Quant Macro Investing

Risk Taking Disciplined

For Traders, Big News Is Old News in Minutes

Twitter in particular has contributed to this phenomenon in recent years, some say. On Tuesday, the stock of Darden Restaurants (DRI: 42.02, -0.26, -0.61%) — owner and operator of casual dining restaurants such as Olive Garden and Red Lobster — started to decline. Ryan Detrick, senior technical strategist with Schaeffer’s Investment Research, an options-trading and investor education firm, looked on the newswires to try to find out why. When he didn’t see anything, he turned to Twitter, where he saw that an analyst had downgraded the stock to hold from buy. (Here for full article)

Editing Assistant: Lingli Li

March 15, 2010 Posted by | Case Study | Leave a comment

China’s 71% Small-Cap Stock Premium Signals Peak

Feb. 26 (Bloomberg)

The rally in China’s small-cap stocks that lifted valuations to a record premium above the largest companies’ shares is a signal to sell, according to three of the country’s biggest money managers.

China’s CSI 500 Index of companies with a median market value of $841 million trades at valuations 71 percent above the CSI 300 Index, up from 31 percent a year ago and near the all- time high of 77 percent in December, based on estimated price- to-earnings ratios compiled by Bloomberg yesterday. Shanghai- listed Guizhou Guihang Automotive Components Co. trades at a record 61 times profit forecasts, triple the multiple for PetroChina Co., the world’s biggest company.

“Small caps are now at the top of their valuations,” said Zhao Zifeng, who helps oversee about $10.2 billion at China International Fund Management in Shanghai. “Big caps have enough safety margin and are likely to outperform.”

Zhao and money managers at JF Asset Management and HSBC Jintrust Fund Management Co., which oversee more than $60 billion, say Chinese small-cap stocks are expensive after fourth-quarter profits trailed analyst estimates by an average 38 percent and the People’s Bank of China raised banks’ reserve requirements to slow the fastest-growing major economy.

The CSI 500 climbed 0.1 percent today to 4,634.67, while the CSI 300 fell 0.3 percent.

The valuation premium on small Chinese companies over their larger peers is wider than in any of the 10 biggest equity markets. Small-caps are valued at a discount to larger stocks in Hong Kong and India, according to data compiled by Bloomberg.

Double Brazil

China stocks surged as investors bet record-low interest rates, a $586 billion stimulus program and $1.6 trillion of state-directed lending would boost profits at the fastest- growing companies. The world’s third-largest economy expanded at a 10.7 percent annual rate in the fourth quarter, up from a revised 6.2 percent in the first three months of last year, the slowest pace in almost a decade.

Property prices climbed 9.5 percent in the year to January, according to the National Development and Reform Commission in Beijing, a rally James Chanos, the founder of New York-based hedge fund Kynikos Associates Ltd., said is a “bubble” poised to burst.

The CSI 500 trades at 29 times profit estimates after an 80 percent jump in the past year that beat the 50 percent advance in the CSI 300 index, according to Bloomberg data. The valuation is more than double the 12 times estimated earnings multiple for the MSCI India Small Cap Index and 13 times for Brazil’s Bovespa Small Cap Index. The Russell 2000 Index of U.S. companies trades at 23 times, Bloomberg data show.

Options Trading

“Big caps look like better value than small caps,” said Howard Wang, head of the Greater China team at JF Asset Management, which oversees about $50 billion. Excluding the risk of a sovereign debt crisis, “we think China big-cap equities are cheap,” Wang said.

Prices are increasing to protect against a tumble in large- cap stocks. Options profiting from a decline in the iShares FTSE/Xinhua China 25 Index Fund are trading near the biggest premium in 11 months compared with contracts that benefit from a gain, Bloomberg data show.

BNP Paribas SA’s Hong Kong-based strategist Erwin Sanft predicts small-caps will be the best-performing segment of the Chinese market this year because of faster earnings growth. Analysts expect profits for companies in the CSI 500 will rise 41 percent this year, topping the 23 percent increase for CSI 300 companies, Bloomberg data show.

Too Optimistic

Estimates for fourth-quarter small-cap profits proved too optimistic, with results reported so far from companies in the CSI 500 index trailing projections by 38 percent, according to Bloomberg data.

Earnings missed forecasts as the government took steps to restrain stock and property gains and consumer inflation. The People’s Bank of China signaled a “gradual” exit on Feb. 11 from monetary stimulus including record loans that were introduced amid the first global recession since the 1940s. The central bank raised reserve requirements 50 basis points to 16.5 percent for the biggest lenders yesterday, the second increase this year. A basis point equals 0.01 percentage point.

“There’s very limited room for small-cap stock valuations to rise further,” said Ally Wang, who helps oversee about $1.2 billion at HSBC Jintrust in Shanghai. “Earnings growth prospects have been priced in.”

Cars to Chemicals

Guizhou Guihang Automotive, which makes auto parts from radiators to air filters, posted third-quarter earnings that trailed analysts’ estimates by 53 percent, according to Bloomberg data. The company, which doubled in Shanghai trading over the past year, is scheduled to report fourth-quarter earnings on March 29, Bloomberg data show.

Xinjiang Qingsong Building Materials & Chemicals Group Co., a producer of cement and fertilizers, has rallied 11 percent since reporting fourth-quarter earnings that missed analyst forecasts by 45 percent on Feb. 5. The company, based in the Xinjiang province, is valued at 39 times earnings, compared with a monthly average of 25 times, based on Bloomberg data since 2004.

Companies in the CSI 300 Index, which have a median market value of $3 billion, have topped analysts’ forecasts for fourth- quarter earnings by an average 5.2 percent, Bloomberg data show. Guangzhou-based developer Poly Real Estate Group Co., which beat fourth-quarter projections by 29 percent, is valued at 15 times profit estimates, near the lowest level in 11 months.

“Valuations of small-caps look too stretched,” said Wu Kan, a Shanghai-based money manager at Dazhong Insurance Co., which oversees about $285 million and plans to reduce holdings of the shares. “Large caps stand a big chance of shining.”

Zhang Shidong, Michael Patterson and Allen Wan. Editors: Gavin Serkin, Stephen Kirkland

March 2, 2010 Posted by | Case Study | Leave a comment



6th Feb 2010


接着,我跟她說了一個小故事:著名棒球隊波士頓紅襪(Boston Red Sox)的班主約翰.亨利(John W. Henry),就是堅持使用簡單的量化模型的基金經理之一。亨利很早就參與大豆和玉米的期貨交易;1976 年,他開始摸索使用量化投資方法;1981年,他的投資公司正式開張,並以自己名字的縮寫JWH來命名,是當時全球最大、面向散戶的另類投資公司。

JWH 使用的交易模型,主要是機械式地捕捉各種價格趨勢和逆向趨勢。以亨利自己的話說,就是「發現長期趨勢,不去理會短期的波動;堅持使用量化模型投資,將人工干預降到最低;積極採取風險管理策略,包括止蝕;全球分散投資。」JWH 的策略,在過去二十多年來鮮有變化,目光只盯着一個指標:「趨勢」,然後「在人們對資訊反應的過程中,尋找偏差帶來的機會」。誰說簡單說賺不到錢?


full article:






名字created by me








「就是created by me。」



Anjaylia眨眨杏眼,「對呀,你不覺得很神奇嗎?量化的意思,是按照事先定好的規則來投資。舉個簡單的例子,如果有一個人每天都於早上10時30分把中石油(857)的股價,跟它前面三個交易日的收市價比較。假設他定好的規則是,如現價高於之前三天其中兩天的收市價,他即買入一萬股,然後在當天收市前15 分鐘沽售;否則,就按兵不動。





當她一再重複「你不覺得很神奇嗎」這句話時,我感覺很詭異。我好像正在跟Hello Kitty討論尼采。





我侃侃而談,「所謂連續時間金融分析,背後有一個假設,就是股價或滙率等金融價格連續不斷地變動。變動的百分比(不是價格本身的變化),符合我們常說的鐘形正態分布(normal distribution),而上一個變化和下一個變化之間又沒有任何關係。在這樣條件下,各種金融工具都可以此方法定價,尤其是衍生工具。」



「可是,長期資本管理一坐,就把46億美元搞沒了!」看不出這小妮子還關心財經新聞,而且記性甚好。我不禁笑道:「哈哈,這只怪肥尾(fat tail)惹的禍!」









接着,我跟她說了一個小故事:著名棒球隊波士頓紅襪(Boston Red Sox)的班主約翰.亨利(John W. Henry),就是堅持使用簡單的量化模型的基金經理之一。亨利很早就參與大豆和玉米的期貨交易;1976 年,他開始摸索使用量化投資方法;1981年,他的投資公司正式開張,並以自己名字的縮寫JWH來命名,是當時全球最大、面向散戶的另類投資公司。

JWH 使用的交易模型,主要是機械式地捕捉各種價格趨勢和逆向趨勢。以亨利自己的話說,就是「發現長期趨勢,不去理會短期的波動;堅持使用量化模型投資,將人工干預降到最低;積極採取風險管理策略,包括止蝕;全球分散投資。」JWH 的策略,在過去二十多年來鮮有變化,目光只盯着一個指標:「趨勢」,然後「在人們對資訊反應的過程中,尋找偏差帶來的機會」。誰說簡單說賺不到錢?

Anjaylia淡然地走到我身後的書櫃,玉手一掃,竟揚出大堆灰塵。「這裏一大堆財經書,有關於畢非德的、索羅斯的、彼得林治(Peter Lynch)的、羅傑斯(Jim Rogers)的……但似乎用來裝飾居多。放在你案頭的,卻永遠都是西蒙斯的零碎資料。」果然心細如塵。



February 7, 2010 Posted by | Case Study | 1 Comment

February 4, 2010 Seven Days Each Month Beats the Market — By a Lot


Since 1932, most of the S&P 500’s capital gain has come during a seven-day period at the turn of each month—specifically, the last four trading days and the first three trading days of each month. This represents about one-third of the total trading days. During the rest of the month, the stock market actually lost money.


Here are the numbers: Since the beginning of 1932, the S&P 500 has gained nearly 14,000% which is about 6.5% annualized. Investing in just the last four days and first three days of each month would have returned over 63,000% (not including trading costs). Annualized, that’s 8.6%. However, if you consider that it’s really only 32% of the time, the true annualized rate is over 28%.

The rest of the month — the other 68% of the time — has resulted in a combined loss of close to 78%.

Let me add some important caveats. First, I’m not offering this as trading advice. I’m merely showing that the market has historically experienced outsized gains at the turn of each month. Remember that trading in and out of the market is costly and these results don’t include taxes or commissions.

Secondly, this only refers to capital gains not dividends. A very large part of the market’s total return is due to dividends, and if you’re only invested one-third of the time, you’re going to lose out.

Having said that, here’s a graph showing what turn-of-the-month investing looks like. The S&P 500 is the red line. The blue line is performance during the seven-day period and the rest of the month is the black line.

February 5, 2010 Posted by | Case Study | Leave a comment

January 21, 2010 – Stock Returns and Changes in Implied Volatility


Are there reliable and exploitable predictive relationships between stock returns and changes inimplied volatility? In the January 2010 version of their paper entitled “The Joint Cross Section of Stocks and Options”, Andrew Ang, Turan Bali and Nusret Cakici investigate the relationship between changes in implied volatility and stock returns for individual stocks. Using monthly implied volatilities and associated stock prices and firm fundamentals for a broad sample of U.S. stocks over the period January 1996 through September 2008 (153 months), they conclude that:

  • Stocks with large increases in call-implied (put-implied) volatilities tend to rise (fall) over the following month.
  • The spread in average next-month returns and three/four-factor alphas between the highest and lowest quintile portfolios formed monthly by ranking the entire sample on changes in call-implied volatilities is about 1% per month. A double ranking first on changes in put-implied volatility for the entire sample and then on changes in call-implied volatilities within the lowest put-ranked quintile enhances this spread. (See the chart below.)
  • Options for stocks with high returns over the past month tend to have increases in call-implied volatility over the next month, with an abnormal stock return of 1% implying an increase in call-implied volatility of about 3%.
  • The predictive power of changes in implied volatilities for stock returns stems from idiosyncratic, not systematic, volatility components. In other words, the predictive relationship derives from information about the stock and not information about the market.
  • Results are consistent with the presence of informed traders in both the equity and options markets, with slow inter-market information diffusion.

The following figure, constructed from data in the paper, shows the average next-month gross returns for two sets of equally weighted quintile portfolios formed monthly over the entire sample period. One set derives from ranking the entire sample on the monthly change in call-implied volatility. The other derives from ranking first on the monthly change in put-implied volatility and then ranking the lowest resulting quintile on the monthly change in call-implied volatility. Results indicate that: (1) the larger the change in call-implied volatility, the larger the expected stock return; and, (2) combining the information in changes in put-implied and call-implied volatilities may enhance power to predict stock returns.

It is not obvious that this predictive power is exploitable at the net level (after trading frictions), especially for individual investors.

In summary, evidence suggests that investors may be able to gain an edge from the power of changes in implied volatilities to predict returns for individual stocks, and the power of stock returns to predict future changes in implied volatilities.

For related research, see Blog Synthesis: Volatility Effects.

January 22, 2010 Posted by | Case Study, Indicator setup | Leave a comment

Tracking A Hedge Fund’s UK Positions



Tracking A Hedge Fund’s UK Positions

Before we continue to look at the positions prominent hedge funds hold in UK markets, we thought it would be prudent to post up an informational piece regarding the nature of the UK regulatory system as it applies to hedge fund disclosure. Firstly, there is no UK equivalent to the SEC’s 13F filing in which funds have to file their holdings on a quarterly basis here in the United States. In the UK, hedge funds do not have to file on a periodic basis at all. Instead, large shareholders are only required to flag long holdings that are greater than 3% of a company’s issued equity. This means that small hedge funds often do not register on the filing radar at all unless they invest in very small companies. Large funds on the other hand often leave a footprint and we can track their activities with ease (particularly when they are buying small and medium sized companies). Their investments in large cap companies, however, often go (legally) unreported and unnoticed because they do not trigger the 3% threshold. This is most similar to an SEC 13G filing (or 13D filing sans the activism) in the United States whereby a fund has to disclose after they have acquired a 5% or greater ownership stake in a company. We routinely cover 13G filings here at Market Folly and these UK filings can be regarded as their regulatory version of a 13G.

In the UK, once a fund crosses above 3% of a company’s equity in issue it has to report any further changes at 1% increments (regardless of whether it is a purchase or a sale). For example, if a fund moves from 3 to 4% of equity in issue or from 4 to 5, they must report. They must also report sales, for example, from 7 down to 6% until it gets below the 3% threshold where one final filing is required to acknowledge that the fund no longer has a concentrated ownership stake.

The additional filings made at 1% increments are interesting because the funds have to provide the trading date on which the threshold was crossed. This date can then be used to make a rough estimate of the price the fund was willing to pay for a company. Arguably, purchase price information is particularly useful if the fund being tracked is well known for excelling at fundamentally driven or deep value research. It is perhaps less meaningful if the fund follows momentum driven investment strategies such as those used by many Commodity Trading Advisers as these funds often move in and out of positions with much more alacrity and disregard for valuation.

Finally, just like in the United States, we can only provide information on a fund’s long positions in UK markets. Short positions do not have to be disclosed except if they are in financial companies or companies involved in rights issues. We will cover the UK disclosure rules on shorts and disclose some hedge fund short positions in a later article, so stay tuned.

Hopefully this gives everyone unfamiliar with the subject a brief background on how regulatory disclosures work in the UK. Now that we’ve presented this preface, look for more articles relating to various positions hedge funds hold in UK markets going forward.We’ve already covered Lone Pine Capital’s UK holdings, Lone Pine’s recent movements, Sprott Asset Management’s defensive UK portfolio, as well as Citadel’s positions. Then later this morning we’re also going to take a look at the UK holdings of legendary macro investor, Louis Bacon. And, as always, we’ll continue to track the US holdings of prominent hedge funds in our portfolio tracking series, so check back daily.


Tracking Hedge Fund Positions in the UK

We had previously published a brief look at how to track a hedge fund’s positions in the UK. We wanted to update that piece a bit and break it down to make it easier to understand. After all, we occasionally cover hedge fund holdings in UK markets. Recently, we’ve detailed how hedge fund Eton Park expanded their UK positions and you can view the rest of our UK updates here. So, let’s examine how to do this:

The UK differs from the US in that disclosure is not required on a periodic basis (as in the case of disclosures required quarterly on a 13F in the US). Instead of “across the board” disclosure on a regular basis the UK system is more event driven. There are four main sets of circumstances under which investment funds and hedge funds are required to disclose long and short positions in UK listed companies.

1. Large holdings in a company

Shareholders with a substantial long position of greater than 3 per cent of a company’s outstanding equity are required to disclose it. Note that this includes rights to acquire shares via derivatives at a later date such as Contracts for Difference (CFDs) or options.

Once a fund crosses above 3% of a company’s equity it has to report any further changes at 1% increments (regardless of whether it is a purchase or a sale). For example, if a fund moves from 3 to 4% of total ordinary shares or from 4 to 5%, they must disclose the change. They must also report sales, for example, from 7 down to 6% until they fall below the 3% threshold where one final filing is required to acknowledge that the fund no longer has a concentrated ownership stake.

Large shareholders in companies that trade on the main market are required to simultaneously inform the issuer and the Financial Services Authority (FSA) of changes to major holdings using a TR-1 form. Substantial shareholders in companies that trade on the exchange-regulated markets (such as AIM or Plus Markets) need only inform the issuer of changes to major holdings in that issuer’s shares. Issuers must then disclose this information to the wider market via the Regulatory News Service of the London Stock Exchange.

2. Takeovers

Under Rule 8.3 of the Takeover Code if a fund holds 1% or more of the stock of the offeror or the offeree in a takeover all dealings (including derivatives) must be disclosed by no later than 3.30 pm (London time) on the day following the date of the relevant transaction. This requirement continues throughout the offer period. A disclosure table giving details of the companies involved in takeovers is available for the public to view on the Takeover Panel’s website.

If two or more hedge funds act together to acquire an interest in the securities of the offeror or the offeree company they are deemed to be a single entity and need to disclose as such. Under Rule 8.1 all transactions in the stock of the offeror or of the offeree company by the offeror or the offeree company must be disclosed by no later than 12.00 noon (London time) on the business day following the date of the relevant transaction.

3. Rights issues and short positions

Hedge funds that have a short position of 0.25% or greater in a UK listed company that is undertaking a rights issue are required to disclose it. The deadline for disclosures is 3.30 pm on the business day following the day the short position threshold was crossed

4. Financial companies and short positions

Hedge funds that are net short of a UK financial sector company are required to disclose the position if it is greater than 0.25% of the firm’s issued share capital. In addition, the fund must disclose each time it increases the short by 0.1% of issued share capital (e.g., at 0.35%, 0.45%). The list of companies deemed to be “fianancial sector companies” is available in PDF format on the FSA website .

We’ll continue to cover hedge fund movements in UK markets. Click here to follow our coverage on UK portfolio updates thus far.

Further Reading

Disclosure of Contracts for Difference – Questions & Answers – Version 2 [PDF]

List! Issue No. 14 – Transparency Directive – December 2006 [PDF]

List! Issue No. 14 (Updated) – April 2007 [PDF]

Additional information on the responsibilities of major shareholders is also available.

Information about third country investment manager disclosure non-EEA investment managers. [PDF]

The Takeover Panel’s website.

January 14, 2010 Posted by | Case Study | Leave a comment

Engineering targeted returns and risks

From Bridgewater Associates (2005) – click here

January 4, 2010 Posted by | Case Study, Cross-asset-class | Leave a comment

Market Folly Portfolio: December & 2009 Full Year Performance

Here are the 2009 results from our Market Folly custom portfolio created with Alphaclone. The portfolio invests in equities held by specific hedge funds as we seek to replicate their portfolios. The overall goal is to generate alpha and outperformance over the long-term by utilizing their stockpicking skills.

December 2009
MF: +4.0%
S&P 500: +1.9%

Full Year 2009
MF: +13.8%
S&P 500: +26.5%

Total Return (Since 2000)
MF: +885.5%
S&P 500: -8.2%

Annualized Return (Since 2000)
MF: +25.7%
S&P 500: -0.9%

Over the life of the portfolio, we’ve seen Alpha of 22.7, Beta of 0.2, and a 0.2 correlation to the Index. The 2009 performance was disappointing and as we’ve pointed out before, a 50% portfolio hedge severely drags on performance when the market rallies 60+% from the lows in one year. To demonstrate just how much the hedge hurt the portfolio, we’ll pull up the long-only version of the portfolio: It returned 28.6% for 2009, outperforming the S&P by 2%. We created the portfolio with Alphaclone and highly recommend checking it out as you can replicate tons of hedge fund portfolios.

While the hedge put a damper on performance this year, it has also shielded from massive drawdowns in previous bear markets and has helped generate long-term outperformance. Keep in mind that you can run long-only versions or hedged versions, it’s completely up to you. We just prefer to run a hedged book in order to protect from drawdowns.

Those of you who desire to invest directly in our hedge fund replicators, stay tuned. We’re working on a newer, updated portfolio (Market Folly v2.0) that will run on auto-pilot in a brokerage account, so all you have to do is sit back and watch. This portfolio is completely separate of MF clone above, so look for it in 2010! In the mean time, go get your free 14-day trial to Alphaclone to see what stocks our original MF portfolio is currently invested in.

January 3, 2010 Posted by | Case Study | Leave a comment

Currency Carry Trade Regimes: Beyond the Fama Regression

Currency Carry Trade Regimes: Beyond the Fama Regression


We examine the factors that account for the returns on currency carry trade strategies. Using a dataset of daily returns spanning 18 years for 5 different long – short currency carry portfolios, we first document a robust empirical relationship between carry trade excess returns and exchange rate volatility, both realized and implied. Specifically, we extend and refine the results in Bhansali (2007) by documenting that currency carry trade strategies implemented with forward contracts have payoff and risk characteristics that are similar to those of currency option strategies that sell out of the money puts on high interest rates currencies. Both strategies have the feature of collecting premiums or carry to generate persistent excess returns that unwind sharply resulting in losses when actual and implied volatility rise.

We next also document significant volatility regime sensitivity for Fama regressions estimated over low and high volatility periods. Specifically we find that the well known result that a regression of the realized exchange rate depreciation on the lagged interest rate differential produces a negative slope coefficient (instead of unity as predicted by uncovered interest parity) is an artifact of the volatility regime: when volatility is in the top quartile, the Fama regression produces a positive coefficient that is greater than unity. The third section of the paper documents the existence of an intuitive and significant co-movement between currency risk premium and risk premia in yield curve factors that drive bond yields in the countries that comprise carry trade pairs. We show that yield curve level factors are positively correlated with carry trade excess returns while yield curve slope factors are negatively correlated with carry trade excess returns. Importantly, we show that this correlation is robust to the current crisis and to the inclusion of equity volatility in the model. What distinguishes carry trade returns in the current crisis from non crisis periods is not changed loading on yield curve factors but a much larger loading on the equity factor.

This paper is available as PDF (718 K) or via email.

December 3, 2009 Posted by | Case Study | Leave a comment

The Lunar Cycle and Stock Returns



November 6, 2008 – Update: The Lunar Cycle and Stock Returns

Does the lunar cycle affect the behavior of investors/traders, and thereby influence stock returns? In the August 2001 version of their paper entitled “Lunar Cycle Effects in Stock Returns” Ilia Dichev and Troy Janes conclude that: “returns in the 15 days around new moon dates are about double the returns in the 15 days around full moon dates. This pattern of returns is pervasive; we find it for all major U.S. stock indexes over the last 100 years and for nearly all major stock indexes of 24 other countries over the last 30 years.” To refine this conclusion and test some recent data, we examine U.S. stock returns during intervals relative to the dates of new and full moons since 1990. When the date of a new or full moon falls on a non-trading day, we assign it to the nearest trading day. Using dates for new and full moons for January 1990 through October 2008 as listed by the U.S. Naval Observatory (233 full and 233 new moons) and daily closing prices for the S&P 500 index over the same period, we find that:

The following chart summarizes average S&P 500 index returns over the 11 trading days (about half a month) centered on new moons or on full moons over the entire sample period, during the 1990s and during the 2000s. Results are in rough agreement with the conclusion of the study cited above, with intervals centered on new moons outperforming those centered on full moons. The difference for the 1990s is, however, small.

Can we refine the interval of new moon outperformance?

The next chart compares average S&P 500 index returns over the entire sample period for three intervals relative to new or full moons: (1) the five trading days just before full or new moons; (2) the five trading days centered on new or full moons; and, (3) the five trading days just after new or full moons. Results suggest that the outperformance of intervals around the new moon comes from returns after, rather than before, the new moon.

The standard deviation of 11-day returns over the entire sample period is 2.64% (3.13%) for new (full) moons, large compared to the difference in average returns.

Might any lunar effects stem from the waxing or waning of the moon rather than new or full moons?

The next chart compares average S&P 500 index returns for the intervals of waxing and waning between new and full moons over the entire sample period, during the 1990s and during the 2000s. Results consistently indicate that the waxing moon (new-to-full) interval on average outperforms the waning moon (full-to-new) interval by about 0.25%.

The standard deviation of returns over the entire sample period is 2.78% (2.93%) for waxing (waning) moons, large compared to the difference in average returns.

Can more granular data help explain why intervals around new moons and during waxing moons outperform those around full moons and during waning moons?

The final charts present the average daily detrended S&P 500 index returns from 11 trading days before new and full moons to 11 trading days after new and full moons. The total interval covered in each chart is roughly a month, but mismatches between lunar and monthly cycles introduce differences between them. We detrend by subtracting the average daily return for the entire sample period from the raw average returns for each trading day in the intervals tested. These charts provide some insight into the less granular results above. However, the lack of systematic variation in daily returns casts doubt on the lunar cycle as the explanation of new-full and wax-wane differences in average returns.

Physicist Charles Pennington employs a quite different approach using a Fourier transform, concluding that lunar cycle effects on SPY are, if they exist, very small.

In summary, the U.S. stock market since 1990 performs better on average around new moons than full moons, and during waxing moons than waning moons. However, the levels of relative outperformance are small compared to market variability, so trading these differences is very risky.

For related research, see Blog Synthesis: Calendar Effects and the Trading Calendar.

December 2, 2009 Posted by | Case Study | Leave a comment