CQG News

Each Wednesday this article will be updated with the current seasonal study using CQG’s Seasonal analysis applied to the Soybean, Wheat and Corn markets. You can download the CQG pac providing the studies and charts here. In addition, the seasonal data lines can be pulled into Excel using RTD formulas. Below each chart are two tables. The first table is the highest correlation of the current market data to the seasonal year using a 20-day, 50-day, 100-day and the 200-day lookback periods. The second table is the previous week’s data. Seasonal analysis is about price direction or the trend.

The CME (and other exchanges) provide data regarding who the aggressor was (buyer or seller) when a trade is executed. An "Aggressor" or "Aggressing Order" by definition is an incoming order matching with one or more orders resting on the order book. The Aggressor pulls liquidity out of the order book by triggering a match event removing resting quantity and potentially effecting the price level from the order book. The Aggressor is identified in each order match during the continuous trading period. Please visit the CME Website for more details about Trade Summary Order Level Detail. The

Each Wednesday this article will be updated with the current seasonal study using CQG’s Seasonal analysis applied to the Soybean, Wheat and Corn markets. You can download the CQG pac providing the studies and charts here. In addition, the seasonal data lines can be pulled into Excel using RTD formulas. Below each chart are two tables. The first table is the highest correlation of the current market data to the seasonal year using a 20-day, 50-day, 100-day and the 200-day lookback periods. The second table is the previous week’s data. Seasonal analysis is about price direction or the trend.

CQG Product Specialist Stan Yabroff designed a CQG page for customers to track and analyze a market’s implied volatility and historical volatility. This post details the features and functionality of the CQG page. The benefit of this CQG page is you can quickly identify across a large portfolio of markets opportunities based on high and low implied and historical volatilities. First, let’s define historical volatility and implied volatility. Historical Volatility measures the market’s past volatility. It is defined as the standard deviation of a series of price changes measured at regular

The Microsoft® Excel 3-D chart is different from the Excel Scatter Plot chart. The Scatter chart uses a fixed size for the chart data points. The 3-D chart accesses an additional column to set the width of the chart data points. In this post setting up a 3-D chart is detailed for monitoring the S&P 500 and the sectors using the Select Sector SPDR® Fund symbols. First, the downloadable Excel sample has this table of data in the top left-hand corner. Column A: Symbol Column B: Last Trade Column C: Net Change Column D: % Net Change Column E: Last Trade Column E repeats using the value of

Each Wednesday this article will be updated with the current seasonal study using CQG’s Seasonal analysis applied to the Soybean, Wheat and Corn markets. You can download the CQG pac providing the studies and charts here. In addition, the seasonal data lines can be pulled into Excel using RTD formulas. Below each chart are two tables. The first table is the highest correlation of the current market data to the seasonal year using a 20-day, 50-day, 100-day and the 200-day lookback periods. The second table is the previous week’s data. Seasonal analysis is about price direction or the trend.