1QBit is a software company focused on solving intractable industry problems with the most advanced quantum and classical hardware available. 1QBit is backed by major corporations including Accenture, Allianz, CME Group, Fujitsu, Royal Bank of Scotland and the Siam Commercial Bank. Its hardware partners include DWave, Fujitsu, IBM, Microsoft, Rigetti and others. 1QBit’s publiclyannounced client list includes DowDuPont, Biogen and NatWest.
1QBit’s 60+ researchers and developers hold over 100 university degrees in a wide variety of specialized areas including medicine and biology, machine learning, computational physics, chemistry, mathematics, computer science, business and engineering. 1QBit develops algorithms in a variety of fields and applies the synergies that occur when concepts and techniques cross from one field to another. This includes the analysis of market sentiment based on volume, price and open interest data available from sources like CME DataMine.
The Market Sentiment Meter is organized around the concept that typical bellshaped riskreturn probability distributions seriously underestimate tail risk and that just augmenting the tails of the distribution is not necessarily sufficient.
As an illustration, take event risk where traders might imagine two dissimilar outcomes. For example, since 2016, we have seen event risk associated with elections – UK Brexit Referendum of June 2016, U.S. Presidential election of November 2016, French and UK elections in 2017, Brazilian elections of October 2018, U.S. Congressional elections of November 2018, etc., where there were two possible scenarios. Before the event, the market typically prices the probabilityweighted outcome, or the middle ground. After the event, when the outcome becomes known, the market immediately moves away from the middle ground to the “winning” scenario – a price break. For example, with Brexit, the leave vote generated a sharp downward move in the British pound (versus USD), while a Remain vote would have presumably generated a sharp almost instantaneous rally in the pound – either way, the pound was no longer going to trade in the middle.
To handle riskreturn probability distributions that may not have bellshaped curves and may be highly asymmetric, the MSM method uses a mixture distribution process, and gathers a variety of information from futures and options prices, volumes and intraday activity to create a proxy for the actual unobservable distribution. While implied volatility from options prices is one of the metrics used in the MSM process, it is not the sole primary driver of the process and it is not allowed to bias the results toward bellshaped solutions.
The MSM riskreturn probability distribution has the four characteristic shapes shown below.
Balanced risk is the most common state and shows a bellshaped riskreturn probability distribution. 

Complacent is when the riskreturn probability distribution is tall and narrow. Market participants have relatively few worries. 

Anxious is when the distribution broadens and may even move offcenter. Market participants see worries everywhere. 

BiPolar or Event Risk occurs when market participants are weighing the probabilities of two starkly different outcomes and the distribution has two modes. Bipolar states are rare and typically shortlived, yet extremely important to recognize. 
The MSM riskreturn probability distribution is calculated using a proprietary process based on multiple metrics from the price, volume and intraday activity of futures and options markets. Read our research paper on “Reimagining Probability Risk Distributions,” for an intuitive explanation of our process.
The time series below shows the states of the Market Sentiment Meter overlaid on the settlement price for the nearby futures contract (the front month) in Henry Hub Natural Gas physically delivered futures (NG).
Casual observation may suggest that bipolar (event risk) periods are sometimes followed by important price moves. As a cautionary note, the concept of event risk is only that after an event, one of the two possible outcomes has clearly occurred, and that all of the market participants are now acting on this common knowledge. That said, the anticipated choice might have been between up or down, moving or staying still, high or low volatility, etc.
The sentiment state embedded in markets is inherently unobservable. Based on their observed actions  prices, volumes and intraday activity in futures and options markets – we hypothetically represent the risks which may be perceived by market participants. We do not claim any predictive value as we are only attempting to describe an unobservable riskreturn distribution to inform discussions and analysis of marketplace risks.
The Market Sentiment Meter is available as a subscription, which may be ordered for any of the following products:
The subscription includes:
The Curated Data Files contain a wide variety of metrics, including futures settlement prices, futures and options volumes, a representative proxy for implied volatility for options, and many other derived series, as well as our market state classifier, which may be:
Application notes and research papers will be made available to assist the subscriber as they are prepared and published.
Subscription files are provided as Comma Separated Values (CSV).
Application notes and R&D papers will be made available either as a downloadable PDF or through a web page, to be determined.
Curated Data File Package (CSV) per product ranges from 6 MB to 10 MB. This depends on the number of zeros in the file, which are represented by “0”, as opposed to the standard 9digit precision.
There is a Curated Data File for each product which is updated after each trading day. There are currently eight products available: equities, treasuries, euro FX, gold, oil, natural gas, corn and soybeans.
The files are updated after the close of each business day, as soon as the preliminary endofday settlement files (P files) have been published by CME Group and made available to 1QBit.
You can always download the most recently updated files from CME DataMine. The updated files will normally be available within four hours of their publication by CME Group. Typically, the files will be available between 2 a.m. and 5 a.m. Central Time (CT). However, from time to time, delays may occur.
The CSV files are not compressed.
Sample files will be available with details available in the future.
Time series in the Curated Data File starts on January 3, 2012, the first futures and options trading day of 2012.
All price and volume data comes from the EndofDay (EOD) settlement files published by CME Group and offered for purchase by CME DataMine.
The settlement price will always be the price published by CME Group.
In order to keep the time series for all of the products in exact alignment, the following special cases were handled as follows:
In recent years, no CME Group markets have been opened on Good Friday. In 2010, 2012 and 2015 however, the Equities, Rates and FX products were allowed to open on Thursday evening with Friday’s trade date, and allowed to trade overnight until 8 a.m. on Friday, after which the markets were closed and the trades booked on the Friday. The volume in all cases was small in comparison to that of nearby days. The Curated Data Files do not include any Good Friday data.
There was no trading at all for interest rate products on December 5. CME Group published endofday settlement prices for December 5 that were identical to the prices reported for December 4. In equities, the markets were closed from 8:30 a.m. CT onward on December 5, but were open overnight, which made it possible for a regular settlement price to be published. All other markets remained open for their usually scheduled hours. The Curated Data Files contain the following data for interest rate futures and options:
In most futures products, volume and open interest is largest in the contract with the nearest expiry date. However, as the expiry date draws nearer, volume and open interest move to the next available expiry. This is referred to as the roll and can be spread over many days.
The Market Sentiment Meter defines a nearby futures contract and second futures contract. The nearby contract is usually exactly that, i.e. the futures contract with the closest expiry and the greatest volume. Each day, however, the MSM program compares the volume in the nearby contract with the volume in all subsequent expiries. When the volume in a later contract surpasses the volume in the nearby contract, the definition of the nearby futures contract is updated to be the new contract with the largest volume. The definition does not move back, even if the volume in the expiring contract temporarily exceeds the volume in the new nearby.
When the nearby futures contract is advanced to a later expiry, the second futures contract also advances.
For contracts such as Corn, which trades in March, May, July, September and December, the next expiry may be more than a month away. There are also contracts, such as Gold, that trade the nearest calendar months in addition to the standard months. The roll logic is driven by volume and does not attempt to select the expiry that “ought” to be next.
In order to keep daytoday ratio data consistently defined across a roll, the Curated Data File reports the previous nearby reference price. This is the settlement price on the previous day for the contract being reported as the nearby contract.
For example, in CME Euro/USD FX futures (EC), the 2016 the Market Sentiment Meter’s nearby roll, from the December 2016 ECZ16 contract to the March 2017 ECH17 contract, took place on December 16. The second futures contract advanced from March to June on the same day.
The return in the nearby contract is always computed from the previous nearby reference price.
Blank price data can be present for several reasons.
For example, if there was no volume traded in the second futures contract, there will be no high or low price to report. Bids and asks that do not trade are not used in the MSM calculations.
In some cases, there may be volume traded in a way that does not establish a high or low price, for example:
This situation occurs most frequently in 10 Year Treasury Note futures, which trade for March, June, September and December. When open interest is rolling from (say) March to June, there is typically not much activity in the September contract.
CME Group calculates a settlement price for all listed contracts, even if there is no trading on any given day. It is not uncommon for contracts with distant expiry dates to slowly accumulate open interest over many lowvolume (and novolume) days.
The Curated Data File contains a variety of smoothed time series. Our research has indicated that comparing shortterm smoothed metrics to longterm smoothed metrics can lead to very useful insights into how market risk perceptions are evolving.
Smoothing is exponential. For example:
(today’s smoothed IVOL) = k * (today's IVOL) + ( k1 ) * (yesterday's smoothed IVOL),
where k = 1/(number of smoothing days).
For shortterm smoothed series, the number of smoothing days is 30 days.
For longterm smoothed series, the number of smoothing days is 200 days.
The number of days is configurable by product and we are continuing to conduct research related to the most appropriate smoothing processes.
We prefer an exponential smoothing process to a moving average window process. Exponential smoothing values recent data more highly than older data. In a moving average window, the data points within the time window are all considered equal, and we strongly believe that market participants do not process information in this manner. With a moving average window method, if a large movement occurs and then is reversed, the large temporary movement would retain the same impact even as it fades into history. With exponential smoothing, the large temporary movement loses influence every day.
All time series in the Curated Data File start on January 3, 2012, the first futures and options trading day of 2012. However, the initial values of the smoothed time series are based on data extending back to January 4, 2010.
Volume data reported in the Curated Data Files is the total daily volume reported by CME Group. This includes:
An EFRP can be an exchange for physical (EFP), e.g. from financiallysettled futures to physical futures such as CL, NG, etc., an exchange of futures for risk (EFR), or an exchange of options for options (EOO). For additional detail on EFRP transactions in a specific product, consult the relevant sections of the Exchange Rule Book.
Historical volatility within the Market Sentiment Meter uses exponential smoothing as described above. For volatility, a weighted historical standard deviation is calculated from a Daily Variance Proxy, defined as the square of the percent change in price. The daily variance proxy is weighted exponentially, so that more recent price movements contribute more to this historically weighted standard deviation. This method mimics the traditional definition of volatility as the standard deviation of the distribution of percent price movements (as it is in the BlackScholes model).
The Market Sentiment Meter is influenced by differences between the forwardlooking volatility estimates seen in options prices, and the backwardlooking volatility estimates made from the settlement prices in the underlying futures contracts.
The historical standard deviation is annualized so that it can be compared to other volatilities, most notably the implied volatilities published by CME Group.
While our MSM metrics process uses exponentially smoothed time series data, for ease of user comparisons and for use in momentum trading models, we also provide some precalculated moving averages. Each moving price average is the uniform windowed average of today’s settlement price and the settlement prices from prior days.
For example, the 20day moving average is computed from today’s settlement price and the settlement prices from 19 prior days. The average is given to nine decimal places, regardless of the price ticking.
The Curated Data Files begin on January 3, 2012. The moving price averages, peak prices and other timedependent data have been initialized with values based on settlement files prior to that date.
The moving price averages are calculated for the nearby futures contract settlement price. The 200day moving price average will therefore contain one or more contract rolls. Even the 20day moving average will contain a roll day in some contracts. Although there may be a small jump in the price when moving from expiry to the next, it is assumed that the averaging will give greater emphasis to the much larger number of nonroll days. That said, the interpretation of a 60day moving price average in Crude Oil futures (which roll monthly) will have to be different from the interpretation of a 60day moving price average in 10Year Treasury Note futures, which roll quarterly.
All time series in the Curated Data File start on January 3, 2012, the first futures and options trading day of 2012. However, the initial values of the moving price averages are based on data extending back 20, 60 and 200 trading days into 2011.
The riskreturn probability distribution is a proprietary process using a mixture distribution method. See our related research papers for more indepth explanations. We report the standard parameters for the MSM riskreturn probability distribution, including mean, median, first mode, second mode if any, standard deviation, skewness, and kurtosis.
The probabilities are calculated using today's riskreturn probability distribution.
For example, to calculate the probability of reaching 20% above today’s 60day average in the coming year: The price value for 20% above the 60day moving average is expressed as a return relative to the today's settlement price and the distribution used to calculate the probability of this return being exceeded.
The target return is used as the lefthand side of a semiinfinite interval, and the probability calculated as the area under the tail of the distribution.
CsvHeaderName 
CsvHeaderLongName 
Definition 
Typical Value 

TRADEDATE 
Trade Date 
Business date for the settlement price and other data reported on this row. Expressed as an eightdigit integer in YYYYMMDD format (ISO 8601). 
20190731 
DATA_SOURCE 
Data Source 
Source or citation information to be included on charts or tables using the data set. 
CME DataMine  Market Sentiment Meter powered by 1QBit 
EODDESC 
EOD Description 
Description of the underlying futures product as included in CME DataMine End of Day (EOD) file documentation. 
10YR NOTE FUTURES 
CHART_TITLE 
Chart Title 
Description of the underlying futures product for inclusion in charts or tables using the data set. 
CBOT US Treasury 10Year Note Futures 
YYYY 
Year 
YEAR of the business date, as an integer 
2019 
MM 
Month 
MONTH of the business date, as an integer 
7 
DD 
Day 
DAY of the business date, as an integer 
31 
DATECODE_EXCEL 
Excel Date Code 
The fivedigit Excel datacode for the Trade Date. 
43677 
DATE_LABEL 
Date Label MMDDYYYY 
The Trade Date expressed in MM/DD/YYYY format. 
7/31/2019 
F_PROD_CODE 
Futures Product Code 
Product code used by CME DataMine for the futures contract, in upper case 
TYF 
O_PROD_CODE 
Options Product Code 
Product code used by CME DataMine for the options contract being used in the model on this day. In most cases, the options code does not change through time; however, there is an exception for the option used for the Euro/USD FX (USD per EUR). The original option code future was ZC from 2012 to 2017, but EUU afterwards, after a shift in the product option type. This field always shows the option that was in use on the corresponding Trade Date. 
TC 
PRICE_SETTLE_ 
Most Active Futures Settlement Price 
The futures contract with the largest daily volume. Usually the most active contract is the nearby contract. When trading "rolls" from one expiry to the next, the actual nearby future is no longer the most active contract and our analysis shifts with the "roll". Once a new "most active" contract has been established, the curated data does not move backwards. 
127.421875 
PRICE_HIGH_ACTIVE 
Most Active Futures High Price 
CME Globex High price as published by CME Group in the EOD settlement P (Preliminary) File for the most active futures contract. 
127.703125 
PRICE_LOW_ACTIVE 
Most Active Futures Low Price 
CME Globex Low price as published by CME Group in the EOD settlement P (Preliminary) File for the most active futures contract. 
127.015625 
YYYY_ACTIVE 
Most Active Futures Contract Year 
The year of the delivery month that defines the most active futures contract. Given as an integer. 
2019 
MM_ACTIVE 
Most Active Futures Contract Month 
The delivery month that defines the most active futures contract, given as an integer. 
9 
F_VOLUME_ACTIVE 
Most Active Futures Contract Volume 
Total volume traded and settled on the business day in the most active futures contract. Includes CME Globex volume, floor volume (where it exists), and EFRP (exchange for a related position). Total volume also includes PNT (privately negotiated trades) that are cleared through CME Clearing. 
2403170 
PRICE_SETTLE_NEXT 
Next Futures Settlement Price 
The settlement price of the next futures contract after the most actively traded futures contract. 
127.890625 
PRICE_HIGH_NEXT 
Next Futures High Price 
CME Globex High price as published by CME Group in the EOD settlement P (Preliminary) File for the next futures contract after the most active. 
128.140625 
PRICE_LOW_NEXT 
Next Futures Low Price 
CME Globex Low price as published by CME Group in the EOD settlement P (Preliminary) File for the next futures contract after the most active. 
127.5 
YYYY_NEXT 
Next Futures Contract Year 
The year of the delivery month that defines the next futures contract after the most active. Given as an integer. 
2019 
MM_NEXT 
Next Futures Contract Month 
The delivery month that defines the next futures contract after the most active, given as an integer. 
12 
F_VOLUME_NEXT 
Next Futures Contract Volume 
Total volume traded and settled on the business day in the next futures contract after the most active. Includes CME Globex volume, floor volume (where it exists), and EFRP (exchange for a related position). Total volume also includes PNT (privately negotiated trades) that are cleared through CME Clearing. 
19066 
F_VOLUME 
Total Futures Volume 
Total futures volume as reported by CME Group for all of the futures contracts for this product. 
2422236 
IMPLIED_VOL 
Representative Implied Volatility 
Representative implied volatility (IVOL) is chosen from the values published by CME Group using the following criteria: furthest expiry with a daily volume greater than 10 lots and a reported delta between 0.45 and 0.55. Of these, the contract with the largest traded volume is chosen, which may be a put or a call. Please note that the MSM intentionally has avoided the use of options contracts that do not trade on a given day even though the exchange is required to publish a settlement price. 
0.0384195 
PUT_VOLUME 
Put Option Volume 
Total put options volume as reported by CME Group for all put options on the given product. 
188522 
CALL_VOLUME 
Call Option Volume 
Total call options volume as reported by CME Group for all call options on the given product. 
156040 
OPTIONS_VOLUME 
Total Option Volume 
Total options volume as reported by CME Group. This is the sum of the total put and total call volumes on the given product. 
344562 
PUT_OI 
Put Option Open Interest 
Total put options open interest as reported by CME Group on the given product. 
2028681 
CALL_OI 
Call Option Open Interest 
Total call options open interest as reported by CME Group on the given product. 
1214521 
O_OI 
Total Option Open Interest 
Total options open interest as reported by CME Group. This is the sum of the total put and total call options open interest on the given product. 
3243202 
CURRENT_PRICE_ 
Most Active Futures Current Day Reference Price 
Settlement price for today's most active futures contract taken from today's Trade Date. This is a duplicate of data provided earlier in a preceding column and included here for ease of use. 
127.421875 
PREVIOUS_PRICE_ 
Most Active Futures Previous Day Reference Price 
Settlement price for today's most active futures contract taken from the previous trading day. 
127.34375 
PRICE_PCT_CHG 
Daily Percent Change in Price using log differences 
The daily percentage change is calculated from today’s price and the previous day's price for the same contract as shown in the preceding two columns. The calculation is the difference in the natural logs, so that for analytical purposes there is symmetry in the calculations for up and down days. 
0.00061331 
EXCESS_RETURN_ 
Excess Return Index (not including return on cash) 
The simple excess return index is calculated without including an estimated riskfree return). Hence, the excess return index does not include any interest that might have been earned in the margin account or by other assets backing the futures position. The excess return index is set to 100 on the Curated Data Start Date of January 3, 2012. For later days, it is calculated from the daily returns, so that it always applies to the most active futures contract (which changes across the rolls). 
111.637441 
IMPLIED_VOL_ST 
ShortTerm Smoothed Implied Volatility 
Smoothing is exponential, i.e. ( today's smoothed IVOL) = k * (today's IVOL) + ( 1k ) * (yesterday's SMOOTHED IVOL), where k = 1/(short term days). Shortterm days are set to 30. 
0.0401246 
IMPLIED_VOL_LT 
LongTerm Smoothed Implied Volatility 
Smoothing is exponential, i.e. ( today's smoothed IVOL) = k * (today's IVOL) + ( 1k ) * (yesterday's SMOOTHED IVOL), where k = 1/(long term days). Longterm days are set to 200. 
0.03905877 
DAILY_VARIANCE 
Daily Variance Proxy 
The daily variance proxy is the square of the daily percent change in price. 
3.7615E07 
HISTORICAL_STD_ST 
ShortTerm Smoothed Historical Standard Deviation 
The shortterm smoothed historical standard deviation is computed by exponential smoothing of the daily variance proxy with a time constant of 30 days, then taking the square root, and then annualizing the value. 
0.03670488 
HISTORICAL_STD_LT 
LongTerm Smoothed Historical Standard Deviation 
The longterm smoothed historical standard deviation is computed by exponential smoothing of the daily variance proxy with a time constant of 200 days, then taking the square root, and then annualizing the value. 
0.03734958 
RATIO_STD_ST_LT 
Ratio of ShortTerm to LongTerm Smoothed Standard Deviation 
The ratio of the shortterm smoothed historical standard deviation to the longterm smoothed historical standard deviation, as defined above. 
0.98273881 
RATIO_STD_ST_ 
Ratio of ShortTerm HISTORICAL STD DEV to Current Implied Volatility 
The ratio of the shortterm smoothed historical standard deviation to the implied volatility of the underlying futures product, computed from the most distant but still actively traded near the money options (See representative implied volatility above). 
0.95537118 
RATIO_HIGH_LOW_PCT 
High Price to Low Price Ratio as Percent Spread 
High price minus the low price, divided by the low price. For the most active futures contract. Computed as a difference of logs. 
0.00539812 
HIGH_LOW_PCT_ST 
ShortTerm Smoothed HighLow Percentage Spread 
Same as other short term smoothed data. Exponentially smoothed with a time constant of 30 days. 
0.00394707 
HIGH_LOW_PCT_LT 
LongTerm Smoothed HighLow Percentage Spread 
Same as other long term smoothed data. Exponentially smoothed with a time constant of 200 days. 
0.00371019 
RATIO_HIGH_LOW_ST_LT 
Ratio of ShortTerm Smoothed to LongTerm Smoothed HighLow Percentage Spread 
The ratio of the shortterm smoothed highlow spread to the longterm smoothed highlow spread. 
1.06384468 
PUT_VOLUME_ST 
ShortTerm Smoothed Put Option Volume 
Same as other short term smoothed data. Exponentially smoothed with a time constant of 30 days. 
252056.728 
PUT_VOLUME_LT 
LongTerm Smoothed Put Option Volume 
Same as other long term smoothed data. Exponentially smoothed with a time constant of 200 days. 
236591.061 
RATIO_PUT_ 
Ratio of ShortTerm Smoothed to LongTerm Smoothed Put Option Volume 
The ratio of the shortterm smoothed put option volume to the longterm smoothed put option volume. 
1.06536877 
CALL_VOLUME_ST 
ShortTerm Smoothed Call Option Volume 
Same as other short term smoothed data. Exponentially smoothed with a time constant of 30 days. 
213453.891 
CALL_VOLUME_LT 
LongTerm Smoothed Call Option Volume 
Same as other long term smoothed data. Exponentially smoothed with a time constant of 200 days. 
246498.25 
RATIO_CALL_ 
Ratio of ShortTerm to LongTerm Smoothed Call Option Volume 
The ratio of the shortterm smoothed call option volume to the longterm smoothed call option volume. 
0.86594485 
RATIO_PUT_CALL_ 
Ratio of ShortTerm Smoothed Put Option Volume to Short Term Smoothed Call Option Volume 
The ratio of ShortTerm Smoothed Put Option Volume to the ShortTerm Smoothed Call Option Volume. 
1.1808486 
RATIO_PUT_CALL_ 
Ratio of LongTerm Smoothed Put Option Volume to LongTerm Smoothed Call Option Volume 
The ratio of LongTerm Smoothed Put Option Volume to the LongTerm Smoothed Call Option Volume. 
0.95980828 
PCT_DIF_PUT_CALL_ST_LT_RATIO 
Percentage Difference ShortTerm to LongTerm Ratio of Put to Call Volume 
The percentage difference between the shortterm and longterm ratios for put to call option volume. 
0.22104032 
MOMENTUM_ST 
ShortTerm Smoothed Return Momentum Annualized 
The singleday return momentum is defined as the percent change in price, computed as a difference of natural logs. The shortterm smoothed return momentum is the exponentiallysmoothed average of these percent changes, with a time constant of 30 days. 
0.0535291 
MOMENTUM_LT 
LongTerm Smoothed Return Momentum Annualized 
The singleday return momentum is defined as the percent change in price, computed as a difference of natural logs. The longterm smoothed return momentum is the exponentiallysmoothed average of these percent changes, with a time constant of 200 days. 
0.04251305 
RATIO_MOMENTUM_ST_LT 
Ratio of ShortTerm to LongTerm Smoothed Return Momentum 
Ratio of shortterm to longterm return momentum. 
1.25912144 
RATIO_MOMENTUM_TO_STD_ST 
Ratio of ShortTerm Return Momentum to ShortTerm Standard Deviation 
Ratio of shortterm momentum to shortterm historical standard deviation. This is a proxy for a signal to noise ratio, such as an information ratio or Sharpe Ratio. 
1.45836447 
RATIO_MOMENTUM_TO_STD_LT 
Ratio of LongTerm Return Momentum to LongTerm Standard Deviation 
Ratio of longterm momentum to longterm historical standard deviation. This is a proxy for a signal to noise ratio, such as an information ratio or Sharpe Ratio. 
1.13824713 
PRICE_20D_MA 
20Day Price Moving Average 
Moving average of most active settlement prices for last 20 trading days. Please note that moving averages equally weight each day, while exponential smoothing gives more weight to more recent observations. For analytical purposes, we use exponential smoothing. Moving averages are provided for comparison purposes. 
127.392969 
PRICE_60D_MA 
60Day Price Moving Average 
Moving average of most active settlement prices for last 60 trading days. Please note that moving averages equally weight each day, while exponential smoothing gives more weight to more recent observations. For analytical purposes, we use exponential smoothing. Moving averages are provided for comparison purposes. 
126.614583 
PRICE_200D_MA 
200Day Price Moving Average 
Moving average of most active settlement prices for last 200 trading days. Please note that moving averages equally weight each day, while exponential smoothing gives more weight to more recent observations. For analytical purposes, we use exponential smoothing. Moving averages are provided for comparison purposes. 
122.968516 
PCT_DIF_CURRENT_ 
Percentage Difference Current Price to 200Day Moving Average 
Percentage difference between the current price and the 200day moving average. 
0.03621544 
PCT_DIF_20D_200D_ 
Percentage Difference 20Day Price Moving Average to 200Day Price Moving Average 
Percentage difference between the 20day and the 200day moving average. 
0.03598037 
PEAK_PRICE 
Peak price from Jan2012 to current 
Peak price since the inception of this data set on 3 January 2012. 
135.265625 
PEAK_200D_PRICE 
Peak Price of Nearby Futures in Last 200 Days 
Peak price occurring in the previous 200 days. 
128.25 
20PCT_BELOW_PEAK_200D 
Price level 20 pct below peak price in last 200business days 
Price level that would be 20 percent below the peak price of the last 200 days. 
102.6 
20PCT_ABOVE_ 
Price level 20 pct above 60business day moving average 
Price level that would be 20 percent above the moving price average for the last 60 days. 
151.9375 
20PCT_BELOW_ 
Price level 20 pct Below 60day moving average of price level 
Price level that would be 20 percent below the moving price average for the last 60 days. 
101.291667 
MIX_PROB_20PCT_ 
Probability of Rising Above 20 pct above 60business day moving average 
Based on our hypothetical mixture riskreturn distribution, we calculate the probability of the price rising above 20 percent above the 60day moving average. 
6.4892E08 
MIX_PROB_20PCT_ 
Probability of Falling Below 20 pct below 60business day moving average 
Based on our hypothetical mixture riskreturn distribution, we calculate the probability of the price falling below 20 percent below the 60day moving average. 
8.6718E09 
MIX_MEAN 
Mean of Mixture Probability Distribution 
Mean of our hypothetical mixture riskreturn distribution is always set to zero by definition. 
0 
MIX_MEDIAN 
Median of Mixture Probability Distribution 
Median of our hypothetical mixture riskreturn distribution, which may differ from zero when skewness is present in the distribution. 
0.01 
MIX_MODE_1 
Primary Mode of Mixture Probability Distribution 
Primary mode of our hypothetical mixture riskreturn distribution, which may differ from zero when skewness is present in the distribution. 
0.02 
MIX_MODE_2 
Secondary Mode of Mixture Probability Distribution 
Secondary mode of our hypothetical mixture riskreturn distribution, which will occur only when a bimodal distribution is present. Otherwise this field is left blank. 

MIX_STD 
Standard Deviation of Mixture Distribution 
Standard deviation of our hypothetical mixture riskreturn distribution. 
0.03635327 
MIX_STD_LT 
Longterm Smoothed STD of Mixture Distribution 
Longterm smoothed standard deviation of the hypothetical mixture riskreturn distribution. 
0.04002093 
MIX_SKEW 
Skew of Mixture Probability Distribution 
Skewness of our hypothetical mixture riskreturn distribution. 
0.2620422 
MIX_KURTOSIS 
Kurtosis of Mixture Probability Distribution 
Kurtosis of our hypothetical mixture riskreturn distribution. 
2.91840249 
MIX_STATE 
State of Mixture Probability Distribution 
Sentiment state of the riskreturn distribution may be classified as complacent, balanced, anxious, or conflicted (bimodal when event risk is identified). 
Balanced 
MIX_COMPLACENT 
Complacent (1 or 0) 
If the sentiment state is complacent, the value is reported a 1, otherwise zero. This data field is provided for ease in charting when the riskreturn distribution is in this specific state. 
0 
MIX_BALANCED 
Balanced (1 or 0) 
If the sentiment state is balanced, the value is reported a 1, otherwise zero. This data field is provided for ease in charting when the riskreturn distribution is in this specific state. 
1 
MIX_ANXIOUS 
Anxious (1 or 0) 
If the sentiment state is anxious, the value is reported a 1, otherwise zero. This data field is provided for ease in charting when the riskreturn distribution is in this specific state. 
0 
MIX_CONFLICTED 
BiModal (1 or 0) 
If the sentiment state is conflicted, the value is reported a 1, otherwise zero. This data field is provided for ease in charting when the riskreturn distribution is in this specific state. 
0 
MIX_MODALITY 
Single Mode or BiModal 
Reports whether the riskreturn distribution is a singlemode or bimodal distribution. 
Single Mode 
MIX_DISTANCE 
Distance Number of Bins between Modes if Bimodal 
If the riskreturn distribution is bimodal (Conflicted sentiment state), we measure the number of element bins between the modes as one measure of the extent of the bimodality. Reported as an integer. For a singlemode distribution this field is blank. 

MIX_INTENSITY 
Intensity Measurement Index of Height of Second Mode compared to Low Point of Valley in between modes. 
If the riskreturn distribution is bimodal (Conflicted sentiment state), we compute the ratio between the height of the second mode and the lowest value of the distribution between the two modes. For a singlemode distribution this field is blank. 

MIX_LOW_BIN 
Origin for Distribution 
The worst case element bin is minus 100% or 1. 
1 
MIX_BIN_SIZE 
Stepsize for Distribution 
The element bins have a width of 1% or 0.01. 
0.01 
MIX_BINS 
Number of elements in the distribution vector 
We report 256 element bins, from 100% to +155% 
256 
MIX_BIN_NEG_100 
1 
Probability associated with each element bin for the discreet riskreturn probability distribution. Probabilities sum to 100% or 1 over the whole riskreturn distribution from 100% to +155%. Low volatility products will have many zeroes on both ends. High volatility products will have fewer zeroes. 
0 
MIX_BIN_NEG_99 
0.99 
Element bin probability. 
0 
MIX_BIN_NEG_98 
0.98 
Element bin probability. 
0 
MIX_BIN_NEG_97 
0.97 
Element bin probability. 
0 
MIX_BIN_NEG_96 
0.96 
Element bin probability. 
0 
MIX_BIN_NEG_95 
0.95 
Element bin probability. 
0 
MIX_BIN_NEG_94 
0.94 
Element bin probability. 
0 
MIX_BIN_NEG_93 
0.93 
Element bin probability. 
0 
MIX_BIN_NEG_92 
0.92 
Element bin probability. 
0 
MIX_BIN_NEG_91 
0.91 
Element bin probability. 
0 
MIX_BIN_NEG_90 
0.9 
Element bin probability. 
0 
MIX_BIN_NEG_89 
0.89 
Element bin probability. 
0 
MIX_BIN_NEG_88 
0.88 
Element bin probability. 
0 
MIX_BIN_NEG_87 
0.87 
Element bin probability. 
0 
MIX_BIN_NEG_86 
0.86 
Element bin probability. 
0 
MIX_BIN_NEG_85 
0.85 
Element bin probability. 
0 
MIX_BIN_NEG_84 
0.84 
Element bin probability. 
0 
MIX_BIN_NEG_83 
0.83 
Element bin probability. 
0 
MIX_BIN_NEG_82 
0.82 
Element bin probability. 
0 
MIX_BIN_NEG_81 
0.81 
Element bin probability. 
0 
MIX_BIN_NEG_80 
0.8 
Element bin probability. 
0 
MIX_BIN_NEG_79 
0.79 
Element bin probability. 
0 
MIX_BIN_NEG_78 
0.78 
Element bin probability. 
0 
MIX_BIN_NEG_77 
0.77 
Element bin probability. 
0 
MIX_BIN_NEG_76 
0.76 
Element bin probability. 
0 
MIX_BIN_NEG_75 
0.75 
Element bin probability. 
0 
MIX_BIN_NEG_74 
0.74 
Element bin probability. 
0 
MIX_BIN_NEG_73 
0.73 
Element bin probability. 
0 
MIX_BIN_NEG_72 
0.72 
Element bin probability. 
0 
MIX_BIN_NEG_71 
0.71 
Element bin probability. 
0 
MIX_BIN_NEG_70 
0.7 
Element bin probability. 
0 
MIX_BIN_NEG_69 
0.69 
Element bin probability. 
0 
MIX_BIN_NEG_68 
0.68 
Element bin probability. 
0 
MIX_BIN_NEG_67 
0.67 
Element bin probability. 
0 
MIX_BIN_NEG_66 
0.66 
Element bin probability. 
0 
MIX_BIN_NEG_65 
0.65 
Element bin probability. 
0 
MIX_BIN_NEG_64 
0.64 
Element bin probability. 
0 
MIX_BIN_NEG_63 
0.63 
Element bin probability. 
0 
MIX_BIN_NEG_62 
0.62 
Element bin probability. 
0 
MIX_BIN_NEG_61 
0.61 
Element bin probability. 
0 
MIX_BIN_NEG_60 
0.6 
Element bin probability. 
0 
MIX_BIN_NEG_59 
0.59 
Element bin probability. 
0 
MIX_BIN_NEG_58 
0.58 
Element bin probability. 
0 
MIX_BIN_NEG_57 
0.57 
Element bin probability. 
0 
MIX_BIN_NEG_56 
0.56 
Element bin probability. 
0 
MIX_BIN_NEG_55 
0.55 
Element bin probability. 
0 
MIX_BIN_NEG_54 
0.54 
Element bin probability. 
0 
MIX_BIN_NEG_53 
0.53 
Element bin probability. 
0 
MIX_BIN_NEG_52 
0.52 
Element bin probability. 
0 
MIX_BIN_NEG_51 
0.51 
Element bin probability. 
0 
MIX_BIN_NEG_50 
0.5 
Element bin probability. 
0 
MIX_BIN_NEG_49 
0.49 
Element bin probability. 
0 
MIX_BIN_NEG_48 
0.48 
Element bin probability. 
0 
MIX_BIN_NEG_47 
0.47 
Element bin probability. 
0 
MIX_BIN_NEG_46 
0.46 
Element bin probability. 
0 
MIX_BIN_NEG_45 
0.45 
Element bin probability. 
0 
MIX_BIN_NEG_44 
0.44 
Element bin probability. 
0 
MIX_BIN_NEG_43 
0.43 
Element bin probability. 
0 
MIX_BIN_NEG_42 
0.42 
Element bin probability. 
0 
MIX_BIN_NEG_41 
0.41 
Element bin probability. 
0 
MIX_BIN_NEG_40 
0.4 
Element bin probability. 
0 
MIX_BIN_NEG_39 
0.39 
Element bin probability. 
0 
MIX_BIN_NEG_38 
0.38 
Element bin probability. 
0 
MIX_BIN_NEG_37 
0.37 
Element bin probability. 
0 
MIX_BIN_NEG_36 
0.36 
Element bin probability. 
0 
MIX_BIN_NEG_35 
0.35 
Element bin probability. 
0 
MIX_BIN_NEG_34 
0.34 
Element bin probability. 
0 
MIX_BIN_NEG_33 
0.33 
Element bin probability. 
0 
MIX_BIN_NEG_32 
0.32 
Element bin probability. 
0 
MIX_BIN_NEG_31 
0.31 
Element bin probability. 
0 
MIX_BIN_NEG_30 
0.3 
Element bin probability. 
0 
MIX_BIN_NEG_29 
0.29 
Element bin probability. 
0 
MIX_BIN_NEG_28 
0.28 
Element bin probability. 
0 
MIX_BIN_NEG_27 
0.27 
Element bin probability. 
0 
MIX_BIN_NEG_26 
0.26 
Element bin probability. 
0 
MIX_BIN_NEG_25 
0.25 
Element bin probability. 
0 
MIX_BIN_NEG_24 
0.24 
Element bin probability. 
0 
MIX_BIN_NEG_23 
0.23 
Element bin probability. 
0 
MIX_BIN_NEG_22 
0.22 
Element bin probability. 
0 
MIX_BIN_NEG_21 
0.21 
Element bin probability. 
0 
MIX_BIN_NEG_20 
0.2 
Element bin probability. 
0.000001 
MIX_BIN_NEG_19 
0.19 
Element bin probability. 
0.000005 
MIX_BIN_NEG_18 
0.18 
Element bin probability. 
0.000021 
MIX_BIN_NEG_17 
0.17 
Element bin probability. 
0.000082 
MIX_BIN_NEG_16 
0.16 
Element bin probability. 
0.000292 
MIX_BIN_NEG_15 
0.15 
Element bin probability. 
0.000968 
MIX_BIN_NEG_14 
0.14 
Element bin probability. 
0.002983 
MIX_BIN_NEG_13 
0.13 
Element bin probability. 
0.008533 
MIX_BIN_NEG_12 
0.12 
Element bin probability. 
0.022671 
MIX_BIN_NEG_11 
0.11 
Element bin probability. 
0.056021 
MIX_BIN_NEG_10 
0.1 
Element bin probability. 
0.129387 
MIX_BIN_NEG_09 
0.09 
Element bin probability. 
0.283008 
MIX_BIN_NEG_08 
0.08 
Element bin probability. 
0.599353 
MIX_BIN_NEG_07 
0.07 
Element bin probability. 
1.247273 
MIX_BIN_NEG_06 
0.06 
Element bin probability. 
2.499117 
MIX_BIN_NEG_05 
0.05 
Element bin probability. 
4.565155 
MIX_BIN_NEG_04 
0.04 
Element bin probability. 
7.201409 
MIX_BIN_NEG_03 
0.03 
Element bin probability. 
9.554258 
MIX_BIN_NEG_02 
0.02 
Element bin probability. 
10.761779 
MIX_BIN_NEG_01 
0.01 
Element bin probability. 
10.742357 
MIX_BIN_POS_00 
0 
Element bin probability. 
10.081583 
MIX_BIN_POS_01 
0.01 
Element bin probability. 
9.25683 
MIX_BIN_POS_02 
0.02 
Element bin probability. 
8.31102 
MIX_BIN_POS_03 
0.03 
Element bin probability. 
7.137581 
MIX_BIN_POS_04 
0.04 
Element bin probability. 
5.758253 
MIX_BIN_POS_05 
0.05 
Element bin probability. 
4.327795 
MIX_BIN_POS_06 
0.06 
Element bin probability. 
3.022312 
MIX_BIN_POS_07 
0.07 
Element bin probability. 
1.959933 
MIX_BIN_POS_08 
0.08 
Element bin probability. 
1.180115 
MIX_BIN_POS_09 
0.09 
Element bin probability. 
0.659754 
MIX_BIN_POS_10 
0.1 
Element bin probability. 
0.342463 
MIX_BIN_POS_11 
0.11 
Element bin probability. 
0.165052 
MIX_BIN_POS_12 
0.12 
Element bin probability. 
0.073858 
MIX_BIN_POS_13 
0.13 
Element bin probability. 
0.030687 
MIX_BIN_POS_14 
0.14 
Element bin probability. 
0.011838 
MIX_BIN_POS_15 
0.15 
Element bin probability. 
0.00424 
MIX_BIN_POS_16 
0.16 
Element bin probability. 
0.00141 
MIX_BIN_POS_17 
0.17 
Element bin probability. 
0.000435 
MIX_BIN_POS_18 
0.18 
Element bin probability. 
0.000125 
MIX_BIN_POS_19 
0.19 
Element bin probability. 
0.000033 
MIX_BIN_POS_20 
0.2 
Element bin probability. 
0.000008 
MIX_BIN_POS_21 
0.21 
Element bin probability. 
0.000002 
MIX_BIN_POS_22 
0.22 
Element bin probability. 
0 
MIX_BIN_POS_23 
0.23 
Element bin probability. 
0 
MIX_BIN_POS_24 
0.24 
Element bin probability. 
0 
MIX_BIN_POS_25 
0.25 
Element bin probability. 
0 
MIX_BIN_POS_26 
0.26 
Element bin probability. 
0 
MIX_BIN_POS_27 
0.27 
Element bin probability. 
0 
MIX_BIN_POS_28 
0.28 
Element bin probability. 
0 
MIX_BIN_POS_29 
0.29 
Element bin probability. 
0 
MIX_BIN_POS_30 
0.3 
Element bin probability. 
0 
MIX_BIN_POS_31 
0.31 
Element bin probability. 
0 
MIX_BIN_POS_32 
0.32 
Element bin probability. 
0 
MIX_BIN_POS_33 
0.33 
Element bin probability. 
0 
MIX_BIN_POS_34 
0.34 
Element bin probability. 
0 
MIX_BIN_POS_35 
0.35 
Element bin probability. 
0 
MIX_BIN_POS_36 
0.36 
Element bin probability. 
0 
MIX_BIN_POS_37 
0.37 
Element bin probability. 
0 
MIX_BIN_POS_38 
0.38 
Element bin probability. 
0 
MIX_BIN_POS_39 
0.39 
Element bin probability. 
0 
MIX_BIN_POS_40 
0.4 
Element bin probability. 
0 
MIX_BIN_POS_41 
0.41 
Element bin probability. 
0 
MIX_BIN_POS_42 
0.42 
Element bin probability. 
0 
MIX_BIN_POS_43 
0.43 
Element bin probability. 
0 
MIX_BIN_POS_44 
0.44 
Element bin probability. 
0 
MIX_BIN_POS_45 
0.45 
Element bin probability. 
0 
MIX_BIN_POS_46 
0.46 
Element bin probability. 
0 
MIX_BIN_POS_47 
0.47 
Element bin probability. 
0 
MIX_BIN_POS_48 
0.48 
Element bin probability. 
0 
MIX_BIN_POS_49 
0.49 
Element bin probability. 
0 
MIX_BIN_POS_50 
0.5 
Element bin probability. 
0 
MIX_BIN_POS_51 
0.51 
Element bin probability. 
0 
MIX_BIN_POS_52 
0.52 
Element bin probability. 
0 
MIX_BIN_POS_53 
0.53 
Element bin probability. 
0 
MIX_BIN_POS_54 
0.54 
Element bin probability. 
0 
MIX_BIN_POS_55 
0.55 
Element bin probability. 
0 
MIX_BIN_POS_56 
0.56 
Element bin probability. 
0 
MIX_BIN_POS_57 
0.57 
Element bin probability. 
0 
MIX_BIN_POS_58 
0.58 
Element bin probability. 
0 
MIX_BIN_POS_59 
0.59 
Element bin probability. 
0 
MIX_BIN_POS_60 
0.6 
Element bin probability. 
0 
MIX_BIN_POS_61 
0.61 
Element bin probability. 
0 
MIX_BIN_POS_62 
0.62 
Element bin probability. 
0 
MIX_BIN_POS_63 
0.63 
Element bin probability. 
0 
MIX_BIN_POS_64 
0.64 
Element bin probability. 
0 
MIX_BIN_POS_65 
0.65 
Element bin probability. 
0 
MIX_BIN_POS_66 
0.66 
Element bin probability. 
0 
MIX_BIN_POS_67 
0.67 
Element bin probability. 
0 
MIX_BIN_POS_68 
0.68 
Element bin probability. 
0 
MIX_BIN_POS_69 
0.69 
Element bin probability. 
0 
MIX_BIN_POS_70 
0.7 
Element bin probability. 
0 
MIX_BIN_POS_71 
0.71 
Element bin probability. 
0 
MIX_BIN_POS_72 
0.72 
Element bin probability. 
0 
MIX_BIN_POS_73 
0.73 
Element bin probability. 
0 
MIX_BIN_POS_74 
0.74 
Element bin probability. 
0 
MIX_BIN_POS_75 
0.75 
Element bin probability. 
0 
MIX_BIN_POS_76 
0.76 
Element bin probability. 
0 
MIX_BIN_POS_77 
0.77 
Element bin probability. 
0 
MIX_BIN_POS_78 
0.78 
Element bin probability. 
0 
MIX_BIN_POS_79 
0.79 
Element bin probability. 
0 
MIX_BIN_POS_80 
0.8 
Element bin probability. 
0 
MIX_BIN_POS_81 
0.81 
Element bin probability. 
0 
MIX_BIN_POS_82 
0.82 
Element bin probability. 
0 
MIX_BIN_POS_83 
0.83 
Element bin probability. 
0 
MIX_BIN_POS_84 
0.84 
Element bin probability. 
0 
MIX_BIN_POS_85 
0.85 
Element bin probability. 
0 
MIX_BIN_POS_86 
0.86 
Element bin probability. 
0 
MIX_BIN_POS_87 
0.87 
Element bin probability. 
0 
MIX_BIN_POS_88 
0.88 
Element bin probability. 
0 
MIX_BIN_POS_89 
0.89 
Element bin probability. 
0 
MIX_BIN_POS_90 
0.9 
Element bin probability. 
0 
MIX_BIN_POS_91 
0.91 
Element bin probability. 
0 
MIX_BIN_POS_92 
0.92 
Element bin probability. 
0 
MIX_BIN_POS_93 
0.93 
Element bin probability. 
0 
MIX_BIN_POS_94 
0.94 
Element bin probability. 
0 
MIX_BIN_POS_95 
0.95 
Element bin probability. 
0 
MIX_BIN_POS_96 
0.96 
Element bin probability. 
0 
MIX_BIN_POS_97 
0.97 
Element bin probability. 
0 
MIX_BIN_POS_98 
0.98 
Element bin probability. 
0 
MIX_BIN_POS_99 
0.99 
Element bin probability. 
0 
MIX_BIN_POS_100 
1 
Element bin probability. 
0 
MIX_BIN_POS_101 
1.01 
Element bin probability. 
0 
MIX_BIN_POS_102 
1.02 
Element bin probability. 
0 
MIX_BIN_POS_103 
1.03 
Element bin probability. 
0 
MIX_BIN_POS_104 
1.04 
Element bin probability. 
0 
MIX_BIN_POS_105 
1.05 
Element bin probability. 
0 
MIX_BIN_POS_106 
1.06 
Element bin probability. 
0 
MIX_BIN_POS_107 
1.07 
Element bin probability. 
0 
MIX_BIN_POS_108 
1.08 
Element bin probability. 
0 
MIX_BIN_POS_109 
1.09 
Element bin probability. 
0 
MIX_BIN_POS_110 
1.1 
Element bin probability. 
0 
MIX_BIN_POS_111 
1.11 
Element bin probability. 
0 
MIX_BIN_POS_112 
1.12 
Element bin probability. 
0 
MIX_BIN_POS_113 
1.13 
Element bin probability. 
0 
MIX_BIN_POS_114 
1.14 
Element bin probability. 
0 
MIX_BIN_POS_115 
1.15 
Element bin probability. 
0 
MIX_BIN_POS_116 
1.16 
Element bin probability. 
0 
MIX_BIN_POS_117 
1.17 
Element bin probability. 
0 
MIX_BIN_POS_118 
1.18 
Element bin probability. 
0 
MIX_BIN_POS_119 
1.19 
Element bin probability. 
0 
MIX_BIN_POS_120 
1.2 
Element bin probability. 
0 
MIX_BIN_POS_121 
1.21 
Element bin probability. 
0 
MIX_BIN_POS_122 
1.22 
Element bin probability. 
0 
MIX_BIN_POS_123 
1.23 
Element bin probability. 
0 
MIX_BIN_POS_124 
1.24 
Element bin probability. 
0 
MIX_BIN_POS_125 
1.25 
Element bin probability. 
0 
MIX_BIN_POS_126 
1.26 
Element bin probability. 
0 
MIX_BIN_POS_127 
1.27 
Element bin probability. 
0 
MIX_BIN_POS_128 
1.28 
Element bin probability. 
0 
MIX_BIN_POS_129 
1.29 
Element bin probability. 
0 
MIX_BIN_POS_130 
1.3 
Element bin probability. 
0 
MIX_BIN_POS_131 
1.31 
Element bin probability. 
0 
MIX_BIN_POS_132 
1.32 
Element bin probability. 
0 
MIX_BIN_POS_133 
1.33 
Element bin probability. 
0 
MIX_BIN_POS_134 
1.34 
Element bin probability. 
0 
MIX_BIN_POS_135 
1.35 
Element bin probability. 
0 
MIX_BIN_POS_136 
1.36 
Element bin probability. 
0 
MIX_BIN_POS_137 
1.37 
Element bin probability. 
0 
MIX_BIN_POS_138 
1.38 
Element bin probability. 
0 
MIX_BIN_POS_139 
1.39 
Element bin probability. 
0 
MIX_BIN_POS_140 
1.4 
Element bin probability. 
0 
MIX_BIN_POS_141 
1.41 
Element bin probability. 
0 
MIX_BIN_POS_142 
1.42 
Element bin probability. 
0 
MIX_BIN_POS_143 
1.43 
Element bin probability. 
0 
MIX_BIN_POS_144 
1.44 
Element bin probability. 
0 
MIX_BIN_POS_145 
1.45 
Element bin probability. 
0 
MIX_BIN_POS_146 
1.46 
Element bin probability. 
0 
MIX_BIN_POS_147 
1.47 
Element bin probability. 
0 
MIX_BIN_POS_148 
1.48 
Element bin probability. 
0 
MIX_BIN_POS_149 
1.49 
Element bin probability. 
0 
MIX_BIN_POS_150 
1.5 
Element bin probability. 
0 
MIX_BIN_POS_151 
1.51 
Element bin probability. 
0 
MIX_BIN_POS_152 
1.52 
Element bin probability. 
0 
MIX_BIN_POS_153 
1.53 
Element bin probability. 
0 
MIX_BIN_POS_154 
1.54 
Element bin probability. 
0 
MIX_BIN_POS_155 
1.55 
Element bin probability. 
0 