Sacramento's population projections for the State of California are already 1.4 million too high only 3 years into the forecast by 2023. The reason is Sacramento's unrealistic migration assumption. This analysis tests in detail how and why this projection went so wrong.
This study analyzes the temperature history of 24 American cities going back to 1895. Using a LOESS model, it forecasts prospective temperature increases over the next 40 years and out to 2100. And, it compares the 2100 forecast with the NOAA model(s). This comparison uncovers serious deficiencies within the NOAA model(s), as it does not fit the historical data well; and it does not differentiate much forecasts between various cities.
Compact Letter Display (CLD). How it worksGaetan Lion
Compact Letter Display (CLD) renders ANOVA & Tukey HSD testing a lot easier to interpret. It readily ranks and differentiate the tested variables. With CLD you can readily identify the variables that are statistically dissimilar vs. the ones that are similar.
This study compares the benefits and the funding for CalPERS pensions vs. Social Security. It also looks in more detail on the financial burden of CalPERS pensions on the Marin Municipal Water District.
This presentation includes two explanatory models to attempt to predict recessions. The first one is a logistic regression. The second one is a deep neural network (DNN). Both use the same set of independent variables: the velocity of money, inflation, the yield curve, and the stock market. As usual, the DNN fits the historical data a bit better than the simpler logistic regression. But, when it comes to testing or predicting, both models are pretty much even.
Objective:
Studying trends in US inequality along several social dimensions including education, ethnicity, percentiles, and work status. We don’t explore gender because it is not disaggregated within the mentioned data that focuses on families (fairly similar to households).
Data source:
US Government Survey of Consumer Finance (SCF) data. The SCF aggregates financial data on US families every three years. And, it discloses a time series from 1989 to 2019.
Sacramento's population projections for the State of California are already 1.4 million too high only 3 years into the forecast by 2023. The reason is Sacramento's unrealistic migration assumption. This analysis tests in detail how and why this projection went so wrong.
This study analyzes the temperature history of 24 American cities going back to 1895. Using a LOESS model, it forecasts prospective temperature increases over the next 40 years and out to 2100. And, it compares the 2100 forecast with the NOAA model(s). This comparison uncovers serious deficiencies within the NOAA model(s), as it does not fit the historical data well; and it does not differentiate much forecasts between various cities.
Compact Letter Display (CLD). How it worksGaetan Lion
Compact Letter Display (CLD) renders ANOVA & Tukey HSD testing a lot easier to interpret. It readily ranks and differentiate the tested variables. With CLD you can readily identify the variables that are statistically dissimilar vs. the ones that are similar.
This study compares the benefits and the funding for CalPERS pensions vs. Social Security. It also looks in more detail on the financial burden of CalPERS pensions on the Marin Municipal Water District.
This presentation includes two explanatory models to attempt to predict recessions. The first one is a logistic regression. The second one is a deep neural network (DNN). Both use the same set of independent variables: the velocity of money, inflation, the yield curve, and the stock market. As usual, the DNN fits the historical data a bit better than the simpler logistic regression. But, when it comes to testing or predicting, both models are pretty much even.
Objective:
Studying trends in US inequality along several social dimensions including education, ethnicity, percentiles, and work status. We don’t explore gender because it is not disaggregated within the mentioned data that focuses on families (fairly similar to households).
Data source:
US Government Survey of Consumer Finance (SCF) data. The SCF aggregates financial data on US families every three years. And, it discloses a time series from 1989 to 2019.
The model development two objectives are:
1) To explain home prices using demographic explanatory variables; and
2) To benchmark the accuracy of OLS regressions vs. DNN models.
For home prices, we used county level data from Zillow. For the explanatory variables, we used data from GEOFRED.
This analysis focuses on population aging, population age categories in % (age pyramids), and overall population growth. It looks at various geographic units (countries, continents, regions, World) from 1950 to the Present (2019 & 2020). And, it looks at projections out to 2100.
Africa is an outlier to the overall global aging; its population growth (historical & projected) is far faster than for other major regions.
We are going to analyze several of the major cryptocurrencies as an asset class. And, we are going to address several related questions:
Do they provide diversification benefits relative to the stock market (S&P 500)?
How do their diversification benefits compare with Gold’s diversification benefit vs. the stock market?
Do cryptocurrencies provide diversification benefits when you really need it… during market downturns?
Are cryptocurrencies truly “digital Gold”? Do they behave in a similar way given that their supply is constrained (supposedly in a similar way as Gold is)?
We will test whether :
a) Sequential Deep Neural Networks (DNNs) can predict the stock market (S&P 500) better than OLS regression;
b) DNNs using smooth Rectified Linear activation functions perform better than the ones using Sigmoid (Logit) activation functions.
Can Treasury Inflation Protected Securities predict Inflation?Gaetan Lion
We look at the spread between Treasuries and TIPS to figure out how effective such observations were in predicting actual inflation several years down the road.
This analysis focuses on measures much beyond PE ratios. And, it concludes that the Stock Market is actually really cheap vs. bonds. But, it appears quite overvalued when focusing on inflation measures.
The relationship between the Stock Market and Interest RatesGaetan Lion
This is a study of the relationship between the Stock Market and Interest Rates. We review how the Stock Market has reacted when interest rates rise. We also factor the influence of other macroeconomics variables.
This is a study using historical data and forecasts of life expectancy for several countries. The data and forecasts come from the UN - Population Division. While the historical data is most interesting, the forecasts are highly optimistic as they project a linear trend way into the future. Meanwhile, those forecasts should have followed a much more realistic logarithmic curve reflecting slower increase in life expectancy as the life expectancy rises.
Will Stock Markets survive in 200 years?Gaetan Lion
This study uncovers 11 international stock markets that are already running into existing and prospective demographic and economic growth constraints. This study evaluates their respective fragile long term viability and the implications this has for the investors in such countries.
This study answers three questions:
1) Does it make a difference whether you standardize your variables before running your model or standardize the regression coefficients after you run your model?
2) Does the scale of the respective original non-standardized variables affect the resulting standardized coefficients?
3) Does using non-standardized variables vs. standardized variables have an impact when conducting regularization (Ridge Regression, LASSO)?
This analysis compares his track record vs. Manning, Montana, Marino, Brees, Favre, and Elway. At the end of this analysis, it makes extensive use of the binomial distribution to figure out how much of their respective track records are due to randomness vs. skills.
Regularization why you should avoid themGaetan Lion
Regularization models are supposed to reduce model over-fitting and improve forecasting accuracy. Very often they do just the opposite: increase model under-fitting, and decrease model forecasting accuracy. This study explains how Regularization models often fail, and how to resolve model issues with far simpler and more robust methods.
This study reviews the increasing prevalence of 3-shot points within the NBA. It also compares the record of the 5 top players in NBA history in 3-pt shots. It also considers how many good years left Curry may have.
Japan vs. US comparison on numerous dimensionsGaetan Lion
This study compares Japan vs. the US on numerous dimensions including demographics (including health and education), and economics (including monetary and fiscal policies). This is to observe when Japan and the US trends are likely to converge over time.
Climate change model forecast global temperature out to 2100Gaetan Lion
This study is leveraging a VAR model introduced in an earlier presentation to forecast global temperature out to 2100, and assess how likely are we to keep such temperatures at or under the + 1.5 degree Celsius threshold.
This study consist in:
1) First, reviewing the historical data of the World population and economic growth over the past several centuries;
2) Second, envisioning what our future over the next several centuries may look like, while assessing scenarios feasibility; and
3) Looking at recent trends over the past several decades.
This is a study attempting to statistically measure the impact of Government policies on the economy and the stock market. The “causal” Government policies considered will include:
Fiscal Policy, entailing Budget Deficit spending;
Monetary Policy with the Federal Reserve managing the Federal Funds rate; and
Monetary Policy with the Federal Reserve conducting large purchases of securities (Treasuries, MBS);
The dependent or impacted macroeconomic variables affected by the above Government policies will include:
The overall economy (RGDP);
Inflation (CPI);
Unemployment Rate; and
Stock market.
Presenting Climate Change Models that estimate and forecast global temperature levels in association or caused by CO2 concentration (ppm) levels. These models also replicate IPCC scenarios.
Medical Decision Making associated with Clinical test interpretations. Depending on the situation one should get a second test to confirm the result of the first one; or one should move on to the treatment phase.
01062024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
The model development two objectives are:
1) To explain home prices using demographic explanatory variables; and
2) To benchmark the accuracy of OLS regressions vs. DNN models.
For home prices, we used county level data from Zillow. For the explanatory variables, we used data from GEOFRED.
This analysis focuses on population aging, population age categories in % (age pyramids), and overall population growth. It looks at various geographic units (countries, continents, regions, World) from 1950 to the Present (2019 & 2020). And, it looks at projections out to 2100.
Africa is an outlier to the overall global aging; its population growth (historical & projected) is far faster than for other major regions.
We are going to analyze several of the major cryptocurrencies as an asset class. And, we are going to address several related questions:
Do they provide diversification benefits relative to the stock market (S&P 500)?
How do their diversification benefits compare with Gold’s diversification benefit vs. the stock market?
Do cryptocurrencies provide diversification benefits when you really need it… during market downturns?
Are cryptocurrencies truly “digital Gold”? Do they behave in a similar way given that their supply is constrained (supposedly in a similar way as Gold is)?
We will test whether :
a) Sequential Deep Neural Networks (DNNs) can predict the stock market (S&P 500) better than OLS regression;
b) DNNs using smooth Rectified Linear activation functions perform better than the ones using Sigmoid (Logit) activation functions.
Can Treasury Inflation Protected Securities predict Inflation?Gaetan Lion
We look at the spread between Treasuries and TIPS to figure out how effective such observations were in predicting actual inflation several years down the road.
This analysis focuses on measures much beyond PE ratios. And, it concludes that the Stock Market is actually really cheap vs. bonds. But, it appears quite overvalued when focusing on inflation measures.
The relationship between the Stock Market and Interest RatesGaetan Lion
This is a study of the relationship between the Stock Market and Interest Rates. We review how the Stock Market has reacted when interest rates rise. We also factor the influence of other macroeconomics variables.
This is a study using historical data and forecasts of life expectancy for several countries. The data and forecasts come from the UN - Population Division. While the historical data is most interesting, the forecasts are highly optimistic as they project a linear trend way into the future. Meanwhile, those forecasts should have followed a much more realistic logarithmic curve reflecting slower increase in life expectancy as the life expectancy rises.
Will Stock Markets survive in 200 years?Gaetan Lion
This study uncovers 11 international stock markets that are already running into existing and prospective demographic and economic growth constraints. This study evaluates their respective fragile long term viability and the implications this has for the investors in such countries.
This study answers three questions:
1) Does it make a difference whether you standardize your variables before running your model or standardize the regression coefficients after you run your model?
2) Does the scale of the respective original non-standardized variables affect the resulting standardized coefficients?
3) Does using non-standardized variables vs. standardized variables have an impact when conducting regularization (Ridge Regression, LASSO)?
This analysis compares his track record vs. Manning, Montana, Marino, Brees, Favre, and Elway. At the end of this analysis, it makes extensive use of the binomial distribution to figure out how much of their respective track records are due to randomness vs. skills.
Regularization why you should avoid themGaetan Lion
Regularization models are supposed to reduce model over-fitting and improve forecasting accuracy. Very often they do just the opposite: increase model under-fitting, and decrease model forecasting accuracy. This study explains how Regularization models often fail, and how to resolve model issues with far simpler and more robust methods.
This study reviews the increasing prevalence of 3-shot points within the NBA. It also compares the record of the 5 top players in NBA history in 3-pt shots. It also considers how many good years left Curry may have.
Japan vs. US comparison on numerous dimensionsGaetan Lion
This study compares Japan vs. the US on numerous dimensions including demographics (including health and education), and economics (including monetary and fiscal policies). This is to observe when Japan and the US trends are likely to converge over time.
Climate change model forecast global temperature out to 2100Gaetan Lion
This study is leveraging a VAR model introduced in an earlier presentation to forecast global temperature out to 2100, and assess how likely are we to keep such temperatures at or under the + 1.5 degree Celsius threshold.
This study consist in:
1) First, reviewing the historical data of the World population and economic growth over the past several centuries;
2) Second, envisioning what our future over the next several centuries may look like, while assessing scenarios feasibility; and
3) Looking at recent trends over the past several decades.
This is a study attempting to statistically measure the impact of Government policies on the economy and the stock market. The “causal” Government policies considered will include:
Fiscal Policy, entailing Budget Deficit spending;
Monetary Policy with the Federal Reserve managing the Federal Funds rate; and
Monetary Policy with the Federal Reserve conducting large purchases of securities (Treasuries, MBS);
The dependent or impacted macroeconomic variables affected by the above Government policies will include:
The overall economy (RGDP);
Inflation (CPI);
Unemployment Rate; and
Stock market.
Presenting Climate Change Models that estimate and forecast global temperature levels in association or caused by CO2 concentration (ppm) levels. These models also replicate IPCC scenarios.
Medical Decision Making associated with Clinical test interpretations. Depending on the situation one should get a second test to confirm the result of the first one; or one should move on to the treatment phase.
01062024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
‘वोटर्स विल मस्ट प्रीवेल’ (मतदाताओं को जीतना होगा) अभियान द्वारा जारी हेल्पलाइन नंबर, 4 जून को सुबह 7 बजे से दोपहर 12 बजे तक मतगणना प्रक्रिया में कहीं भी किसी भी तरह के उल्लंघन की रिपोर्ट करने के लिए खुला रहेगा।
role of women and girls in various terror groupssadiakorobi2
Women have three distinct types of involvement: direct involvement in terrorist acts; enabling of others to commit such acts; and facilitating the disengagement of others from violent or extremist groups.
03062024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
31052024_First India Newspaper Jaipur.pdfFIRST INDIA
Find Latest India News and Breaking News these days from India on Politics, Business, Entertainment, Technology, Sports, Lifestyle and Coronavirus News in India and the world over that you can't miss. For real time update Visit our social media handle. Read First India NewsPaper in your morning replace. Visit First India.
CLICK:- https://firstindia.co.in/
#First_India_NewsPaper
हम आग्रह करते हैं कि जो भी सत्ता में आए, वह संविधान का पालन करे, उसकी रक्षा करे और उसे बनाए रखे।" प्रस्ताव में कुल तीन प्रमुख हस्तक्षेप और उनके तंत्र भी प्रस्तुत किए गए। पहला हस्तक्षेप स्वतंत्र मीडिया को प्रोत्साहित करके, वास्तविकता पर आधारित काउंटर नैरेटिव का निर्माण करके और सत्तारूढ़ सरकार द्वारा नियोजित मनोवैज्ञानिक हेरफेर की रणनीति का मुकाबला करके लोगों द्वारा निर्धारित कथा को बनाए रखना और उस पर कार्यकरना था।
In a May 9, 2024 paper, Juri Opitz from the University of Zurich, along with Shira Wein and Nathan Schneider form Georgetown University, discussed the importance of linguistic expertise in natural language processing (NLP) in an era dominated by large language models (LLMs).
The authors explained that while machine translation (MT) previously relied heavily on linguists, the landscape has shifted. “Linguistics is no longer front and center in the way we build NLP systems,” they said. With the emergence of LLMs, which can generate fluent text without the need for specialized modules to handle grammar or semantic coherence, the need for linguistic expertise in NLP is being questioned.
16. Robert Barro’s Study Fig. 1
Overall, there is no
relationship between
the Gini coefficient and
economic growth.
16
17. Robert Barro’s Study Fig. 2
There is a negative relationship There is a somewhat positive
between Gini coefficient and relationship between Gini coefficient
economic growth for developing and economic growth for developed
countries. countries. 17