Throughput, Inventory, and Operating Expense—TOC's Financial Metrics Applied to Options Trading
When I first read The Goal in 2016, and learned about Goldratt's logical approach to financial and accounting metrics, I started to see how they were universal—they did not apply only to manufacturing companies! This video (h/t Dr Alan Barnard ) inspired me to revisit those early days when I first started applying TOC to trading.
Let's go through the six questions covered in the video.
(1) What is Productivity?
From the article: Productivity is defined as the act of bringing a company closer to its goal. Every decision and action that moves you toward that goal is productive; decisions and actions that don’t, are not.
How does this apply to trading? It's straightforward -- the goal in trading is to make profits. At least, that's a good enough place to start.
(2) What is the Goal?
From the article: The goal of any business is to?make money, now and in the future. Don’t confuse the means or necessary conditions like having enough demand, capacity, supply, cash, innovation etc. with the goal. Each of these have a level of “good enough” to support the goal.
How does this apply to trading? It's pretty much the same as what Goldratt defines for a manufacturing organization: the goal is to make profits. That is never really the "ultimate" goal—the profits are just an indicator of how well we are able to reach other, more fundamental, more personal goals—but if you aren't trying to make money with your trading, then I guess you just like expensive habits.
In addition to the common goal of making profits, trading has similar necessary conditions as well—each with its own level of "good enough":
Demand
Is there "demand" for what we bring to the market? As the traders and teachers at Robot Wealth often repeat, traders get paid for "doing something useful that sucks". We traders provide liquidity by participating in the markets. We accept risks that others don't want to accept, and thereby bring down the cost of those risks, allowing others to offload those risks to us. We make the market more efficient—we sell at prices that are a little bit too high, and we buy at prices that are a little bit too low—thereby pushing the prices closer to where an efficient market would have them.
These "useful things that suck" are the source of our edge—they are what pays our bills.
If we think our edge is "buying when the price bounces off a 100-day moving average when the RSI is above N%" or something along those lines—then we need to seriously ask ourselves: why would anybody pay us to do that? Who is willingly taking the opposite side of that trade? If we can't think of anyone who would want to take the opposite side—someone who has a legitimate reason to take the other side—then there probably isn't any real demand, and therefore no real edge either.
Capacity
Do we have enough margin (or capital) to trade a particular market or strategy?
Supply
In trading, this is pretty much the same thing as capacity. Our "supply chain" is essentially our access to margin.
Cash
Do we maintain enough cash to take advantage of new opportunities? Do we maintain enough cash to maintain a margin cushion so our broker doesn't force us to close our trades? Do we have enough cashflow that we can pull cash out of our trading account from time to time to help pay the bills?
Innovation
The markets are always changing, and we need to be vigilant to update our strategies, seizing new opportunities, and protecting against new risks.
All of these conditions are necessary for us to become consistently profitable traders, and to maintain that status "now and in the future."
(3) Evaluating Strategic Decisions
From the article: Strategic decisions must be judged by its impact on three financial metrics: Net Profit (NP), Return on Investment (ROI), and Cash Flow (CF). A “productive” strategic decision SIMULTANEOUSLY improves all three. Improving any one of these at the expense of another is easy, but have severe downsides, now or in the future.
We have similar problems in trading.
For example, some trades have a low win rate, but when they win, they win big. Over time, they might generate high Net Profit and high ROI, but they have a negative impact on Cash Flow.
Thus these trades can be difficult to sustain:
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Another example: let's say your trading generates $5000 per week in profit, on average, and it's very consistent. Sounds pretty good for an individual retail trader, right? But what if that trader has a $25M account? (I certainly don't have an account of that size, but I know retail traders who do!) In that case, $5000 per week is looking pretty awful. You could get a much better ROI by putting your capital in a money market account.
(4) Evaluating Operational Decisions
From the article: Operational decisions should be evaluated based on their impact on Throughput?(T), Investment (I), Operating Expense?(OE). A “productive” operational decision SIMULTANEOUSLY improves all three. Improving any ONE at the EXPENSE of others is EASY, but have severe downsides, either now or in the future.
This basic "throughout accounting" framework is very useful for trading. It was this framework that helped validate my intuition that, all other things being equal, shorter-term trades are much better than longer-term trades. Why? Because the inventory turnover is so much better.
Basically, the money you have locked up in stocks or options or other trading positions is your "inventory". If your margin is all locked up in inventory, then it is taking too long to give you a return. And this does have carrying costs in many forms. For example, lost opportunities.
But even more fundamentally, you want to increase the RATE at which your OE turns your I into T. And this means you want HIGH INVENTORY TURNOVER. In trading terms, which is better? A trade that turns $100 into $200 every week, at a cost of $25? Or a trade that turns $100 into $200 every day, at a cost of $25?
Some retail trading coaches advise against higher-frequency trading, because the transaction costs add up. This is true—but it also generally assumes that high-frequency trading is going to take the form of scalping, or some other strategy that gets lots and lots of tiny wins and even tinier losses. With trades like that, the transaction costs are a large percentage of your expected profits, and can be a very significant drag.
But what if you can take a higher P/L trade, and increase the frequency and preserve the high P/L rate, where the transaction costs are a low percentage of your profits? Then the transaction costs don't create any extra drag at all.
(5) The Simultaneity Imperative
From the article: Productive decisions enhance all three metrics simultaneously. This is much HARDER that improving any one in isolation. But it is so worth it.
This can be a useful framework for defining the basic parameters of a desirable trade.
Increasing throughput means you want a trade that has a stronger edge—higher expectancy and higher consistency. This generates more profit, more ROI, and more cashflow.
But you also want to lower investment. This means you want a way to tie up less margin (capital or buying power) in each trade, and keep it tied up for shorter periods of time. So in addition to high expectancy and high consistency, you also need high margin efficiency.
And you also need to reduce operating expenses. These can take many forms. There are commissions and fees, which are usually transparent and reported as such by your broker. But there are less visible forms, such as the bid/ask spread, or slow/delayed order fills. These also form create a drag on your trade. So ideally, you want to use highly liquid vehicles that are actively traded, and thus have tight bid/ask spread and fast fills.
These criteria alone will not tell you what to trade—but they will tell you immediately what to avoid—where NOT to look for trading ideas. And they give you a set of criteria to evaluate your trading ideas.
(6) The Balancing Demand and Supply Paradox
From the article: The other big mistake companies make is trying to balance or maintain “just enough” capacity and inventory - to match average demand. It might seem efficient, but leaves no buffer to cope with real world supply and demand variability. Without enough capacity and inventory buffers, a business is fragile and underperforms.
Managing your buying power is critical in options trading. If you run too close to the edge, you can find yourself in a "buying power trap"—where don't have enough margin to cover an exit order. This can be very dangerous in options trading, where your positions are inherently leveraged and you can have unlimited risk in your short positions. As an adverse move works against you, it consumes more and more of your buying power till you have none left. And then your exit orders (which require at least some minimal buying power) cannot execute or might even be cancelled, and you are trapped in the losing position.
And aside from these critical situations, you also want to always have enough buying power on hand to take advantage of new opportunities as they arise. Thus it is imperative to maintain a buffer of buying power for when there is a critical need.
Personally, I watch my fluctuating buying power very closely, and establish "green/yellow/red" buffer zones that are easy to track. I have various tactics to adjust my trades if I approach the danger zones. I also examine my buying power usage after each trading session to note anything I may have missed during the heat of battle. As a side effect, this scrutiny also helps me find opportunities to increase my buying power usage efficiency—get the same edge for less buying power—which can be a powerful way to boost returns.
Summary
In summary, these basic financial metrics give powerful insights not only into the dynamics of complex manufacturing organizations but also into trading dynamics and strategies. Thank you Dr Alan Barnard for the great reminder!
#theory_of_contraints
#toc
#options_trading
#throughput_accounting