Explain everything using matlab codes

Explain everything using matlab codes

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Hi

First, you need to install matlab before taking my lectures because I explain everything using matlab codes. BTW, you can use R in case you can use it (Rapach provides R codes in his website. Most of stuffs I am going to teach can be done with these codes) but I will provide only limited support on R.

Second, if you don’t have any access to Database, then that will be really issue. It turns out you may not be able to get any data from Bloomberg. Anyway, in that case, could you search for Datastream tickers of your predictors? For example, you are going to say you need short term interest rate for your chosen country and need to tell me the ticker for that is xxxx. Then I will be able to collect data xxxx for you.

Dear Students

I would like to provide some info. on datastream ticker (called Mnemonic). You need first search for Mnemonics of aggregate market return/risk free rate for your chosen country. I am attaching some references you can use when you try to locate these.

Hello students

At least you have an access to WRDS. For example, you can get an excess return to the market index from MSCI available in WRDS. I think you could find some useful data in WRDS while you still need to ask me to get most of data from datastream. BTW, if you want to get macroeconomic variables (e.g., interest rate and exchange rate, etc), you could use data service from IMF/OECD/US FED (Saint louis and FED BOARD). These are free.

Hello Students

I have posted the first video clip on lecture slide 1 and one matlab code. This is available under the folder ‘Return Predictability’ inside ‘Week 9 and 10: Regime Switching Models’. BTW, please read all of my emails from June 2. Some of you haven’t responded to my email at all. I am a bit worried. Please let me know if you have any problem.

I would like to confirm several things (For more info. on the following things, you need to read my previous emails).

1) Program: you should have matlab in your pc.

2) Data: you should have an access to WRDS (please check my previous email on how to get it). And if you need certain data series for your dissertation, you could find the ticker (mnemonic) of that for Datastream (please see datastream.zip I sent for some info.). If you provide me that information, then I could get the data for you. For macroeconomic variables, you could use IMF/OECD/US Fed (saint louis)

3) please read my previous emails on how to search for predictors in your chosen country.

4) You also need to provide me a list of recent papers on return predictability on your chosen asset by the end of this week.

Dear Students

I have uploaded all lecture slides/matlab codes you need. Please notice that I have changed the name of matlab codes in lecture 2 folder (perhaps it would be easier if you download all files again).

I will post my next video clips within a few days. BTW, you need to collect the returns to your chosen asset and risk-free rates for your country. I have one announcement on this. You will find both $ returns and local currency returns for your chosen asset. Normally you will use local currency market return and risk free rate. Here the assumption is that you are an investor in that country, and want to invest there. On the other hand, if you use $ market return and $ risk-free rate, that means you are a us investor and want to invest into that market. Now, in this case, you have to deal with what would impact the exchange rate of US $ against the local currency (since $ return includes the changes in exchange rate), and it involves with bunch of exchange rate related theory/story/variables. So, I think it would be more appropriate for you to use local currency asset return and local currency risk free rate.

BTW, if you want to know 1) how to generate technical indicators, 2) how to generate dividend price ration, and 3) how to get the US variables used in Welch and Goyal by using the raw data in Goyal’s website, you can look at the matlab codes I have uploaded in ‘searching for predictors’ holder. I will explain this later but you are ok to try running this if you want.

Dear Students

I have posted two video clips on BB. The first is about lecture slides 2,3,4 and class02program_2019.m, and the second is about matlab codes generating US predictors (using Goyal’s raw data), technical indicators, and dividend price ratio. If you have any questions, ask them on the discussion forum as I explained in my previous email. I will post more video clips next week.

Hi

I have two announcements. First, clearly I have no intention to cover everything in Rapach’s lecture slides. His slides are for 1 semester teaching (3 to 4 months). So, I select/teach only relevant (arguably most important) parts of his slides for your thesis, and accordingly my lecture video clips only cover them. For your thesis, you need to study only the material I cover in my video clips.

Second, I would like to provide some info. on how to structure your MSc dissertation. Typically there are 6 or 7 sections in your thesis in the following order. I am attaching an exemplar MSc thesis as a reference.

1. Introduction: you need to provide some ‘motivations’ at least briefly such as why return forecasting is important, why you chose your country, etc. You can also provide a brief overview of your thesis.

2. Literature review: first you need to summarize at least key papers on stock return forecasting (papers on US and international predictability). And you should have a separate section summarizing

a list of predictability papers using your country’s data.

3. Methodologies: you need to summarize all the techniques used in the thesis clearly as much as you can. For example, any methodology you learn from me should be explained in details as much as you can (for this,

you may need to provide more details than the materials in the slides by reading some textbooks on them).

4. Empirical results: I expect you to write the following.

– Data section: provide definition/source of data you use. You need to provide descriptive statistics for all variables (mean, variance, skewness, kurtosis, autocorrelation, etc)

– In-sample regression results: regression results on the whole sample. We will talk about this in the last lecture.

– Out-of-sample forecasting results: everything you have learned and decided to use based on the lecture materials.

You need to study all of my lecture slides to know what you are going to do in ‘in-sample’ and ‘out-of-sample’ sections. You need to report/summarize every empirical results.

5. Conclusion: your verdict on return predictability on your chosen asset, and discuss implications and limit on your research (along with some discussions on possible future research).

6. References

7. Appendix (if necessary)

Note 1: you can put all the figures/tables at the end (before Appendix) if you want.

Note 2: when you write equations and provide tables/figures/references, you should do it consistently and clearly. Please read the exemplar thesis for more information.

Hi

I have posted two video clips in ‘lecture 2’ folder. I will post two more video clips (lecture 8 and 9) by the end of this week.

You should have now attempted to collect market index return, risk-free rate, and some predictors for your chosen country. If you haven’t, please try doing it this week.

Once you compute excess return and collect some predictors, you should try modifying the matlab codes with your own data. You can ask questions on discussion forum or by email in case you have difficulty in understanding my lectures/matlab codes and data collection/code modification.

Hi

Most of you have sent me the list of predictors for your chosen asset. Thanks for that. I think some of you haven’t read one of my emails on this carefully. I will provide that again with some more comments. Here is what I wrote before + new comments (in red)

===============================================================

I have recommended you to search for possible return predictors for your country’s market excess return. For that purpose,

I would like to provide more information on how to do that. Inside the folder ‘searching for predictors’, you can find the following information.

Please read the papers mentioned below, which I have posted in this directory, and study the video clip on ‘searching for predictors’ I posted.

1) Typical Predictors: this is part of Goyal and Welch’s paper on typical return predictors for US market excess returns.

You don’t need to search for the updated data. You can find this in Goyal’s website.

If your country is not U:S, then you need to search for similar variables in your chosen country (via Bloomberg or others). Be aware of this. Some variables are only

available on US, but not in your country. BTW, US predictors can be still useful if your chosen country is not US. See 3) below.

You should aim to find the corresponding variables used in Goyal and Welch for your country. But only some of those will be available. I commented a bit in my video clip in ‘searching for Predictor’ folder as follows. Please listen to it. I think you should be able to find at least dividend price ratio, short-term interest rate, default spread, term spread, inflation, stock market volatility.

2) Technical indicators: One of Rapach’s papers demonstrates that technical indicators (e.g., simple trading rule based on return/volume signal) can forecast US market excess return.

Perhaps you can say the same thing to your country. Please look at what are the necessary data to generate this.

You can use a group of equivalent technical indicators used in Rapach’s paper for your country.

3) Role of US variables: One of Rapach’s papers demonstrates that US variables could be helpful to forecast other countries’ market excess returns.

Some of the US return predictors or market excess returns in 1) (available at Goyal’s website) can be useful.

So, it is possible to include US variables as one of potential predictors for your non-US asset.

4) Investor sentiment: this is one of newly discovered predictors for US. If you can find similar one in your chosen country, that will be great.

But this might not be possible. Because of 3), you could still use US investor sentiment for your chosen country.

Search for investment sentiment data for your country. Investment sentiment data for US is available in Zhou (one of the authors of the investment sentiment paper)’s website.

5) Various factor premiums: One of Rapach’s new papers claim that factor premiums (e.g., SMB, HML, etc) can forecast US market excess returns.

Perhaps this would be true to other countries. Or because of 3), US factor premiums can be useful for other countries.

And perhaps you can find some relevant factor premiums for your chosen country in French’s data library (just google it).

You can find the data in French’s data library (this is French in Fama and French model)

6) I have added a recent survey on international return predictability there. Perhaps you can find some info. from reading this paper.

And please also search for some unique predictors used for your chosen country from the literature. Please read this.

I think you need to decide which variables should be used in your dissertation. Often data availability will determine that. Please make a list of

predictors you wish to use in your dissertation based on data availability and your preference. And please try to search for these variables, and

once you determine which variables to include, please let me know about that.

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