Sentences with phrase «high negative correlation»

If you want to hedge some of the systematic cryptocurrency risk in your portfolio then you could look at assets that have a high negative correlation with cryptocurrencies.

Graph with high negative correlation between the Fed funds rate and the spread between 10 and 5 - year Treasury yields.

The red regions marked with a blue cross have high positive correlation around the origin point, while the blue regions marked with a yellow cross have high negative correlation.

Not exact matches

Under this scenario stock - bond correlations are likely to be higher than the consistently negative levels that have defined the post-crisis environment (see the chart below).

To limit volatility within a pre-determined threshold, the fund can shift to fixed income and cash, favoring the fixed income component due to its greater negative correlation to equity and higher yields than cash.

The correlation is negative because higher valuations imply weaker subsequent returns.

Instead of keeping 20 % in cash, thereby reducing expected risk to 12 %, the investor could move into 10y government bonds with a higher return than cash and even a little bit of negative correlation with equities.

But in the last few episodes of sharp stock market drops, bonds went up (US government bonds are a safe haven asset and appreciate in crisis periods) so the only thing better than 3 months worth of expenses in a money market fund is having 3 + x months worth of expenses in the bond portfolio due to higher bond yields and negative correlation between bonds and stocks.

So while low and negative interest rates across the globe has inspired flows into stocks, emerging market bonds and corporate credit in search of higher yields, keep in mind the high correlations of these assets to oil prices and the advantages of holding actual diversifiers in your portfolio to smooth the ride.

From a historical perspective, there appears to be no clear evidence as to why a negative start does not more strongly imply a negative year, compared with the high correlation of a positive January translating to a positive year.

The correlation is negative because higher valuations imply lower subsequent market returns.

Indeed, «data on firearms ownership by constabulary area in England,» like data from the United States, show «a negative correlation,» that is, «where firearms are most dense violent crime rates are lowest, and where guns are least dense violent crime rates are highest.»

Because this breaks the energy - entropy correlation, it marks the start of the negative temperature scale, where the distribution of energies is reversed — instead of most particles having a low energy and a few having a high, most have a high energy and just a few have a low energy.

The branch lengths of the high - variance exon tree showed a strong positive correlation with GC content and a negative correlation with the average body mass of species, seen at a much lesser magnitude in the low - variance exon tree (Fig. 6, A to D).

Correlation analysis between scores in negative emotionality and history of marijuana abuse showed a negative correlation between age of initiation of marijuana abuse and negative emotionality scores (r = 0.58, P = 0.003) such that the younger the initiation, the higher Correlation analysis between scores in negative emotionality and history of marijuana abuse showed a negative correlation between age of initiation of marijuana abuse and negative emotionality scores (r = 0.58, P = 0.003) such that the younger the initiation, the higher correlation between age of initiation of marijuana abuse and negative emotionality scores (r = 0.58, P = 0.003) such that the younger the initiation, the higher the scores.

Field observations from West Africa and Ethiopia have indeed established a strong correlation between absence or low endemicity of P. vivax malaria and the high prevalence of the Duffy negative allele [20, 21].

There seems to be a rather strong negative correlation between the two: Countries with the lowest per capita rice consumption seem to have the highest incidence of cancer, and vice versa.

Researchers have likewise reported a negative correlation between self - reported hours of sleep and school grades among both middle - and high - school students.

Looking at only American students» PISA scores, we see that reading engagement had a higher correlation with reading literacy achievement than time spent on homework, relationships with teachers, a sense of belonging, classroom environment, or even pressure to achieve (which had a negative correlation).

So what exactly is the relationship between student achievement and motivation, if there seems to be a negative correlation between the «high flyers» and the least motivated?

Then I insert a group of teachers (as Audrey described) who represent 20 % of a population and teach a disproportionate number of students who come from relatively lower socioeconomic, high racial minority, etc. backgrounds, and I assume this group is measured with negative bias on both indicators and this group has a moderate correlation between indicators of r = 0.50.

She used R (i.e., a free software environment for statistical computing and graphics) to simulate correlation scatterplots (see Figures below) to illustrate three unique situations: (1) a simulation where there are two indicators (e.g., teacher value - added and observational estimates plotted on the x and y axes) that have a correlation of r = 0.28 (the highest correlation coefficient at issue in the aforementioned post); (2) a simulation exploring the impact of negative bias and a moderate correlation on a group of teachers; and (3) another simulation with two indicators that have a non-linear relationship possibly induced or caused by bias.

The sector's tax - exempt status is another plus, and munis are a portfolio diversifier, with negative correlations to equities and high yield, our analysis shows.

Specifically, the S&P China Corporate Bond Index had a negative correlation with the U.S. issued high yield and investment grade bonds.

To limit volatility within a pre-determined threshold, the fund can shift to fixed income and cash, favoring the fixed income component due to its greater negative correlation to equity and higher yields than cash.

Commodities have a high correlation to inflation, but negative correlation to stocks and bonds.

In one of my previous blog posts, we demonstrated that high yield bonds exhibited a strong negative correlation with VIX and an even stronger one with VIX futures, which comes mostly from down markets.

Negative credit report information will often cause you to have a higher insurance rate because a correlation has been made between low credit scores and number of claims filed.

Though unconstrained bond funds do show periods of low, or at times negative, correlation to the U.S. Aggregate Bond Index, they also tend to demonstrate persistently high correlation of above 0.50 to the Global Aggregate Bond Index, though only until 2014.

This is a direct and high - magnitude negative correlation.

High correlations mean that things go up and down at the same time; negative correlations mean that they offset.

The negative correlation of -0.66 between these two variables indicates that when the broad high yield universe benefited from spread tightening, the HYLV index underperformed the benchmark from spread changes, and that spread widening would have less downward impact on the HYLV index than the benchmark.

The highest correlations (riskiest two - asset portfolio combinations) are colored the darkest red; the lowest (negative) correlations (least risky two - asset portfolio combinations) are colored the darkest green.

Edit in response to comment: Corporate bond correlation with stocks is positive but generally not very strong (except for high - yield junk bonds) so while they don't offset stock volatility (negative correlation) they do help diversify a stock portfolio.

In fact there's a real contraversy going on with high latitude studies where a third of the trees show positive correlation of ring width to temperature and another third show negative correlation... the rest showing no correlation at all.

The (negative) correlation between (low) cloud cover and solar irradiation is high and significant, see Kristjà ¡ nsson ea.

That puts it in the universe of almost a perfect inverse (negative) correlation - higher CO2 levels seemingly drives temperatures to deceleration and cooling.

In fact a strong negative correlation exists between population growth and development, as the most developed countries have a small population growth rate, so that a flattening global population is consistent with global development leading to higher fuel consumption per capita.

The negative correlation between temperature and CO2 in ice cores does not prove that low CO2 causes climatic cooling and high CO2 would cause warming including a time lag of 500-1000 years.

However, the AMO exhibits the highest magnitude correlations for all subdomains of mid-level cloud cover having negative correlation coefficients of − 0.223, − 0.205, and − 0.218 for ocean, land, and entire domain respectively.

This conflicts with previous findings which utilize satellite observations which find widespread negative correlation between low and middle to high cloud cover.

The spatial distribution of GCR correlation with high cloud (Fig. 3) shows a plume of negative correlation covering much of the southern to northeastern United States.

With the correlations obtained, droughts coincide with periods of negative irradiance differences (dry high - pressure development), and wet periods coincidewith periods of positive differences (moist low - pressure development).

«Working with data pertaining to 7450 cardiovascular - related deaths that occurred within Budapest, Hungary, between 1995 and 2004 — where the deceased were «medico - legally autopsied» — Toro et al. looked for potential relationships between daily maximum, minimum and mean temperature, air humidity, air pressure, wind speed, global radiation and daily numbers of the heart - related deaths... scientists report and restate their primary finding numerous times throughout their paper, writing that (1) «both the maximum and the minimum daily temperatures tend to be lower when more death cases occur in a day,» (2) «on the days with four or more death cases, the daily maximum and minimum temperatures tend to be lower than on days without any cardiovascular death events,» (3) «the largest frequency of cardiovascular death cases was detected in cold and cooling weather conditions,» (4) «we found a significant negative relationship between temperature and cardiovascular mortality,» (5) «the analysis of 6 - hour change of air pressure suggests that more acute or chronic vascular death cases occur during increasing air pressure conditions (implying cold weather fronts),» (6) «we found a high frequency of cardiovascular death in cold weather,» (7) «a significant negative relationship was detected between daily maximum [and] minimum temperature [s] and the number of sudden cardiovascular death cases,» and (8) «a significant negative correlation was detected between daily mean temperature and cardiovascular mortality.»

It is obvious that higher correlation among cryptocurrencies has a negative impact on diversification.

Many of the scales demonstrated weak psychometrics in at least one of the following ways: (a) lack of psychometric data [i.e., reliability and / or validity; e.g., HFQ, MASC, PBS, Social Adjustment Scale - Self - Report (SAS - SR) and all perceived self - esteem and self - concept scales], (b) items that fall on more than one subscale (e.g., CBCL - 1991 version), (c) low alpha coefficients (e.g., below.60) for some subscales, which calls into question the utility of using these subscales in research and clinical work (e.g., HFQ, MMPI - A, CBCL - 1991 version, BASC, PSPCSAYC), (d) high correlations between subscales (e.g., PANAS - C), (e) lack of clarity regarding clinically - relevant cut - off scores, yielding high false positive and false negative rates (e.g., CES - D, CDI) and an inability to distinguish between minor (i.e., subclinical) and major (i.e., clinical) «cases» of a disorder (e.g., depression; CDI, BDI), (f) lack of correspondence between items and DSM criteria (e.g., CBCL - 1991 version, CDI, BDI, CES - D, (g) a factor structure that lacks clarity across studies (e.g., PSPCSAYC, CASI; although the factor structure is often difficult to assess in studies of pediatric populations, given the small sample sizes), (h) low inter-rater reliability for interview and observational methods (e.g., CGAS), (i) low correlations between respondents such as child, parent, teacher [e.g., BASC, PSPCSAYC, CSI, FSSC - R, SCARED, Connors Ratings Scales - Revised (CRS - R)-RSB-, (j) the inclusion of somatic or physical symptom items on mental health subscales (e.g., CBCL), which is a problem when conducting studies of children with pediatric physical conditions because physical symptoms may be a feature of the condition rather than an indicator of a mental health problem, (k) high correlations with measures of social desirability, which is particularly problematic for the self - related rating scales and for child - report scales more generally, and (l) content validity problems (e.g., the RCMAS is a measure of anxiety, but contains items that tap mood, attention, peer interactions, and impulsivity).

Specifically, PWB has: (1) strong negative correlation with the MHI - 5, where the higher the mental health (as measured by the MHI - 5), the less unfavourable the PWB (as measured by the ASSET; r = − 0.79), (2) moderate negative correlation with the SHS, where the higher the subjective happiness (as measured by the SHS), the less unfavourable the PWB (as measured by the ASSET; r = − 0.47) and (3) moderate negative correlation with CD - RISC, where the higher the resilience (as measured by the CD - RISC), the less unfavourable the PWB (as measured by the ASSET; r = − 0.44).

Similar findings were obtained in a study of foster care breakdown, noting a high correlation between placement breakdown and the service provider having a negative relationship with the foster parents (Pardeck, 1985).

The relationship between depressive symptoms and step count has only been assessed in specific populations with small sample sizes, such as low - socioeconomic status Latino immigrants, 16 elderly Japanese people17 or patients with chronic conditions such as heart failure18 19 or chronic obstructive pulmonary disease.20 21 Studies yield contradictory results, with some observing no association between depressive symptoms and daily step count, 19 21 while others report a negative correlation.16 — 18 20 In one cross-sectional sample of healthy older adults, an inverse association between depressive symptoms (using the Goldberg Depression Scale - 15) and accelerometer measured daily step count disappeared after controlling for general health and disability.22 While a systematic review suggests reduced levels of objectively measured PA in patients with depression, 23 it is not known whether this association is present in those at high risk of CVD and taken into account important confounding such as gender and age.

Specifically, the low - high subscale was used as the reflective functioning variable, and the negative parenting behaviors sub-scale was used as the parenting variable (given the results of the correlation analyses noted above).