How seriously is past volatility a fair estimate of future volatility or risk useful in financial models?
Historical Volatility based on empirical data sample observations.
Data Sample Observations can be historic baseline data for a particular asset class/exposure or simulated data derived from iterations using some historical data sets.
Another branch of data which can be used to observe future volatility is exploratory data drawn from within a sample or a population using data #visualization tools.

This technique is becoming popular as data science and machine learning advancements are taking place
with the support of modern programming languages such as #Python, AI - #Neural #Networks, and coding machines.
I would not discuss the difference between Simulation and Emulation Models in this reply. Emulation is used as a computer-aided technique where historical data sets are not present as baseline data to make future projections/simulations/ extrapolations.
Most of the financial institutions do not use emulated models to make projections of the volatility surface.
Design space(market space) of a financial market traded product cannot be compared to a tangible product which is developed through a manufacturing engineering process using SPC - Statistical Process Control Assumptions.
Now whether past is a good indicator of the future per se?
In Financial Markets it is not!
Most of the modelling crisis and market crashes are strongly correlated.
Let's begin from #LTCM and go right up to the banking (global credit crisis) and if we can extend a little further and include Swiss France Devaluation that took place
a few years ago. The market tails are deep and are getting deeper as every day goes by!

Normal probability distribution model (everybody's favourite whipping boy) can no longer be relied upon to predict risk in the future with certainty.
Hence, historical volatility can at best only be used as a proxy to indicate future risks and volatility using some baseline assumptions. One of them is that the market values will remain normal and stable over the time series.
Model Validation is now emphasized upon by BIS as a primary form of operational risk, and several measures were taken to tackle this problem after BASEL 2 failed to live up to our expectations.
Basel 2.5 and Basel 3 made some headway in dealing with the problem by issuing renewed guidelines on model back-testing, stress testing, and model validation risks. @BIS_org
All of this is now included within the Operational Risk Taxonomy.

Most of the banks have hired model validation and model risk experts to design a model risk governance architecture within the much larger #ERM framework.
All of this is now included within the Operational Risk Taxonomy.

Most of the banks have hired model validation and model risk experts to design a model risk governance architecture within the much larger #ERM framework.
Another way of finding out whether Implied Volatility and Historical Volatility in the Spot Market could differ, s by observing the forward markets
you can use a variant of the BSOP Black Scholes Option Pricing Model to compute Implied Volatility using real-time option premiums.
But this can only be done if an Active Traded Options Market for certain marketable security or other asset class exists in either local or international markets.
Fx - options traders use implied volatility instead of historical volatility to price and dynamically hedge option portfolios.

The #VIX - Volatility Index in the USA, is another quantifiable BI tool which provides forward-looking volatility metrics to traders.
If you are living in the USA, it becomes much easier to compute and measure implied volatility using this index.

In Financial #Econometrics various ARCH / #GARCH Models can also be used to forecast volatility patterns. Volatility always exists in the form of clusters.
Tail dependencies are often found to be very strong in financial markets.

An Inverted -S-shaped Curve can be further explored to study the data outliers and patterns for an asset class in a traded market.
Do study data mining methods as they are now being used in machine learning in Finance to get another perspective of how volatility true and false positives and negatives affect overall forecasting risk and CAP - Cumulative Accuracy profile and AR - Accuracy Ratios.
But going back to your question!

Can historic data be used to study the future with 100 per cent certainty and accuracy!


• • •

Missing some Tweet in this thread? You can try to force a refresh

Keep Current with Risk Manager(Banks,Asset Management,Insurance)

Risk Manager(Banks,Asset Management,Insurance) Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!


Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @SAH16928046

11 Jan
Would you start your career as a model validator in a major bank if you hope one day to become a front office quant?
@GARP_Risk @actuarynews
@Actuary_Dot_Org @actuarialpost
@iSixSigma @artemisbm @SOActuaries
@CQFInstitute @aier @CFAinstitute
Many Financial / Middle Office Risk and other Quantitative Economics/ Financial Market-led research roles interface at one level or the other across FIs.
I don't know if a bank uses Employee Rotation, to foster employee learning, training and development across the 3LOD Model?
But, most of the banks, in the Advanced Markets, to use job rotation as a tool, to disseminate professional knowledge and understanding of financial market operations, among their employees.
Read 21 tweets
22 Dec 20
Did the Asian Financial Crisis (1997) had any influence in the 2008 crisis?
No, Not really!

#SOX Compliance came after ENRON and WORLD COM Frauds and Financial Reporting Failures.

You cannot mix the two events.
Asian Financial Crisis came about as a result of Unsound Macroeconomic Policies, disrespect for stabilization, excessive price competition among trading nations, lack of Asset Liability Risk Management done at the Central Banks, monopolistic market structures,
Read 33 tweets
13 Dec 20
What are the different ways in which banks can reduce and manage different types of risk?
@GARP_Risk @actuarynews @SOActuaries @RiskDotNet
By understanding what risk is in terms of its purported definition?
If you get the definition wrong, you won't understand the technical expression in either theory or practice.
So, get that right first!
#Risk is a two-sided phenomenon, like a coin!

2. The one side of the coin presents an Opportunity!
2.The another side of the coin presents a Threat!

On which side would you like to do betting?
Read 18 tweets
11 Dec 20
What is the difference between financial econometrics, econometrics and quantitative finance?
@GARP_Risk @CQFInstitute @SOActuaries
Financial Econometrics basically utilizes Financial Market Data to build mathematical and statistical financial models and later analyze the statistical significance and make predictions.
It is generally used by risk managers and economists to predict(forecast) and study the return market characteristics. GARCH models and other Time Series Models are used to study the pattern of Return Volatility Clusters, Tail Dependence Events, Covariances,
Read 14 tweets
11 Dec 20
How do I know if #Actuarial Science is meant for me?
@SOActuaries @actuarynews
It is not easy to assess your aptitude in a given subject by only passing high school exams or getting good grades in Math, Statistics and/or Further Maths(Advance Math) at the higher secondary level.
I know many Math geniuses, who entered into Actuarial Science and Risk, but later moved out because they didn't want to restrict themselves & their field of specialization to just Insurance and risk management sectors in the economy.
So, it all depends on whether you would like to work solely within the risk management area and insurance, or you would like to have a more broad-based career.
Read 4 tweets
11 Dec 20
How do I secure a role in FRM - Financial Risk Management at Fis Financial Institutions?
What would be the starting point for a person interested in risk management?
@GARP_Risk @actuarynews
Do a basic undergraduate or preferably a postgraduate degree in Quantitative Finance/ FE Financial Engineering / Risk management or Actuarial Science.
Even a degree in other highly numerate fields such as Data Science and Machine Learning can help you in different areas of FRM.
Some students, who come from other numerate backgrounds, such as Engineering, Physics, Mathematics, Statistics, or even Computing Sciences with a strong background in Technology or Programming/Coding, can also end up doing well in the FRM Profession.
Read 8 tweets

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!