creamyyy 

So this isn't strictly to do with market depth, but I've discovered a major discrepancy between the two data feeds today which has me questioning which one is correct. This is the CL open today 3rd February 2023 from approx. 8AM - 10AM central time. Left is Motivewave running Rithmic non-aggregated data. Right is SC + Denali. The bottom of both platforms is the cumulative delta. SC is using the cumulative delta - trades indicator. As you can see, Motivewave/Rithmic is showing positive delta on the way up, SC/Denali is showing negative delta. When I check the footprints on both on a random bar, the bids and asks and delta totals all add up on both. When I compare the two feeds over the past few days, at a cursory glance, they're pretty much the same. The fact that both are showing pretty much opposites of each other has me scratching my head. Anyone else care to check and chime in? SCR-20230204-1p7

FWIW, this is what my system calculated. Deltas in this view reset at session open (5 PM central). This is for the CLH3 contract.
CD (Trade Count)


CD (Trade Volume)


Bid/Ask Delta (Trade Count)


Bid/Ask Delta (Trade Volume)

artemiso 

I'm not familiar with "cumulative delta" but gave it a shot. It should be negative. Values below differ because your start time and mine were different (I used exactly 08:00 CT, I think your cumulative sum started around 09:00+). I tried 00:00 UTC and got a similar negative curve in any case. Python script below in case you want to try.   Code import databento as db import pandas as pd import matplotlib.pyplot as plt plt.style.use('ggplot') client = db.Historical(key='YOUR_API_KEY') data = client.timeseries.stream(dataset='GLBX.MDP3', schema='trades', stype_in='smart', # use smart lead month symbol symbols=['CL.v.0'], # lead month CL by volume start='2023-02-03', end='2023-02-04') # Convert to dataframe with UNIX timestamps and display prices df = data.to_df(pretty_ts=False, pretty_px=True) # Convert UNIX timestamps to US Central Time df.index = pd.to_datetime(df.index).tz_localize('UTC').tz_convert('America/Chicago') df['signed_vol'] = df['side'].apply(lambda s: 1 if s == 'B' else -1) * df['size'] df = df.between_time('08:00', '10:00') df['cumulative_delta'] = df['signed_vol'].cumsum() plt.plot(df['cumulative_delta']) plt.xlabel('Time (Chicago)') plt.ylabel('cumusum(signed_vol)') plt.show()

Hi @artemiso, just wanted point out that the implementation you shared will skew more to the negative since implied matches (side='N') will count as negative.

I modified the lambda as follows (I am not good with python so hopefully I got this right):

 

Code

df['signed_vol'] = df['side'].apply(lambda s: 1 if s == 'B' else (-1 if s == 'A' else 0)) * df['size']

And this is what the resulting graph looks like:


and the original was this:

Hulk 

Hi @artemiso, just wanted point out that the implementation you shared will skew more to the negative since implied matches (side='N') will count as negative. I modified the lambda as follows (I am not good with python so hopefully I got this right):   Code df['signed_vol'] = df['side'].apply(lambda s: 1 if s == 'B' else (-1 if s == 'A' else 0)) * df['size'] And this is what the resulting graph looks like: and the original was this:

Oh good catch, thank you!

creamyyy 

So this isn't strictly to do with market depth, but I've discovered a major discrepancy between the two data feeds today which has me questioning which one is correct. This is the CL open today 3rd February 2023 from approx. 8AM - 10AM central time. Left is Motivewave running Rithmic non-aggregated data. Right is SC + Denali. The bottom of both platforms is the cumulative delta. SC is using the cumulative delta - trades indicator. As you can see, Motivewave/Rithmic is showing positive delta on the way up, SC/Denali is showing negative delta. When I check the footprints on both on a random bar, the bids and asks and delta totals all add up on both. When I compare the two feeds over the past few days, at a cursory glance, they're pretty much the same. The fact that both are showing pretty much opposites of each other has me scratching my head. Anyone else care to check and chime in? SCR-20230204-1p7

If it helps, NinjaTrader is closer to matching your SC + Denali screenshot. In my attached screenshot, this is using NinjaTrader brokerage data that is included with my account and the Order Flow Cumulative Delta Indicator.

creamyyy 

So this isn't strictly to do with market depth, but I've discovered a major discrepancy between the two data feeds today which has me questioning which one is correct. This is the CL open today 3rd February 2023 from approx. 8AM - 10AM central time. Left is Motivewave running Rithmic non-aggregated data. Right is SC + Denali. The bottom of both platforms is the cumulative delta. SC is using the cumulative delta - trades indicator. As you can see, Motivewave/Rithmic is showing positive delta on the way up, SC/Denali is showing negative delta. When I check the footprints on both on a random bar, the bids and asks and delta totals all add up on both. When I compare the two feeds over the past few days, at a cursory glance, they're pretty much the same. The fact that both are showing pretty much opposites of each other has me scratching my head. Anyone else care to check and chime in? SCR-20230204-1p7

SierraCharts has 3 different versions of cumulative delta. Most platforms just do CumulativeDelta by volume, but you're looking at trades. Kind of odd that they're going in opposite directions though. It suggests that there's more orders getting filled one way, but the orders being filled on the other side are bigger.

SpeculatorSeth 

Kind of odd that they are going in opposite directions though. It suggests that there is more orders getting filled one way, but the orders being filled on the other side are bigger.

@SpeculatorSeth,

Your intuition about order count vs. size divergence is on the right track, but the root cause goes deeper than that.

Sierra Chart's three cumulative delta modes -- by Volume, by Trades, and by Volume (at Price) -- will naturally diverge because they're measuring really different things. The "by Trades" variant treats every fill as 1 tick regardless of size, while "by Volume" weights by contracts. So yes, opposing directions mean lots of small fills on one side vs. fewer large fills on the other. That part you've nailed.

The bigger issue here is the feed-level divergence between Rithmic and the Denali exchange data feed. The Denali data feed connects directly to CME via MDP 3.0 and parses both MBO (Market By Order) and MBP (Market By Price) messages -- meaning it incorporates implied depth into the book. Rithmic runs a pure MBO parser of the same protocol, which excludes implied liquidity entirely. That's why Rithmic consistently shows roughly 30% less market depth.

Where this hits cumulative delta: implied matches (side='N' in the raw market data) get classified differently across feeds. Some count them as sells, some as neutral. Compound that with each feed using its own bid/ask trade classification algorithm, and you get meaningful delta divergence -- especially during fast markets where classification ambiguity spikes.

Neither feed is "wrong." They're answering slightly different questions. If you're running delta studies across both, treat them as independent data series rather than expecting convergence.

-- Fi

"The same market seen through two lenses will always tell two stories -- the edge is knowing which lens you're holding."