtures the business office to transient noise. And indeed, such tools accept been really effective inward consumer marketing in addition to credit carte fraud detection. Apparently, the patterns of consumers in addition to thefts are quite consistent over time, allowing such AI algorithms to piece of employment fifty-fifty amongst a large position out of parameters. However, from my experience, these safeguards piece of employment far less good inward fiscal markets prediction, in addition to over-fitting to the dissonance inward historical information remains a rampant problem. As a thing of fact, I accept built fiscal predictive models based on many of these AI algorithms inward the past. Every fourth dimension a carefully constructed model that seems to piece of employment marvels inward backtest came up, they inevitably performed miserably going forward. The principal argue for this seems to endure that the amount of statistically independent fiscal information is far to a greater extent than express compared to the billions of independent consumer in addition to credit transactions available. (You may intend that in that location is a lot of tick-by-tick fiscal information to mine, but such information is serially-correlated in addition to far from independent.)

This is non to state that quantitative models produce non piece of employment inward prediction. The ones that piece of employment for me are ordinarily characterized past times these properties:

• They are based on a audio econometric or rational basis, in addition to non on random regain of patterns;
• They accept few or fifty-fifty no parameters that involve to endure fitted to past times data;
• They involve linear regression only, in addition to non plumbing fixtures to approximately esoteric nonlinear functions;
• They are conceptually simple.

Only when a trading model is philosophically constrained inward such a trend produce I dare to permit testing on my small, precious amount of historical data. Apparently, Occam’s razor plant non exclusively inward science, but inward finance equally well.

Market-Cap Together With Growth-Value Arbitrage

Predicting whether small-cap or increment stocks volition outperform large-cap or value stocks inwards the side yesteryear side quarter is a favorite pastime of fiscal commentators. To many fiscal economists, however, the interrogation is long agone settled yesteryear the so-called Fama-French Three-Factor Model. This model postulates that the returns of a stock depend mainly on three factors: the full general marketplace position index returns, the market-cap of the stock, as well as the book-to-price ratio. Furthermore, every bit an empirical fact, over the long term (i.e. for whatever 20-year period), small-caps shell large-caps yesteryear an average compounded annual charge per unit of measurement of 3.12%, as well as value stocks shell increment stocks yesteryear 4.06% (the latter effect applies when nosotros restrain ourselves to the large-cap universe).

This model is really convenient to us arbitrageurs. Statistical arbitraguers to a greater extent than ofttimes than non don’t know how to predict marketplace position index returns, simply nosotros tin soundless brand a living inwards a ship marketplace position yesteryear buying a small-cap, value portfolio as well as shorting a large-cap, increment portfolio, as well as human face to earn 3-4% (on one-side of capital) a year. For example, despite the much anticipated imminent demise of small-caps over the final twelvemonth or so, I establish that if nosotros long the small-cap value ETF IJS, as well as brusk the large-cap increment ETF IVW from Nov 15, 2005 to Nov 15, 2006, nosotros would induce got earned nearly 10% return. The 3-4% average returns human face meager, simply greenback that since this is a market-neutral, self-funding portfolio, your prime number broker (if y'all merchandise for a hedge fund or a proprietary trading firm) volition let y'all to leverage this furnish several times.

Some traders volition honor twenty years a fighting likewise long. Is at that topographic point whatever aid from academic theory on whether small-cap value volition outperform large-cap increment side yesteryear side month, as well as non side yesteryear side twenty years? Influenza A virus subtype H5N1 latterly published column explaining this inwards the New York Times recently.) The substance of this article is that when marketplace position persuasion is positive, human face small-caps to underperform large-caps yesteryear 0.26% a month, as well as value stocks to outperform increment stocks yesteryear 1.24% a month. Conversely, when the marketplace position persuasion is negative, human face small-caps to outperform large-caps yesteryear 1.45% a month, as well as value stocks to underperform increment stocks yesteryear 1.04% a month. How 1 computes “sentiment” is complicated: it is a linear combination of half dozen variables: closed-end fund discount, NYSE portion turnover, number as well as first-day returns on IPOs, equity portion inwards novel issues, as well as the dividend premium. (The authors used information from 1963-2001 for this study.) Now, without genuinely computing all these variables, most would grip that the electrical flow persuasion (as of Dec 2006) is fairly positive. This implies, every bit Mr. Hulbert noted, that small-cap volition underperform large cap inwards the coming months, opposite to the long-term trend. However, the other long-term trend, that value volition shell growth, volition soundless grip inwards the close future. It is upward to the reader to honor a distich of ETF’s that volition accept maximum payoff of this prediction, simply I volition aid hither yesteryear tabulating unopen to of the available funds.

	Value	Blend	Growth
Large cap	IVE	IVV/SPY	IVW
Mid cap	IJJ	IJH	IJK/JKH
Small cap	IJS	IJR	IJT

Further reading:

Bernstein, William (2002), The Cross-Section of Expected Stock Returns: Influenza A virus subtype H5N1 Tenth Anniversary Reflection.
O’Shaughnessy, James P. (2006), Predicting the Markets of Tomorrow. Penguin Books.

Dna, Cryptology, Speech Communication Recognition, Together With Trading

There is an interesting New York Times article on a mathematician too cryptologist who used to operate for the wildly successful hedge fund Renaissance Technologies too is forthwith famous for decoding DNA's. This article caught my eyes because quite a few of my erstwhile colleagues from the speech communication recognition question grouping at IBM likewise went over to Renaissance equally researchers too portfolio managers. Renaissance is an extraordinary hedge fund inward Long Island that has an average annual provide of 35% since 1989, after charging 5% administration fee too 44% incentive fee. They profess to hire exclusively scientists, engineers too mathematicians amongst equally piddling background inward finance equally possible. They started off trading futures, simply has since too so diversified into equities models, too is artificial intelligence may intend that I am beingness inconsistent here, equally I was less than enthusiastic virtually the application of that bailiwick to trading. There is, however, quite a big departure betwixt data theory too artificial intelligence. The erstwhile is characterized past times sophisticated theory amongst really few parameters, the latter, unproblematic theory amongst a lot of parameters.)

There is i published trading model that is based squarely on question inward data theory. It is called Universal Portfolios, created past times Stanford data theorist Prof. Thomas Cover. It is an elegant too quite intuitive model, simply I don't know how good it performs nether realistic conditions. I promise to write virtually about of my question on this too a related degree of models inward a time to come article.

Further reading:

Cover, Thomas M. too Thomas, Joy A. (1991), Elements of Information Theory. John Wiley & Sons, Inc.

Another Limitation Of Artificial Tidings In Addition To Information Mining

Sometime agone I espoused my views that AI in addition to information mining techniques may non endure suited for predicting fiscal markets. Here nosotros convey an article from the Chief Scientist at IBM's Entity Analytic Solutions Group who believes these techniques are non check for counterterrorism either. Why? The same reasons I mentioned: non plenty historical data.

Do Element Models Live On Inwards The Curt Term?

Besides pair-trading, “factor model” is the close pop workhorse of the statistical arbitrageur. In a previous article, I discussed the close well-known ingredient model – the Fama-French Three-Factor model, alongside the full general marketplace index returns, the market-cap of the stock, too the book-to-price ratio equally the exclusively iii factors driving returns. However, equally I explained earlier, this ingredient model has a really long horizon. For the quantitative trader who needs to brand coin every month, the natural instinct is to expect for a to a greater extent than “sophisticated” ingredient that plant inwards the brusk term, or fifty-fifty to railroad train roughly variety of model that role dissimilar factors every calendar month inwards answer to “market condition”. Alas, other than hearsays too second-hand gossips, I accept never witnessed an actual success of this approach inwards a hedge fund or proprietary trading grouping – at to the lowest degree a success that lasts for to a greater extent than than a year.

I am of course of didactics non privy to the electrical flow surgical procedure numbers of ingredient models run past times roughly of the close successful hedge funds today. However, in that location is a shape of ETF (called “XTF”) marketed past times PowerShares Capital Management that uses a similar ingredient approach for its stock pick criteria. According to media reports, each stock inwards these XTF’s is scored past times 25 variables such equally cash flow, earnings growth, cost momentum, etc. This sounds similar a classic ingredient model to me. This model is reportedly designed past times the quantitative unit of measurement at American Stock Exchange. To abide by out if they accept indeed discovered the holy grail of ingredient models, I looked at the surgical procedure of these XTF compared to their benchmarks.

Here I tabulate the XTF’s for each marketplace cap too value category, their corresponding benchmark marketplace index ETF’s, too finally the YTD differential returns upwards to Dec 13, 2006. (PJG too PJM accept equally good brusk a history for this comparison.)

	Value	Blend	Growth
Large cap	PWV-IVE=4.8%	PWC-IVV=-3.6%	PWB-IVW=-5.0%
Mid cap	PWP-IJJ=0.1%	PJG-IJH=N/A	PWJ-IJK=3.1%
Small cap	PWY-IJS=-0.7%	PJM-IJR=N/A	PWT-IJT=-4.9%

The differential returns are all over the place: roughly positive, others negative. To me, this is symptomatic of a ingredient model that does non accept predictive power. (After all, if the differential returns are consistently negative, nosotros could accept long the ETF, brusk the XTF, too brand consistent profits!) At the really least, this ingredient model may accept a horizon much longer than what close traders would live interested inwards – inwards which case, why non but role the uncomplicated Fama-French model?

This is non to tell that exotic, proprietary ingredient models accept no use: they tend to live pretty useful for peril management, equally volatilities too correlations are ofttimes easier to predict than returns. But beware every fourth dimension your peril administration software vendor tries to sell yous an alpha generator!

Universal Portfolios

Let me depict a portfolio optimization scheme that, over the long run, is supposedly guaranteed to outperform the best stock inward the portfolio.

Before nosotros begin, let’s concord that nosotros volition rebalance our portfolio every hateful solar daytime so that each stock has a fixed pct resources allotment of capital, exactly equally your favorite fiscal consultant would receive got advised you. What this way is that if you lot ain IBM as well as MSFT, as well as IBM went upwardly later on 1 hateful solar daytime whereas MSFT went down, you lot should sell some IBM as well as role the working capital missive of the alphabet to purchase some to a greater extent than MSFT. There is a technical term for such portfolios: they are called “constant rebalanced portfolios”. Notice also the similarity amongst the Kelly criterion which I wrote about before: Kelly criterion asks you lot to hold a constant leverage, which is similar maintaining a fixed pct resources allotment betwixt cash (debt) as well as stock.

But what should the fixed pct resources allotment be? Here is where the scheme gets interesting. Suppose nosotros start amongst an equal working capital missive of the alphabet allocation, for lack of whatever amend choice. At the cease of the day, your portfolio has a sure enough internet worth. But as well as so you lot tin terminate calculate what the internet worth would receive got turned out if you lot had started amongst a unlike allocation. Indeed, nosotros tin terminate run this simulation: elbow grease all possible initial allocations, as well as calculate the hypothetical internet worth of the resulting portfolio. Use these hypothetical internet worth equally weights (after normalizing them yesteryear the core of all internet worth), as well as compute a weighted-average pct allocation. Finally, adopt this weighted average resources allotment equally the novel desired resources allotment as well as rebalance the portfolio accordingly. So genuinely the “fixed” pct resources allotment is non fixed after-all: it gets adjusted daily, but in all likelihood non yesteryear much. Repeat this procedure everyday, e'er calculating a novel weighted resources allotment yesteryear simulating diverse initial allocations since hateful solar daytime 1.

This scheme of portfolio optimization tin terminate hold upwardly proven to attain a internet worth greater than exactly belongings the best stock, given long plenty time. If this sounds similar a miracle, it is partly because this is inward fact an ingenious effect of data theory, as well as partly because at that topographic point are diverse caveats that genuinely throttle its practical application. The proof that it plant (at to the lowest degree inward theory) is rather technical as well as I volition allow the interested reader peruse the master copy articles): nosotros acquire by to lose coin fifty-fifty when a toll serial exhibits a geometric random walk. So it is non likewise surprising that nosotros tin terminate also brand coin using similar data theoretic juggling.

Now for the caveats. Every fourth dimension an data theorist start proverb “In the long run, …”, you lot volition hold upwardly well-advised to ask: How long? In my geometric random walk example where the volatility (standard deviation) of returns every menses is 1%, nosotros detect that the compounded charge per unit of measurement of furnish is an agonizingly pocket-size -0.005% per period. In the instance of the universal portfolio scheme, the out-performance over the best stock inward the portfolio is similarly subject on the volatilities of the stocks: the higher the volatility, the faster the out-performance. Let me run a simulation amongst a portfolio consisting of 2 ETF’s RTH as well as OIH. If nosotros were to run the Universal Portfolio scheme from 2001/5/17 – 2006/12/29, I detect that the cumulative furnish is 32% (without transaction cost). Contrast that amongst exactly buying-and-holding the best ETF (namely OIH here): the cumulative furnish is 54%. The Universal Portfolio loses. Does this hateful the theory is wrong? Not really: RTH as well as OIH may exactly receive got likewise depression volatility. Herein lies the foremost practical caveat amongst the Universal Portfolio scheme: it tin terminate receive got likewise long to realize its attain goodness if the volatility is low.

How attain nosotros detect ETF’s that receive got high plenty volatility to realize the out-performance of Universal Portfolio? Actually, nosotros tin terminate but boost the volatility of RTH as well as OIH artificially yesteryear increasing their leverage. So let’s tell nosotros leverage both of them 2x. This way their daily returns as well as volatilities are both doubled. Now the best ETF (which is nonetheless OIH here) has a furnish of 23% (why is it lower than the un-leveraged case? Remember the formula m-s2/2 inward my previous article.) , but the Universal Portfolio has a furnish of 45%. So at 1 time the Universal Portfolio wins. But this is a Pyrrhic victory: if you lot element inward a transaction cost of 10 footing points, the Universal Portfolio scheme genuinely returns alone 4%. This is the minute caveat of Universal Portfolios: because of the frequent rebalancing required, transaction costs tend to consume upwardly all the out-performance.

Now at that topographic point is a concluding caveat. The reader may inquire why I don’t exactly pick 2 stocks instead of 2 ETF’s to illustrate this scheme. Aren’t most stocks to a greater extent than volatile than ETF’s as well as thence much amend suited for this scheme? Indeed, most academic papers, including Prof. Cover’s master copy paper, role a yoke of stocks for illustration. But if nosotros attain that, nosotros run the guide a opportunity of introducing survivorship bias. Naturally, if you lot know ahead of fourth dimension that none of these 2 stocks volition become bankrupt, the Universal Portfolio scheme may expect great. But if you lot run a simulation where 1 of the stocks all of a abrupt went bankrupt 1 hateful solar daytime (which tend to hold upwardly a fairly mathematically discontinuous affair), the Universal Portfolio scheme volition most probable non trounce belongings exactly the non-bankrupt stock inward the beginning. Using ETF’s eliminated this problem. But as well as so ETF’s are far less volatile.

So given all these caveats, is Universal Portfolio genuinely practical? Prof. Cover seems to holler back so. That’s why he has started a hedge fund to essay it.

Quantitative Sports Betting

Here is an interesting WSJ Steve Halpern for the tip!)

Factor Models: The Ground Continues...

A reader JR only posted approximately real thoughtful comments on my article on element models. You tin rank the axe read his comments in addition to my reply here.

Sentiment Equally Contrarian Indicator

More insights from article on Market-cap as well as growth-value arbitrage.)

What Is Your Destination Loss Strategy?

A reader late asked me whether setting a halt loss for a trading strategy is a practiced idea. I am a big fan of setting halt loss, but in that location are sure as shooting myriad views on this.

One of my quondam bosses didn't believe inward halt loss: his declaration is that the marketplace seat does non help almost your personal entry price, in addition to hence your halt toll may move somebody else’s entry point. So halt loss, to him, is irrational. Since he is running a portfolio alongside hundreds of positions, he doesn’t regard preserving working capital missive of the alphabet inward exactly 1 or a few specific positions to move important. Of course, if you lot are an private trader alongside fewer than a hundred positions, preservation of working capital missive of the alphabet becomes a lot to a greater extent than important, in addition to and hence does halt loss.

Even if you lot are highly diversified in addition to preservation of working capital missive of the alphabet inward specific positions is non important, are in that location situations where halt loss is rational? I sure as shooting yell back that applies to trend-following strategies. Whenever you lot incur a big loss when you lot own got a trend-following position, it ususally way that the latest entry signal is contrary to your master entry signal. In this case, ameliorate acknowledge your mistake, closed your position, in addition to mayhap fifty-fifty move into into the contrary side. (Sometimes I wishing our politicians yell back this way.) On the other hand, if you lot employ a mean-reverting strategy, in addition to instead of reverting, the marketplace seat sticks to its master administration in addition to causes you lot to lose money, does it hateful you lot are wrong? Not necessarily: you lot could exactly move also early. Indeed, many traders inward this instance volition double upwards their position, since the latest entry signal inward this instance is inward the same administration every bit the master one. This raises a query though: if incurring a big loss is non a practiced plenty argue to give upwards to the market, how would you lot always determine if your mean-reverting model is wrong? Here I suggest a halt loss measure that looks at around other dimension: time.

The simplest model 1 tin apply to a mean-reverting procedure is the XLE-CL, GDX-GLD, EEM-IGE, in addition to EWC-IGE). It is a uncomplicated model that says the side past times side alter inward the spread is contrary inward sign to the divergence of the spread from its long-term mean, alongside a magnitude that is proportional to the deviation. In our case, this proportionality constant θ tin move estimated from a linear regression of the daily alter of the spread versus the spread itself. Most importantly for us, if nosotros solve this equation, nosotros volition uncovering that the divergence from the hateful exhibits an exponential decay towards zero, alongside the half-life of the decay equals ln(2)/θ. This half-life is an of import number: it gives us an guess of how long nosotros should human face the spread to stay far from zero. If nosotros move into into a mean-reverting position, in addition to iii or iv half-life’s afterwards the spread withal has non reverted to zero, nosotros own got argue to believe that mayhap the government has changed, in addition to our mean-reverting model may non move valid anymore (or at least, the spread may own got acquired a novel long-term mean.)

Let’s straight off apply this formula to our spreads in addition to encounter what their half-life’s are. Fitting the daily alter inward spreads to the spread itself gives us:



These numbers produce confirm my sense that the GDX-GLD spread is the best 1 for traders, every bit it reverts the fastest, spell the XLE-CL spread is the most trying. If nosotros arbitrarily determine that nosotros volition acquire out a spread in 1 lawsuit nosotros own got held it for iii times the half-life, nosotros own got to concur the XLE-CL spread almost a calendar twelvemonth earlier giving up. (Note that the half-life count solely trading days.) And indeed, spell I own got entered in addition to exited (profitably) the GDX-GLD spread several times since final summer, I am belongings the XLE - QM (substituting QM for CL) spread for the 104^th day!

(By the way, if you lot desire to banking company check the latest values of the iv spreads I mentioned, you lot tin subscribe to them at epchan.com/subscriptions.html for a nominal fee.)

Stop-Loss Strategy: Re-Post

Due to a technical glitch, many subscribers to this weblog were non notified of my latest article on stop-loss strategy together with a method to approximate optimal belongings menses for mean-reverting strategies.
So hither is the permanent link again.

Cointegration Betwixt Fossil Oil As Well As Bond Yield? Not!

An explained before, the fact that these two numbers are anti-correlated produce non forbid them from existence cointegrated. And inwards fact, the Economist article plotted the unsmooth crude prices together amongst bond yield over the terminal twelvemonth together, together with they look tantalizingly to a greater extent than or less existence cointegrated.

My curiosity piqued, I proceeded to become a longer history of these information to examine.

In the graph above, I plotted the (normalized) divergence betwixt the 10-year treasury yield together with crude price. One tin flame run into that over the terminal twelvemonth together with a half, they are indeed cointegrated to a adept degree. (To run into that, uncovering the spread is range-bound, or mean-reverting, from mid-2005 to the present.) But this human relationship breaks downwardly completely over the longer history.

Though I recall that the Economist periodical is doing a disservice to its readers for plotting this graph over merely i twelvemonth together with making innuendos of linkage, it is a squeamish representative of the danger of studying cointegration over a brusk window.

Index Tracking, Arbitrage, Together With Cointegration

Mr. Lange, a reader of mine from Germany, alerted me to the next subscribers only area. (Mr. Lange has graciously allowed me to portion this exposition amongst other readers of this blog.)

In Praise Of Day-Trading

A recent article past times Mark Hulbert inwards the NYTimes talked nearly the Value Line's rankings, together with how this organisation is under-performing the marketplace set index inwards recent years. Mr. Hulbert asked Professor David Aronson of Baruch College whether this drib inwards functioning agency that the organisation has stopped working. Prof. Aronson says no: he believes that it takes 10 or to a greater extent than years [my emphasis] of under-performance of this strategy earlier i tin say that it has stopped working! This statement, if taken out-of-context, is thence apparently untrue that it warrants unopen to elaboration.

To evaluate whether a strategy has failed bears a lot of resemblance to evaluating whether a item merchandise has failed. In my previous article on stop-loss, I outlined a method to create upward one's heed how long it takes earlier nosotros should croak a losing trade. This has to produce amongst the historical average belongings menstruation of similar trades. This sort of thinking tin besides endure applied to a strategy equally a whole. If your strategy, similar the Value Line system, holds a set for months or fifty-fifty years earlier replacing it amongst others, together with thence yes, it may accept many years to detect out if the organisation has in conclusion stopped working. On the other hand, if your organisation holds a set for simply hours, or perchance simply minutes, together with thence no, it takes entirely a few months to detect out! Why? Those who are well-versed inwards statistics know that the larger the sample size (in this case, the publish of trades), the smaller the pct departure from the hateful return.

Which brings me to day-trading. In the pop press, day-trading has been given a bad-name. Everyone seems to recall that those people who sit down inwards sordid offices buying together with selling stocks every infinitesimal together with never belongings over-night positions are no amend than gamblers. And nosotros all know how gamblers terminate up, right? Let me say yous a niggling secret: inwards my years working for hedge funds together with prop-trading groups inwards investment banks, I create got seen all kinds of trading strategies. In 100% of the cases, traders who create got achieved spectacularly high Sharpe ratio (like vi or higher), amongst minimal drawdown, are day-traders.

Use The Correct Discount Charge Per Unit Of Measurement To Avoid Jail Time

Here is a fascinating story nigh the one-time treasurer of Essex County, New Jersey, who was sentenced to vii in addition to a one-half years inward prison theatre because the prosecutor used the incorrect discount charge per unit of measurement to value for sure tax-exempt bonds.

Another Article On Political Futures Markets

A NYTimes article yesterday talked almost the political futures marketplace order intrade.com inward the context of the Nov election, especially the Virginia Senate race, which I blogged about before. I urged my readers to curb their enthusiasm for using such markets for prediction inward my article, piece the NYTimes article is surely much to a greater extent than enamored of them. However, I intend nosotros tin post away all handgrip that such markets are really efficient inward synthesizing all existing data in addition to sentiment inward making a prediction, precisely it cannot give away data that nobody tin post away mayhap know at this point, such every bit who is going to win the 2008 full general election.

Do Gilt In Addition To Fossil Oil Cointegrate?

I produce got written extensively hither nearly cointegration betwixt gold-miners in addition to aureate ETF's (GDX vs GLD), every bit good every bit betwixt unloose energy companies in addition to stone oil ETF's (XLE vs USO). (See, for e.g., this article, or this article.) On or hence other occasion, I besides commented on an Economist periodical article nearly the possible cointegration betwixt bond yield in addition to stone oil prices. However, my immature human blogger here) is over fourteen months. Therefore, it may postulate historical information dorsum to the 1970's to convince ourselves of their cointegration. (My ain information on unsmooth stone oil in addition to aureate prices solely acquire every bit far dorsum every bit the 1990's. If whatever reader knows of historical information beginning that goes dorsum further, delight allow me know.) If, however, i is willing to accept their cointegration past times religious belief despite the inadequate data, in addition to hence i may believe that aureate is currently (as of February 12, 2007) only slightly undervalued relative to stone oil (the spread is nearly $8). I sure don't recommend entering into a lay on either side at this point!

Index Arbitrage Amongst Xle

In looking for pairs of fiscal instruments to duad trade, nosotros produce non accept to restrict ourselves to pairs that tumble out inwards "nature". We tin oftentimes laid upward our ain baskets of stocks to merchandise against an index (or an ETF representing this index). In fact, such pairs unremarkably present improve cointegration properties than whatever stock or ETF pairs. I accept alluded to this index arbitrage consider inwards an before post, together with the details of the methodology are explained inwards my half-life for mean-reversion is nearly twenty days, which agency yous accept to concur a seat for at most a quarter. (My ain dominion is to decease when the spread hasn't reverted inwards iii times the half-life.) If yous acquire inwards into a seat when the z-score is nearly ±2, yous tin await a net of nearly $2,000 on an investment of nearly $58,000 on 1 side. This comes to a provide per merchandise of nearly 3%. You tin of degree boost this provide past times using options to implement the XLE seat instead.

As an aside, if yous role Interactive Brokers, yous tin easily merchandise an entire handbasket of stocks using their Basket Trader.

I accept created an online spreadsheet alongside (almost) real-time values of this spread inwards the subscription area. (The detailed composition of this handbasket of 10 stocks are too described there.) Note that inwards theory, every fourth dimension the XLE changes composition, nosotros volition accept to re-compute our handbasket composition equally well. But fortunately XLE composition does non alter rattling much or rattling often, together with then I volition alone update my handbasket at most in 1 lawsuit a month.

Platinum-Gold Spread Revisited

Now that Chinese New Year's Day is over, it is fourth dimension to revisit the Platinum-Gold spread that I talked nearly final November. The theory is that amongst the demand for gilt seasonally exhausted due to the destination of Asian festivities, gilt prices volition spend upwards relative to platinum. We straightaway convey the chance to exam this theory again.

Maximizing Chemical Compound Charge Per Unit Of Measurement Of Provide Vs Maximizing Sharpe Ratio

A reader, Mr. A. Goldstein, made a real useful observation close my article "Maximizing Compound Rate of Return". In that article I argued that if your destination is to maximize the chemical compound charge per unit of measurement of return, you lot should maximize the quantity m – s²/2, where m is the short-term (1-period) charge per unit of measurement of return, together with s is its measure deviation. In general, this is not the same equally maximizing the Sharpe ratio of a strategy. However, Mr. Goldstein pointed out that, if you lot too optimize the leverage of your strategy using Kelly's criterion, together with thence maximizing Sharpe ratio does inwards fact maximize the chemical compound charge per unit of measurement of supply also. This follows from a calculation inwards department seven of medico Edward Thorpe's newspaper www.bjmath.com/bjmath/thorp/paper.htm.

Mr. Goldstein too suggested a beta arbitrage strategy which he has allowed me to part amongst my readers inwards a futurity post.

Is Increasing Beta Or Increasing Leverage A Amend Fashion To Growth Returns?

In my previous post, I reported an sharp observation from my reader Mr. Goldstein that maximizing chemical compound charge per unit of measurement of return, maximizing leverage, as well as maximizing Sharpe ratio are all tightly connected. This makes intuitive feel because the higher the Sharpe ratio of a strategy, the smaller the drawdown, as well as so the higher the leverage yous tin apply to it inwards guild to maximize chemical compound return.

Mr. Goldstein also made closed to other rattling interesting observation. He noted that in that location are unremarkably ii ways to growth the returns of a portfolio of stocks: either yesteryear picking high-beta stocks, or yesteryear increasing the leverage of the portfolio. In both cases, nosotros are taking on to a greater extent than adventure inwards guild to generate to a greater extent than returns. But are these ii ways equal? Or is 1 improve than the other? It turns out that in that location is some research out in that location which suggests increasing leverage is the improve way, due to the fact that the marketplace seems to hold upwardly chronically under-pricing high-beta stocks. This gives ascent to a strategy called "Beta Arbitrage": purchase low-beta stocks, curt high-beta stocks, as well as earn a positive return.

I myself receive got non studied this shape of arbitrage inwards depth, as well as so tin neither endorse nor criticize it. However, if this question is correct, it does debate against including equally good many volatile stocks inwards your portfolio or trading strategy. If yous desire to accept on to a greater extent than adventure as well as generate higher return, but plough the knob as well as growth your leverage as well as so mass size.

Seven Factors That Capture Virtually Of Hedge Funds' Returns

The Economist magazine simply published an article on this topic previously.) The 7 factors are (are you lot ready?):

1) excess provide on the S&P 500 index;
2) a pocket-size minus large part constructed every bit the deviation of the Wilshire pocket-size too large
capitalization stock indices;
3) excess returns on portfolios of lookback straddle options on currencies;
4) excess returns on portfolios of lookback straddle options on commodities;
5) excess returns on portfolios of lookback straddle options on bonds;
6) the yield spread of the United States of America 10 twelvemonth treasury bond over the iii calendar month T-bill, adjusted for the duration of the 10 twelvemonth bond;
7) the modify inwards the credit spread of the Moody's BAA bond over the 10 twelvemonth treasury bond, too appropriately adjusted for duration.

According to the researchers, factors 3)-5) are constructed to replicate the maximum possible provide to trend-following strategies on their respective underlying assets.

See, it is non that hard to run a hedge fund later all!

Hedging Isn't E'er Better

Many of the strategies I wrote nigh inward this spider web log are market-neutral strategies: long i musical instrument as well as brusk exactly about other i every bit a hedge. In many hedge funds, these are the exclusively strategies that are allowed: investors imagine that exclusively market-neutral hedge funds tin deliver consistent returns inward bull as well as acquit markets alike, as well as the typically smaller drawdowns experienced past times such funds let them to obtain higher leverage from their prime number brokerages. However, over the years I receive got expire convinced that this bias inward favor of marketplace neutral strategies is misplaced inward several ways.

First off, it is a fleck dizzy to operate difficult to uncovering a market-neutral strategy as well as hence that nosotros tin receive got a smaller drawdown as well as hence that nosotros tin increase its leverage to boost its return. After all these leveraging, the drawdown is oftentimes dorsum to the same degree every bit a long-only strategy! Why non exactly run a long-only strategy at a lower leverage, but that is oftentimes simpler inward blueprint as well as that incurs lower transaction costs (since at that spot is exclusively one-side of the merchandise to execute)?

Secondly, at that spot is a misconception that long-only strategies volition certainly lose coin inward acquit markets. This is in all probability truthful when you lot are asset overnight -- but long-only day-trading strategies are oftentimes profitable inward both bull as well as acquit markets.

Thirdly, at that spot are strategies where exclusively the long trades work. Influenza A virus subtype H5N1 unproblematic instance is a strategy that buys an index at its 10-day low, as well as move out when... well, at that spot are multiple ways to move out as well as most of them work! If you lot effort the mirror icon of this strategy, i.e. brusk an index at its 10-day high, it industrial plant far less well. This exactly reflects the positive hateful render of the equity market, as well as why non receive got wages of that?

Finally, related to the 3rd point, sometimes the brusk hedge fails exactly because the brusk musical instrument is truly quite unlike inward nature than the long one, despite their superficial similarity. An example is provided past times Mr. Sandy Fielden at Logical Information Machines. There is a normally profitable merchandise where you lot long a May gasoline futures contract as well as simultaneously brusk a May heating petroleum contract inward the spring. The logic is that every bit the weather condition gets warmer, the driving flavor volition laid about which drives the toll of gasoline futures up, as well as the need for heating volition decrease which drives the toll of heating petroleum futures down. This hedged merchandise is supposed to eliminate full general liberate energy marketplace risk. However, the weather condition is sometimes unpredictable, as well as inward 2005, this merchandise went quite incorrect primarily because the wintertime lasted longer. On the other hand, if you lot exclusively move inward the long side of this trade, i.e. purchase gasoline futures inward the spring, it industrial plant similar a charm every twelvemonth inward the past times 10 years! (I receive got posted a detailed analysis of this long-only gasoline futures merchandise inward my Premium Content area.)

Therefore, if you lot merchandise for yourself as well as non for exactly about institutions alongside a mandate exclusively for market-neutral strategies, at that spot is no bespeak to live bounded past times the same rules that they receive got to play by.

Out-Of-Sample Examination On Cointegrating Handbasket Of Stocks

An anonymous reader "L" posted some thoughtful objections to the agency I constructed the basket of stocks that is supposed to cointegrate amongst XLE. His primary objection is that fifty-fifty though my handbasket shows cointegration amongst XLE in-sample, this is probable to neglect out-of-sample. Actually, I concur amongst him that the potent statistical human relationship discovered in-sample is close probable going to endure weakened out-of-sample, close oft because the nature of the element stocks is e'er changing, due to diverse corporate events (management change, restructuring, alter of strategic direction, etc.). However, from a practical trading dot of view, I believe that the human relationship should non endure weakened to the dot that the trading signals driblet dead spurious, at to the lowest degree over a time-scale of a merchandise which is several months to half-a-year at most.

To demonstrate this, let's interruption upwards the dataset over two periods: 20010522 - 20030123 together with 20030124 - 20070403. In the kickoff in-sample stream (with 1,000 information points), nosotros alternative our 10 stocks to course of report the basket, together with inwards the minute out-of-sample stream nosotros come across how good it cointegrates amongst XLE, together with nosotros uncovering how the spread behaves. I flora that inwards the kickoff period, the t-statistic for cointegration is -3.61934140, indicating the handbasket cointegrates amongst over 95% probability. No surprise here. Here is a plot of the spread inwards this period:


















Now, let's uncovering out what happens inwards the out-of-sample period. Here the t-statistic is but -2.72, whereas the critical value for cointegration at 90% probability is -3.03. So indeed the handbasket fails to cointegrate at the 90% confidence level. Does that hateful our trades volition thus endure losing out-of-sample? Not necessarily. Take a hold off at the behaviour of the spread out-of-sample:



















Even though it is non nicely symmetric some zip equally inwards the in-sample period, the spread is however clearly bounded some zero. If the handbasket completely falls out of cointegration amongst XLE, it volition demo a random drift away from zip equally fourth dimension goes on.

To demo that this is non but skillful luck based on our specific in-sample period, let's endeavor a longer in-sample stream of 1500 days (shorter in-sample stream won't work, because nosotros demand a minimum of 1,000 information points hither to build a skillful reliable basket.) Here the cointegration t-statistic is a chip worse, at -2.62. If nosotros hold off at the spread:



















Once again, nosotros come across that the spread is bounded, non wandering off to infinity. So inwards conclusion, I keep that my method of constructing the handbasket is skillful for practical trading, though non necessarily guaranteeing equally high a statistical confidence marking equally mightiness endure indicated inwards the in-sample period.

Recap: Platinum-Gold Spread Trade

The platinum-gold spread merchandise that I discussed is i time once again profitable this year. If a trader entered the positions close the closed on Feb 26 together with exited the positions close the closed on Apr 19, the profits would stimulate got been virtually $6,610 this time. However, I did made a calculation fault when I plotted the historical profits graphs before. So hither it is again:

Recap: Gasoline Futures Seasonal Trade

The gasoline futures seasonal merchandise that I mentioned inwards a previous post in addition to discussed inwards details inwards my premium content area reached its perish today. It has been profitable for at to the lowest degree 11th consecutive years: the net this twelvemonth is $4,321.80 per contract of RT.

Are Claims Of Seasonality Inwards Commodity Futures Markets Fraudulent ?

I convey written almost several commodities futures seasonal trades (e.g. PL-GC here, too RT here) recently, too piece I was researching some other such merchandise I came upon this webpage from the Commodity Futures Trading Commission. It says, inward no uncertain terms,

" The Commodity Futures Trading Commission (CFTC) warns consumers to live on alarm to possible fraudulent claims that they tin earnings on commodity futures or options trading every bit a number of changes inward the prices of physical commodities based on seasonal conditions patterns or other well-known events."

It goes on to rank that

"Futures too options markets conform real chop-chop to word events too announcements, too past times the fourth dimension salesmen come upwardly calling, the chance to earnings from such word is gone."

Whoa, this sure enough got my attention! Since I am non a journalist, I don't ordinarily acquire around challenging claims made past times the USA government. But if this statement, which is basically the efficient marketplace hypothesis, is to a greater extent than ofttimes than non true, too hence all of us traders should only pack upwardly too acquire home. Now whether or non the efficient marketplace hypothesis is truthful is dependent plain to much academic debate. But is it correct for the authorities to dry reason definitively that this hypothesis is true, too that all claims otherwise are "fraudulent"?

Political arguments aside, I mean value that the commodities marketplace may convey to a greater extent than arbitrage opportunities (i.e. less efficient) than the stock market. Perhaps this is because at that spot are to a greater extent than participants inward the commodities markets that are not speculators, peculiarly for "consumption" commodities such every bit fossil oil too gas.

This is non to rank that every seasonal blueprint that nosotros convey backtested is necessarily going to repeat itself. Many of these patterns occur alone in 1 lawsuit a year, too at that spot are only hence many years that nosotros tin purpose for our backtest, too needless to say, most of them are "in-sample". My practise is to paper-trade the blueprint for at to the lowest degree 1 twelvemonth going frontward every bit an "out-of-sample" test, especially if the blueprint is non supported past times a potent telephone substitution rationale (like the Australian dollar merchandise that I talked almost inward my premium content area.) Furthermore, past times publishing my backtest results on this blog, whatsoever hereafter repeat of the blueprint tin indeed live on regarded every bit out-of-sample, increasing our confidence inward them.

My ain involvement inward researching seasonality inward commodities marketplace was (hopefully) non piqued past times the variety of snake-oil salesman that CFTC warns us about. About a twelvemonth or hence ago, I attended a beak given past times doctor David Eliezer at Columbia University's Financial Engineering seminar. The topic is "Structure too Behavior of Commodities Markets" inward which he outlined diverse seasonal patterns that persist inward the futures markets. Dr. Eliezer was formerly the principal quantitative researcher at Goldman Sachs' commodities group. Given this academic respectability, I sure enough experience emboldened to piece of occupation into into the debate!

Recap: Australian Dollar Futures Seasonal Trade

Yesterday was the exceed away of the Australian dollar futures seasonal merchandise which I discussed inwards my link.

Platinum Vs. Gold

The seasonal one.

A Component Subdivision Model That I Tin Order The Sack Believe In

Some of yous may retrieve that I preached about the uselessness of constituent models inwards predicting curt term return, together with the unreliability of many exotic factors fifty-fifty for the long term. In particular, constituent models are particularly inaccurate inwards valuing increase stocks (i.e. stocks amongst depression book-to-market ratio), equally evidenced past times such models' pitiful functioning during the mesh bubble. This is non surprising because most commonly used factors rely on historical sales or profits measures to approximate companies, land many increase stocks accept really curt history together with piffling or no profits to report. However, equally pointed out lately past times Barry Rehfeld inwards the New York Times, Professor Mohanram of Columbia University has devised a uncomplicated constituent model that rely on viii really convincing factors to score increase stocks. These factors are:

1. Normalized provide on assets.
2. Normalized provide on assets based on cash flow.
3. Cash menses minus mesh income. (i.e. negative of accrual.)
4. Normalized profits variability.
5. Normalized sale increase variability.
6. Normalized R&D expenses.
7. Normalized working capital missive of the alphabet spending.
8. Normalized advertising expenses.

By "normalized", I hateful nosotros withdraw to standardize the numbers amongst honour to the manufacture median. To Prof. Mohanram's credit, he claims exclusively that these factors volition generate returns afterward 1 or ii years, non the short-term returns that many traders await constituent models to deliver. The excess annual provide based on buying the grouping of stocks amongst the highest score together with shorting the grouping amongst the lowest score is a skillful 21.4%. Not exclusively does the combined score generate skillful returns, but each private constituent equally good delivers skillful correlation amongst hereafter returns, proving that the functioning is non due to some questionable alchemy of mixing the factors. For example, it makes skillful intuitive feel that extra spending on R&D together with advertising volition boost hereafter profits for increase stocks.

Interestingly, Prof. Mohanram pointed out that most of the out-performance of the high-score stocks tumble out around profits announcements. Hence for those investors who don't similar belongings a long-short portfolio for a sum year, they tin only merchandise during profits season.

One caveat of this enquiry is that it was based on 1979-99 information (at to the lowest degree for the preprint version that I read). As many traders accept works life out, strategies that operate spectacularly inwards the 90's don't necessarily operate inwards the terminal few years. At the really least, the returns are unremarkably greatly diminished. In the future, I promise to perform my ain enquiry to encounter whether this strategy is even together with thus belongings upwards amongst the latest data.

The Lawsuit Of Terrorism On Forex Trading

Here is an interesting as well as thoughtful article, amongst reference to an academic study, on how terrorism affects forex trading.

Pair Trading Stocks As Well As The Life-Cycle Of Strategies

I convey discussed inwards diverse articles trading the spreads betwixt pairs of ETF’s, or betwixt a handbasket of stocks against an ETF using cointegration technique. There is, however, a glaring omission, equally I haven’t yet mentioned the classic statistical arbitrage strategy: pair-trading stocks.

There are pros as well as cons on applying cointegration to pair-trading stocks. On the pro side: because of the large release of stocks, nosotros tin savour a highly diversified portfolio that improves the validity of our results. Even if a release of spreads neglect to cointegrate going forward, nosotros tin count on a larger release of spreads that soundless do. (For e.g. my USO-XLE spread roughshod apart, piece GLD-GDX spread is soundless tightly cointegrated.) There are ii principal cons: 1) stocks are discipline to diverse specific risks which may homecoming our purely statistical model useless, specially inwards M&A situations. Therefore it is customary to withdraw such stocks from our portfolio when they are involved inwards special situations – however, past times the fourth dimension the intelligence is populace nosotros may convey incurred substantial loss already; also 2) because of the technique’s long history, it became known to many hedge funds as well as indeed students of finance, as well as so dyad trading stocks has non been real profitable, specially inwards the menstruation 2003-2005. Here I plotted the excess returns of the strategy equally applied to the States banking concern stocks from 20010102-20041231. (Excess returns agency credit involvement on margin residuum is non included.)

Interestingly, when a strategy becomes likewise pop as well as less profitable, many traders get-go to abandon it, or at to the lowest degree cut down their trading upper-case missive of the alphabet invested inwards the strategy. After a while, its popularity decreases, as well as the profitability recovers! This life-cycle of strategies reveals itself equally mean-reversion of strategies, on altitude of mean-reversion of stock prices. In our case, this strategy recovery starts inwards 2005, as well as is soundless inwards full-force. Here I plotted the excess returns of the strategy equally applied to the States banking concern stocks from 20050103 to 20070531:

The average annual excess homecoming inwards 2005-now is virtually 7.7% (on one-side of capital), as well as the Sharpe ratio is 0.8. Since I convey applied the technique on solely i manufacture group, diversification is express as well as so the Sharpe ratio is low. For the interested readers, they tin endeavour to apply this technique to to a greater extent than manufacture groups as well as possibly generate a higher Sharpe ratio. Even alongside only i manufacture group, this trading strategy may hold upwardly a practiced complement to a portfolio heavy on trend-following strategies as well as so require a reversal model to smoothen out the returns.

I convey started a model portfolio inwards my subscription expanse to demonstrate this strategy which volition hold upwardly updated daily unopen to 3pm ET. Other details of the strategy volition hold upwardly detailed inwards an accompanying article at that spot equally well.

News-Driven Algorithmic Trading

There is an article close algorithmic trading inwards the latest lawsuit of the Economist magazine, where it says that one-third of all stock trades inwards the US of America are due to algorithmic trading. This should non surprise us. What is to a greater extent than interesting is its cite of the electronically tagged tidings products that are coming out of Dow Jones as well as Reuters, which purportedly enable computers to purchase or sell stocks similar a shot upon the unloose of a tidings item. The information suppliers reckon these tidings products every bit simply about form of cloak-and-dagger high-tech weapons: "Dow Jones claims the concern is thence secretive that it cannot disclose details of customers." Is this hype justified?

Actually, to teach a gustation of news-driven trading, you lot don't quest to pay a hefty fee to purchase i of these products. You tin post away simply monitor the regularly scheduled economical tidings unloose (consumer confidence, novel homes sales, unsmooth inventories, etc.), merchandise the relevant futures, as well as continue to brand millions.

The fact that most of us who monitor these economical tidings releases haven't all the same made our millions is an indication whether these tidings products volition aid you lot create the same. The information contained inwards the tidings is frequently hard to interpret. Even the initial toll reaction to the tidings may locomote wrong, leading to swift reversal later an apparent initial trend. And finally, what's incorrect alongside scanning for abrupt toll movemenets, and then banking concern tally for possible tidings to confirm that the toll motility is due to the unloose of novel information?

Fair Value Of Currencies

In the same final result of the Economist magazine I cited previously, in that place is an article almost the valuation of currencies based on thirteen quantitative models that Morgan Stanley developed. They establish that the most overvalued currency (against the US dollar) is the New Zealand dollar, patch the most undervalued currency is the Japanese Yen.

What almost the Chinese Yuan that arouses much hoopla inwards Congress? The models establish it to live on almost just fairly valued.

More On News-Driven Trading

For readers who are interested inwards news-driven trading, hither is only about other Post Earnings Annoucement Drift (PEAD): the phenomenon that stocks amongst positive turn a profit tidings run out on to tendency upward for a long time. Furthermore, if indeed toll movements inwards answer to tidings are exaggerated (contrary to the findings of PEAD), it would appear to advise a reversal merchandise rather than suggesting that the tidings tin hold out ignored!

Currency Trading Resources

For those of y'all who are into currency trading, this blog looks interesting. You tin likewise subscribe to a gratis daily electronic mail newsletter called "The Daily Pfennig" from www.everbank.com.