Every factual claim the video makes, chased to a primary source. Where a figure could not be traced to one, it is not printed on screen and it is listed at the end instead.
A note on the charts. The price series, equity curves, parameter sweeps and trade ledgers in this video are generated from stated models rather than taken from a market, because each one is teaching a mechanism rather than reporting a result. Every frame that uses one is marked Illustrative on screen. Nothing in the video asserts that a particular strategy returned a particular number.
The US Securities and Exchange Commission’s own investor bulletin states that the stop price is a trigger which converts the order into a market order, and that the execution price “can deviate significantly from the stop price in a fast-moving market where prices change rapidly”. It further warns that a stop order may be triggered by a short-term intraday price move and fill at a price substantially worse than expected.
The same bulletin notes that a stop-limit order’s limit price requires execution at that price or better, and that the limit price “may prevent the order from being executed”.
Liquidity providers withdraw quotes around high-impact economic releases, and the resulting drop in available liquidity widens quoted spreads. Liquidity also thins around the daily rollover and at session edges. The direction of this effect is well established in the academic literature on price discovery and liquidity in foreign exchange.
No multiple is stated for how far spreads widen, on screen or in the narration. See Not traced to a primary source below.
Testing only on instruments that still exist today excludes those that failed or delisted, which makes the surviving history look cleaner than the real one was. Elton, Gruber and Blake (1996) measured survivorship bias in mutual fund returns at approximately 0.9% per year. Brown, Goetzmann, Ibbotson and Ross found that survivorship can inflate Sharpe ratios by as much as 0.5, which is substantial against a Sharpe of 1.0 being considered strong.
TradingView’s Pine Script documentation carries a dedicated page on indicator repainting: a script behaves differently on historical bars than in real time when its output depends on data that arrives later. A zigzag requires subsequent bars to confirm a pivot, so its markers move after the fact. On a historical bar Pine shows finalised values; on a real-time bar those values are still changing until the bar closes.
Bailey, Borwein, López de Prado and Zhu (2014), in the Notices of the American Mathematical Society, show that high simulated performance is easily achievable after testing a relatively small number of strategy configurations, and that the probability a backtest is overfit rises with the number of configurations tried. They also note that the number of configurations tried is almost never reported, which leaves a reader unable to judge the degree of overfitting.
White’s Reality Check and Hansen’s Superior Predictive Ability test exist specifically to adjust significance when many models are compared against the same data, which is the formal treatment of the same problem.
Robert Pardo set out walk-forward analysis in Design, Testing and Optimization of Trading Systems (1992; second edition 2008): the strategy is optimised on an in-sample window, tested on the out-of-sample span immediately following it, and the window is then advanced and the process repeated, so the reported result is composed only of out-of-sample segments.
Moskowitz, Ooi and Pedersen (2012) document time series momentum across 58 liquid futures instruments spanning equity indices, currencies, commodities and bonds: returns persist at horizons of one to twelve months and partially reverse over longer horizons. The same rule is therefore working with the grain of the market at one horizon and against it at another.
Daniel and Moskowitz (2016) show that momentum strategies suffer infrequent and persistent strings of negative returns which are partly forecastable: they occur in “panic” states, following market declines and when market volatility is high, and coincide with market rebounds. The strategy is unchanged throughout; the paper names the conditions that turn against it.
Barber and Odean (2000) studied 66,465 households holding common stock at a large discount broker between 1991 and 1996. The households that traded most earned an annual return of 11.4% against a market return of 17.9%, and the average household underperformed a value-weighted market index by roughly 3.7 percentage points a year. The authors attribute the excess trading to overconfidence. A live result is therefore the strategy combined with the decisions taken around it, not the strategy alone.
These claims are made in the narration and are not supported by a citation above. None of them appears as a figure on screen.