Key performance indicators commodity trading

Key Performance Indicators - KPI.

What are 'Key Performance Indicators - KPI'

Key performance indicators (KPI) are a set of quantifiable measures that a company uses to gauge its performance over time. These metrics are used to determine a company's progress in achieving its strategic and operational goals, and also to compare a company's finances and performance against other businesses within its industry.

BREAKING DOWN 'Key Performance Indicators - KPI'

KPIs also referred to as key success indicators or KSIs, vary between companies and industries, depending on the pertinent priorities or performance criteria. For example, if a software company's goal is to have the fastest growth in its industry, its main performance indicator may be the measure of revenue growth year over year (YOY). In the retail industry, same-store sales is a common metric used to measure sales growth between different store locations.

Financial KPIs.

Some of the most common KPIs revolve around revenue and profit margins. The most basic profit-based metric is net profit. Also known as the bottom line, net profit represents the amount of revenue that remains as profit for a given period after accounting for all the company's expenses, taxes and interest payments for the same period. Since net profit is calculated as a dollar amount, it must be converted into a percentage of revenue, or profit margin, to be used in comparative analysis. If the standard net profit margin for a given industry is 50%, for example, a new business in the industry knows it needs to work toward meeting or beating that figure to be competitive. The gross profit margin, which measures revenues after accounting for only those expenses directly associated with the production of goods for sale, is another common profit-based KPI.

The current ratio is a common financial KPI and is calculated by dividing a company's current assets by its current debts. A financially healthy company typically has more than enough cash and cash equivalents on hand to meet all its financial obligations for the current 12-month period. However, different industries use different amounts of debt financing, so comparing a company's current ratio to those of other businesses within the same industry is a good way to establish whether the business' cash flow is in line with industry standards. A company's financial KPIs are stated in its annual report.

Nonfinancial KPIs.

Not all KPI metrics are related directly to a company's cash flow. A business' success depends on more than its balance of cash and debt; it depends on its relationship with its customers and employees. Some common nonfinancial KPIs include measures of foot traffic YOY or month over month, employee turnover, the number of repeat customers versus new customers, and various quality metrics. The specific metrics a company tracks are dictated by its current aims and may change over time as the business evolves and sets new performance measures.

Utilizing Data and Key Performance Indicators to Successfully Execute a Phase III Influenza Treatment Clinical Trial.

November 30, 2015.

Introduction.

SGS was recently engaged in a global Phase III influenza treatment clinical trial, providing both overall project management and study monitoring. The trial was one of the largest influenza treatment trials conducted to date, and as a result presented several challenges, due in part to the seasonality of influenza and the geographic imbalance in the outbreaks. This paper will address how SGS utilized constant data tracking to mitigate the disease-specific challenges and successfully execute this Phase III clinical trial.

The study team focused on integrating quality into every aspect of the trial. SGS tracked several key performance indicators (KPIs) to measure and monitor the quality of study conduct in four main areas:

Start-Up Timeline Adherence Site Engagement Influenza Positivity Data Monitoring.

Study Overview.

The trial ran over multiple flu seasons in more than 150 sites throughout several countries. In order to ensure the opportunity to recruit subjects year-round, the distribution of sites spanned both hemispheres. Enrollment into the study alternated between the two hemispheres, occurring from November through March in the Northern Hemisphere and from April through August in the Southern Hemisphere (Figure 1). The sites screened for subjects with signs and symptoms of uncomplicated influenza.

Start-Up Timeline Adherence.

Due to the seasonality of influenza, sites may only have a period of six to eight weeks to actively recruit for the clinical trial in a given year. This challenge is compounded by the significant seasonal variability of outbreaks and peak activity, which remains unpredictable. Per Figure 2, the flu season in the United States historically occurs in February; however, historical records show seasonal peaks are possible as early as October or November. Therefore, it was very important to prepare sites for initiation early enough that the peak of flu season was not missed while also taking into account that sites should not actually recruit for the study until flu activity was confirmed in their areas.

For this study, the target date for initiation of the majority of sites was mid-November during flu season in the Northern Hemisphere. This allowed sites to be open and ready to start enrollment during the time period with highest flu incidence. In order to ensure that study start-up activities were progressing quickly enough to achieve this goal, the SGS study management team tracked two relevant KPIs:

Percentage of contracts to be executed by November 1st Time from Institutional Review Board (IRB) approval to Site Initiation Visit (SIV) for each site.

To monitor the KPI related to site contracts, SGS tracked the number of Clinical Trial Agreements signed each week as well as the cumulative number of contracts near final negotiations. These values were then used to project the total number of agreements expected by the first of November, the goal of which was 90% of all sites. The metric for the timing of SIVs was tracked on a site-by-site basis with a target of initiating each site within 10 business days of IRB approval. Monitoring this KPI allowed the SGS team to ensure that the opening of sites was done promptly following all required start-up activities and that it was not delayed due to staff availability or scheduling issues. Although the primary objective was to initiate sites within ten days following IRB approval, flu incidence rates in the respective areas were used to determine if there was a need for a more rapid initiation of each site on a case-by-case basis.

Site Engagement.

A critical factor to the success of any given clinical trial is the performance and commitment of the study sites. While the sponsor and CRO can provide planning and careful monitoring, the sites are vital contributors to studies because they drive recruitment and overall data quality. In this particular study, promoting a strong commitment of the sites was especially important given the short window to recruit subjects and the need for prompt attention to data queries. The SGS study management team worked diligently to keep sites engaged in both recruitment activities and ongoing data cleaning through regular monitoring visits and frequent phone or contact. SGS tracked three relevant metrics to examine site performance:

Number of days from site activation to first subject enrolled at each site Average number of days to complete electronic Case Report Forms (eCRFs) following a subject visit Average number of days to resolve queries.

Sites were considered active and ready to recruit following the SIV and once the presence of influenza was confirmed in the local community. It was essential to know that enrollment was progressing in areas where influenza was prevalent so that sites did not miss the transient flu activity in their areas. The KPI for first subject enrolled looked at the number of sites which enrolled a subject within one week of activation. The overall goal was to ensure that at least 75% of sites were enrolling within this timeframe. SGS Clinical Research Associates (CRAs) followed up closely with sites that had difficulty meeting this goal and provided support and suggestions to facilitate recruitment.

Once a site did enroll subjects, the SGS team calculated the number of days from each subject visit to completion of the respective eCRFs by site staff. The goal for this metric was to see data entered within five days. Additionally, SGS monitored a KPI on data queries in order to assess sites’ attentiveness to pending data clarifications in the Electronic Data Capture (EDC) system. We tracked the total number of days that queries remained open and expected to see at least 90% of queries closed, including additional source data verification by the CRA as needed, within 30 days of initial generation. The metrics on data cleaning allowed the study management team to identify sites that needed more frequent follow-up between interim monitoring visits.

Influenza Positivity.

Recruitment was based on the presence of signs and symptoms of influenza (versus a confirmed diagnosis of flu by means of a rapid antigen or polymerase chain reaction test). The study team took several measures, both at the site and study levels, to maximize the flu positivity rate of enrolled subjects. Again it was important for the study team to use metrics to track overall quality. In this case, the two metrics tracked were:

Overall study-wide flu positivity Site-level flu positivity rates.

The goal for flu positivity was 45% across all sites. By calculating this value, the management team was able to confirm that the targeted activation of sites based on the presence of influenza in the community was, in fact, effective. The site-level KPI was a bit different in that we tracked the number of flu positive subjects enrolled at each site and monitored for multiple negative subjects in a row. If a site enrolled four consecutive flu-negative subjects, that site was placed on an enrollment hold pending retraining and reconfirmation of local influenza activity. The retraining for the site included topics such as inclusion/exclusion criteria, collection of nasopharyngeal swabs, and proper handling and shipping of samples. Following enrollment of eight consecutive flu-negative subjects, a site was directed to permanently halt recruitment. This was an unfortunate but necessary step in order to ensure optimal use of investigational product, which meant providing drug to sites that were successfully enrolling flu-positive subjects.

In addition to tracking metrics on flu positivity, SGS implemented community surveillance plans to serve as tools to help sites confirm local influenza activity. These were site-specific plans which required each site to identify a combination of public health surveillance sources and local certified laboratories that could provide data on confirmed influenza cases. The site then needed to obtain documentation from one of the identified sources to serve as evidence of local flu activity. The sponsor encouraged the use of local laboratories, such as those embedded within hospitals, to provide data as this generally resulted in more contemporaneous, localized flu confirmation versus relying on public health surveillance data. A completed community surveillance plan verified by the Principal Investigator was required in order for a site to be considered activated and ready to recruit.

Data Monitoring.

With highly-engaged sites working diligently to recruit flu-positive subjects, SGS was tasked with providing thorough clinical trial monitoring of a vast amount of data on a very tight timeline.

Achieving the goal for database lock required a very large, dynamic team of CRAs as well as close monitoring of CRA workload by the study management team. Not only was there a substantial amount of data in this trial, there were two main added challenges specific to the indication. Due to the seasonality of influenza, enrollment in the Northern Hemisphere was concentrated during the months of December, January and February. This spike in enrollment resulted in a large surge of eCRFs generated in a short period of time, as shown in Figure 3.

Additionally, the data was not evenly dispersed across all sites. The top 15 enrolling sites in the U. S. recruited approximately half of all enrolled subjects, meaning about 10% of the sites generated roughly 50% of the data (Figure 4). Because of the uneven distribution of data, it was not effective to use the traditional model of allocating a certain number of sites to each CRA. Therefore, the SGS team carefully tracked the number of subjects assigned to each CRA. If the workload of one CRA became too high, it was necessary to quickly readjust the distribution of sites and subjects.

In addition to watching the CRA workload, the study team tracked the percent of data that was Source Data Verified (SDVed), at both the study and site levels, on a near-daily basis to ensure the monitoring continually progressed even as enrollment was occurring very rapidly. If the percent of data SDVed at one or more sites dropped significantly, the team arranged for CRAs to attend visits as co-monitors to assist with data verification. Assessing these metrics and adjusting the allocation of resources frequently was essential to locking the database promptly after completion of the study.

Conclusion.

The SGS study management team dedicated a great deal of time to tracking and calculating multiple metrics on a frequent, often daily, basis. The information obtained through analysis of these KPIs was crucial to steering the day-to-day study action plan and to guiding the trial to a successful database lock. SGS applies this practice across all therapeutic areas, defining relevant, indication-specific metrics to improve overall study quality and efficiency.

SGS Life Science Services.

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EU Strengthens Chemical Safety in Certain Toys.

The European Union (EU) has recently amended the Toy Safety Directive 2009/48/EC (TSD) to include the restriction of formamide and 4 preservatives in certain toys. The enforcement dates are dependent on the nature of the restricted substance and will start on 24 May 2017.

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Technical Indicators and Commodities.

Learning Center.

Technical indicators are additional tools used by the technician in order to develop commodity price forecasts. In this section you will examine a few of the more popular technical indicators used to supplement the basic analytical tools of support, resistance and trendlines. These include; moving averages and oscillators.

The moving average is a trend following indicator which is easy to construct and one of the most widely used mechanical trend following systems used. A moving average, as the name suggests, represents an average of a certain body of data that moves through time. The most common way to calculate the moving average is to work from the last 10 days of closing prices. Each day, the most recent close ( day 11) is added to the total and the oldest close ( day 1) is subtracted. The new total is then divided by the total number of days ( 10) and the resultant average computed.

The purpose of the moving average is to track the progress of a price trend. The moving average is a smoothing device. By averaging the data, a smoother line is produced, making it much easier to view the underlying trend. The decision as to what time period to include ( 10 day, 30 day, 40 day) as well as the type of chart ( daily, weekly, or monthly ) is a subjective one that you will have to make for yourself. If a shorter time period is used ( ie., 10 day moving average), the resultant trend line will exhibit a greater degree of trend variation than a longer term moving average, such that the underlying trend may be more difficult to determine. If a longer term moving average is employed ( ie., 40 day moving average) the time lag between the transformation from an uptrend to a downtrend will be delayed long after the change of price trend is underway. In some markets, it is more advantageous to use a shorter term moving average, and in others, a longer term average proves to be more useful.

Generally the closing price is used to compute the moving average, however opening, high, low and mid point of the trading range values can also be selected. Several types of moving averages can be calculated. Some analysts believe that a heavier weighting should be given to the most recent data and in an attempt to correct this problem, construct other types of moving avenges such as the linearly weighted and exponentially smoothed moving average. The most common application is the simple moving average as discussed above.

In a simple moving average each day's price receives equal weight. The moving average is plotted on the bar chart on top of the appropriate trading day and along with that day's price action. When the daily closing price moves above the moving avenge a buy signal is generated. When the daily closing price moves below the moving average a sell signal is generated.

If a very short term moving average is employed, numerous crossovers will occur such that the trader may be exposed to many false signals and higher commission costs of trading. If a longer term moving average is used the trader may be too slow in responding to a change in trend, forsaking much of the profit potential. A shorter term moving avenge works best in a sideways trending market, allowing the trader to capture more of the shorter swings. A longer moving avenge works best in trending markets, allowing the trader to stay with the trend and minimizing the chance of getting caught in short term corrections. The correct approach is to use a shorter average during non-trending periods and a longer average during trending periods.

Moving averages are trend following systems which do not have forecasting capabilities. They are used only to help in identifying the underlying trend and as an aid in entering and exiting the market. One of the greatest advantages in using a moving average is that by nature it follow the trend and by selecting a suitable time period, allows profits to run and losses to be cut short. This system works best when markets are trending. During choppy or sideways markets a non trending method such as an oscillator will yield better results.

An oscillator is an extremely useful tool that provides the technical trader with the ability to trade non-trending markets where prices fluctuate in horizontal bands of support and resistance. In this situation, trend following systems such as the moving average do not perform satisfactorily, as many false signals are generated. The oscillator can also be used to provide the technician with an advance warning of short term market extremes, commonly referred to as overbought and oversold conditions. Oscillators provide a warning that a trend is losing momentum before the situation becomes apparent in the price action which is referred to as divergence. As is the case with other types of technical tools there are times when oscillators are more useful than others and they are not infallible.

The concept of momentum is the most basic application of oscillator analysis. Momentum measures the rate of change of prices by continually taking price differences for a fixed time interval. The formula for momentum is:

Where C is today's market close and Cx is the close �x" days prior. To construct a 10 day momentum line, today's closing price is subtracted from the closing price 10 days ago. If the most recent closing price is lower than the closing price 10 days prior, a negative number will be generated. Conversely if today's closing price is higher than the closing price 10 days ago a positive number will be generated. These values are then plotted on the top or bottom of the bar chart with a horizontal zero line in the middle. As with the moving avenge, the number of days chosen to compute the oscillator can vary, with shorter term oscillators ( 5 day ) producing a more sensitive line with more pronounced oscillations. A longer term oscillator ( 20 days ) produces a smoother line in which the oscillator swings are less pronounced.

By plotting price differences over a fixed period of time, the technician is studying rates of change in price trends. If prices are rising and the momentum line is above zero and rising, an accelerating uptrend would be in place. If the momentum line begins to flatten out, the rate of as cent indicates that the uptrend has leveled off and provides the technician with a lead indication that the uptrend may be coming to an end. Because of the nature of its construction, the momentum line will always lead the price action. It will lead the advance or decline of prices by a few days, then will level off while the current price trend is still in effect, before moving in the opposite direction as prices begin to level off.

The most widely followed momentum oscillator in technical analysis is Welles Wilder's Relative Strength Index ( RSI). The formula for the RSI is as follows:

The RSI is plotted on a graph with a vertical scale from zero to one hundred, with highlighted horizontal lines drawn at scaled values of 30 and 70. The horizontal axis corresponds to the time line on the bar chart.

Interpretation of the RSI is twofold. First the areas on the chart above seventy and below thirty are critical areas for the technician. When the indicator is in the area above 70, the market is said to be overbought. When the indicator is in the area below 30, the market is said to be oversold. These terms refer to a market condition where prices have moved too far too quickly, such that the technician can expect a correction to take place before the market resumes its trend .

One of the most valuable ways to utilize an oscillator is to watch for a divergence. A divergence describes a situation when the trend of the oscillator moves in a different direction from the prevailing price trend. In an uptrend divergence occurs when prices continue to rise, but the oscillator fails to confirm the price move into new highs. This often provides an early warning of a possible price decline and is called bearish or negative divergence. In a downtrend, if the oscillator fails to confirm a new low in the price trend, a positive or bullish divergence exists, which warns of a potential price advance. An important requirement for divergence analysis is that the divergence should take place near the oscillator extremes of 70 and 30 respectively.

Various chart patterns show up on the RSI indicator as well as support and resistance levels. Trend line analysis can then be employed to detect changes in the trend of RSI. The process of updating the RSI on a daily basis is greatly facilitated by accessing technical analysis software programs on a personal computer to perform the calculations and plot the indicator on the bar chart.

4 Key Indicators That Move The Markets.

Every week, dozens of economic surveys and indicators are released and reported on in the business news. In fact, there are so many - and the data points often makes such small moves - that it can be easy to overlook the importance of this data on the markets. However, as an educated investor, it's important to keep your finger on the pulse of the economy, and indicators are an important way to do that. This article will examine some of the most important economic indicators and market indicators for investors to monitor. Get to know them, and you'll be better prepared to anticipate and react to future market developments.

Employment.

Perhaps the most important indicator of the health of the economy is employment. On the first Friday of each month, the U. S. Bureau of Labor Statistics releases its monthly unemployment report and nonfarm payroll. These indicate the current unemployment rate and how many jobs have been gained or lost by the U. S. economy, respectively. Market participants eagerly await these reports, and they often result in some of the biggest one-day movements in both bond and stock markets. The employment situation report also influences other important indicators, such as consumer confidence and consumer sentiment.

Because consumers make up nearly 70% of U. S. economic activity, the state of the labor market is of paramount importance to the overall well-being of the economy. This means that a weakening or strengthening labor market can influence the economy. For example, a weakening labor market often translates into lower corporate profits. The basic premise is that when people are out of work, they cannot buy homes or make the necessary purchases that drive corporate profits. (To learn more about the unemployment rate, see The Unemployment Rate: Get Real .)

The mandate of the Federal Reserve is to promote economic growth and price stability in the economy. Price stability is measured as the rate of change in inflation, so market participants eagerly monitor monthly inflation reports to determine the future course of Federal Reserve monetary policy.

There are many indicators of inflation, but perhaps most widely known is the Consumer Price Index, or CPI. The CPI measures the change in consumer prices and, theoretically, determines to what extent life is getting more expensive for the average consumer. Another important measure is the Producer Price Index, or PPI. PPI fluctuations measure the rate of change in inflation for producer goods. If these prices increase substantially, it is more likely that companies will eventually pass the price increases along to consumers. Many economists and market participants prefer to analyze both CPI and PPI without the impact of food and energy, as these industries are known to be volatile.

Market participants also keep track of the price of key commodities such as oil. Since oil is such a key component of economic activity around the globe, its price is worth paying special attention to. Increases in the price of oil can sometimes have offsetting effects. However, higher oil prices can lead to higher prices for a wide variety of goods, because oil is part of many materials as well as a determinate in the cost of transporting goods waiting to be sold. (For more on inflation and the economy, see The Importance of Inflation and GDP .)

Inflation is a useful metric of corporate valuation because the discount rate to perform discounted cash flow analysis factors is the rate of inflation. Higher inflation corresponds with a high discount rate and subsequently lower project value. On the other hand, deflation is also dangerous because decreased revenue may mean future layoffs for firms that cannot maintain their full workforce.

Consumer Activity.

Changes in the activity level of consumers have a direct impact on corporate profits and the level of stock prices. There are several ways of measuring consumer activity. What people buy and where they shop can provide valuable information about the economy. (To learn more, see Using Consumer Spending as a Market Indicator .)

One of the most popular ways to measure consumer activity is through consumer confidence. There are several measures of consumer confidence, but all are designed to determine how consumers feel about their economic prospects in the coming months. The theory is that when consumers feel more confident, they are more likely to spend. Conversely, they are less likely to spend when they feel less confident. Also, because markets are forward looking, there is a tendency for stock prices to reflect the future opinions of consumers today. Another measure of the consumer is retail sales. While consumer confidence is forward looking, retail sales indicators reveal historic shopping patterns. (For more insight, read Understanding the Consumer Confidence Index .)

The housing market serves as another vital economic indicator. Although housing is highly localized and difficult to measure on a national basis, there are several indicators that do a reasonable job. Market participants pay attention to monthly releases such as housing starts, building permits and new home sales in order to get a reading on the level of activity in the housing market. Market watchers also monitor price changes through a variety of indicators such as the S&P/Case-Shiller Home Price Index, which monitors home price changes in 20 large American cities. By synthesizing a variety of housing reports, market participants can deduce whether or not people are willing to make large purchases.

Investor Activity.

In addition to economic indicators, market participants focus closely on measures of investor activity for market clues. Despite popular belief, the best time to invest is not when everyone is bullish, but instead when most investors are bearish. If everyone else is bullish, there is no one left to buy and drive prices higher – but this does, of course, depend on your investment strategy. Therefore, readings of investor sentiment are important. A variety of indicators are available. Some are published by large investment firms or research firms, which periodically poll their clients to determine market consensus.

[Technical analysis is a common way to quantitatively measure investor activity. For example, the Relative Strength Index (RSI) is a great way to determine if a stock is overbought or oversold. Investopedia's Technical Analysis Course provides an in-depth overview of both technical indicators and chart patterns that can be used to gauge investor activity.]

As overseas investors have become increasingly important participants in the U. S. financial markets, measures of their activity have garnered more attention. One of the most closely watched reports focuses the purchase of U. S. Treasuries by foreign central banks. When central banks are buying more Treasuries, interest rates often head lower, and when rates are lower, stock prices tend to move higher. The reverse – less buying, higher interest rates and depressed stock prices – also tends to hold true.

Other important market indicators include advance/decline ratios and the number of new highs and new lows in the market. These readings indicate how healthy the overall stock market is and can provide confirmation as to the "quality" of a stock market advance or decline.

The Bottom Line.

Knowing what economic and market indicators move markets is only half the battle. The real trick is interpreting the indicators and determining their likely market impact. In addition to the absolute level of an indicator, two other important factors to consider are the trend in the indicator and the market's expectation for that indicator. Taken together, these often determine the market's reaction to a given economic or market report. Learning to anticipate the market's reaction to various indicators requires careful monitoring of financial markets, as well as experience interpreting these reports. As with most aspects of investing, hard work and persistence will help an investor determine the likely reaction to economic and market data. (To learn more about indicators, check out Leading Economic Indicators Predict Market Trends .)