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.
The presentation investigates whether the Federal Reserve can possibly manage asset bubbles (real estate, stocks) in addition to managing its primary goals (inflation, sustainable growth).
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.
The presentation investigates whether the Federal Reserve can possibly manage asset bubbles (real estate, stocks) in addition to managing its primary goals (inflation, sustainable growth).
Below please find a link to our monthly market perspective piece for May. This month we explore the reality behind market anomalies such as “sell in May and go away.”
Monthly Market Perspective - January 2017Mark Biegel
Below please find a link to our monthly market perspective piece for January. This month, with the transition in Washington upon us, we reflect on what impact prior presidential cycles had on markets, and assess how this one may turn out.
Below please find a link to our monthly market perspective piece for February. This month, with the prospect for potential policy changes ahead, we take a deeper dive into the concept of inflation and what it means to investors.
Below please find a link to our monthly market perspective piece for August. Due to the recent rebound in quarterly corporate earnings, this month we explore the importance of this fundamental underpinning to the equity markets.
Following an impressive bounce back from February lows, the durability of the current bull market remains suspect. The benefits of the recent rally appear limited to the large cap, defensive sectors of the market. In prior market cycles, this has portended that the latter stages of a bull market are fast approaching and as such, caution is warranted.
Below please find a link to our monthly market perspective piece for June. This month we dive deeper into equity market year-to-date returns and discuss the narrow leadership that has re-emerged, primarily from several large technology companies.
Below please find a link to our monthly market perspective piece for December. This month we examine the impacts of the rapidly changing low interest rate environment.
Below please find a link to our monthly market perspective piece for December. This month we explore a variety of factors potentially driving markets and evaluate the risks and rewards lying beneath the surface.
A review of Q4 2015 corporate earnings reveals a significant slowdown in revenue and earnings growth. While these developments have been affected by the sharp decline in commodity prices,they may reveal early signs of recessionary conditions.
Impact of Macro-Economic Factors on Customer Behaviour in the US Insurance In...Pranov Mishra
A project was done to understand macro economic factors in US significantly impact a customer's decision to continue with an existing insurance policy or not. Data exploration, visualization, data transformation and model building was done to derive insights on whether any or a combination of the macro economic factors significantly impact customer behavior. The macro economic factors considered are GDP, Corporate Bond rate, Market Returns (5 year FD, Stocks S&P 500, Treasury Bonds), CPI (Consumer Price Index), HPI (Housing Price Index) , Unemployment rate and Mortgage rate.
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.
Below please find a link to our monthly market perspective piece for May. This month we explore the reality behind market anomalies such as “sell in May and go away.”
Monthly Market Perspective - January 2017Mark Biegel
Below please find a link to our monthly market perspective piece for January. This month, with the transition in Washington upon us, we reflect on what impact prior presidential cycles had on markets, and assess how this one may turn out.
Below please find a link to our monthly market perspective piece for February. This month, with the prospect for potential policy changes ahead, we take a deeper dive into the concept of inflation and what it means to investors.
Below please find a link to our monthly market perspective piece for August. Due to the recent rebound in quarterly corporate earnings, this month we explore the importance of this fundamental underpinning to the equity markets.
Following an impressive bounce back from February lows, the durability of the current bull market remains suspect. The benefits of the recent rally appear limited to the large cap, defensive sectors of the market. In prior market cycles, this has portended that the latter stages of a bull market are fast approaching and as such, caution is warranted.
Below please find a link to our monthly market perspective piece for June. This month we dive deeper into equity market year-to-date returns and discuss the narrow leadership that has re-emerged, primarily from several large technology companies.
Below please find a link to our monthly market perspective piece for December. This month we examine the impacts of the rapidly changing low interest rate environment.
Below please find a link to our monthly market perspective piece for December. This month we explore a variety of factors potentially driving markets and evaluate the risks and rewards lying beneath the surface.
A review of Q4 2015 corporate earnings reveals a significant slowdown in revenue and earnings growth. While these developments have been affected by the sharp decline in commodity prices,they may reveal early signs of recessionary conditions.
Impact of Macro-Economic Factors on Customer Behaviour in the US Insurance In...Pranov Mishra
A project was done to understand macro economic factors in US significantly impact a customer's decision to continue with an existing insurance policy or not. Data exploration, visualization, data transformation and model building was done to derive insights on whether any or a combination of the macro economic factors significantly impact customer behavior. The macro economic factors considered are GDP, Corporate Bond rate, Market Returns (5 year FD, Stocks S&P 500, Treasury Bonds), CPI (Consumer Price Index), HPI (Housing Price Index) , Unemployment rate and Mortgage rate.
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.
The five steps in financial planning, forecasting internalexternal .pdfamrahlifestyle
The five steps in financial planning, forecasting internal/external finds is critical. With today\'s
economic and interest rate market conditions, along with the volitility of the captial markets,
what factors would you emphasize when you are preparing your forecasts?
Solution
Connect with Vanguard > vanguard.com Executive summary. Some say the long-run outlook for
U.S. stocks is poor (even “dead”) given the backdrop of muted economic growth, already-high
profit margins, elevated government debt levels, and low interest rates. Others take a rosier view,
citing attractive valuations and a wide spread between stock earnings yields and Treasury bond
yields as reason to anticipate U.S. stock returns of 8%–10% annually, close to the historical
average, over the next decade. Given such disparate views, which factors should investors
consider when formulating expectations for stock returns? And today, what do those factors
suggest is a reasonable range to expect for stock returns going forward? We expand on previous
Vanguard research in using U.S. stock returns since 1926 to assess the predictive power of more
than a dozen metrics that investors would know ahead of time. We find that many commonly
cited signals have had very weak and erratic correlations with actual subsequent returns, even at
long investment horizons. These poor Vanguard research October 2012 Forecasting stock
returns: What signals matter, and what do they say now? Authors Joseph Davis, Ph.D. Roger
Aliaga-Díaz, Ph.D. Charles J. Thomas, CFA 2 predictors include trailing values for dividend
yields and economic growth, the difference between the stock market’s earnings yield and
Treasury bond yields (the so-called Fed Model), profit margins, and past stock returns. We
confirm that valuation metrics such as price/earnings ratios, or P/Es, have had an inverse or
mean-reverting relationship with future stock market returns, although it has only been
meaningful at long horizons and, even then, P/E ratios have “explained” only about 40% of the
time variation in net-of-inflation returns. Our results are similar whether or not trailing earnings
are smoothed or cyclically adjusted (as is done in Robert Shiller’s popular P/E10 ratio). The
current level of a blend of valuation metrics contributes to Vanguard’s generally positive outlook
for the stock market over the next ten years (2012–2022). But the fact that even P/Es—the
strongest of the indicators we examined—leave a large portion of returns unexplained
underscores our belief that expected stock returns are best stated in a probabilistic framework,
not as a “point forecast,” and should not be forecast over short horizons. The variation of
expected returns Forming reasonable long-run return expectations for stocks and other asset
classes can be important in devising a strategic asset allocation. But what precisely are
“reasonable” expectations in the current environment, and how should they be formed? For
instance, should investors expect t.
This slide deck describes how CBO used a Markov-switching model to assess the uncertainty of the economic forecast presented in CBO’s Current View of the Economy in 2023 and 2024 and the Budgetary Implications (November 2022).
The tested causal hypothesis is whether change in Consumer Spending causes Unemployment [rate] or vice versa...
This presentation details the steps to demonstrate causality using Granger Causality, Path Analysis, and narrative tests.
Unemployment Economic Growth
Unemployment, as we all know, is the rate of people who
want to work and are actively searching for jobs, but
cannot find any. From the graph above, which describes
the rates of unemployment from 2000 to 2015, one can see
that 2010 was the highest point of unemployment. The red
bars describe the times of recession which were from 2001
to 2002 and 2008 to 2009. There was a rise in the
unemployment rate between 2000-2003 and 2008-2011.
The unemployment rate decreased, meaning the economy
was improving, between 2004-2006 and 2011-2015.
After each recession, there exists a trend. Not directly
after, but very soon, the economy will begin to improve
and gain its strength back. This is when the rate of
unemployment will decline and people will get the jobs
they have been longing for. The average rate for the data
in the graph in between the year 2000 and 2015 is about
6.3 %. Compared to the natural average of 5%, it can be
concluded that this unemployment rate is slightly higher
than that average. This means that the average
unemployment rate from 2000 to 2015 was at an unhealthy
rate above the natural average.
Economic growth rate is the measure of gross domestic
product (GDP) in a country; it is the growing rate of the
economy which can be found by examining GDP. There
were many spikes in the economy shown in the graph
between the years 2000 to 2015. There were drops in the
economic growth rate in the years of 2000-2002, 2005-
2007, 2008-2009, 2011-2013, and 2014-2015. There were
improvements in the economy between 2003- 2005, 2007-
2008, 2009-2011, and 2013-2014. Once the recessions hit,
the economy slowly started to gain speed until another
negative impact hit. The economy will always be a
fluctuating mess, but it is beginning to improve again as
we come into the year 2016.
If we compared this graph to that of the unemployment
rate, then we would be able to see similarities in the
fluctuations of each graph. When the economy was getting
worse, the unemployment rate would increase; these two
variables were almost inversely related. The historical rate
of economic growth is 3.2%. The average rate of the data
from the graph is around 1.9%. This is a little more than
half of the historical rate. This means that our economy
between 2000 and 2015 is growing slowly, not as fast as
Current economic
trends…
May 9, 2016
1
EconoMagazine
the historical rate. Looking at the positive side, it is
growing which means the economy is improving and
finally out of the recession of 2008-2009.
Interest
Interest rates affect the United States’ stocks and bonds,
which can either be good or bad for the economy. The
graph above describes the activity, ups and downs, of
interest rate. From 2000-2003 the interest rates were
dropping. Lower interest rates, in turn, make borrowing
funds easier for people. In 2003 all through 200 ...
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.
Does High Public Debt Consistently Stifle Economic Growth? A Critique a Reinh...Marco Garoffolo
Proprio in questi giorni abbiamo avuto una prova, decisiva, dell'utilità della non-cooperazione con la ragion di Stato. Ne ha riferito Paul Krugman, in un articolo che dichiara defunta, almeno nelle accademie, l'Austerità (Repubblica, 27 aprile). È un dogma cui l'Europa è appesa da anni: se non cresciamo economicamente, è solo perché gli Stati sono troppo indebitati. A sfatare l'assioma: tre economisti non ortodossi dell'università di Massachusetts-Amherst (i professori Michael Ash e Robert Pollin, lo studente di dottorato Thomas Herndon) che hanno scoperto errori di computer (l'errore Excel) commessi nel 2010 dai due economisti di Harvard, Kenneth Rogoff e Carmen Reinhart. Il dogma ("i Paesi che si indebitano oltre il 90 per cento del Pil non possono crescere") è in pezzi. http://www.peri.umass.edu/fileadmin/pdf/working_papers/working_papers_301-350/WP322.pdf
In the paper we test the new Phillips curve for Central and Eastern European EU accession countries for the period from 1990 to 2002 and use it to compare the efficiency of the traditional Phillips curve. More specifically, we want to see whether real marginal cost, which includes labor productivity and real wage components, can account for inflation dynamics in the observed sample. Surprisingly, when observing all eight selected countries, the relation between real marginal cost and inflation is opposite than expected. On the other hand, inflation in Baltic States and Slovenia seems to be influenced by real marginal cost. The elasticity coefficient of real wages on inflation for Slovenia shows that inflation was quite responsive to movement in wages during the total period, however, inflation became quite inelastic with respect to wages after 2000. Thus, economic policies that were introduced in Slovenia after 2000 were quite efficient in wage regulation, although the real effect will be observed in a more advanced period.
This paper investigates the link between forecast disparity and macroeconomic instability that results from the data revision of GDP and inflation in Japan. The recent Japanese case, which reflects the unconventional monetary policy conducted since 2013, is also examined. The empirical results show that such disparities do not cause economic instability; however, they have have done so after the unconventional and drastic monetary policy was conducted. On the other hand, exchange rates impacted economic stability for the total period. For the first part of the period under study (from 2000 to 2012), currency appreciation caused instability; however, for the more recent period, depreciation has caused such instability. Recently, macroeconomic instability has been linked with exchange rate movements.
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.
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.
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.
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.
what is the future of Pi Network currency.DOT TECH
The future of the Pi cryptocurrency is uncertain, and its success will depend on several factors. Pi is a relatively new cryptocurrency that aims to be user-friendly and accessible to a wide audience. Here are a few key considerations for its future:
Message: @Pi_vendor_247 on telegram if u want to sell PI COINS.
1. Mainnet Launch: As of my last knowledge update in January 2022, Pi was still in the testnet phase. Its success will depend on a successful transition to a mainnet, where actual transactions can take place.
2. User Adoption: Pi's success will be closely tied to user adoption. The more users who join the network and actively participate, the stronger the ecosystem can become.
3. Utility and Use Cases: For a cryptocurrency to thrive, it must offer utility and practical use cases. The Pi team has talked about various applications, including peer-to-peer transactions, smart contracts, and more. The development and implementation of these features will be essential.
4. Regulatory Environment: The regulatory environment for cryptocurrencies is evolving globally. How Pi navigates and complies with regulations in various jurisdictions will significantly impact its future.
5. Technology Development: The Pi network must continue to develop and improve its technology, security, and scalability to compete with established cryptocurrencies.
6. Community Engagement: The Pi community plays a critical role in its future. Engaged users can help build trust and grow the network.
7. Monetization and Sustainability: The Pi team's monetization strategy, such as fees, partnerships, or other revenue sources, will affect its long-term sustainability.
It's essential to approach Pi or any new cryptocurrency with caution and conduct due diligence. Cryptocurrency investments involve risks, and potential rewards can be uncertain. The success and future of Pi will depend on the collective efforts of its team, community, and the broader cryptocurrency market dynamics. It's advisable to stay updated on Pi's development and follow any updates from the official Pi Network website or announcements from the team.
What website can I sell pi coins securely.DOT TECH
Currently there are no website or exchange that allow buying or selling of pi coins..
But you can still easily sell pi coins, by reselling it to exchanges/crypto whales interested in holding thousands of pi coins before the mainnet launch.
Who is a pi merchant?
A pi merchant is someone who buys pi coins from miners and resell to these crypto whales and holders of pi..
This is because pi network is not doing any pre-sale. The only way exchanges can get pi is by buying from miners and pi merchants stands in between the miners and the exchanges.
How can I sell my pi coins?
Selling pi coins is really easy, but first you need to migrate to mainnet wallet before you can do that. I will leave the telegram contact of my personal pi merchant to trade with.
Tele-gram.
@Pi_vendor_247
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
Abhay Bhutada Leads Poonawalla Fincorp To Record Low NPA And Unprecedented Gr...Vighnesh Shashtri
Under the leadership of Abhay Bhutada, Poonawalla Fincorp has achieved record-low Non-Performing Assets (NPA) and witnessed unprecedented growth. Bhutada's strategic vision and effective management have significantly enhanced the company's financial health, showcasing a robust performance in the financial sector. This achievement underscores the company's resilience and ability to thrive in a competitive market, setting a new benchmark for operational excellence in the industry.
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
BYD SWOT Analysis and In-Depth Insights 2024.pptxmikemetalprod
Indepth analysis of the BYD 2024
BYD (Build Your Dreams) is a Chinese automaker and battery manufacturer that has snowballed over the past two decades to become a significant player in electric vehicles and global clean energy technology.
This SWOT analysis examines BYD's strengths, weaknesses, opportunities, and threats as it competes in the fast-changing automotive and energy storage industries.
Founded in 1995 and headquartered in Shenzhen, BYD started as a battery company before expanding into automobiles in the early 2000s.
Initially manufacturing gasoline-powered vehicles, BYD focused on plug-in hybrid and fully electric vehicles, leveraging its expertise in battery technology.
Today, BYD is the world’s largest electric vehicle manufacturer, delivering over 1.2 million electric cars globally. The company also produces electric buses, trucks, forklifts, and rail transit.
On the energy side, BYD is a major supplier of rechargeable batteries for cell phones, laptops, electric vehicles, and energy storage systems.
how can i use my minded pi coins I need some funds.DOT TECH
If you are interested in selling your pi coins, i have a verified pi merchant, who buys pi coins and resell them to exchanges looking forward to hold till mainnet launch.
Because the core team has announced that pi network will not be doing any pre-sale. The only way exchanges like huobi, bitmart and hotbit can get pi is by buying from miners.
Now a merchant stands in between these exchanges and the miners. As a link to make transactions smooth. Because right now in the enclosed mainnet you can't sell pi coins your self. You need the help of a merchant,
i will leave the telegram contact of my personal pi merchant below. 👇 I and my friends has traded more than 3000pi coins with him successfully.
@Pi_vendor_247
how can i use my minded pi coins I need some funds.
Can Treasury Inflation Protected Securities predict Inflation?
1. Can Treasury Inflation Protected
Securities (TIPS) predict Inflation?
Gaetan Lion, March 3, 2022
2. Treasuries Yield – TIPS Yield = Inflation Expectation
The equality above is why TIPS are very interesting. They reflect the bond market’s
inflation expectation over different terms including: 5, 7, and 10 years. This is since there
are regular Treasuries and TIPS of such maturities (or adjusted constant maturity) that we
can readily match and compare to derive the related inflation expectation over the
mentioned terms.
Unfortunately, TIPS data is very limited as it goes back only to 2003.
The source of the data is the Federal Reserve H.15 Selected Interest Rates.
2
3. What we are looking at
Inflation forecast:
5 year horizon:
Compare the difference in 5 year Treasuries – TIPS respective yield back in 2003 vs. the annualized
5 year inflation rate over the 2003 to 2008 period. Let’s say the Treasuries – TIPS difference back in
2003 was 2.50% and the annualized 5 year inflation rate over the 2003 to 2008 period was also
2.50%; we conclude that the prediction was perfect. So, any time series graph depicting this data
will start with January 2008 as the first observation.
7 year horizon:
Same as above, except that we look at an annualized 7 year inflation rate over the 2003 – 2010
period. And, the first observation on any graph will be January 2010.
10 year horizon:
Same as above, except that we look at an annualized 10 year inflation rate over the 2003 – 2013
period. And, the first observation on any graph will be January 2013.
3
5. 5
5 Year Inflation Expectation has near Zero correlation with the corresponding
annualized 5 year inflation rate
The inflation expectation (Treasuries – TIPS yields) is representative. The
measures of central tendencies (average, median) and volatility (standard
deviation) are very close. But, the correlation between the two variables is very
close to Zero.
6. 6
Modeling the relationship between 5 Year Inflation Expectation and Actual
If you had a perfect relationship: Expectation = Actual;
the linear regression equation would have a Slope of 1,
an Intercept of Zero, and an R Square of 1.
If you have no relationship between the two, the Slope
is Zero, the Intercept is equal to the Average of Actual
inflation, and the R Square is Zero.
The scatter plot, visualizing this regression, denotes a
model that is far closer to the situation depicting no
relationship between the two variables. Indeed, the
Slope and the R Square are close to Zero.
8. 8
7 Year Inflation Expectation slightly overstates the corresponding
annualized 7 year inflation rate
Overall, the 7 year inflation expectation overstates a bit the actual
annualized 7 year inflation rate. Indeed, the measures of central
tendencies are a bit higher. And, 73.8% of the Expectation observations
are greater than Actual.
9. 9
Modeling the relationship between 7 Year Inflation Expectation and Actual
On a relative basis, this linear regression
model is marginally better than the one for
5 year; but, it is still really poor with an R
Square that is still very close to Zero.
11. 11
10 Year Inflation Expectation slightly overstates the corresponding annualized 10
year inflation rate. And, correlation between the two is close to Zero
Overall, the 10 year inflation expectation overstates a bit the actual
annualized 10 year inflation rate. Measures of central tendencies are
higher. And, 72.5% of the inflation expectation observations are higher
than Actual.
12. 12
Modeling the relationship between 10 Year Inflation Expectation and Actual
This is another really poor linear regression model
indicating that there is close to no relationship
between the two variables. Indeed, the Slope is very
close to Zero, the Intercept very close to the Average of
Actual. And, the R Square also is very close to Zero.
13. Looking at all three horizons (5, 7, and 10 Year) together
13
14. 14
This graph shows the inflation expectation of
Treasury investors during the Great Recession by
the end of 2008.
Back in 2008, the inflation expectation for:
• Annualized 5 year inflation was reflected in 2013
(5 year period 2008 to 2013);
• Annualized 7 year inflation was reflected in 2015
(7 year period 2008 to 2015;
• Annualized 10 year inflation was reflected in
2018 (10 year period 2008 – 2018).
In 2008, investors expected a long standing
deflationary environment with negative annualized
inflation rates. They were influenced by the
recency effect associated with the onset of the
Great Recession.
As shown, on the previous slides these predictions
were way off.
15. 15
Actual Inflation vs. Expectation. Two completely different pictures
You can readily observe the mentioned downward deflationary spikes within the Inflation Expectation graph on the
right. These downward spikes are totally absent within the Actual Inflation data within the left graph.
16. 16
Considerations
The Federal Reserve QE activities are deemed to have a large influence on TIPS yield (potentially larger than on
regular Treasuries). If that is the case, it would depress TIPS yield and increase the related Inflation Expectation. The
latter is at odds with the Federal Reserve (Fed) objectives. Nevertheless, this could be an unintended consequence
that the Fed has not resolved.
The data is a bit ambivalent. It indicates that in average, the 7 year and 10 year Inflation Expectation are higher than
Actual Inflation. And, that this difference is very statistically significant but not very large (0.14% for 7 year and 0.27%
for 10 year). This supports the hypothesis that the Fed influences TIPS more than regular Treasuries. On the other
hand, when considering the 5 year horizon, the average Inflation Expectation is lower ( (-0.11%). And, it is statistically
significant only when using a lenient Alpha threshold of < 0.10).