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How do I handle bank errors in a reconciliation?
Bank errors adjust the bank side because the bank statement is wrong, not the company's books. If the bank incorrectly charged the company's account, add the amount back to the bank statement balance. If the bank incorrectly credited the company's account, subtract the amount from the bank statement balance. The goal is to correct the bank statement to what it should have shown. Do not record a journal entry for a pure bank error unless the company's books also contain an error.
Which bank reconciliation items adjust the books?
Items adjust the books when the bank has recorded something that the company has not recorded yet, or when the company recorded something incorrectly. Common book side items include bank service charges, interest income, NSF checks, electronic collections, automatic loan payments, and company errors. These usually require journal entries because the cash ledger is wrong or incomplete. Deposits in transit and outstanding checks usually do not adjust the books because the company already recorded them.
Why does my bank reconciliation not tie?
A bank reconciliation usually fails to tie because one item is on the wrong side, omitted, or corrected in the wrong direction. Start by separating the bank side from the book side. Deposits in transit, outstanding checks, and bank errors adjust the bank statement balance. Bank service charges, NSF checks, interest earned, automatic bank transactions, and company recording errors adjust the book balance. If the adjusted bank balance and adjusted book balance do not agree, do not force the answer. Reclassify each item and check whether it requires a journal entry.
What makes investing and financing cycles harder on CPA AUD simulations?
Investing and financing cycles often have fewer transactions, but each one carries more accounting and disclosure detail. A routine sale may be tested with invoices and shipping documents. A financing transaction may require the note agreement, board approval, lender confirmation, interest recalculation, classification analysis, and disclosure review. For debt, watch for completeness of obligations, accrued interest, current versus noncurrent classification, covenant disclosures, and authorization. For investments, watch for existence, rights, fair value, income recognition, impairment, and classification. The exam trick is that a single document may affect several assertions. A loan agreement can support existence, obligations, interest terms, maturity, collateral,
When should I trace instead of vouch in a CPA AUD cycle question?
Use the direction of the test. Tracing usually starts with source evidence and follows it into the accounting records. It is helpful for completeness because you are asking whether something that happened made it into the books. For example, tracing shipping documents to the sales journal can test whether shipments were recorded. Vouching usually starts with the recorded accounting population and moves backward to supporting evidence. It is helpful for occurrence or existence because you are asking whether recorded items are valid. For example, vouching recorded sales to customer orders and shipping documents can test whether sales actually occurred. A
How do I translate overstatement or understatement into an audit adjustment?
Start with the account that is wrong, not with the audit procedure. If revenue is too high, the correction usually reduces revenue. If a payable is too low, the correction usually increases the liability. If interest expense is missing, the correction records the expense and the related payable. Example: a client has a $300,000 note at 8% signed on November 1, and no year end interest accrual was recorded at December 31. The missing interest is $300,000 x 8% x 2/12 = $4,000 . The adjustment is: Debit interest expense for $4,000. Credit interest payable for $4,000. That entry follows
Why do CPA AUD transaction-cycle questions feel like FAR questions?
They feel that way because many AUD simulations test whether you can connect evidence to the accounting records. The procedure is only the last step. Use this path: For example, if a receiving report is dated before year end but the vendor invoice was recorded after year end, the issue is not just "inspect invoices." The underlying accounting risk is an unrecorded liability. That points to completeness of accounts payable and a search for unrecorded liabilities. The exam rewards candidates who can translate documents into account effects. When you see a transaction cycle task, ask which account is too high
Why can a statistically significant result still be economically small?
A small p-value means the evidence is strong enough to reject the null at the chosen alpha. It does not automatically mean the effect is large enough to matter economically. Imagine a low-cost index overlay shows average annual outperformance of `0.03%` with a p-value of `0.01` over a very large sample. The result may be statistically significant because the sample is large and the estimate is precise. But after transaction costs, implementation limits, and taxes, a three-basis-point effect may not justify changing the portfolio. For CFA questions, separate the two judgments: - Statistical significance: compare p-value to alpha. - Economic
What does it mean when a p-value is called the minimum significance level?
It means the p-value is the rejection threshold expressed as an alpha level. If a test has `p-value = 0.023`, then the test rejects the null for any alpha of 2.3% or higher. It fails to reject for any alpha below 2.3%. That definition is useful when answer choices list several significance levels. Suppose a question asks at which significance levels a result with `p-value = 0.023` is significant: - At 10%: reject. - At 5%: reject. - At 1%: fail to reject. The result is statistically significant at 10% and 5%, but not at 1%. The p-value does not
How do I compare a p-value to alpha in CFA hypothesis testing?
If the question gives the p-value and alpha, make the decision directly: reject the null when `p-value <= alpha`; otherwise fail to reject the null. Use one decision route at a time. The p-value route compares p-value to alpha. The critical-value route compares the test statistic to the critical value. Mixing those routes is a common mistake. Example: Rowan Analytics tests whether average forecast error differs from zero. The two-tailed p-value is `0.047`, and the test uses `alpha = 0.05`. Because `0.047 <= 0.05`, reject the null at the 5% level. If the same question used `alpha = 0.01`, fail
Does a bigger p-value mean the result is more significant?
No. A bigger p-value means weaker evidence against the null hypothesis. The p-value asks how unusual the sample result would be if the null hypothesis were true. If the p-value is small, the result is hard to explain under the null, so rejecting the null becomes easier. If the p-value is large, the result is not unusual enough to reject the null at common significance levels. For example, if `alpha = 0.05` and the p-value is `0.032`, reject the null. If the p-value is `0.32`, fail to reject. The second result is not "more significant"; it is much less persuasive
Should I use my calculator to understand duration or just memorize the formula?
Repricing can be a very good check, but it should support the concept instead of replacing it. Suppose Harbor Foods has a bond priced at 102.40 with modified duration of 4.75. If yields rise by 0.20 percentage points, duration estimates: `-4.75 x 0.0020 = -0.0095 = -0.95%` Estimated new price: `102.40 x 0.9905 = 101.43` If you reprice the bond at the higher yield and get a price near 101.43, the calculator check supports the duration estimate. If the yield change is large, convexity may explain a wider difference. The workflow is: Do not jump straight to keys. First identify
How does duration connect market price risk and reinvestment risk?
The risk-offset interpretation is mainly tied to Macaulay duration for a plain fixed-rate bond. When yields rise, the bond's price falls, but future coupon reinvestment becomes more attractive. When yields fall, the bond's price rises, but future coupons are reinvested at lower rates. Macaulay duration approximates the investment horizon where those two effects can offset each other. Modified duration is the price-sensitivity version. It answers a different question: how much should price change for a small yield change? Use Macaulay duration for timing and horizon intuition. Use modified duration for first-order price sensitivity.
When converting Macaulay duration to modified duration, which yield should I divide by?
Use the yield per period that matches the cash-flow period used in the bond valuation. For a semiannual-pay bond quoted at a 7.00% annual yield with semiannual compounding, the per-period yield is 3.50%. If Macaulay duration is 4.10 years, the conversion is: `Modified duration = 4.10 / 1.035 = 3.961 years` Using `1.07` would over-adjust the duration because it treats the annual yield as if it applied to each six-month period. The exam trap is not the division itself. It is mismatching the yield convention with the coupon period.
Why is modified duration measured in years if it estimates a price percentage?
Modified duration is measured in years because it is a sensitivity ratio built from cash-flow timing. It tells you the approximate percentage price change for a 1.00 percentage point change in annual yield. The useful way to see the unit is: `Modified duration = percent price change / annual yield change` If a bond has modified duration of 5.20, then a 0.25 percentage point yield increase gives: `-5.20 x 0.0025 = -0.0130 = -1.30%` The output is a price percentage. The input yield change is annual. The duration measure sits between them as the years-like sensitivity. So the unit is
Can a large test statistic fail to reject the null if it is in the wrong direction?
No. Direction matters. In a left-tailed test, the rejection region is in the left tail. A positive statistic is on the opposite side of the distribution, so it does not support a less-than alternative. Example: - `H0: mu >= 6%` - `Ha: mu < 6%` - Left-tail critical value at 5%: `-1.645` - Test statistic: `+2.10` Even though `2.10` has a large absolute value, it is not less than `-1.645`. Fail to reject the null. Magnitude is not enough. The statistic must be extreme in the direction specified by the alternative.
Should the p-value approach and critical-value approach always agree?
Yes, they should agree if you use the same alternative hypothesis, significance level, and tail direction. For a right-tailed 5% test: - Critical-value approach: reject if the statistic is greater than the right-tail critical value. - P-value approach: reject if the right-tail p-value is less than 5%. The approaches can seem inconsistent when the tail is mixed up. For example, using a one-tailed p-value for a two-tailed test can make the evidence look stronger than it really is. So if your answers conflict, check the tail before checking the arithmetic.
Why does a two-tailed test split alpha across both tails?
The significance level is the total probability of rejecting the null when it is true. In a two-tailed 5% test, unusual results in either direction count against the null, so the total 5% rejection probability is split across the two tails. That means: - 2.5% in the left tail. - 2.5% in the right tail. - 5.0% total rejection probability. If you put 5% in each tail, the total rejection probability would be 10%, not 5%.
How do I know which tail a hypothesis test should use?
Read the alternative hypothesis first. The alternative tells you what kind of evidence would contradict the null. - `Ha: mu > 4%` means right-tailed. - `Ha: mu < 4%` means left-tailed. - `Ha: mu != 4%` means two-tailed. After that, the rest is mechanical: calculate the statistic, place it on the correct distribution, and compare it with the correct rejection region.
How do I avoid picking overbroad answers in CFA Ethics?
Strict is not always correct. The best Ethics answer states what the Standards require, not the harshest action imaginable. If a research note says a model "guarantees downside protection," the fix is accurate communication about assumptions and limits. It does not mean models can never be used. If a firm updates clients about a recommendation, fair dealing requires a fair dissemination process. It does not mean every client must receive identical trades at the exact same time regardless of mandate. When two answers sound ethical, ask: - Does this answer match the exact duty? - Does it add a requirement
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