• C++ Programming for Financial Engineering
    Highly recommended by thousands of MFE students. Covers essential C++ topics with applications to financial engineering. Learn more Join!
    Python for Finance with Intro to Data Science
    Gain practical understanding of Python to read, understand, and write professional Python code for your first day on the job. Learn more Join!
    An Intuition-Based Options Primer for FE
    Ideal for entry level positions interviews and graduate studies, specializing in options trading arbitrage and options valuation models. Learn more Join!

Time series questions

Joined
12/4/17
Messages
5
Points
11
1) What is so special about financial time series and among different asset classes? (cash vs derivatives as well)
2) What subtopics in time series should one focus on? (maybe FI specifically)
3) Does it make sense to perform time series analysis on stuff that's not moderately liquid?
4) What happens if my data is not great? How does that affect the analysis relative to work done with good data?
5) In the skill differential MFE vs a Stats PhD, how much of an disadvantage is the MFE at wrt to most tasks? Like what is an interesting project that you would want a stats PhD to perform over a MFE guy?
6) What is your opinion of python vs R vs julia for time series?
7) Besides Tsay, Hamilton seems heavy, any other book suggestions?
 
Last edited:
1) What is so special about financial time series and among different asset classes? (cash vs derivatives as well)
2) What subtopics in time series should one focus on? (maybe FI specifically)
3) Does it make sense to perform time series analysis on stuff that's not moderately liquid?
4) What happens if my data is not great? How does that affect the analysis relative to work done with good data?
5) In the skill differential MFE vs a Stats PhD, how much of an disadvantage is the MFE at wrt to most tasks? Like what is an interesting project that you would want a stats PhD to perform over a MFE guy?
6) What is your opinion of python vs R vs julia for time series?
7) Besides Tsay, Hamilton seems heavy, any other book suggestions?


Lots to address here.

1. Serial correlation, seasonality, mean reversion, time-varying volatility (stochastic vol, ARCH/GARCH).

2. See above.

3. Without liquidity, you have no idea if your price is real. Just because there’s a price observation doesn’t necessarily mean that anything transacts there.

4. Use what you have. Clean it where justified (but document how you cleaned it).

5. Stat people have much more experience with these techniques. MFEs usually take a single course. (I teach in several programs. Most students have little, if any exposure to TS ex ante. I’d ask a stat guy to study seasonality. An MFE would likely get stumped on anything past dummy variables and basic ARIMA.

6. I’m clueless here.

7. Start with thenmany summary papers available as .pdfs from major universities.

Hope this helps. PM me to discuss more. (Me: MS in stats)
 
Lots to address here.

1. Serial correlation, seasonality, mean reversion, time-varying volatility (stochastic vol, ARCH/GARCH).

2. See above.

3. Without liquidity, you have no idea if your price is real. Just because there’s a price observation doesn’t necessarily mean that anything transacts there.

4. Use what you have. Clean it where justified (but document how you cleaned it).

5. Stat people have much more experience with these techniques. MFEs usually take a single course. (I teach in several programs. Most students have little, if any exposure to TS ex ante. I’d ask a stat guy to study seasonality. An MFE would likely get stumped on anything past dummy variables and basic ARIMA.

6. I’m clueless here.

7. Start with thenmany summary papers available as .pdfs from major universities.

Hope this helps. PM me to discuss more. (Me: MS in stats)
well said
 
Back
Top