Screenshot from account.
My portfolio heavy in to Bonds. TLT/TMF.. Monthly OOM call and their premiums.
Hoping for good return this year ( if FED starts reducing interest rates)
Daily I help teams with solution engineering aspect of connected vehicle data projects. (massive datasets & always some new datasets with new car models aka new technologies.) Lately in the spare time, applying some of the ML/Deep learning techniques on datasets (many are create based on observations of real datasets)To Share some thoughts on my work (main half of this blog) and the other half will be about my family and friends.
Screenshot from account.
My portfolio heavy in to Bonds. TLT/TMF.. Monthly OOM call and their premiums.
Hoping for good return this year ( if FED starts reducing interest rates)
2023 is a mixed year. ( kind of little early to long term bonds.. both vanguard and TLT... both recovered a lot.) need to see my luck in 2024. hopefully bond will give much needed returns to my account.
Stocks side, heavy in to energy and healthcare. ( both are duds in 2023.) now all bet in to 2024.
Cash is earning 4.7%. GAS is looking attractive, will wait till the year end and may make a move.
Everything's Bigger in Texas, Including My Insurance Premiums hike:
From $380 to $530 aka 39% Price Increase!
Waiting on other shocks.
In my earlier post, I
mentioned that I work as a solution architect for a vehicle data platform. In
this post, I will discuss how we use trip data information to score driver behavior,
using what we call a "smart driver" score. Like a credit score, a
driver score is an indicator of a driver's behavior, which can be used for
things like usage-based insurance.
The term "smart
driver" typically refers to an individual who can optimize their driving
behavior to improve safety, fuel efficiency, and comfort. A smart driver might
use advanced technologies, such as real-time traffic information or
driver-assist features, to make informed decisions about how to operate their
vehicle. They might also adjust their driving habits, such as reducing speed,
avoiding sudden acceleration and braking, and following a consistent pace, to
minimize fuel consumption and emissions.
Smart driver programs and
initiatives are often designed to educate drivers about the benefits of safe and
efficient driving, and to provide tools and resources to help drivers make
informed decisions on the road. Some programs may also offer incentives, such
as rewards or discounts, to encourage drivers to adopt safe and efficient
driving practices.
In the context of
connected and autonomous vehicles, the term "smart driver" may also
refer to the vehicle's advanced systems and technologies, which are designed to
optimize driving performance and provide a more comfortable and efficient
driving experience.
The term "smart
driver" is used by a variety of organizations and companies, including
automotive manufacturers, government agencies, non-profit organizations, and
technology companies.
Automotive manufacturers, such as
Tesla and General Motors, may use the term to describe the advanced
driver-assist technologies and safety features that they offer in their
vehicles.
Government agencies, such as the
National Highway Traffic Safety Administration (NHTSA) and the Environmental
Protection Agency (EPA), may use the term to describe their initiatives to
promote safe and efficient driving practices.
Non-profit organizations, such as
the National Safety Council, may use the term to describe their educational
programs that aim to promote safe and responsible driving practices.
Technology companies, such as
telematics providers and software developers, may use the term to describe
their products and services that aim to improve driving performance and provide
a more efficient and connected driving experience.
Overall, the term "smart
driver" is used to describe individuals and organizations that are focused
on optimizing the driving experience, and promoting safe, efficient, and
sustainable driving practices.
Core trip concepts, data collection,
scoring methodology
When owner is driving vehicle from point A to point B, Ignation ON/OFF cycle, smart driver system will rate your trip based on various factors such as the duration of the trip, the condition of the road, the traffic, and your driving experience. Here are some examples of factors you might consider when rating a trip:
Drive Time: How long did it take
you to complete the trip? Was it faster or slower than expected?
Driving experience: Did you enjoy driving the vehicle? Was it easy to handle, or were there any challenges with maneuvering or controlling the vehicle?
Comfort: Was the trip
comfortable? Did you experience any issues with the vehicle, such as discomfort
from the seats, or noise from the engine or road?
Road condition: Was the
road in good condition? Were there any obstacles, such as potholes or
construction, that impacted your trip?
Traffic: Was there a lot of traffic on the road? Did you experience any delays or slowdowns due to congestion?
In 1993, the global financial markets had a
positive performance overall. The Dow Jones Industrial Average (DJIA) had a
total return of 8.25% for the year, while the S&P 500 had a total return of
4.46%. The NASDAQ also had a positive performance, with a total return of
7.62%. The yield on the 10-year Treasury note also fell during this period,
which generally indicates a strong bond market.
In terms of international markets, the Nikkei 225 in Japan had a
total return of -0.31%, while the FTSE 100 in the United Kingdom had a total
return of 3.57%. The DAX in Germany had a total return of 9.58%.
The U.S. economy continued to expand during this period, with
the Gross Domestic Product (GDP) growing by 2.9% in 1993, and the unemployment
rate falling to 6.9%. The inflation rate was also relatively low, at 3.0%.
It was worth mentioning that the interest rates were relatively
high at that time, with the Federal funds rate at 3.25% by the end of 1993.
Overall, the financial markets in 1993 were characterized by
steady growth, low inflation, and a strong bond market.
I am working
in vehicle data management system design, development, and support.
While I can not specify
fine details, (i.e. data used by specific auto insurance providers), data is
being collected heavily and used by many.
1.
Risk assessment: By
collecting and analyzing data about a vehicle's usage, insurance companies can
better understand the risks associated with insuring that vehicle. For example,
data about a vehicle's speed, acceleration, and location can be used to assess
the likelihood of an accident occurring.
2.
Premium calculation:
Based on the risk assessment, insurance companies can calculate the premium for
insuring a vehicle, taking into account the specific risks associated with that
vehicle.
3.
Fraud detection: By
collecting data from onboard systems and other sources, insurance companies can
detect instances of fraud, such as staged accidents or false claims.
4.
Claims management: In
the event of a claim, insurance companies can use the data collected by the
vehicle data management system to verify the details of the claim and assess
the damage to the vehicle.
5.
Usage-based insurance:
Insurance companies can offer usage-based insurance plans, which allow drivers
to pay premiums based on the actual usage of their vehicles. By collecting and
analyzing data about the usage of vehicles, insurance companies can determine
the appropriate premium for each driver.
Here are some popular vehicle data signals that are commonly collected and analyzed by vehicle data management systems.
1.
Speed: The speed at
which the vehicle is traveling can provide insights into the driving behavior
of the driver and the likelihood of an accident occurring.
2.
Acceleration: The rate
at which a vehicle accelerates can provide insight into the driving style of
the driver and the likelihood of an accident occurring.
3.
Location: By tracking
the location of a vehicle, insurance companies can determine the risk
associated with insuring that vehicle, based on factors such as the road
conditions, traffic density, and likelihood of accidents.
4.
Engine data: Engine
data, such as RPM and fuel consumption, can provide insights into the health
and performance of a vehicle, which can impact the likelihood of an accident
and the cost of repairs.
5.
Brake data: By tracking
the usage of a vehicle's brakes, insurance companies can assess the driving
behavior of the driver and the likelihood of an accident occurring.
6.
Steering data: Steering
data, such as the angle of the steering wheel and the force applied to the
steering wheel, can provide insight into the driving style of the driver and
the likelihood of an accident occurring.
7.
Fuel data: Fuel data,
such as the amount of fuel consumed and the fuel efficiency of a vehicle, can
provide insights into the driving behavior of the driver and the likelihood of
an accident occurring.