代做FIN 418: Quantitative Finance with Python代做留学生Python程序

FIN 418: Quantitative Finance with Python

Final Project

Idea Generation and Road Show

Your group is an investment vehicle. You should design an investment strategy proposal, implement it, and

advertise it to potential sophisticated investors.  You should think about who would be a good clientele for this strategy.

The strategy has to be “ new,” i.e. something that we did not implement in python either in a class notebook or in a homework. You will have to do your own research to find something interesting. You have to explain the strategy in detail, discuss its pros and cons, and argue why your strategy choice is better than the alternative ones. It can involve any asset class, as long there is data on publicly traded prices and returns that you can use in you analysis.

Deliverables:

•    One page (font 12) summary. It should contain (at least)

o Name of fund, name and university ID of both principals

o A description of the trading strategy

o Why should the investor follow your strategy as opposed to alternative strategies?

o Is your strategy delivering alpha? Is it a mispricing that will bearbitraged away, or is it a compensation for risk?

o What are the main costs and risks associated with your strategy?

o Quantify the expected excess return, volatility, and Sharpe ratio, Appraisal ratio, beta with respect to systematic factors, cumulative returns, when it performs poorly/well, …

•    (at most) 5 pages (font 12)  prospectus where you elaborate on the points presented in the summary. Explain the strategy incomplete detail. You can present additional empirical results, sub-sample analysis that backup your argument of why this strategy is a good investment for the investors that you have in mind- Use tables and plots! The more the merrier! But always explain what you show. Do not show anything that you do not care to explain. Do not explain anything that you do not show. All the tables and plots should be copies of what you generate in Python! (Just use screenshots)

o (1) and (2) should be submitted as one pdf of 6 pages (maximum)

•   Code in jupyter notebook that replicates the strategy and the numbers and figures you use in the one page summary and prospectus. The code should have comments so we can understand what you are  doing and also the data that uses. You should submit the .ipynb file

•    2 minutes video where you pitch the strategy to a potential investor. (one person or more than one,

it's up to the group to decide). You have to clearly to present your idea and you are free to refer to the results you present in your one page/5 page summary.

•     DO not prepare additional slides! I would like your 6 page pdf to be clear enough that you can just go

through the highlights in the video —talking about the most important plots and tables.

You should upload this video to Youtube and put a link to it in the one page summary.

•   Your write-up should contain a section describing the empirical procedure- How you construct the strategy and how you evaluate it. Someone reading this should be able to replicate your code.

•   You should also Address and justify the following questions:

o Quantify the strategy's performance in terms of exposures to other risk factors.

o Estimate factor models'alphas and beta. For instance, use the CAPM and/or FF3 model

o To validate your strategy, which robustness exercises do you implement?

o Be specific about the sample period/data that you use.

-     Be Creative!

-     Your material will be available online for public view. So please deliver something professionally looking!

-     - start simple and build from there.

How are you going to be evaluated?

I am not going to evaluate you based on the strategy performance, i.e. the final output. I will evaluate you by the quality of your process. The rationale behind the strategy, the sophistication and complexity behind it’s    implementation, how much attention goes into the details of it, the quality of your statistical analysis, and the quality and sophistication of your discussion and analysis of the risks involved in the strategy.

ONE  IDEA (to make your life easier)

I know that lots of you are feeling overwhelmed and the thought of having to work with stock level data might make you even less hopeful that you can accomplish something in a few days. So here is a project idea that everyone could pursue.

One important thing that we learned in the class is that there are factors beyond the market portfolio that have earned very sizable risk-adjusted returns relative to the market portfolio. So some investors could benefit of investing in them. The question is how? While we have lots of investment products that hold the total market   portfolio and charge tiny fees, only now there has been of investment products claiming to get you exposure to the factors we discussed in class (and many others).

Suppose you are opening a fintech shop that will get retail investors exposure to the factors. I want you to research the ETF options available to trade, download their returns, and conduct a careful analysis of how much exposure to the different factor these ETFs give investors, analyze the costs involved in each ETF (such as expense ratios, tracking error, alphas, and illiquidity) , and come up with a set of ETFs that would get your clients the cheapest way to get exposure to some set of factors.

All the ETF providers provide return series in their website, so you can easily download and construct a rock solid ETF database. You don’t need to look at all ETFs, but simply focus on the ones that claim to get you exposure to equity factors.

Here are some useful links

https://www.ishares.com/us/products/etf-product-list#!type=ishares&tab=overview&view=grouped&fac=43511

https://investor.vanguard.com/etf/list#/etf/asset-class/month-end-returns

https://finance.yahoo.com/screener/etf/new