This chart is the clearest representation of the immense damage that emanated from the GFC on the US economy.

In the ~60 years following WWII, US real GDP seemed to grow at ~3% trend like clockwork.

2008 marked the end of this trend, with growth downshifting to ~2% since. 1/

1/

Get a cup of coffee.

In this thread, I'll help you understand Geometric Expectations.

2/

Imagine we have an investment opportunity.

If the investment goes well, we get to double our money.

But if it goes badly, we'll end up losing three fourths of it.

There's a 50/50 chance of either outcome.

The question: is this a good bet or not?

3/

A simple way to approach this question is to calculate the bet's "expectation".

For every $1 we bet, there are 2 possibilities:

1. The lucky case, where we double our money and end up with $2, and

2. The unlucky case, where we lose (3/4)'th to end up with just $0.25.

4/

Each of these outcomes is equally likely.

So, on *average*, every $1 we put in turns into ($2 + $0.25)/2 = $1.125.

This is a *positive* 12.5% return.

Such bets are called *positive expectation* bets. On average, we expect to *make* (rather than *lose*) money on them.

5/

Suppose we could take many turns betting at these odds.

In any one turn, we could of course lose money.

But because our bet has positive expectation, *over time* we expect to make money.

30 books I wish I read before Investing my hard-earned money:

1. You can be a Stock Market Genius by Joel Greenblatt
2. Common Stocks, Uncommon Profits by Phil Fisher
3. Margin of Safety by Seth Klarman
4. The Crowd by Gustave Le Bon
5. Winning the Loser's Game by Charles Ellis

6. The Zurich Axioms by Max Gunther
7. The Most Important Thing by Howard Marks
8. Thinking, Fast and Slow by Daniel Kahneman
9. The Intelligent Investor by B. Graham
10. A Zebra in Lion country by Ralph Wanger and Everett Mattlin
11. Learn to Earn by Peter Lynch

12.Poor Charlie's Almanack - The wit and wisdom of Charles T Munger
13.Speculative Contagion by Frank Martin
14. The Long and the Short of it by John Kay
15. More than you know by Michael Maubossin
16. Influence - The Psychology of Persuasion by Robert Cialdini

17. The Psychology of Judgment and Decision making by Scott Plous
18. The Real Warren Buffett by James O'Loughlin
19. Devil take the Hindmost by Edward Chancellor
20. Risk Intelligence by Dylan Evans
21. The Emotionally Intelligent Investor by Ravee Mehta

22.Accounting for Value by Stephen Penman
23. Common Stocks and Common Sense by Edgar Wachenheim III
24. Big Money Thinks Small by Joel Tillinghast
25. Memos from the Chairman by Alan C Greenberg

Working on some execution optimisation related backtesting. I have so far been executing with market orders only. Going towards higher lot sizes, I'd like to optimise for minimal slippage.

First off, on NSE, if you place a market order, you get filled at the best bid/ask right?

If we want to optimise this, the first non-creative idea one can think of is, slicing the order into different lot sizes, and placing a limit order for each slice at the mid point of current best bid & ask.

But this requires your latency to be the least.

Why would latency affect it?

I looked at tick historical data, and there are more than 18-20 ticks in a second (auction and quote combined).

Even if you keep 10 ticks per second, your best bid/ask can shift from the time you place to the time exchange receives the order.

So, the next best thing that people can do is place tranches of orders every 1s, 3s, 5s, 10s, 15s - in their preferred time range, and get filled at the midpoint or best-bid+1/2/3/4/5 in the depth.

What you need is liquidity.

But if you're trading breakouts, then it's highly likely that your limit orders may not get filled if the action is too fast.

So, a retry mechanism is required in such cases.

If nothing works, you convert your orders to marketable and get filled at worse slippage.