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.
Prices, volumes and intraday activity in futures and options markets are taken to represent the risks perceived by market participants and based on their observed actions. 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 7 MB to 13 MB. This depends on the number of zeros in the file, which are represented by “0”, as opposed to the standard 9digit precision.
The Curated Data File for each product is updated after each trading day. There are currently eight products available.
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 has been arbitrarily set at 30 and for longterm smoothing is set at 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.
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.
The riskreturn probability distribution is a proprietary process using a mixture distribution method. See our related research papers for more indepth explanations.
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 
Description 
Typical Value 

BizDate 
Business date for the settlement price and other data reported on this row. In general, this will be the last trading date. Expressed as a string. 
2018Oct23 
Y 
YEAR of the business date, as an integer 
2018 
M 
MONTH of the business date, as an integer 
10 
D 
DAY of the business date, as an integer 
23 
Futures Product Code 
Product code used by CME DataMine for the futures contract, in upper case 
TYF 
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 FX (USD per EUR). The original option code 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 business date. 
TC 
Nearby Futures Settlement Price 
The nearby future is the futures contract with the largest daily volume. When trading “rolls” from one expiry to the next, the nearby future moves as soon as the next expiry has a larger volume and does not move back. 
118.265625 
Nearby Futures High Price 
CME Globex High price as published by CME Group in the EOD settlement P File. For the nearby futures contract. 
118.65625 
Nearby Futures Low Price 
CME Globex Low price as published by CME Group in the EOD settlement P File. For the nearby futures contract. 
117.96875 
Nearby Futures Contract Year 
The year of the delivery month that defines the nearby futures contract. Given as an integer. For example, the SH19 (March 2019) Soybean future has a contract year of 2019. 
2018 
Nearby Futures Contract Month 
The delivery month that defines the nearby futures contract. Given as an integer. For example, the SH19 (March 2019) Soybean future has a contract month of 3. 
12 
Nearby Futures Contract Volume 
Total volume traded and settled on the business day in the nearby future. Includes CME Globex volume, floor volume (where it exists), EFRP (exchange for a related position). Total volume also includes PNT (privately negotiated trades) that are cleared through CME Clearing. 
2923885 
Second Futures Settlement Price 
The second future is the most actively traded futures contract with a date after the nearby future 
118 
Second Futures High Price 
Same definition as for the corresponding nearby futures contract, but for the second future 
118.375 
Second Futures Low Price 
Same definition as for the corresponding nearby futures contract, but for the second future 
117.78125 
Second Futures Contract Year 
Same definition as for the corresponding nearby futures contract, but for the second future 
2019 
Second Futures Contract Month 
Same definition as for the corresponding nearby futures contract, but for the second future 
3 
Second Futures Contract Volume 
Same definition as for the corresponding nearby futures contract, but for the second future 
13050 
Total Futures Volume 
Total futures volume as reported by CME Group 
2936935 
Representative Implied Volatility 
Representative 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. 
0.0377374 
Year of Implied Volatility Contract 
Year of the delivery month date for the selected options contract. The delivery month for an options contract is typically the same as the delivery month for its underlying futures contract. 
2019 
Month of Implied Volatility Contract 
Delivery month for the selected options contract 
3 
Put Option Volume 
Total put options volume as reported by CME Group 
435889 
Call Option Volume 
Total call options volume as reported by CME Group 
964321 
Total Option Volume 
Total options volume as reported by CME Group. This is the sum of the total put and total call volumes. 
1400210 
Put Option Open Interest 
Total put options open interest as reported by CME Group 
2158047 
Call Option Open Interest 
Total call options open interest as reported by CME Group 
2145525 
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. 
4303572 
Nearby Futures Previous Day Reference Price 
Settlement price for today's nearby futures contract on the previous trading day. 
118 
Daily Percent Change in Price 
Ratio calculated as the difference of natural logs 
0.002248529 
Excess Return Index 
The simple return index (i.e. without subtracting an estimated riskfree return). The index is set to 1.0 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 nearby futures contract (which changes across the rolls). 
1.4733518461 
ShortTerm Smoothed Implied Volatility 
Smoothing is exponential, i.e. (today’s smoothed IVOL) = k * (today's IVOL) + ( k1 ) * (yesterday's SMOOTHED IVOL), where k = 1/(short term days).
The number of days for shortterm smoothing is 30. 
0.036760346 
LongTerm Smoothed Implied Volatility 
Same as short term smoothing, except with a scale factor of 200 days. 
0.040106398 
Daily Variance Proxy 
The daily variance proxy is the square of the daily percent change in price. 
5.05588E06 
ShortTerm Smoothed Historical Standard Deviation 
The shortterm smoothed historical standard deviation is computed by smoothing the daily variance proxy with a time constant of 30 days, and then taking the square root. The value in the file is annualized. 
0.032103478 
LongTerm Smoothed Historical Standard Deviation 
The longterm smoothed historical standard deviation is computed by exponentially smoothing the daily variance proxy with a time constant of 200 days, and then taking the square root. The value in the file is annualized. 
0.066664962 
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. 
0.48156449 
Ratio of ShortTerm HISTORICAL STD DEV to Current Implied Volatility 
The ratio of the shortterm smoothed historical standard deviation the implied volatility of the underlying futures product, computed from the most distant but still actively traded options. 
0.850707209 
High Price to Low Price Ratio as Percent Spread 
High price minus the low price, divided by the low price. For the nearby futures contract. Computed as a difference of logs. 
0.005810899 
ShortTerm Smoothed HighLow Percentage Spread 
Same as other short term smoothed data. Exponentially smoothed with a time constant of 30 days. 
0.003180144 
LongTerm Smoothed HighLow Percentage Spread 
Same as other long term smoothed data. Exponentially smoothed with a time constant of 200 days. 
0.00355142 
Ratio of ShortTerm Smoothed to LongTerm Smoothed HighLow Percentage Spread 
The ratio of the shortterm smoothed highlow percentage spread to the longterm highlow percentage spread. Indicates when a change in the highlow percentage spread has been sustained for some time. 
0.895457119 
ShortTerm Smoothed Put Option Volume 
Same as other short term smoothed data. Exponentially smoothed Put Option Volume with a time constant of 30 days. 
270539.8194 
LongTerm Smoothed Put Option Volume 
Same as other long term smoothed data. Exponentially smoothed Put Option Volume with a time constant of 200 days. 
233339.6376 
Ratio of ShortTerm Smoothed to LongTerm Smoothed Put Option Volume 
The ratio of ShortTerm Smoothed Put Option Volume to the LongTerm Smoothed Put Option Volume. Indicates when a change in the put option volume has been sustained for some time. 
1.159425043 
ShortTerm Smoothed Call Option Volume 
Same as other short term smoothed data. Exponentially smoothed Call Option Volume with a time constant of 30 days. 
254917.8039 
LongTerm Smoothed Call Option Volume 
Same as other long term smoothed data. Exponentially smoothed Call Option Volume with a time constant of 200 days. 
223050.7492 
Ratio of ShortTerm to LongTerm Smoothed Call Option Volume 
The ratio of ShortTerm Smoothed Call Option Volume to the LongTerm Smoothed Call Option Volume. Indicates when a change in the Call Option Volume has been sustained for some time. 
1.142869077 
Ratio of ShortTerm Smoothed Put Option Volume to Short Term Smoothed Call Option Volume 
Puttocall ratio using shortterm exponentially smoothed volumes. The ratio of the of ShortTerm Smoothed Put Option Volume to the ShortTerm Smoothed Call Option Volume. 
1.06128256 
Ratio of LongTerm Smoothed Put Option Volume to LongTerm Smoothed Call Option Volume 
Puttocall ratio using longterm exponentially smoothed volumes. The ratio of the of LongTerm Smoothed Put Option Volume to the LongTerm Smoothed Call Option Volume. 
1.046128015 
Percentage Difference ShortTerm to LongTerm Ratio of Put to Call Volume 
Difference in percentage points between the shortterm smoothed puttocall ratio and the longterm puttocall ratio. 
0.015154544 
ShortTerm Smoothed Return Momentum 
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. 
0.000180041 
LongTerm Smoothed Return Momentum 
The longterm smoothed return momentum is the exponentiallysmoothed average singleday return momentum with a time constant of 200 days. 
0.000121053 
Ratio of ShortTerm to LongTerm Smoothed Return Momentum 
The ratio of the short term (30d) smoothed return momentum to the longterm (200d) smoothed return momentum. 
1.487289033 
Ratio of ShortTerm Return Momentum to ShortTerm Standard Deviation 
Ratio of the short term smoothed return momentum to the short term smoothed standard deviation. Provides a measure of how much the price of the nearby future has changed as opposed to simply moving around over the most recent 30day period (the time constant for shortterm smoothing) 
0.005608151 
Ratio of LongTerm Return Momentum to LongTerm Standard Deviation 
Ratio of the long term smoothed return momentum to the long term smoothed standard deviation. Provides a measure of how much the price of the nearby future has changed, as opposed to simply moving around over the 200day period associated with long term smoothing 
0.001815845 
20Day Price Moving Average 
Average settlement price for the nearby future over a 20day window, i.e. today's business date and the previous 19 business dates. 
118.209375 
60Day Price Moving Average 
Average settlement price for the nearby future over a 60day window. 
119.2205729 
200Day Price Moving Average 
Average settlement price for the nearby future over a 200day window. 
120.0017969 
Percentage Difference Current Price to 200Day Moving Average 
Ratio of today’s nearby futures contract settlement price to the 200day moving average. 
0.985532118 
Percentage Difference 20Day Price Moving Average to 200Day Price Moving Average 
Ratio of the 20day moving average to the 200 day moving average. 
0.985063375 
Peak price over total period 
Highest nearby futures contract settlement since January 3, 2012. 
135.265625 
Peak Price of Nearby Futures in Last 200 Days 
Highest nearby futures contract settlement price in the last 200 days, including today. 
123.125 
20 pct below peak price in last 200business days 
A reference price level calculated from the peak price in the last 200 days. 
98.5 
20 pct above 60business day moving average 
A reference price level calculated from the 60day moving average, for upward movements. 
143.0646875 
Target 1 Nearest round number around 20 pct above 60business day moving average 
A reference price level for upward movement, calculated from the 60day average, but rounded heuristically to a number that is easy to grasp, and expected to remain constant over a period of time, as might be used in media commentary. 
145.0 
Target 2 Nearest round number around 20 pct below 60business day moving average 
A reference price level for downward movement, calculated from the 60day average, but rounded heuristically to a number that is easy to grasp, and expected to remain constant over a period of time, as might be used in media commentary. 
95.0 
20 pct Below 60day moving average of price level 
A reference price level calculated from the 60day moving average, for downward movements. 
95.37645833 
One 504Day Standard Deviation Above the Mean 
The "mean" here is the mean of the 504 most recent values for the Mean of the Mixture Probability Distribution (2 year’s worth). The current model fixes the mean at 0.0, which effectively fixes its standard deviation at zero. 
0.0 
One 504Day Standard Deviation Below the Mean 
The current model fixes this field to zero. 
0.0 
Kurtosis 504Day Moving Average 
The kurtosis (fourth moment) of the Mixture Probability Distribution is taken at the 504 most recent business dates (including today) and averaged. 
3.198579951 
Kurtosis 504Day Standard Deviation 
The kurtosis (fourth moment) of the Mixture Probability Distribution is taken at the 504 most recent business dates (including today). The standard deviation is then calculated for these 504 samples. 
0.325183199 
Skewness 504Day Moving Average 
The skewness (third moment) of the Mixture Probability Distribution is taken at the 504 most recent business dates (including today) and averaged. 
0.005028247 
Skewness 504Day Standard Deviation 
The skewness (third moment) of the Mixture Probability Distribution is taken at the 504 most recent business dates (including today). The standard deviation is then calculated for these 504 samples. 
0.120287122 
Probability of Rising Above 20 pct above 60business day moving average 
Calculated using today's Mixture Probability Distribution. The price value for 20 % above the 60 day 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.

1.30943E08 
Probability of Rising Above Target 1 (up) 
Calculated using today's Mixture Probability Distribution, but with the rounded price target instead of the pure +20%. The rounding is typically away from the current price, so the probability will be smaller. The price value target 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. 
1.3E08 
Probability of Falling Below Target 2 (down) 
Calculated using today's Mixture Probability Distribution, but with the rounded downward price movement target instead of the pure minus 20%. The rounding is typically away from the current price, so the probability will be smaller. The price value target 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. 
2.0E07 
Probability of Falling Below 20 pct below 60business day moving average 
Calculated using today's Mixture Probability Distribution. The price value for 20 % above the 60 day 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. 
2.09266E07 
Mean of Mixture Probability Distribution 
Computed according to the model. At present, this value is fixed to zero in the calculations. 
0.0 
Median of Mixture Probability Distribution 
The median of a distribution is the point on the horizontal axis where the area to the left is the same as the area to the right. This is computed from the vector representation of the distribution by integrating numerically until the accumulated sum is 0.5. 
0.01 
Primary Mode of Mixture Probability Distribution 
A mode of a distribution is a point on the horizontal where the distribution has a local maximum. The riskreturn probability distribution may have one or two modes. The primary mode is the first mode encountered in iterating along the vector representation of the distribution. 
0.0 
Secondary Mode of Mixture Probability Distribution 
If the distribution is bimodal, this will be the location of the second peak. 
0.0 
Skew of Mixture Probability Distribution 
The third moment of riskreturn probability distribution. 
0.022213535 
Kurtosis of Mixture Probability Distribution 
The fourth moment of riskreturn probability distribution. 
3.37197243 
State of Mixture Probability Distribution 
The state is determined by comparing the standard deviation of today’s Mixture Probability Distribution with thresholds computed from a rolling 252day window of standard deviations. The upper threshold is for wide, and the lower threshold is for narrow.
Current state definitions include Complacent, Balanced, Anxious and Event Risk, a.k.a. BiModal or BiPolar. 
Balanced 
Risk Index 
To be defined. 
0.0 
Origin for Distribution 
1.00 
1 
Stepsize for Distribution 
0.01 
0.01 
Number of elements in the distribution vector 
Currently 256 
256 
0.01 
Column headers run from 0.01 to +1.55. The data for any one business day represents the Mixture Probability. 
0 
0.99 
Computed values that differ from zero by small amounts, currently 0.000000001 (the 9th decimal place), are forced to zero. 
0 
0.98 
Data is scaled so that the vector will integrate numerically to unity. If the distribution is very wide and the tails are chopped off, then the data points in the interval are puffed up slightly to compensate. 
0 
. . . 
varies 

1.53 
0 

1.54 
0 

1.55 
0 