FIN 418: Quantitative Finance with Python Final Project
Quantitative Finance代写 Your group is an investment vehicle. You should design an investment strategy proposal, implement it, and advertise
You should work with your homework group.
Idea Generation and Road Show Quantitative Finance代写
Submission due: 11/18 Midnight
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 (atleast)
- A description of the tradingstrategy
- Why should the investor follow your strategy as opposed to alternativestrategies?
- Is your strategy delivering alpha? Is it a mispricing that will be arbitraged away, or is it a compensation for risk?
- What are the main costs and risks associated with yourstrategy?
- Quantify the expected excess return, volatility, and Sharperatio,…
- 5 pages (font 12) prospectus where you elaborate on the points presented in the summary. Explain the strategy in complete 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
- This two documents should be submitted as one pdf of 6pages
- Name of file should be group name andnumber
- Code in jupyter notebook that replicates the strategy and the numbers and figures you use in the one page summary andprospectus Quantitative Finance代写
- 2-3 minutes video where the group 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 torefer
to the results you present in your one page/5 page summary. 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
- You should also Address and justify the followingquestions:
- Quantify the strategy’s performance in terms of exposures to other risk
- Estimate factor models’ alphas and beta. For instance, use the CAPM and/or FF3model
- To validate your strategy, which robustness exercises can youimplement?
- Be split about the sample period/data that you Be Creative!
Your material will be available online for public view. So please deliver something professionally looking!
How are you going to be evaluated? Quantitative Finance代写
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 rational 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 10 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.Quantitative Finance代写
You would them come up with a process to discuss how you would combine these different factor, with portfolio weights that are potentially client dependent.
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
Useful places to get data
Tips on where to get data Quantitative Finance代写
Wrds (https://wrds-web.wharton.upenn.edu/wrds/).
Fred (https://fred.stlouisfed.org/categories/32991)
Global Financial Data (https://www.globalfinancialdata.com/gfdplatform/Account/Login?ReturnUrl=%2fgfdplatform%2f)
(need to be at U of R)
Ken French website http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html
AQR website https://www.aqr.com/Insights/Datasets
Useful places to get ideas that can be quickly implemented are academic papers. I put a list down below. But don’t fell constrained in any way. In fact I will reward a group that thinks something entirely new or a clever deviation of a classic strategy. So this list below is just for your convenience Quantitative Finance代写
(You can find them by putting these titles in Google Scholar)
Summary of all anomalies known to men: Harvey, Campbell, Yan Liu and Heqing Zhu, “ . . . and the Cross- Section of Expected Returns”, Review of Financial Studies, 2016, 29, 5-68.
Fama, Eugene and Kenneth French, “Common Risk Factors in the Returns on Stocks and Bonds,” 1993, Journal of Financial Economics, 33, 3-56.
Lamont, Owen and Richard Thaler, “Can the Market Add and Sub- tract? Mispricing in Tech Stock Carve-Outs,” 2002, Journal of Political Economy.
Daniel, Kent and Sheridan Titman, “Evidence on the Characteristics
of Cross-Sectional Variation in Stock Returns,” 1997, Journal of Finance, 52, 1-33.
Momentum Quantitative Finance代写
Jegadeesh, Narasimhan and Sheridan Titman, “Returns to Buying Winners and Selling Losers: Implications for Stock Market E_ciency,” 1993, Journal of Finance, 48, 65-91.
Moskowitz, Tobias and Mark Grinblatt, “Do Industries Explain Mo-
mentum?”, 1999, Journal of Finance, 54, 1249-1290.
Grinblatt, Mark and Tobias Moskowitz, “Predicting Stock Price Movements from Past Returns: The Role of Consistency and Tax-Loss Selling”, 2003, Journal of Financial Economics.
Daniel, Kent and Tobias Moskowitz, “Momentum Crashes,” 2015, forth- coming Journal of Financial Economics.
Novy-Marx, Robert, “The Other Side of Value: The Gross Profitability
Premium,” Journal of Financial Economics, 2013.
Novy-Marx, Robert, “The Quality Dimension of Value Investing,”Working paper,
2013.
Asness, Cliff, Andrea Frazzini, and Lasse Pedersen, “Quality Minus Junk,” AQR working paper, 2014.
Frazzini, Andrea, and Lasse H. Pedersen, Betting against Beta,” 2013, Journal of Financial Economics.
Frazzini, Andrea, and Lasse H. Pedersen, “Embedded Leverage,” 2013, Working paper.Quantitative Finance代写
McLean, David and Jeff Pontiff_, “Does Academic Publication Destroy
Stock Return Predictability?” 2016, Journal of Finance., 71, 5-32.
Fama, Eugene and Kenneth French, Dissecting Anomalies,” Journal of Finance, 2008, Volume 63, 4, 1653-1678.
Nagel, Stefan, “Evaporating Liquidity,” Review of Financial Studies, 2012, 25, 2005-2039.
Pastor, L. and Stambaugh, R. F., “Liquidity risk and expected stock
returns,” Journal of Political Economy, 2003.
Fama, Eugene and Kenneth French, “Size, value, and momentum in international stock returns,” Journal of Financial Economics, 2012, Volume 105, Issue 3, 457-
472.
Asness, Cli_, Tobias Moskowitz, and Lasse Pedersen, “Value and Mo- mentum Everywhere,” 2013, Journal of Finance.
Moskowitz, Tobias, Yao Hua Ooi, and Lasse Pedersen, “Time Series Momentum,” Journal of Financial Economics, 2012, 104(2), pp. 228-50.
Brunnermeier, Markus, Stefan Nagel, and Lasse H. Pedersen, “Carry
Trades and Currency Crashes,” 2008, NBER Macroeconomics Annual, 23, 313-348.
Koijen, Ralph, Tobias Moskowitz, Lasse H. Pedersen, and Evert Vrugt, “Carry,” 2015, Working paper. Lustig, H., N. Roussanov, and A. Verdhelan, “Common Risk Factors in Currency
Markets,” 2012, Review of Financial Studies.
Fama, Eugene and Kenneth French, “A Five-Factor Asset Pricing Model,” 2015, Journal of Financial Economics.Quantitative Finance代写
Carhart, Mark, “On Persistence in Mutual Fund Performance,” 1997,
Journal of Finance, 52, 57 – 82.
Mitchell, Mark and Todd Pulvino, 2001, “The characteristics of risk and return in risk arbitrage” Journal of Finance 56, 2135-2176.
Coval, Joshua and Tobias Moskowitz, “The Geography of Investment: Informed Trading and Asset Prices,” 2001, Journal of Political Economy vol. 109, No. 4, 811-841.
Cohen, Lauren and Andrea Frazzini, “Economic Links and Predictable
Returns,” 2008, Journal of Finance.
Frazzini, Andrea, Lauren Cohen and Christopher Malloy, 2008, “The Small World of Investing: Board Connections and Mutual Fund Re- turn” Journal of Political Economy 16.
Andrew Ang, Robert J Hodrick, Yuhang Xing, and Xiaoyan Zhang. “The cross-
section of volatility and expected returns. The Journal of Finance, 61(1):259{299, 2006.
Dong Lou and Christopher Polk. Comomentum: Inferring arbitrage activity from return correlations. 2013.
John H Cochrane. Presidential address: Discount rates. The Journal of Finance, 66(4):1047{1108, 2011. Read pages 1047{1058.Quantitative Finance代写
John Y Campbell and Samuel B Thompson. Predicting excess stock returns out
of sample: Can anything beat the historical average? The Review of Financial Studies, 21(4): 1509{1531, 2007.
Jakub W Jurek and Erik Sta_ord. The cost of capital for alternative investments. The Journal of Finance, 70(5):2185{2226, 2015.
Mark Broadie, Mikhail Chernov, and Michael Johannes. Understanding index option returns. The Review of Financial Studies, 22(11):4493{4529, 2009.
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