(1/n) Should investors be prepared for a longer period of negative returns? Or are the #Nifty and #Sensex in for a prolonged struggle? Let's analyze some data from the #VIX (India VIX) into consideration.
Chart 1: Line Chart of IndiaVIX starting 2007 to present.
(2/n) As of close today, the India VIX ended at 58.88. The first close above 30.00 was registered on March 9, 2020 (7 days ago).
Let's look at similar instances in the past, where the VIX stayed above 30.00 for over a week (on a closing basis).
(3/n) Rest of the instances (VIX closing back below 30 within a calendar week (17 instances).
(4/n) Takeaways: 1) Despite limited sample size, data since 2007 suggests that 1-3 bar excursions beyond 30 on the VIX typically align with short-term corrections in a bull market, typically showing positive follow-through over the next several weeks and months.
(5/n) Takeaways (Continued) 2) The initial precedents to a longer-duration correction (or a bear market) are VIX staying above 30, with the jump in volatility triggered by a meaningful sell-off (in this scenario, #Nifty is down by 12% since March 9 (the 1st close on the VIX > 30)
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Position sizing is a key determinant of your P&L. If your bet size is too small, the outcome is meaningless, while if it is too big an account is blown!
A 🧵 on the basics of position sizing for a capital base of Rs. 100,000 based on my approach: Fixed-Percentile Units (or FPU)
(2/n) Recommended Approach: Fixed-Percentile Units
The FPU approach standardizes risk-per-trade based on a % of capital.
What you select depends on your personal risk tolerance, but anything <1% would be miniscule for a capital size under a crore, while >4% would be too big.
(3/n) Step 1: Standardize your Sizing based on FPU per trade
Decide the rupee amount of risk per trade based on your capital size, and keep it constant until account equity changes by +/- 10%.
For e.g., Capital = 100,000, FPU is 3% per trade,
Per Trade risk = Rs. 3,000
A coin has a 50% chance of landing on either heads or tails. Over a large sample size, one may expect this probability to close-in on 50% given a “fair” coin.
Let’s explore this topic from a trading standpoint.
2/n Suppose you’re trading the Nifty index on the basis of a coin toss at 9.15 AM. If the coin lands on heads, you take an intra-day long trade at the open (or a short trade if it lands on tails).
3/n For the purpose of simplicity, let’s assume:
•Trading capital of 1 Lakh (Starting balance);
•Rs. 1000 rupees risk per trade. (Profit: +1000, Loss: -1000);
•Ignore transaction costs, slippage etc.
What is the expected the portfolio balance after 1000 trades?
Based on the poll response, the focus on Positive Expectancy & Risk management seems to be understated, while a visible weightage to Trading psychology and discipline is as expected.
So what really is most essential for successful trading?
2/n The only 2 pillars (that really matter) to successful trading are positive expectancy and risk management.
Once these are aligned, everything else takes care of itself. Skills of trading discipline, efficient execution, etc. can all be acquired over a period of time.
3/n
-> Positive expectancy is an outcome of identifying and exploiting a statistical edge (WHAT TO DO) over a reasonably large sample size.
-> Risk management refers to efficient allocation of trading capital or a methodical calculation of risk per trade (HOW MUCH TO BET).