| Course | MT483 Investments |
|---|---|
| Unit | Unit 8 |
| Paper type | Behavioral bias analysis |
| Length | About 1,070 words, 6 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Business Administration |
| Updated | October 2026 |
Free sample paper for MT483 Unit 8
Buying What Already Rose, Waiting to Get Even: An MT483 Unit 8 Behavioral Bias Analysis of One Trade Log
[Student Name]
Purdue University Global
MT483: Investments
Unit 8 Behavioral Bias Analysis
[Instructor Name]
[Date]
Kevin Brooks, his trade log, the companies and their prices are composite; the studies cited are real.
The Log
The log belongs to Kevin Brooks, a composite investor with a $40,000 taxable brokerage account opened after an inheritance. Over fourteen months he made twelve trades, each recorded with a date, a price and the one-line reason he wrote at the time.
1. Month 1: bought $20,000 of an S&P 500 index fund. Reason: "core holding."
2. Month 2: bought 80 shares of Pemberton Foods at $62.00. Reason: "solid dividend payer."
3. Month 2: bought 160 shares of Ashby Retail at $31.00. Reason: "cheap after earnings dip."
4. Month 3: bought $3,000 of Ridgeway Solar. Reason: "up 48% in six months, momentum."
5. Month 5: placed a sell order for Pemberton at $62.00. Reason: "out when I'm back to even."
6. Month 5: placed a sell order for Ashby at $31.00. Reason: "same, get my money back."
7. Month 6: bought $3,000 of Calloway Biotech. Reason: "up 61% since spring, everyone's talking about it."
8. Month 8: sold half the index fund to buy $3,000 of Northgate Software. Reason: "up 47%, can't miss this run."
9. Month 9: sold Ridgeway Solar after its loss. Reason: "dead money."
10. Month 11: added $2,000 to the index fund. Reason: "monthly savings."
11. Month 12: sold Calloway Biotech. Reason: "trial news, moving on."
12. Month 14: sold Northgate Software. Reason: "need cash for car repair."
The log is given unedited so that each claim below can be checked against the entries. A bias is not named until the trades behind it have been shown.
Pattern One: Buying After Large Gains
Three purchases share a pattern. Ridgeway Solar, Calloway Biotech and Northgate Software were each bought after six-month gains of 48, 61 and 47 percent, an average of about 52 percent. Kevin's recorded reasons cite the recent rise in every case, "momentum," "everyone's talking about it," "can't miss this run," and none mentions the company's sales, earnings or prospects. Over the six months after each purchase, Ridgeway returned minus 12 percent, Calloway minus 4 percent and Northgate minus 11 percent, an average of minus 9 percent. The index fund returned 2.1, 4.6 and 3.2 percent over the same three windows, an average of 3.3 percent.
Each purchase was justified by what the price had already done, not by what the company was expected to do.
The pattern fits extrapolation: treating a recent trend as if it will continue. De Bondt and Thaler (1985) found that portfolios of prior long-term losers went on to outperform prior winners, which they interpreted as investors overreacting to past performance and pushing prices too far. Kevin's horizon was shorter than theirs, and three trades prove nothing statistically, but his written reasons show the reasoning the study describes.
Pattern Two: Holding Losers to Get Even
Two holdings follow a different pattern. Pemberton Foods fell from $62.00 to $47.50 and Ashby Retail from $31.00 to $24.80 within three months of purchase. In month 5, Kevin placed sell orders at exactly his purchase prices, and his reasons, "out when I'm back to even" and "get my money back," make the reference point explicit. To fill, Pemberton needed to rise 30.5 percent from $47.50 and Ashby 25.0 percent from $24.80. Neither did. Eleven months after the orders were placed, Pemberton traded at $49.00 and Ashby at $23.75, and the orders were still waiting.
The purchase price had become an anchor. Tversky and Kahneman (1974) showed people settling on numbers close to whatever figure they started with, even a figure produced by a spinning wheel. For Kevin's decision the purchase price was arbitrary: the market did not know or care what he had paid, and the only relevant question in month 5 was whether these two stocks were the best use of $7,768. Odean (1998) studied 10,000 brokerage accounts and found that investors realized gains more readily than losses, and that the losing stocks they held went on to underperform the winners they sold.
What Each Pattern Cost
Each cost is measured against a stated alternative chosen before looking at the results: holding the index fund over the same dates.
For the extrapolation buys, $3,000 in each of the three stocks lost $360, $120 and $330, a total of $810. The same $9,000 in the index fund would have gained about $63, $138 and $96, or $297. The difference, about $1,107, is the cost of the three trades relative to doing nothing.
For the anchored pair, the two positions were worth $7,768 when the sell orders were placed. Eleven months later they were worth $7,720, 80 shares at $49.00 plus 160 at $23.75. Had the $7,768 moved into the index fund, which returned a composite 7.8 percent over those eleven months, it would have been worth about $8,374. The anchored holds cost about $654.
Together the two patterns cost about $1,761 on a $40,000 account, roughly 4.4 percent of its value, during a period when the index fund alone performed well.
Other Explanations Weighed
Not every losing trade shows a bias, and three alternatives deserve a hearing. News could explain a sale: Kevin sold Calloway after trial results, a reasonable reaction to new information, so that sale is not counted as bias. Cash needs explain the Northgate sale in month 14, which was forced by a car repair. Bad luck could explain the losses in any single trade: a solar stock can fall for reasons nobody could foresee.
What luck does not explain is the recorded reasoning. Three purchase notes cite only past price gains, and two sell orders are placed at the purchase price with reasons that name breaking even. The behavioral reading rests on what Kevin wrote before the outcomes were known.
A Rule for the Next Trade
The analysis ends with two specific rules rather than a general call for discipline. First, every purchase note must state one reason about the business itself, not its price history; a note that cites only the recent gain blocks the order. Second, every exit price must be written before the purchase and based on the investment case, so that a later exit is never set at the price paid.
References
De Bondt, W. F. M., & Thaler, R. (1985). Does the stock market overreact? The Journal of Finance, 40(3), 793-805. https://doi.org/10.1111/j.1540-6261.1985.tb05004.x
Odean, T. (1998). Are investors reluctant to realize their losses? The Journal of Finance, 53(5), 1775-1798. https://doi.org/10.1111/0022-1082.00072
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131. https://doi.org/10.1126/science.185.4157.1124
MT483 Unit 8 instructions, in plain terms
For Unit 8 of MT483, the assignment generally supplies or asks you to build a trade log and then identify the biases it shows. Present the log before naming anything, with dates, prices and the reason recorded for each trade. Choose two or three biases the entries actually support and point to the specific trades behind each. Cite the research that defines each bias with author, year and finding. Measure what each pattern cost against an alternative chosen before looking at the results, often an index fund over the same dates. Consider other explanations, such as news, cash needs or simple bad luck, before settling on a behavioral reading. Personal logs are welcome in some sections, but a composite log is acceptable in most and keeps private finances out of the discussion.
How this MT483 Unit 8 example is built
The twelve entries appear first, numbered and unedited, each with Kevin's own words. The extrapolation section groups three purchases by their run-ups and quotes his reasons, then compares their next six months with the index and cites De Bondt and Thaler under a highlighted line about price history. The anchoring section follows two sell orders placed at purchase prices, computes the recoveries they required and cites Tversky and Kahneman and Odean's study of 10,000 brokerage accounts. A cost section prices each pattern, $1,107 and $654, for about 4.4 percent of the account. The section on alternatives clears the Calloway sale as a reaction to news and the Northgate sale as a cash need. Two rules end it, a business reason for every purchase and an exit price written in advance.
Reading the MT483 Unit 8 grading rubric
Each bias needs evidence from the log, and labels pulled from a glossary with no trade attached give graders nothing to check. Credit rises when the investor's own recorded reasons support the label, since outcomes alone cannot separate bias from luck. Costs carry a large share of the points and are the part most often missing; they require a stated alternative, the dates and the figures. Research is graded on accuracy, so authors, year and the actual finding should appear in APA form. A section weighing other explanations shows judgment and protects the analysis from reading as forced. Composite logs should be labeled as composite. The strongest endings propose a specific, checkable rule rather than a general resolution to be more disciplined.
MT483 Unit 8 help from the desk
Many analyses list five or six biases and support none of them. Others treat every loss as evidence of bias, which ignores the role of chance in any single trade. A related problem picks the comparison after seeing results, choosing whatever makes the bias look most expensive. Students frequently describe anchoring and the disposition effect as the same thing; they overlap, but the paper should say which pattern each trade shows. Quoting definitions from websites instead of the original studies weakens the evidence. Before submitting, mark each bias with the trade numbers behind it, compute its cost against an alternative you named in advance, and write one sentence for each trade explaining why news or luck does not account for it.
Get an MT483 Unit 8 example written to your instructions
Trade logs arrive in every form: supplied by the Unit 8 prompt, drawn from a simulation, or invented. Whichever kind applies, attach it to the rubric; the first MT483 analysis is returned free in 24-48h, each bias tied to entries, costed against a stated alternative and cited to its research. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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MT483 Unit 8 questions, answered
Can I analyze my own trade log?
Some prompts invite it. If you use your own trades, decide how much you are comfortable sharing, since instructors and sometimes classmates read the paper. A composite log built from realistic trades is equally acceptable in most sections and lets you design clear evidence for each bias. Label whichever you use.
How many biases should the analysis identify?
Two or three, each supported by specific trades, usually beats a long list supported by none. Choose the biases the log actually shows, cite the research behind each and measure what it cost. A bias that appears in one trade only may be coincidence, which is worth saying plainly.
How do I measure what a bias cost?
Compare the actual outcome with a plausible alternative chosen before looking at the results, such as holding an index fund over the same dates. State the alternative, the dates and the figures. The measured difference is the cost, with the caveat that one period cannot prove the bias always loses money.
Where can I find a free MT483 Unit 8 sample paper?
The complete MT483 Unit 8 analysis is on this page, identifying extrapolation and anchoring in a composite twelve-trade log and costing each against an index fund.
Why is the Calloway sale not counted as a bias in the MT483 Unit 8 sample?
Kevin sold after trial results, a reasonable response to new information, so the paper treats that trade as news rather than behavior.