Hello Sir, I´m currently reading the FX Primers and I´m going through the Month in Macro from Prometheus. I find his contribution-charts to the respective indicators (such as contribution of an industry group to Employment, Inflation etc.) very helpful, but don't know which formula to apply to create such data or even charts. I´m asking because I´m trying to use this feature to improve my analysis of other FX-markets (economies). Do you have any tips or idea which formula to use to calculate such things? Kind Regards Art
Youre going to have to spend a ton of time in the actual economic data releases and the rules that the BEA or other agencies are using for data quality. You basically need to spend time going through all the boring documents of the data releases that explain the why and how behind the data.
That is what I'm doing,but I got stuck with the formula needed to calculate the contributions, let's say how much the manufacturing sector is contributing to overall employment or how much a subgroup in the manufacturing is contributing to the manufacturing employment. I did not find some useful stuff on google,jusr some complicated mathematical theories. So I was reaching to you for some adice :)
I mean if you have the overall number then account for each attribution to the overall market then you should see it pretty clearly ? Just basic division ?
Youre going to have to spend a ton of time in the actual economic data releases and the rules that the BEA or other agencies are using for data quality. You basically need to spend time going through all the boring documents of the data releases that explain the why and how behind the data.
Stupid Q but why is it that PCE for monthly and quarterly almost identical? Wouldn't monthly use to extrapolate into quarterly, so quarterly PCE = monthly PCE x 3?
What I mean is Personal Consumption Expenditure on a monthly basis is 18,215. Quarterly is 17,749. Wouldn't the correct extrapolation for quarterly is to take monthly, and multiply it by 3, which is 18,215 x3?
sorry are we using PCE from the personal income and outlays datasset or GDP?
having difficulty understanding your question but the monthly PCE number from personal income and outlays, when added together for an entire quarter should equal the PCE number in GDP
This is a great question. Steps 1-6 are a really good set up. You want to define everything into regimes to see the highest probability for returns. Then you want to identify any discontinuity from past returns and what the potential drivers might be. Then after you have that information, you want to overlay technical signals such as momentum and mean reverion signals to execute with risk management on the fundamental signals you have generated. Future Substacks incoming on this topic!
Hello Sir, I´m currently reading the FX Primers and I´m going through the Month in Macro from Prometheus. I find his contribution-charts to the respective indicators (such as contribution of an industry group to Employment, Inflation etc.) very helpful, but don't know which formula to apply to create such data or even charts. I´m asking because I´m trying to use this feature to improve my analysis of other FX-markets (economies). Do you have any tips or idea which formula to use to calculate such things? Kind Regards Art
Youre going to have to spend a ton of time in the actual economic data releases and the rules that the BEA or other agencies are using for data quality. You basically need to spend time going through all the boring documents of the data releases that explain the why and how behind the data.
That is what I'm doing,but I got stuck with the formula needed to calculate the contributions, let's say how much the manufacturing sector is contributing to overall employment or how much a subgroup in the manufacturing is contributing to the manufacturing employment. I did not find some useful stuff on google,jusr some complicated mathematical theories. So I was reaching to you for some adice :)
I mean if you have the overall number then account for each attribution to the overall market then you should see it pretty clearly ? Just basic division ?
Just need to account for every line item
That's right,but sometimes there is just an index for every item and the percentage change of the item and then it's not so easy anymore.
well yeah so just see how they construct the index
NFP should all be in number of employees.
Thank you for the reply and help.
Youre going to have to spend a ton of time in the actual economic data releases and the rules that the BEA or other agencies are using for data quality. You basically need to spend time going through all the boring documents of the data releases that explain the why and how behind the data.
This is so capitalastic ،thank you
Am looking forward for your next article ❤️❤️❤️
Fantastic break down, really appreciate the effort put into these pieces.
Super excited to join the journey 👍
Stupid Q but why is it that PCE for monthly and quarterly almost identical? Wouldn't monthly use to extrapolate into quarterly, so quarterly PCE = monthly PCE x 3?
not sure i understand the question
What I mean is Personal Consumption Expenditure on a monthly basis is 18,215. Quarterly is 17,749. Wouldn't the correct extrapolation for quarterly is to take monthly, and multiply it by 3, which is 18,215 x3?
sorry are we using PCE from the personal income and outlays datasset or GDP?
having difficulty understanding your question but the monthly PCE number from personal income and outlays, when added together for an entire quarter should equal the PCE number in GDP
Great article! So is the goal to do something like this?
1. Have a deep understanding how all the parts in the economy works and influence each other.
2. Create a nowcast model for GDP and Inflation based on macro data points.
3. Create a model based on financial data that tries to see what regime the market is pricing in right now.
4. Forecast future Growth and Inflation.
5. Forecast what the central bank will do.
6. Take positions based on backtests in the positions that have the highest return in the regime we are in/going towards.
Did I miss something?
This is a great question. Steps 1-6 are a really good set up. You want to define everything into regimes to see the highest probability for returns. Then you want to identify any discontinuity from past returns and what the potential drivers might be. Then after you have that information, you want to overlay technical signals such as momentum and mean reverion signals to execute with risk management on the fundamental signals you have generated. Future Substacks incoming on this topic!