Sentences with phrase «lag times of the period»

Not exact matches

Multipliers are frequently used in offsetting to compensate for the risk of failure of the offset measures and the time lag between when negative impacts of the development project are felt and the positive impacts of offsetting come to fruition, often a period of many years.

... [H] is risk - adjusted returns... have lagged the market over a number of time periods over the trailing 15 years.»

To test robustness of influencers, they consider: (1) subsamples to test consistency over time; (2) daily and monthly measurements to test consistency across sampling frequencies (except consumer price indexes, available only monthly); and, (3) contemporaneous and one period - lagged (predictive) relationships.

Even if you count yourself among the lucky dead dedicated index investors, the performance lag only comes into play over a long period of time.

He notes that even «Warren Buffett's Berkshire Hathaway lagged the S&P 500 in more than one - third of rolling three - year periods in the 25 years since 1987,» which, he says, is «something to keep in mind when trying to gauge manager skill over shorter time periods.

If the price of oil balloons to $ 110 + in a short period of time, it will lag all of the oil majors.

«Ten years ago, we were probably 95 percent lager and 5 percent ale, and lagers generally take longer periods of time,» Wiener explains.

«If humans have similar circuitry, it should be possible to adjust to jet lag during a west - to - east flight by having a period of starvation, followed by refeeding at 7 a.m. or 8 a.m. in your new time zone.»

Here, the study argues that, notwithstanding changes in tests and proficiency thresholds in the states over this period of time, the relative position of Arizona vis - a-vis these comparison entities remains very similar, with Arizona continuing to lag behind both in percent of ELL students achieving proficiency in reading and math.

There's a noticeable period of lag between the time you hit the throttle and when the car starts moving.

Even the most powerful devices around can get the dreaded lag that comes around after using it for a prolonged period of time.

Some studies have also shown that DCA strategies lag those of lump - sum investing over long periods of time.

Following are the things that can effect changes on your scores: • Consistent and constant late payments • Increased or reduced credit limits • Higher credit card balances • Higher HELOC (Home Equity Line of Credit) balance • Closing revolving accounts • Recent credit inquiries made In the same way, any new practice you start in managing your credit takes effect and influence your credit scores within 30 to 60 days; due to the lag time between the action you take against the period it takes the creditor to report the action to the agencies who handle credit reports.

A friend related to me a conversation he had had with the director of equity research at an investment management firm that was seeing consistent outflows because of index - lagging performance for the year - to - date, one year, and three year periods (not surprising as most investment and financial consultants have a much shorter investment time - horizon than the one they advise their clients to have).

The Fund's Chief Compliance Officer, or a Compliance Manager designated by the Chief Compliance Officer, may also grant exceptions to permit additional disclosure of Fund portfolio holdings information at differing times and with different lag times (the period from the date of the information to the date the information is made available), if any, in instances where the Fund has legitimate business purposes for doing so, it is in the best interests of shareholders, and the recipients are subject to a duty of confidentiality, including a duty not to trade on the nonpublic information and are required to execute an agreement to that effect.

Since a market's P.A. reflects all variables affecting that market for any given period of time, using lagging price indictors like stochastics, MACD, RSI, and others is just a flat waste of time.

However, keeping too much in cash over long periods of time can cause your investment returns to lag.

Many traders get caught up in using different combinations of lagging indicators, these methods often have not been used for long periods of time by many other traders due to their ineffectiveness to adapt to ever - changing market conditions.

We can define periods of economic and market agreement and periods of discord by using timely variables, such as the New Orders series from the monthly Institute for Supply Management (ISM) Report, to forecast the probability, at any time, of agreement between the economy and the market.5 Typically macro-based measures suffer from a significant lag in reporting as well as frequent revisions, making them inferior to the immediacy of observing market data, month by month, day by day, even tick by tick.

Exposure to these works — with which many Chinese artists might be familiar only in reproduction or online — is seen by Tinari as a means of fostering creative dialogue between the two artistic traditions and diminishing the «time - lag» that hindered domestic art for so long after the Reform and Opening Up period that followed Mao's death in 1976, traditionally taken as the «starting point» of contemporary Chinese art (Tinari concedes that this is a useful marker, but suggests that a new generation of art historians should «complicate» such simplified narratives).

Re # 33 (Dave D.): Ice core measurement issues aside, remember that there has to be some degree of lag because a) the initial warming is from Milankovitch changes, not CO2, and 2) the delayed turnover of ocean water means that not all the CO2 will outgas in a short period of time.

Perhaps this implies that ENSO is a leading indicator of whatever is driving global climate over an intermediate time period, and the actual temperatures is more of a lagging indicator.

So if the second half of the 20th century had the highest average absolute levels of solar activity for «several thousand years» (Solanki) and at least 350 + years (Lean), then this could well have been a significant cause of late 20th century warming (building in all the «time lags» one might envision), despite the fact that the absolute level of solar activity was declining over this period.

There is a climate lag time of 5 to 14 years as the Earth slowly warms and cools in this Global warming period.

Similarly, in a study of air temperature and CO2 data obtained from Dome Concordia, Antarctica for the period 22,000 - 9,000 BP — which time interval includes the most recent glacial - to - interglacial transition — Monnin et al. (2001) found that the start of the CO2 increase lagged the start of the temperature increase by 800 years.

General Introduction Two Main Goals Identifying Patterns in Time Series Data Systematic pattern and random noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Data Systematic pattern and random noise Two general aspects of time series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time Setime series patterns Trend Analysis Analysis of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices of Lack of Fit (Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results Tables Computed by the X-11 Method Specific Description of all Results Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation of FFT in Time SeTime Series

I've understood that he also predicted the ~ 1000 year time lag between temperature rise and CO2 at the end of a glacial period, before it was observed in the ice cores thanks to better dating techniques.

For earlier times, we adopt Greenland temperature estimated as follows (33): For the period 128,700 B.P. to 340,000 B.P., this temperature was derived from a proxy based on Antarctic ice core methane data using the relation T = − 51.5 + 0.0802 [CH4 (ppb)-RSB- from a linear regression of Greenland temperature estimates on Antarctic methane for the period 150 B.P. to 122,400 B.P.. For the remaining period of 122,400 B.P. to 128,700 B.P., data from a variety of climate archives indicate that Greenland warming lags that of Antarctica, with rapid warming commencing around 128.5 ky B.P. in the northern North Atlantic and reaching full interglacial levels by about 127 ky B.P. (51).

The lag is a different (and mostly unresolved) problem: while the lag during warming periods is explainable as the about 800 year turnover time for deep ocean down / upwelling flows, the much longer delay of CO2 during periods of cooling towards a new ice age is difficult to explain, the more that methane does follow temperature far more closely, thus errors in ice age — gas age difference are not at the base of the lag...

My arithmetic for a 2x C02 would be: Present Warming: 0.75 deg C Current warming Rate 0.15 deg C per decade Time to 2x C02 (BAU scenario) approx 100 years So 0.15 x 10 +0.75 = 2.25 deg C Further warming due to time lag at end of 100 year period ~ 0.75 deg, probably over several decaTime to 2x C02 (BAU scenario) approx 100 years So 0.15 x 10 +0.75 = 2.25 deg C Further warming due to time lag at end of 100 year period ~ 0.75 deg, probably over several decatime lag at end of 100 year period ~ 0.75 deg, probably over several decades.

Now we have a period where the decline in temperature and CO2 don't overlap, even if the timing of the CO2 lag may have some error: that is the end of the previous interglacial, the Eemian.

To facilitate compliance with the new data breach reporting regime under PIPEDA, the proposed Regulations provide for implementation at the same time as the related statutory requirements under Division 1.1 of PIPEDA, and allow for a lag period between the publication of final Regulations and their coming into force.

This lag refers to the period of time between when an incident occurs, and when that incident is first reported to us.

That said, iOS 11 is currently lagging behind its previous versions of iOS, as iOS 10 was said to have surpassed a 60 percent adoption rate in a similar time period after its 2016 release.