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

堅持用簡單量化模型

HKEJ

6th Feb 2010

堅持用簡單量化模型

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:

在交易大廳混了一段日子以後,我被分派到一個銷售小組,職銜稍稍更改,變成「戰地量化分析師」。

這銜頭聽起來嚇人,但工作內容其實甚為膚淺,至少用不着隨機微積分和偏微分方程等學問。說得得體一點,我是專門負責為銀行大客戶提供量化諮詢;說得坦白一點,這種諮詢服務只為討客人歡心,以後多跟我們銀行做生意。

不過,客戶的問題五花八門,接觸層面亦比較寬闊,正好適合我的沒有耐性的性格。

一天早上起來,我發現眼睛有些發紅,便在回公司的路上,隨意走進一家藥店找駐診的醫生看看。我知道也明白藥店裏的駐診醫生服務一般都是有傾向性的,例如大多建議客戶購買售價高昂、獨家銷售批發,或該店自家品牌的藥物。

可是,那個駐診醫生實在太過分,他只看了我一眼,便建議我購買先鋒黴素!我一向討厭醫生亂開抗生素,便指着他的鼻子,破口大罵他「缺乏醫德」,然後氣沖沖的返回公司。

名字created by me

經過見習分析員Anjaylia的位子時,她見我怒目圓睜,問發生什麼事,我便一五一十的告訴他。誰知這小妮子沒半點同情心,反而嫣然一笑謂:「這不是跟我們的工作很相似嗎?」

我一怔,想想也是的,但還是憤憤難平。「我們的服務自然也談不上公允,但這是雙方事先都知道的。」

「那人家給你看眼睛,也沒收你錢呀!」她的牙尖嘴利,有時真把人氣死。

Anjaylia是我新聘用的下屬。當初面試她自我介紹,我傻了眼,還以為自己聽錯。

「Angela?Angelina?Anjolie?」

「是A-N-J-A-Y-L-I-A,Anjaylia。」

「這名字是什麼意思?」

「就是created by me。」

我差點暈倒。當然,我不會因為她年輕貌美或名字古怪而輕易聘用,遂問道:「你為什麼想要這份工作?」「因為我想弄清楚什麼是量化投資。」她一臉認真的說。

我瞄瞄她的履歷表,嗯,祖籍四川,長春藤大學金融系畢業。於是,我搬出教科書的定義敷衍她:「量化投資,廣義來說,是指使用數學工具來計算和評估的投資決策方法。這跟憑藉判斷來投資的方法,是完全相對的。」

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。

「以金融的術語來說,這個人建立了一個『模型』或『系統』來進行量化投資。而『10時30分』、『前三天中的兩天』、『一萬股』、『收市前15分鐘』就是模型的參數。問題是,為什麼這個人要選10時30分?為什麼是前三天中的兩天,而不是三天中的三天?再說,他是怎麼發現這個投資規則的呢?你不覺得很神奇嗎?」

「如果不是他自己想出來的,就是別人想出來的,或是根據數據研究出來的,有什麼神奇之處?模型中的參數,不過是隨便想出來罷了。這個人可以選10時35分、10時37分,甚至下午的交易時段;同樣,他也可以將現價與之前四天、五天、七天、三個月,甚至五年比較。參數的變化無窮無盡,交易模型的參數設定亦然。」我說。

肥尾惹的禍

「對呀,你剛才不是說量化投資是用數學工具來投資,而不涉及判斷嗎?可是,說到底,原來還是需要依靠人腦來設定咯!你不覺得很神奇嗎?」

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。

「要判定某種投資方法,到底是量化型還是判斷型,主要是看一個條件:如果資訊相同,同一個量化投資的模型會做出一樣的決定;但是判斷投資的結果卻因人而異,因為每個人的性格、經歷和判斷的方法都有所不同。」

Anjaylia把頭一側,轉轉眼珠,緩緩說道:「雖說每個蘋果都是獨特的,但味道其實也大同小異。我們只要吃過幾個,大概就知道蘋果是什麼味道了,不用每個都去嚐一口嘛!那大多數的所謂『判斷』,其實就是『跟風』、隨波逐流;量化投資也沒有什麼神秘可言,不就是有一條公式,然後按部就班地做就行了。所以兩類投資方法的變化,其實沒有想像中多咯!」

雖然蘋果的比喻非常怪異,但我不得不承認,Anjaylia的確頭腦敏捷、認真好學。

「其實,量化投資並不止於一個定義,有時候我們對這個概念的範圍會窄一些,有時候寬一些。狹義的量化投資,特別是指跟Black-Scholes-Merton定價模式有關,亦即所謂連續時間金融分析有關的投資方法。」

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。」

「喔,原來用這種定價模型來投資,也叫量化投資……」

「長期資本管理就是典型的例子,其模型用以估測各種金融產品的實際市價與理論價格的差異。如果兩者不符的話,就可以通過買賣各種產品,建立頭寸,然後坐等市價回到理論價格。」

「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!」

簡單也可以美

要得到投行的一紙聘書,須過五關、斬六將。我不知道Anjaylia如何說服其他人聘請她,反正她輕輕鬆鬆就過了我這一關。正當我後悔自己面試新人過於衝動時,Anjaylia把一份文件遞給我說:「負責交易的『禿頭Albert』給你的。他發現有一個量化基金客戶交易非常頻繁,而且每次交易的貨幣組合比較類似,所以當中可能有些規律存在,但他又弄不清楚究竟是怎麼一回事。」

我故意不作聲,等她發表意見。「沒有什麼特別高深嘛!只要把這家客戶過去幾年所有的交易紀錄,從系統裏下載到指標軟件上面分析,不就行了嗎?」Anjaylia說。「那你去做吧,回頭給我一份報告。」我暗笑,沒有幾小時的測試,你休想得到什麼交易規律。

結果不出我所料,直到下班時間已過,Anjaylia才拖着累得半死的身軀,倚在我辦公室的門前說:「其實,只是一種比較簡單的趨勢模型。這客戶過去95%的交易,都符合這個規律。」

「進來,坐吧。我們研究一下那5%不能解釋的交易,看看是什麼原因。」說着說着,我們還談論到,萬一錯讀這家公司的交易方向,我們S銀行可能要賠多少錢,了解風險。

當一切處理好後,我就寫了一個很簡單的小程式,放在每個銷售同事的電腦系統內。以後這客戶打電話來問價,銷售同事立即便可以判斷他到底是要買、還是要賣,然後迅速將價格整體移位。就算每筆交易金額不算大,但是只要交易次數頻繁,每次多賺一點差價,一年下來就有上百萬美元的額外收入。

事後,Anjaylia問我:「我用不到一天的時間就能逆向推斷出來的簡單交易策略,怎麼會有用呢?」「是你聰明伶俐吧!」我故意逗她。

堅持用簡單量化模型

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。

五之五

節錄自忻海著的《戰勝畢菲特的隱世股神》

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

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

http://www.crossingwallstreet.com/archives/2010/02/the_entire_stoc.html?

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.

image902.png

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

http://www.cxoadvisory.com/blog/external/blog1-21-10/

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

http://www.marketfolly.com/2009/09/tracking-hedge-funds-uk-positions.html

http://www.marketfolly.com/2010/01/tracking-hedge-fund-positions-in-uk.html?utm_source=feedburner&utm_medium=email&utm_campaign=Feed:+MarketFolly+(Market+Folly)

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.

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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

http://www.nber.org/papers/w15523

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

CXO

http://cxoadvisory.com/blog/internal/blog11-06-08/

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