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The Model Thinker #16 : Markov Models
By Growing your tree of prosperity  •  April 30, 2019

Markov models capture systems that transition probabilistically between a finite set of states.

One application in finance are Bond credit ratings. A "AAA" bond has a 95% every year of retaining it's high credit rating but there is a 5% of it being downgraded to "AA". In similar vein a "CCC" bond has a probability to be upgraded to "B" or go into default. Credit analysts construct a table of transition probabilities to gain a helicopter view of the bond markets.

A Markov process can converge into a unique statistical equilibrium if it satisfies four conditions :

a) It has a finite set of states.
b) Probabilities of transition between each state is fixed.
c) The system can get from any state or any other state through a series of transitions.
d) The system does not produce a deterministic cycle through a sequence of states.

If only these four conditions are met, the number of bonds

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By Growing your tree of prosperity
I have recently completed my Juris Doctor and I am waiting to be called by the Singapore Bar. For the past 15 years I was an IT manager and I have worked in multinationals, financial exchanges, trade unions and even a government agency. I started my career as an AS/400 administrator and moved on to manage IT projects and operations
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