In the culminating project, you will develop new trading strategies, evaluate them using the tools learned in the course, integrate them with the existing portfolio and also develop a plan to start a hedge fund.

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來自 Indian School of Business 的課程

Design your own trading strategy – Culminating Project

18 個評分

In the culminating project, you will develop new trading strategies, evaluate them using the tools learned in the course, integrate them with the existing portfolio and also develop a plan to start a hedge fund.

從本節課中

Week 2 - Strategy

In this module you will go through the paper based on
'Pairs Trading' strategy and understand the details of the strategy completely. You will also identify the sector and related sector on which you want to base your strategy.

- Ramabhadran ThirumalaiAssistant Professor

Indian School of Business

[MUSIC]

Learning Outcomes.

After watching this video, you will be able to understand what

parts of an academic paper are relevant for trading strategy.

You will also understand how to comprehend the relevant part of an academic paper.

[MUSIC]

Welcome to this module on training strategies.

I'm assuming that by now, you are familiar with basic accounting concepts.

You know some market terminologies, like what you mean by shorting a stock.

You know some basics about sports and equity markets, futures and options.

Not that you need to know all these in detail for actual trading, but

understanding of basic terms will help.

So with this assumption, I'm going to proceed.

We are going to start now with how to read an academic paper.

You may be wondering, why do you need to know about reading an academic paper in

a trading strategy course?

The answer is source of our idea,

source of trading ideas is going to come from academic papers.

Why are we doing this?

This is because there is a wealth of ideas, which are there in academic papers,

which have not been exploited by market participants.

People do value investing, people do growth investing,

people do technical analysis, people do nowadays text mining.

A lot of things.

But there are low hanging fruits,

which are available, which academicians have published.

This is there in the public domain.

You may not have some private information, but

these ideas haven't been fully exploited by market participants.

By undergoing this course, you will nod which those ideas are.

That's the first point.

Second, you will also learn to think in those lines and

improvise on those strategies.

You can create your own strategies based on the ideas which come from these papers.

Third, we have the rigor, which is involved in these academic papers is so

high that it's very close to causal.

What do you mean by causal?

Two variables moving together does not necessarily

mean that one is causing another.

All of us understand that, right?

But in these academic papers, these authors try to show that

what they are claiming, the relationship between two particularly two or

more variables is as close to causal as possible.

Although perfectly, you know no one can say that anything is causal.

So that is why the replicability of these ideas, the chance that these ideas work

is much higher than a normal strategy that come from some data mining exercise.

What do you mean by a data mining exercise.

So if you're good at programming, take past data.

Try thousand types of different type of strategies.

A simple strategy, any stock which fell 5% the previous day,

or some x percent the previous day, you will buy.

This could be one simple strategy.

Or something which went up 1% previous week, you will buy or sell, whatever.

So if you try thousands of such strategies, Purely

because of chance that you will find that some strategies work.

Now, if you start putting your money in those strategies,

you may be in for disaster.

Whereas strategies that come from academic papers, based on academic research,

these are strategies which are being devised by scholars,

experts in these areas, and hence these are not pure data mining exercises.

There is an economical logic as to why these strategies work or

why they don't work.

And author also defines the circumstances under which these strategies work.

Now, does that mean that you can always make money?

We have reminded you right at the beginning itself,

this course does not guarantee that you just read,

undergo this course you go trade tomorrow, and you start making money.

No, that's not guaranteed.

But then, what can we say with high level of confidence that this

strategies work better than most of the data mining exercises?

And more importantly, this way of thinking that you will get from these papers,

that's going to help you devise your own strategies.

And the chances of success of those strategies are even higher.

Because there you will combine your practical experience with this rigor

that'll make a very good combination.

So let me re-emphasize again, don't think that users undergo this course,

and from next day, you'll start minting money.

That's not going to happen.

It may happen for some of you, but that's not our purpose.

Our purposes, the learners, the students who learn these

strategies should be able to apply and also improvise, and

more importantly, inculcate this rigorous way of thinking about trading strategies.

These are trading strategies which have economic intuition.

There is some reason why these strategies work.

So that's the purpose of this course.

Now, how are we going to go through this model?

So let me tell you what are we going to do in the next couple of hours.

Of course, you have the facility of pausing at any time.

That's the beauty of this medium.

But what we're going to do is that first,

we are going to give an outline as to how our academic paper is structured.

It's very important.

There are large number of strategies available out there in the public domain.

So obviously, in this limited time, I won't be able to cover all strategies.

I'll be able to go to very few of them.

But then, I will point out sources where you can read about more strategies.

The one major challenge that is going to come here is that all these papers

tend to be highly technical.

What do I mean by technical?

These papers are returned with scholarly audience in mind.

These papers are not written for general audience.

So the writer assumes that reader has some level of understanding,

and more importantly, writer also assumes that the reader is up-to-date with

the existing literature on that data.

So if you pick up any paper, you will see large number of citations of other papers.

Now, does it mean that for trading, you will have to go through all those papers?

Take a five-year accounting course, take a five-year finance course and

learn mathematics, statistics.

The good news is no.

So and that is what the purpose of this module is.

What we are going to do is that in this dense,

dense jungle of an academic paper, we are trying to pick up.

We will try to pick up exactly those parts which are required for understanding

the trading strategy the comes out of the paper and implementing it.

And also understanding how the strategy has performed in the past.

Well, that's the purpose of this module.

Okay, so let's start.

So instead of picking some paper, which we are not going to use,

let's start with the paper that we will use in this course.

So this is apaper by Joseph Piotroski.

This paper is published, I repeat, published.

This is in the public domain.

So there is no secret recipe out there which you will not be able to get.

This is fully publicly available.

It's a paper by Piotroski, a [INAUDIBLE] Value Investing.

So you can see on the screen the exact title of the paper.

You can also see where the link that you can see,

where the paper is available publicly.

So this is published in Journal of Accounting Research,

which is a top journal in the area of accounting.

The idea of paper is very simple.

You'd have heard about value investing, right?

I'm sure if you are interested in trading, you'll have already heard about

value investing, or you would have heard about Warren Buffett for sure.

What these people do,

value investors generally pick up stocks which are neglected by the market.

And by the matter of time when they are valued very,

very low when compared to their intrinsic price.

And then hope that these stocks, the market with realize some time that these

were good stocks and then the price will go up.

And that's how they make money.

Now, the question comes, why markets neglect these stocks?

How do you identify these stock, and

how do you trade these stocks?

Now, what Piotroski's paper does,

the paper use an algorithm who identify a subset of stocks

within this value stocks which are likely to outperform others.

That's what these paper does.

And why don't you pick up all value stocks and just buy and hold?

Can you make money, is the question.

You're to ask yourself, if that were so easy, if you can just pick up stocks which

are valued low, then why are there only so few successful value investors?

All of us will have become value investors, right?

Just take a list of stocks, look at stocks which are valued very low.

I'll come to this point that, how do you see that a stock is valued low or high?

Assume that there is a way of finding it out.

Then just pick up those stocks which are valued very low, and just buy them and

hold, and you make money.

You don't need to do, you can party for rest of your life if it were so simple.

As you would guess, it's not that simple.

Financial economists have pointed out,

including Nobel laureates like Eugene Fama and others.

The reason why these stocks are valued low is because many of them

are on the verge of bankruptcy.

There are serious problems for these stocks.

Some of them may have liquidity constraints,

some of them may be on the verge of default,

some of them may be making losses, and so on and so forth.

And some of them may have governance problems.

Their numbers may be saying something, accounting numbers may be projecting

a rosy picture, but there may be some scandal going on.

We have had numerous instances like this.

Some of them may be taking risks, which a lot of people may not realize.

So that may be one of the reasons why these stocks are valued low.

Now, if you buy all these stocks, and if you tend to buy such stocks

just because they're valued low, you may end up losing all your money.

And that is precisely why we have very few Warren Buffets.

We don't have too many of them.

So now, what Piotrosky does is within this universe of low value stocks,

how do you pick up those stocks which are are likely to be potential winners?

That's the question that Piotrosky tries to answer.

And more importantly, he gives you a specific formula.

Now, I can tell you right, this is a skill.

If I tell you it's a skill,

then there is no answer as to how do you acquire that skill.

This is not like painting and drawing and music and all that.

Piotrosky gives you a specific formula.

Does that mean that you just have to know that formula, and

there is no scope for skill?

No, not at all.

That's not what I mean.

What I mean is by understanding this Piotrosky's paper,

you will get a specific formula to start with.

You'll get a screen, basic screen, and from there, you can build on.

So this score, the Piotroski score, which is called the f-score,

tells you whether you have to buy or sell a stock, right?

So that's the starting point.

Now, what we are going to do in this module is take you through

different sections of a paper.

Of course, we are going to use Piotroski's paper.

Why do burden you with another paper which any of would use?

And tell you, suppose you are given a paper, how do you locate

that particular area or part of the paper that contains what you want?

The meat of the paper, so to speak.

A paper typically has some 60 to 70 pages.

You will have around typically 30 pages of text,

some 20 pages of tables, and some 5, 6 graphs.

That how you will seek in a paper.

As I've told you before,

the author's purpose is to publish these paper in a peer review journal.

So there are referees who look at this paper, ask questions.

They say that they ask the author to explain how this works.

They come out with alternative explanations.

The author has to show that the paper is robust to this kind of alternative

explanations, and so on and so forth.

What I mean is that a lot of parts of the paper which are not essential

from a training point of view.

Of course, I encourage you to read the paper fully, understand the paper fully.

Some of you may get Interested in pursuing a PhD,

that's an unintended consequence, that's great.

But purely from our trading point of view, you do not need to read the entire paper.

So first, let me tell you how a paper is structured.