I asked cohesive.so to give me a paragraph on how observation sources are related to numerical weather prediction, but it wrote a bunch of stuff I wasn't interested in as well. Still, I can get to the heart of the matter by simply copying and pasting the conclusion and leaving out everything else out: Conclusion Let's recap the key takeaways from our journey through the various types of observation sources. Surface observations, such as weather stations, weather balloons, and weather buoys, provide valuable data about weather conditions at the Earth's surface. These ground-based observations give us insights into temperature, humidity, wind speed, and precipitation, helping us to better understand and predict weather patterns. Moving up the atmosphere, we encountered upper-air observations. From radiosondes to commercial aircraft observations and wind profilers, these observations provide crucial information about temperature, moisture, and wind patterns at different altitudes. By analyzing these data, meteorologists can create more accurate numerical weather prediction models. And then there are satellite observations, where geostationary and polar orbiting satellites, armed with radiometers and lidar, give us a bird's-eye view of our planet's weather systems. These observations capture images and data about clouds, aerosols, temperatures, and more, contributing to a comprehensive understanding of global weather dynamics. Last but not least, radar observations, including weather radars and the mighty Doppler radar, help us monitor precipitation, detect severe storms, and track the movement of rainfall. These observations are particularly useful for short-term weather predictions and for issuing timely warnings during hazardous weather events. Now that we've explored the different observation sources, we can truly appreciate their significance in improving numerical weather prediction. By combining data from these sources, meteorologists can enhance the accuracy and reliability of their forecasts, helping us stay one step ahead of Mother Nature.
15 minutes into the 10 PM PDT EURUSD two-hour binary option contract sees a $16 payout gap between the middle two strike prices.
So far, USDCAD appears to have been unable to climb higher than 1.3278. But, the problem now is that though the five-day price flow is still bearish, the one- and two-day baselines are not. Consequently, even if the four-hour measures follow through on heading south, the resumption of an overall southbound trajectory will not be validated or confirmed until and unless the one- and two-day measures rejoin the effort.
Five minutes into the 5 AM PDT EURUSD two-hour binary option contract, the gap between the payouts for the two middle strike prices is just $7.50. This is the lowest I've seen it thus far. So, what was it at 4 AM, and where will it be at 6 AM?
The difference between the strike prices at 7:20 AM today is $10.75 as opposed to $11.75 yesterday. Though I suspect that yesterday I might have been looking at the second half of a two-hour binary option contract, whereas now, I am only making comparisons between the first half of two-hour binary option contracts. I will now begin filling out the spread sheet I said (yesterday) that I would get started on.
So then, buy comparison, I suppose observation sources when it comes to the Forex market comes down to technicals, fundamentals, and I suppose world events as well. But, all I really care about are the technicals, because they automatically tell me what impact the fundamentals and world events are having on the market. With stocks however, I suppose there's a lot of other stuff too, like Internet chatter, insider trading, and a whole host of factors I don't even know I'm overlooking. I could get more specific with Forex and actually list stuff like central banks, geopolitics, employment, production, growth, inflation, interest rates, quantitative easing, relative strength/weakness, correlations, etc. And with stocks you have earnings and whatnot. So all of this, I guess, corresponds to what would fall under the category of "observation sources" with respect to weather.
I asked cohesive.so: In what way is quality a foundational principle in numerical weather prediction? In order to provide accurate and reliable weather forecasts, the data used in the prediction models must be of the highest quality. This includes both the initial observations and the model output. To ensure quality, rigorous quality control measures are implemented at every step of the forecasting process. The observations are carefully collected and processed, removing any erroneous or inconsistent data. Various quality control techniques, such as outlier detection and consistency checks, are utilized to identify and correct any errors or biases in the measurements. Once the observations have been quality controlled, they are assimilated into the numerical weather prediction models. During this process, techniques such as data assimilation and model verification are employed to improve the accuracy of the forecasts. The models themselves are thoroughly tested and evaluated to ensure their reliability and performance. By emphasizing quality as a foundational principle, numerical weather prediction aims to provide precise and reliable forecasts that are essential for various sectors, including aviation, agriculture, and emergency management. These accurate forecasts enable informed decision-making and help mitigate the impact of severe weather events. Overall, quality is of utmost importance in numerical weather prediction, as it underpins the reliability and usefulness of the forecasts. Stringent quality control measures and testing procedures ensure that the data and models used in weather prediction are of the highest standard, enabling accurate and dependable forecasts to be generated.
Looking back on Monday with respect to daily binary options... ...let me test whether the data offered by my charts might offer a 100% success rate so that the fact that the Nadex risk-to-reward structure is extremely odious in my view would, in effect, not matter; by first purchasing an AUDJPY demo put contract that will return about a $9 payout from forecasting that the pair will be below 96.40 fifteen hours from now (at noon Friday PDT). 0.6656 is above bearish AUDUSD's current four- and eight-hour resistance levels. This implies the rate will be below this strike price at noon tomorrow, to return a $12.50 payout. Let me see if this actually happens. EURJPY is slightly bullish, and 156.40 is very near the bottom of its daily price range. So, will the pair close above it and pay out approximately nine bucks? Let me buy it and see.
Again, based on my "Daily Price Flow Is Easy to See" forecast models, even though GBPUSD is currently rising, the fact the the overall day-to-day flow is bearish, coupled with the rate's present location at the top of the typical four- and eight-hour price range envelopes, implies that price will not be above the 1.2700 daily strike price at expiry six-and-a-half hours from now, which would return an $20 payout. This strikes me as a very risky proposition, but I'm going to put it to the test, nonetheless. Other trades I will be looking to make are buying USDCHF and USDJPY, where price is falling in rising markets, and selling EURUSD, where the price is rising in a falling market.