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2018 Incident Report (Part 4)

Today I continue with an unfinished July 2019 draft evaluating my 2018 trading performance.

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Other considerations regarding the problematic strategy include:


With regard to my trading on Oct 24-25, 2018:


I will continue next time.

2018 Incident Report (Part 3)

Today I continue with an unfinished July 2019 draft evaluating my 2018 trading performance.

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These possibilities aside, one thing I can do is have a system for when I get into trades and when I stay out. Maybe I use something like the STFS and never enter when the trend is going against me. Maybe I use a simple pivot system and only enter long (short) at a buy (sell) signal. Maybe I watch the price for a time period and enter a limit order that seems reasonable based on recent trading activity. While none of these ideas will guarantee I get better fills, they would all provide some objective framework to follow. If nothing else, at the end of a trading session I could say “I followed my plan.” Ultimately, that may be the most important thing anyway.

Related to Goal #3 is a thought I’ve had about day trading futures. This would give me extended face time with the market and help me to become more comfortable watching. Trading futures can also hedge my option portfolio if I am trading the trend while having theta positive option positions in place.

Trading futures may also help me find some “co-workers.” I’ve had one heck of a time finding serious option traders around. I might fare better finding futures day traders since “day trading” seems to be a stronger buzzword than “options.”

In addition to having a defined approach, all of the above would require me to spend more time looking at the market. This brings me back to Goals #1 and #2 described previously.

With regard to the worst sales pitch ever, here are some ideas I have for potential trade indicators:

  1. IV % increase (consider closing if IV has increased 30-50% when the position is losing money)
  2. Option price (regardless of M/S, I’ve found level of comfort and strength of discipline to be inversely proportional to option price. Delta may be a confounding variable as higher-priced options move faster in terms of gross amount)
  3. Distance OTM (some efficient frontier exists between moneyness and days to expiration. This may be hard to define but I know it exists)
  4. Number of contracts (I dare not call this “position size” since other things play into the latter like notional risk, PMR, etc. I may look to change my trading to a fixed number of contracts per month rather than a dynamic approach where I trade every day despite the DD improvements enjoyed by the latter from time diversification. PMR is proportional to number of contracts)
  5. ATM IV:10-delta IV (the idea here is to take note of vertical skew. A steeper skew may or may not be the time for me to be in the market: need further testing. Another approach could be to monitor delta X% OTM. This would change with DTE. I may have 12 data points per year, however, and it might [not] be useful to determine a percentile rank for where the current ordered pair fits into the whole distribution)
  6. Technical analysis. While I won’t believe in untested strategies, I may be able to specify criteria for entry, to stay out, to add new positions, or to sit on my hands. Things to watch could include trend direction (e.g. 8/34 crossover, price closing above/below 5/20/200-SMA, slope of 50-SMA), $TICK strong or weak (tags of +/- 1000), etc.


I will continue next time.

2018 Incident Report (Part 2)

I left off reviewing my 2018 trading performance (originally written June 2019). This is part of my year-long quest to get more organized by converting incomplete drafts into finished blog posts.

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Part 1 concluded with three goals for the coming year.

#1 addresses the observation that I really don’t like looking at the market. My style of trading has generally been “no news is good news” even though news has so little to do with any of it (see paragraph below excerpt here). When I get around to checking the market (and subsequently trading), I sometimes notice holding my breath before the visuals display on the screen with a subsequent sigh of relief when I realize things are under control.

Filled with trepidation is not exactly the way I want to approach my job on an everyday basis. I think the worst sales pitch ever has something to do with that concern. I would much rather look at the market with anticipation, calm assurance, collectedness and confidence, peace, security, contentment, and serenity: choose a synonym.

Goal #2 addresses the fact that I typically check the market once daily. I should look more often especially if I get into more frequent trading like Weeklys (I have seen both positive and negative reviews).

Goal #3 pertains to a feeling that I usually end up getting bad fills. A bad fill is when I pay $3.00 for something only to see it cost $2.60 a few seconds later. Reasons exist for this sort of thing to happen (e.g. displayed bid/ask shrinking when someone actually places an order, market makers wanting to transact toward their side of the natural to realize bigger margins, etc.). The only way I can ensure this does not happen is to place an order for an advantageous price and then wait for a fill.

Goal #3 is related to #2 because I can’t always accomplish this by popping in and out once to check the market. I may have to sit with the market, watch the chart, perhaps work the trade, etc.

I have a couple ideas as to how to achieve #3. One possibility is to create trading strategies that give me leeway to pick up my bat and ball and come back another day when conditions are more advantageous. Another possibility is to only enter trades that would be down money right now if placed on a previous day (or bar). If the backtest as a whole looks good, then I would think being more selective and getting more advantageous entries should be added benefit. The drawback would be a [small?] percentage of trades that would have posted zero MAE. Missing out on these trades may lower my overall average profit.

I will continue next time.

2018 Incident Report (Part 1)

I have been getting more organized this year by converting incomplete drafts into finished blog posts. Completing this draft made me realize I was overdue for a performance report.

As it turns out, I had a never-completed mini-series from July 2019 about my 2018 performance.

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Originally, this was supposed to be an incident report of major losses suffered the week of October 8, 2018. Now, it’s going to be an incident report for all of 2018.

After having my best year ever in 2017, 2018 was decisively my worst (including 2008 when I actually made money). I took big losses in February, October, and into December.

One of the biggest sources of both frustration and optimism is that whenever I experience big losses, I always seem to be able to look back to a point where I can easily say “I should have gotten out” and avoided the worst. The big question is whether these points are visible prospectively. Anything knowable only in hindsight is mirage and not a useful indicator.

I feel like I need to do a few different things every day to maintain trading preparedness.

First and foremost, I need to develop a checklist with daily monitoring parameters. I will take pre-planned action when triggers get hit. The main focus of my trading will then be to follow the checklist: no questions asked.

I had a monitoring spreadsheet created this year for naked puts. I stopped using it once I closed partial positions. My discipline waned throughout the remainder of the year. This needs to be iron clad throughout. Discipline, in the trading business, may be said to be everything.

One repetitive theme I have noticed about myself is that when I stop the bleeding, I rarely stop the bleeding. If I use some sort of equity stop-loss or [set of] indicators to determine whether I am in [for at least a percentage of my standard size] or out of the market [entirely], then that needs to be it. I always seem to fear the whipsaw. I fear being out when the market suddenly reverses thereby leaving me on the sidelines. This fear has not helped because time and time again, I have maintained a partial position that proceeded to aggravate my losses.

Here are three things to work on for the coming year:

  1. I need to feel comfortable in the markets.
  2. I need to look at the markets more.
  3. I need to have an approach to trading when I actually trade.


I will discuss these further next time.

Automated Backtester Research Plan (Part 10)

I’ve been getting more organized this year by converting incomplete drafts into finished blog posts. From the mini-series on the automated backtester, here is one further post (Jan 2019) on the off chance that someone out there could possibly benefit.

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Relatively simple adjustment criteria to study: rolling out a short option or closing a losing vertical. Maybe also rolling a wing closer when the market is up X% or when the market reaches the opposite long strike (because it has become cheaper to roll).

The next step will be to tabulate several statistics for the serial, non-overlapping approach. These include number (and temporal distribution) of trades, winning percentage, compound annualized growth rate (CAGR), maximum drawdown percentage, average days in trade, PnL per day, risk-adjusted return (RAR), and profit factor (PF). Equity curves will represent just one potential sequence of trades and some consideration could be given to Monte Carlo simulation. We can plot equity curves for different account allocations such as 10% to 50% initial account value by increments of 5% or 10%.

Allocation may be done based on maximum risk of the position (wing width minus credit received for iron spreads) or stop-loss at max potential profit. When considering this, it would be interesting to see what the distribution of losers looks like as a percentage of max potential profit (credit received, for an iron butterfly).

RAR may have two meanings. As used above, RAR is CAGR (or total return) divided by maximum drawdown percentage. When studied with filters, RAR may mean CAGR (or total return) divided by percentage of time in the market.

Some elementary filters can also be studied. Average true range (ATR) (eight or 14 periods) under a certain value (analyzed as a range) could be an entry criterion. Determining the exact range could be done by studying ATR distribution by date across the whole data set. Maybe we use absolute number or maybe we use a percentile over the last X days, which may have to be optimized as well. We could also study VIX (or RVX) to see if it makes sense to stay out with VIX above Y or above the Z’th percentile over the last W days. A more complicated combination would be to center the trade above (below) the money when momentum is positive (negative) or when we get a Donchian channel breakout to the upside (downside). This may be more a study of mean reversion vs. trend following and probably something to study closely with stability in mind.

Butterfly Backtesting Ideas (Part 2)

I’ve been going through my “drafts” folder this year trying to finish partially-written blog posts and get more organized. Here is a one-off post whose sequel simply did not get completed. As I have said before, in the longshot case that someone out there could possibly benefit from any of this, what follows is Part 2 from June 15, 2017.

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Everywhere I look people seem to be doing butterflies of some sort so I’m really interested to find the attraction.

I would like to do a backtest of the flat iron butterfly but before that I’d like to do a typical, symmetric butterfly. I’d like to place this above the money because of all the talk of doing the asymmetric in order to balance NPD, which is normally negative at inception on an ATM symmetric butterfly due to vertical index skew. Rather than take on a boatload of additional risk in the form of asymmetric wings (embedded vertical spread), centering the trade above the money will offset natural negative delta at trade inception.

How far above the money?

If I’m looking at 10-point RUT strikes then going below the money could be 1-10 points, which is 0.25% to 2.5% with RUT at 400 or 0.071% to 0.71% for RUT at 1400. The former is much larger but if the average move (ATR?) is much smaller in case of the former (it should be) then everything should be fine.

One thought that comes to mind is that IV might tell me whether we’re in a relatively volatile (high ATR) or channeling (low ATR) market, but it’s possible that all incidents of RUT < 400 are relatively volatile whereas higher prices may lack volatility on a relative basis. This is true because of the limited sample size of trading days < 400. I should do a study of # days with RUT price between certain ranges (maybe look every 100 points) and check average IV and IV SD.

How wide should my wings be?

Part of me would like to take a fixed wing width and use it throughout. The problem I see is that the percentage will differ greatly if the index is at 400 vs. 1400. This is an argument for using a constant percentage. Of course, I can take whatever width and multiply by the appropriate number of contracts to somewhat normalize margin requirement (MR). My concern here is that a fixed width might be relatively wide with respect to ATR for some butterflies and relatively narrow for others. In other words, if a fixed width ends up being a minimal move in some markets vs. a huge move in others, then maybe I should use another indicator to tell me what width best fits a certain market and then adjusting total risk (MR) by adjusting position size.

Worst Drawdown is Always Ahead

Today I want to explain and provide a caveat to the claim “backtesting fails because my worst drawdown is always ahead.” *

Regardless of backtesitng interval, future market conditions can always be worse than historical. The only case where this would not be true is one where the underlying goes to zero. Were that to happen, of course, the underlying would not be tradeable today.

The worst drawdown being ahead is a consideration to be made in trading system development rather than a failure of said development. Backtesting is a phase of trading system development. Monte Carlo simulation might be another phase… position sizing yet another. The latter two can potentially offer better perspective on likely worst-case future drawdowns based on historical backtrades.

Any systematic approach to trading is based on backtesting and live-trading experience. Nevertheless, drawdown is always a nervous time. The deeper the drawdown, the fewer similar occurrences to anything seen in the past. This gives rise to uncertainty at the right edge of the chart. I can hold through a -10%, -25%, etc. correction and say “well this has only happened X, Y, etc. times in the last 15 years,” but to then believe this can in any way forecast a market turnaround is flawed. The chance of Tails on the next coin flip is 50% regardless of how many consecutive Heads have just turned up.

I like the idea of position sizing based on historical drawdowns plus additional margin of error in case of a worse-case future drawdown. Ultimately, though, I am always just crossing my fingers for a reversal in fortune. A drawdown 50% worse than 2008 is enormous and can certainly come to pass. The deeper a correction becomes, the more I will be hoping the Big One is not taking place now.

Two things can benefit me in the unlikely case the worst drawdown in history is in progress. First is the alluring case for insurance. Second is trading with constant position size because the profits already generated can then serve to offset drawdowns proportionally. Other position sizing algorithms will be position sized largest at portfolio highs, which can lead to the largest gross losses.

* — This post was written in May 2016 but never completed. I find this interesting
       to revisit in lieu of my recent algorithmic trading experience.

Implications of “No Fear Investing”

Inspired by this, the current post completes a draft I started to write on July 6, 2014.

In the linked post, I asked the question: how can I possibly manage other people’s money during crazy market environments when I am so fear-stricken and on-edge for myself?

The difficulty of trading without fear is probably why so few succeed as full-time retail traders.

Only a couple ways exist to for me to live without fear and have skin in the game.

First, I have a full-time J-O-B that enables me to be adequately position-sized. The job prevents me from needing trading profits to pay living expenses every month. My level of fear is therefore decreased because even when the market goes sour, I still have my J-O-B to pay the bills.

Second, my level of wealth may afford me to cover living expenses by putting a “small” fraction at risk in the market. Little at risk means no, or little fear.

Malcolm Gladwell writes about why the first case is hard to navigate. Gladwell writes the key to success in any particular field is a matter of practicing the specific task for 10,000 hours. I would have a hard time getting to 10,000 hours as a part-time investor, which means I may never make a whole lot in the markets because I’ll never be invested large. Thank goodness for the J-O-B. This circular reasoning pretty much eliminates the possibility of full-time trading.

The second case is difficult for two reasons. First, I believe this requires [multi-] millionaire status, which only accounts for a small percentage of the population. Most traders aspire to be millionaires but are not and are therefore unable to get away with risking a little. Second, if I were a millionaire then I would have to be content making only enough to cover living expenses. Many people with lots of money aim to make lots more. A business owner may want to buy/run more businesses or locations, for example. Doing this in the financial markets means putting more wealth at risk, which opens the door to fear when the market environment goes ballistic (e.g. March 2020).