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The Misbehavior of Markets

$30-250 USD

Closed
Posted over 5 years ago

$30-250 USD

Paid on delivery
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. 2. It 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. 3. Verify whether returns from these broad market indices followed a normal distribution? 4. 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. 5. One 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. 6. 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. 7. It 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.
Project ID: 17341869

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10 proposals
Remote project
Active 6 yrs ago

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10 freelancers are bidding on average $208 USD for this job
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Hi there..... Warm Greetings We came along with your request for excel and python task and we reviewed your project description. We'd like to help you with confidence and satisfying results... We have professionals working here with 100% results and more creative and renovative ideas for our clients ! We have worked on several similar projects before! We are offering our services for more than 5 years in the field of Excel, Python, Software Architecture, Statistical Analysis, Statistics We have worked on 350+ Projects. Please check the profile reviews Feel free to message us to discuss briefly about your project !
$250 USD in 3 days
4.9 (357 reviews)
8.0
8.0
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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 I am also working to be more of a Full-Stack developer, so that means I have more experience than indicated by just my Python background. I enjoy working with passionate people who know what it is they need and where they are headed. I've worked with individual people and with organizations in teams of 3+ people from all over the world.
$194 USD in 3 days
4.9 (36 reviews)
5.2
5.2
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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.
$125 USD in 2 days
4.7 (35 reviews)
5.4
5.4
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We are a team of engineers and data scientists experienced with machine learning, statistics, forecasting and data analysis with Python. If you have 7-8 days, we can help you with this project.
$250 USD in 8 days
4.9 (16 reviews)
4.6
4.6
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Hello, I have extensive experience in python and financial markets and would love to help you out on this project. I currently work part-time as a consultant for a long/short equity hedge fund part/time in Palo Alto, CA and have a Masters in financial mathematics/engineering. I think I can be of great help to you. My credentials are below: * Responsible for creating proprietary quantitative models and algorithmic trading strategies for long/short equity optimization models with specific risk and return parameters specified by the investor profile, utilizing machine/deep learning, along with Q reinforcement learning agents. •Created predictive vectorized/event-based machine learning models utilizing multivariate/logistic regression, lasso/ridge regression, linear/quadratic discriminant analysis, decision trees, K neighbors, Naive Bayes, random forest, support vector machine, Adaptiveboost, GradientBoost, XGB, and portfolio optimization to maximize return and minimize volatility for various investor risk profiles. •Responsible for deep learning modeling using recurrent neural networks, Tensorflow, nltk, sentiment analyzer, Keras LSTM, and convolutional neural networks, in attempt to predict specific asset class forecasted prices through stocks, forex, bonds, futures, ETFs, and other derivatives. •Designed a proprietary machine/deep learning long/short intraday algorithm utilizing the Interactive Brokers API, IB_Insync python library. Speak soon! Sam
$244 USD in 3 days
5.0 (8 reviews)
4.1
4.1

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