The Misbehavior of Markets

Project Outline

1. Write a python program(s) to download end-of-day data last 25 years the major global stock market indices from Google Finance, Yahoo Finance, Quandl, CityFALCON, or another similar source.

[login to view URL] is a common assumption in quantitative finance that stock returns follow a normal distribution whereas prices follow a lognormal distribution For all these indices check how closely price movements followed a log-normal distribution.

[login to view URL] whether returns from these broad market indices followed a normal distribution?

For each of the above two parameters (price movements and stock returns) come up with specific statistical measures that clearly identify the degree of deviation from the ideal distributions. Graphically represent the degree of correspondence.

[login to view URL] of the most notable hypothesis about stock market behavior is the “Efficient market hypothesis” which also internally assume that market price follows a random-walk process. Assuming that Stock Index prices follow a geometric Brownian motion and hence index returns were normally distributed with about 20% historical volatility, write a program sub-module to calculate the probability of an event like the 1987 stock market crash happening ? Explain in simple terms what the results imply.

What does "fat tail" mean? Plot the distribution of price movements for the downloaded indices (in separate subplot panes of a graph) and identify fat tail locations if any.

[login to view URL] is often claimed that fractals and multi-fractals generate a more realistic picture of market risks than log-normal distribution. Considering last 10 year daily price movements of NASDAQ, write a program to check whether fractal geometrics could have better predicted stock market movements than log-normal distribution assumption. Explain your findings with suitable graphs.

*Use the following stock market indices for this project:

Use the following stock markets

1. Dow Jones (USA)

2. S&P 500 (USA)

3. Nasdaq (USA)

4 DAX (Germany)

5. FTSE (UK)

6. HangSeng (Hong Kong)

6. Kopsi ( Korea)

7. CNX NIFTY (India)

Beceriler: Excel, Mali Analiz, Python, İstatistiksel Analiz, İstatistik

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İşveren Hakkında:
( 9 değerlendirme ) Toronto, Canada

Proje NO: #17304632

Bu iş için 13 freelancer ortalamada $185 teklif veriyor


Hello, I can help with you in your project python program to download data. I have more than 5 years of experience in Excel, Financial Analysis, Python, Statistical Analysis, Statistics. We have worked on several si Daha Fazla

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(254 Değerlendirme)

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(46 Değerlendirme)

Hello, i have read the details provided..please contact me to discuss more on the project deadline and some other few things

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(15 Değerlendirme)

sounds like a very good project I am an expert python developer and consider this project as suiting to my statistics domain. please do chat with me.

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(3 Değerlendirme)

Hi, I am experienced with web scraping, data analysis, statistical modeling, stochastic processes, etc. would love to help you with this project. can we chat for more details? thanks, G.

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(8 Değerlendirme)

Hello! I am a python developer. I looked at your project and it seems interesting. I have all necessary skills required for this project. Ping me to discuss in detail.

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(16 Değerlendirme)

I am a Python developer with 4+ years of experience that specializes in multi-platform applications using PyQt, PySide/PyQt,Scrapy, BeautifulSoup 4, Pillow, Matplotlib, Xml, json, and csv modules, Celery As a develop Daha Fazla

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(1 Yorum)

Hey its Abbas Can do this job with cost and time efficient we can develop professional relation, trust worthy

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(0 Değerlendirme)

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Hi, I am an actuarial consultant working in the banking and insurance sectors. I graduated with a Masters of Mathematics degree from the University of Warwick in 2016 with a first class degree. I have sat and passed Daha Fazla

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in %bids___i_period_sub_35% gün içinde155%project_currencyDetails_sign_sub_37% %project_currencyDetails_code_sub_38%
(0 Değerlendirme)

I'm trained as a financial engineer and I've done many similar assignments like this during my education. I can help you with this project

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Professional team, good at machine learning and big data analysis, there are former big data analysts of aliyun among the team members, hoping to help you

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