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Tuesday, July 08, 2025

ARBITRAGE OPPORTUNITY IN COREWEAVE (CRWV) AND CORE SCIENTIFIC (CORZ)

تم إعداد هذا المنشور من قبل سنشري للاستشارات

ARBITRAGE OPPORTUNITY IN COREWEAVE (CRWV) AND...
Platinum Primed for Take-off as it Breaks Out of 17-Year Consolidation

Soybean/Corn Ratio Chart

Source: Bloomberg
Date: 20 June 2025

 

Fundamental

In recent years, the battle for acreage between corn and soybean have become more prevalent influenced by factors like prices, biofuel policies, and trade dynamics. This year, it is expected to jump a notch higher as US farmers are expected to plant one of their largest corn corps these years.
Based on surveys of farmers, the Agriculture Department expects corn acreage to rise 5.2%, to about 95.3 million acres, which would be the third most in records dating to 1944.
The number of acres planted with soybeans, meanwhile, is expected to decline by 3.6 million, or 4.1%, to 83.5 million. In 2024, the US produced about 4.36 billion bushels of soybean, or about 28% of the total global production.
Looking at the Ending Stocks, according to WASDE’s latest estimates, the US soybean ending stock is at 295 million bushels, a significant 16% drop YoY, pushing the stock to use ratio to historically low ~6%, reinforcing bullish price signals. And in contrast, corn ending stocks remain ample at 1.75 billion bushels, keeping corn prices under pressure amid the acreage shift toward corn.

Technical

The Soybean/Corn price ratio chart has provided a breakout, supporting a bullish stance on Soybean and a bearish stance on Corn.
The next resistance is at 0.135, while support is at 0.124.
Looking at the Soybean futures chart individually, a huge base formation can be seen, with a bullish momentum expected above $10.86.
Risks and Assumptions related to Back-tested trading strategies
The risks and assumptions listed here are not intended to be an exhaustive summary of all the risks and assumptions involved.
The strategy might suffer from look-ahead bias which occurs due to the use of information or data in a study or simulation that would not have been known or available during the period being analyzed. This can lead to inaccurate results in the study or simulation.
Future price movements may not be exactly the same as the historical price movements and this could lead to variation in performance.
Testing can sometimes lead to over-optimization. This is a condition where performance results are tuned so high to the past they are no longer as accurate in the future.
The model assumes no slippages in trading. Slippage refers to the difference between the expected price of a trade and the price at which the trade is actually executed.
The back-tested strategy might be at risk of data dredging, which is the behavior of testing multiple hypotheses at one time, resulting in picking the data that best supports your main hypothesis.
Drawdowns in actual trading can be higher than the tested system and losses could be significant in the event of leverage.
Unforeseen events can lead to variation in performance from the tested trading strategy.
The tested result has been computed with price feeds available from Bloomberg.
The testing environment has not considered transaction or any other costs.
Trading indicators used for the purpose of testing has been provided by Bloomberg.
The strategy might suffer from data mining fallacy, selection bias and backfill bias.
A trading strategy that performs well on multiple datasets from one market (e.g., forex) might not perform as well in another market (e.g., stocks).
The strategy may not depict accuracy in terms of spread changes due to the spread-widening events.
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