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 楼主| 发表于 2013-3-14 12:43 PM | 显示全部楼层


通胀来了怎么办(from SeekingAlpha)
http://hutong9.net/forum.php?mod ... 98&fromuid=9090
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 楼主| 发表于 2013-3-14 05:41 PM | 显示全部楼层
忘了经济增长吧,信用周期驱动股市(from Economist)
http://hutong9.net/forum.php?mod ... 52&fromuid=9090
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 楼主| 发表于 2013-3-23 01:47 PM | 显示全部楼层
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 楼主| 发表于 2013-3-23 06:24 PM | 显示全部楼层
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 楼主| 发表于 2013-4-4 05:16 PM | 显示全部楼层
经济衰退股市照涨,只要有QE(From SeekingAlpha)
http://hutong9.net/forum.php?mod ... 01&fromuid=9090
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 楼主| 发表于 2013-4-8 04:55 PM | 显示全部楼层
本帖最后由 Diffusion 于 2013-4-8 04:57 PM 编辑

本季ER不被看好(from Barron's)
http://hutong9.net/forum.php?mod ... 16&fromuid=9090
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 楼主| 发表于 2013-4-27 10:03 PM | 显示全部楼层
为什么猜顶难,猜底容易。

标准答案(有推导过程):

因为统计上看,股市3/4的时间在涨,1/4的时间在跌 。

所以任给一点,继续涨(=不是顶)的概率是继续跌(=不是底)的概率的3倍(3/4 : 1/4 = 3 : 1)。

所以猜顶的难度是猜底的难度的3倍。

证毕。

注1:如果是3/4时间在涨,1/4时间在跌,为什么最近几十年股市都在原地打转?因为跌的速度是涨的速度的3倍。
注2:虽然统计和概率是两码事,历史统计不能说明将来。但是根据大数定理和中心极限定理,样本空间足够大的时候,统计结果是概率分布的良好近似。
注3:为什么考虑任给一点是顶是底的概率?因为原问题没有指定用何种方法猜顶,猜底 。所以应该考虑所有的猜顶,猜底方法。不失一般性,可以用抛硬币猜顶,猜底方法代替。所以考虑任给一点是顶是底的概率。
注4:该统计针对的是美国股市大盘指数,不适用于个股,不适用于其他有价证券,不适用于其他国家。

http://www.hutong9.net/forum.php ... 40&fromuid=9090

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 楼主| 发表于 2013-4-30 01:36 PM | 显示全部楼层
Unsustainable, but dare you fight the Fed? (from Barron's)
http://hutong9.net/forum.php?mod ... 17&fromuid=9090
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 楼主| 发表于 2013-4-30 04:04 PM | 显示全部楼层
Quote Read0nly

月末发薪日,许多人的退休账户新进的钱按自动allocation会进入MF,对多方有利。
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 楼主| 发表于 2013-5-2 05:31 PM | 显示全部楼层
Bond funds buying stocks (from Barron's)
http://hutong9.net/forum.php?mod ... 98&fromuid=9090
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 楼主| 发表于 2013-5-15 06:24 PM | 显示全部楼层
In general, behavioral biases, whether by Wall Street analysts, company management, and/or traders in the marketplace, create opportunities to earn excess returns. We believe that because these opportunities are behavioral and thus repetitive, they can be exploited with quantitative tools. We also recognize that there are limits to the size and frequency with which we discover these opportunities so we attempt to preserve our ability to add value for our clients by limiting the amount of capital we’re willing to manage. Finally, we believe that process evolution through continuous research is the only way to maintain a competitive advantage and add value through time.


Just for me to remember this. http://blogs.barrons.com/focuson ... ex-again-this-year/
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 楼主| 发表于 2013-6-19 10:07 PM | 显示全部楼层
加息,一般是指央行加息,央行加息都是短期利率。

利率上扬,一般指长期国债利率,央行没法控制长期利率(一般情况下,QE属于非常手段),一般长期利率由市场调节。

通胀,经济增长一般伴随温和的通胀,是好事。恶性通胀才是坏事。

一般而言,经济周期中,增长周期利率上扬,直到央行加息,控制经济过热,一般央行加息周期伴随经济衰退周期。恶性通胀可能发生在增长周期末端。

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发表于 2013-6-19 10:18 PM | 显示全部楼层
学习了!
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发表于 2013-6-21 01:50 PM | 显示全部楼层
Diffusion 发表于 2013-6-19 09:07 PM
加息,一般是指央行加息,央行加息都是短期利率。

利率上扬,一般指长期国债利率,央行没法控制长期利率 ...

利率上扬, 债券价格下跌是针对新发行的而言吧。那原来已经有的,不可以持到到期日吗?
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 楼主| 发表于 2013-6-23 11:46 PM | 显示全部楼层
lilitulip 发表于 2013-6-21 01:50 PM
利率上扬, 债券价格下跌是针对新发行的而言吧。那原来已经有的,不可以持到到期日吗?

可以,实际上利率影响的都是新发行的债。除非你是trader,一般的income investor都持有到到期日。
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发表于 2013-7-28 08:45 AM | 显示全部楼层
http://online.barrons.com/articl ... L_hpp_dc#text.print

Hulbert: 长篇大论的, 其实就是讲了三个指标逼近historical average of market tops. 值得引起警惕。
但不能作为做空操作依据。P/E ratio from now= 17.9 to historical average 18.7,SPX就可以上80 points.

军师还看见什么值得看的文章,贴这里吧。

点评

多谢,好的。  发表于 2013-7-28 11:02 AM

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发表于 2013-8-2 08:20 AM | 显示全部楼层
抄来的,贴一下以后借鉴
In the last 24 reports since June 2011, the S&P 500 has averaged a decline of 0.09%
on NFP Fridays with positive returns just eleven out of twenty-four times (46%). That
being said, the last three months have all seen better than expected reports that were
met with positive market reactions.
Of those 24 reports, the actual reported number has been better than expected 13
times (54%). On those days, the S&P 500 has averaged a gain of 0.48% with positive
returns 69% of the time. Sectors that have historically done the best on days when the
report is better than expected are Consumer Discretionary (0.77%), Industrials
(0.70%), and Energy (0.48%).
Sectors that have been positive the most consistently
when the report is better than expected include Consumer Discretionary (85%),
Consumer Staples (85%), and Health Care (85%). Sectors that typically underperform
on days when the NFP report is better than expected are Telecom Services (0.02%),
Utilities (0.21), and Technology (+0.24%).
When the NFP report is worse than expected, the S&P 500 (-0.76%) and all ten
sectors have averaged declines. Sectors that have typically held up the best include
Utilities (-0.34%), Telecom Services (-0.46%), and Consumer Staples (-0.53%). On
the downside, if the NFP report is worse than expected, two sectors to avoid are
Technology (-1.02%) and Financials (-0.87%)

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多谢!  发表于 2013-8-2 01:15 PM

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 楼主| 发表于 2013-8-4 11:04 PM | 显示全部楼层
本帖最后由 Diffusion 于 2013-8-4 11:30 PM 编辑

http://www.dfaus.com/2009/05/exp ... erature-survey.html

Earnings / Price
One of the early studies that contradicted the predictions of the CAPM was Basu (1977). Using a sample period that stretched from April 1957 to March 1971, Basu showed that stocks with high earnings/price ratios (or low P/E ratios) earned significantly higher returns than stocks with low earnings/price ratios. His results indicated that differences in beta could not explain these return differences. In a follow-up study, Basu (1983) showed that this "E/P effect" is not just observed among small cap stocks. A later study by Jaffe, Keim and Westerfield (1989) confirmed this finding and also showed that the E/P effect does not just appear in the month of January, as had been claimed by some researchers. The E/P effect is a direct contradiction of the CAPM; beta should be all that matters.

Firm Size
Banz (1981) uncovered another apparent contradiction of the CAPM by showing that the stocks of firms with low market capitalizations have higher average returns than large cap stocks. Other researchers (e.g., Basu, 1983) showed that the size effect is distinct from the E/P effect discussed above. Small firms tend to have higher returns, even after controlling for E/P.

Proponents of the CAPM are quick to point out that small firms tend to have higher betas than large firms, so we would expect to see higher average returns for small firms. However, the beta differences are not large enough to explain the observed return differences. Once again, the CAPM predictions are violated.

Long-Term Return Reversals
DeBondt and Thaler (1985) identify "losers" as stocks that have had poor returns over the past three to five years. "Winners" are those stocks that had high returns over a similar period. The main result of DeBondt and Thaler is that losers have much higher average returns than winners over the next three to five years. Chopra, Lakonishok and Ritter (1992) show that beta cannot account for this difference in average returns. This tendency of returns to reverse over long horizons (i.e., losers become winners) is yet another contradiction of the CAPM. Losers would have to have much higher betas than winners in order to justify the return difference. Chopra, Lakonishok and Ritter (1992) show that the beta difference required to save the CAPM is not there.

Book-to-Market Equity
Rosenberg, Reid and Lanstein (1985) provide yet another piece of evidence against the CAPM by showing that stocks with high ratios of book value of common equity to market value of common equity (also known as book-to-market equity, or BtM) have significantly higher returns than stocks with low BtM. Since the sample period for this study is fairly short (1973-1984), the empirical results did not receive as much attention as some of the other studies discussed above. However, when Chan, Hamao and Lakonishok (1991) found similar results in the Japanese market, BtM began to receive serious attention as a variable that could produce dispersion in average returns.

Leverage
Bhandari (1988) finds that firms with high leverage (high debt/equity ratios) have higher average returns than firms with low leverage for the 1948-1979 period. This result persists after size and beta are included as explanatory variables. High leverage increases the riskiness of a firm's equity, but this increased risk should be reflected in a higher beta coefficient. Consequently, Bhandari's results are yet another deviation from the CAPM predictions.

Momentum
Jegadeesh (1990) found that stock returns tend to exhibit short-term momentum; stocks that have done well over the previous few months continue to have high returns over the next month. In contrast, stocks that have had low returns in recent months tend to continue the poor performance for another month. A study by Jegadeesh and Titman (1993) would later confirm these results, showing that the momentum lasts for more than just one month. Their study also indicates that the momentum is stronger for firms that have had poor recent performance. The tendency of recent good performance to continue is weaker. Note that the pattern here is the opposite of that found in the long-term overreaction papers. In those studies, long-term losers outperform long-term winners. In the momentum studies, short-term winners outperform short-term losers.

   *   *   *

According to the three-factor model, small cap stocks and value stocks have high average returns because they are risky—they have high sensitivity to the risk factors that are being measured by SMB and HML.

In contrast to the risk-based story is the proposition that value stocks have higher returns than growth stocks because markets are not efficient. This position is well represented by Lakonishok, Shleifer and Vishny (1994), who contend that investors naively extrapolate firms' past performance into the future. Value stocks typically have had poor past performance, and investors assume that this poor performance will continue. Then, when some of these poorly performing firms get things turned around, investors are surprised, and the stocks of these firms experience high returns. According to this hypothesis, the high returns to value stocks (and the low returns to growth stocks) are due to investors being systematically wrong about the future. An implication of this is that investors can increase returns without increasing risk, simply by buying value stocks and selling (or not buying) growth stocks.
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 楼主| 发表于 2013-8-5 05:49 PM | 显示全部楼层
http://www.dfaus.com/2009/05/the ... rices-a-review.html

If securities prices reflect all publicly available information in an unbiased way, what would be the resulting traits of securities markets? Three come to mind:
1. Return predictability. The difference between realized returns and expected returns should not be predictable. There are two parts to this—a time series part and a cross-sectional part. The time series part says that investors should not be able to predict which time periods will produce abnormally high or low stock market returns. The cross-sectional part says that investors should not be able to predict which stocks are likely to have abnormally high or low returns during a subsequent period. In both cases, realized returns are compared to an estimate of expected returns to determine what part of the return is abnormal.
2. Financial market link to the real economy. Cross-sectional differences in expected return should be related to risk factors that have a meaningful effect in the economy. If a company's operating results are highly sensitive to a particular macroeconomic variable, and if this variable affects large segments of the economy, then the company's stock should earn a risk premium to compensate investors for this non-diversifiable risk. Sensitivity to pervasive risks in the real economy should be reflected in stock prices.1
3. Performance persistence. Professional money managers should not consistently be able to earn high returns by analyzing financial information. If the information is already reflected in securities prices, gathering and analyzing the available information should not provide a reliable payoff for investors. In any given period, some investors will realize high returns just by chance. But in an efficient market, certain skilled investors should not be able to profit consistently from their analytical abilities.
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 楼主| 发表于 2013-8-8 11:45 AM | 显示全部楼层
很早以前我就说过,市场是半可预测的。凡是我说看明天的时候,就是我觉得无法预测的时候。多空力量均衡的时候,市场方向靠消息,而消息是无法预测的。所以周一说等明天,昨天也说等明天。但是周二就可以预测还有一腿下到1685。是即使是等明天情况,第二天开盘后,很快就可以判断,一般这种情况,低开会低走(周二),高开会高走(今天)。这是新消息带动的技术型追涨杀跌盘造成的,而周二预测下跌,则是技术趋势的延续。市场的本质就是消息和对消息的反应。前者无法预测,后者就是我认为的所谓的technical analysis。所以预测最多只有50%的作用。发现和扑捉机会的能力则是盈利的关键。

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